A cumulant functional for static and dynamic correlation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hollett, Joshua W., E-mail: j.hollett@uwinnipeg.ca; Department of Chemistry, University of Manitoba, Winnipeg, Manitoba R3T 2N2; Hosseini, Hessam
A functional for the cumulant energy is introduced. The functional is composed of a pair-correction and static and dynamic correlation energy components. The pair-correction and static correlation energies are functionals of the natural orbitals and the occupancy transferred between near-degenerate orbital pairs, rather than the orbital occupancies themselves. The dynamic correlation energy is a functional of the statically correlated on-top two-electron density. The on-top density functional used in this study is the well-known Colle-Salvetti functional. Using the cc-pVTZ basis set, the functional effectively models the bond dissociation of H{sub 2}, LiH, and N{sub 2} with equilibrium bond lengths and dissociationmore » energies comparable to those provided by multireference second-order perturbation theory. The performance of the cumulant functional is less impressive for HF and F{sub 2}, mainly due to an underestimation of the dynamic correlation energy by the Colle-Salvetti functional.« less
Syed, Maleeha F; Lindquist, Martin A; Pillai, Jay J; Agarwal, Shruti; Gujar, Sachin K; Choe, Ann S; Caffo, Brian; Sair, Haris I
2017-12-01
Functional connectivity in resting-state functional magnetic resonance imaging (rs-fMRI) has received substantial attention since the initial findings of Biswal et al. Traditional network correlation metrics assume that the functional connectivity in the brain remains stationary over time. However, recent studies have shown that robust temporal fluctuations of functional connectivity among as well as within functional networks exist, challenging this assumption. In this study, these dynamic correlation differences were investigated between the dorsal and ventral sensorimotor networks by applying the dynamic conditional correlation model to rs-fMRI data of 20 healthy subjects. k-Means clustering was used to determine an optimal number of discrete connectivity states (k = 10) of the sensorimotor system across all subjects. Our analysis confirms the existence of differences in dynamic correlation between the dorsal and ventral networks, with highest connectivity found within the ventral motor network.
Role of the Pair Correlation Function in the Dynamical Transition Predicted by Mode Coupling Theory
NASA Astrophysics Data System (ADS)
Nandi, Manoj Kumar; Banerjee, Atreyee; Dasgupta, Chandan; Bhattacharyya, Sarika Maitra
2017-12-01
In a recent study, we have found that for a large number of systems the configurational entropy at the pair level Sc 2, which is primarily determined by the pair correlation function, vanishes at the dynamical transition temperature Tc. Thus, it appears that the information of the transition temperature is embedded in the structure of the liquid. In order to investigate this, we describe the dynamics of the system at the mean field level and, using the concepts of the dynamical density functional theory, show that the dynamical transition temperature depends only on the pair correlation function. Thus, this theory is similar in spirit to the microscopic mode coupling theory (MCT). However, unlike microscopic MCT, which predicts a very high transition temperature, the present theory predicts a transition temperature that is similar to Tc. This implies that the information of the dynamical transition temperature is embedded in the pair correlation function.
NASA Astrophysics Data System (ADS)
Cremer, Dieter
The electron correlation effects covered by density functional theory (DFT) can be assessed qualitatively by comparing DFT densities ρ(r) with suitable reference densities obtained with wavefunction theory (WFT) methods that cover typical electron correlation effects. The analysis of difference densities ρ(DFT)-ρ(WFT) reveals that LDA and GGA exchange (X) functionals mimic non-dynamic correlation effects in an unspecified way. It is shown that these long range correlation effects are caused by the self-interaction error (SIE) of standard X functionals. Self-interaction corrected (SIC) DFT exchange gives, similar to exact exchange, for the bonding region a delocalized exchange hole, and does not cover any correlation effects. Hence, the exchange SIE is responsible for the fact that DFT densities often resemble MP4 or MP2 densities. The correlation functional changes X-only DFT densities in a manner observed when higher order coupling effects between lower order N-electron correlation effects are included. Hybrid functionals lead to changes in the density similar to those caused by SICDFT, which simply reflects the fact that hybrid functionals have been developed to cover part of the SIE and its long range correlation effects in a balanced manner. In the case of spin-unrestricted DFT (UDFT), non-dynamic electron correlation effects enter the calculation both via the X functional and via the wavefunction, which may cause a double-counting of correlation effects. The use of UDFT in the form of permuted orbital and broken-symmetry DFT (PO-UDFT, BS-UDFT) can lead to reasonable descriptions of multireference systems provided certain conditions are fulfilled. More reliable, however, is a combination of DFT and WFT methods, which makes the routine description of multireference systems possible. The development of such methods implies a separation of dynamic and non-dynamic correlation effects. Strategies for accomplishing this goal are discussed in general and tested in practice for CAS (complete active space)-DFT.
Non-Gaussian lineshapes and dynamics of time-resolved linear and nonlinear (correlation) spectra.
Dinpajooh, Mohammadhasan; Matyushov, Dmitry V
2014-07-17
Signatures of nonlinear and non-Gaussian dynamics in time-resolved linear and nonlinear (correlation) 2D spectra are analyzed in a model considering a linear plus quadratic dependence of the spectroscopic transition frequency on a Gaussian nuclear coordinate of the thermal bath (quadratic coupling). This new model is contrasted to the commonly assumed linear dependence of the transition frequency on the medium nuclear coordinates (linear coupling). The linear coupling model predicts equality between the Stokes shift and equilibrium correlation functions of the transition frequency and time-independent spectral width. Both predictions are often violated, and we are asking here the question of whether a nonlinear solvent response and/or non-Gaussian dynamics are required to explain these observations. We find that correlation functions of spectroscopic observables calculated in the quadratic coupling model depend on the chromophore's electronic state and the spectral width gains time dependence, all in violation of the predictions of the linear coupling models. Lineshape functions of 2D spectra are derived assuming Ornstein-Uhlenbeck dynamics of the bath nuclear modes. The model predicts asymmetry of 2D correlation plots and bending of the center line. The latter is often used to extract two-point correlation functions from 2D spectra. The dynamics of the transition frequency are non-Gaussian. However, the effect of non-Gaussian dynamics is limited to the third-order (skewness) time correlation function, without affecting the time correlation functions of higher order. The theory is tested against molecular dynamics simulations of a model polar-polarizable chromophore dissolved in a force field water.
Role of the Pair Correlation Function in the Dynamical Transition Predicted by Mode Coupling Theory.
Nandi, Manoj Kumar; Banerjee, Atreyee; Dasgupta, Chandan; Bhattacharyya, Sarika Maitra
2017-12-29
In a recent study, we have found that for a large number of systems the configurational entropy at the pair level S_{c2}, which is primarily determined by the pair correlation function, vanishes at the dynamical transition temperature T_{c}. Thus, it appears that the information of the transition temperature is embedded in the structure of the liquid. In order to investigate this, we describe the dynamics of the system at the mean field level and, using the concepts of the dynamical density functional theory, show that the dynamical transition temperature depends only on the pair correlation function. Thus, this theory is similar in spirit to the microscopic mode coupling theory (MCT). However, unlike microscopic MCT, which predicts a very high transition temperature, the present theory predicts a transition temperature that is similar to T_{c}. This implies that the information of the dynamical transition temperature is embedded in the pair correlation function.
Local Descriptors of Dynamic and Nondynamic Correlation.
Ramos-Cordoba, Eloy; Matito, Eduard
2017-06-13
Quantitatively accurate electronic structure calculations rely on the proper description of electron correlation. A judicious choice of the approximate quantum chemistry method depends upon the importance of dynamic and nondynamic correlation, which is usually assesed by scalar measures. Existing measures of electron correlation do not consider separately the regions of the Cartesian space where dynamic or nondynamic correlation are most important. We introduce real-space descriptors of dynamic and nondynamic electron correlation that admit orbital decomposition. Integration of the local descriptors yields global numbers that can be used to quantify dynamic and nondynamic correlation. Illustrative examples over different chemical systems with varying electron correlation regimes are used to demonstrate the capabilities of the local descriptors. Since the expressions only require orbitals and occupation numbers, they can be readily applied in the context of local correlation methods, hybrid methods, density matrix functional theory, and fractional-occupancy density functional theory.
Spectral functions of strongly correlated extended systems via an exact quantum embedding
NASA Astrophysics Data System (ADS)
Booth, George H.; Chan, Garnet Kin-Lic
2015-04-01
Density matrix embedding theory (DMET) [Phys. Rev. Lett. 109, 186404 (2012), 10.1103/PhysRevLett.109.186404], introduced an approach to quantum cluster embedding methods whereby the mapping of strongly correlated bulk problems to an impurity with finite set of bath states was rigorously formulated to exactly reproduce the entanglement of the ground state. The formalism provided similar physics to dynamical mean-field theory at a tiny fraction of the cost but was inherently limited by the construction of a bath designed to reproduce ground-state, static properties. Here, we generalize the concept of quantum embedding to dynamic properties and demonstrate accurate bulk spectral functions at similarly small computational cost. The proposed spectral DMET utilizes the Schmidt decomposition of a response vector, mapping the bulk dynamic correlation functions to that of a quantum impurity cluster coupled to a set of frequency-dependent bath states. The resultant spectral functions are obtained on the real-frequency axis, without bath discretization error, and allows for the construction of arbitrary dynamic correlation functions. We demonstrate the method on the one- (1D) and two-dimensional (2D) Hubbard model, where we obtain zero temperature and thermodynamic limit spectral functions, and show the trivial extension to two-particle Green's functions. This advance therefore extends the scope and applicability of DMET in condensed-matter problems as a computationally tractable route to correlated spectral functions of extended systems and provides a competitive alternative to dynamical mean-field theory for dynamic quantities.
Revealing time bunching effect in single-molecule enzyme conformational dynamics.
Lu, H Peter
2011-04-21
In this perspective, we focus our discussion on how the single-molecule spectroscopy and statistical analysis are able to reveal enzyme hidden properties, taking the study of T4 lysozyme as an example. Protein conformational fluctuations and dynamics play a crucial role in biomolecular functions, such as in enzymatic reactions. Single-molecule spectroscopy is a powerful approach to analyze protein conformational dynamics under physiological conditions, providing dynamic perspectives on a molecular-level understanding of protein structure-function mechanisms. Using single-molecule fluorescence spectroscopy, we have probed T4 lysozyme conformational motions under the hydrolysis reaction of a polysaccharide of E. coli B cell walls by monitoring the fluorescence resonant energy transfer (FRET) between a donor-acceptor probe pair tethered to T4 lysozyme domains involving open-close hinge-bending motions. Based on the single-molecule spectroscopic results, molecular dynamics simulation, a random walk model analysis, and a novel 2D statistical correlation analysis, we have revealed a time bunching effect in protein conformational motion dynamics that is critical to enzymatic functions. Bunching effect implies that conformational motion times tend to bunch in a finite and narrow time window. We show that convoluted multiple Poisson rate processes give rise to the bunching effect in the enzymatic reaction dynamics. Evidently, the bunching effect is likely common in protein conformational dynamics involving in conformation-gated protein functions. In this perspective, we will also discuss a new approach of 2D regional correlation analysis capable of analyzing fluctuation dynamics of complex multiple correlated and anti-correlated fluctuations under a non-correlated noise background. Using this new method, we are able to map out any defined segments along the fluctuation trajectories and determine whether they are correlated, anti-correlated, or non-correlated; after which, a cross correlation analysis can be applied for each specific segment to obtain a detailed fluctuation dynamics analysis.
Cumulants and correlation functions versus the QCD phase diagram
Bzdak, Adam; Koch, Volker; Strodthoff, Nils
2017-05-12
Here, we discuss the relation of particle number cumulants and correlation functions. It is argued that measuring couplings of the genuine multiparticle correlation functions could provide cleaner information on possible nontrivial dynamics in heavy-ion collisions. We also extract integrated multiproton correlation functions from the presently available experimental data on proton cumulants. We find that the STAR data contain significant four-proton correlations, at least at the lower energies, with indication of changing dynamics in central collisions. We also find that these correlations are rather long ranged in rapidity. Finally, using the Ising model, we demonstrate how the signs of the multiprotonmore » correlation functions may be used to exclude certain regions of the phase diagram close to the critical point.« less
Cumulants and correlation functions versus the QCD phase diagram
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bzdak, Adam; Koch, Volker; Strodthoff, Nils
Here, we discuss the relation of particle number cumulants and correlation functions. It is argued that measuring couplings of the genuine multiparticle correlation functions could provide cleaner information on possible nontrivial dynamics in heavy-ion collisions. We also extract integrated multiproton correlation functions from the presently available experimental data on proton cumulants. We find that the STAR data contain significant four-proton correlations, at least at the lower energies, with indication of changing dynamics in central collisions. We also find that these correlations are rather long ranged in rapidity. Finally, using the Ising model, we demonstrate how the signs of the multiprotonmore » correlation functions may be used to exclude certain regions of the phase diagram close to the critical point.« less
Thermal form-factor approach to dynamical correlation functions of integrable lattice models
NASA Astrophysics Data System (ADS)
Göhmann, Frank; Karbach, Michael; Klümper, Andreas; Kozlowski, Karol K.; Suzuki, Junji
2017-11-01
We propose a method for calculating dynamical correlation functions at finite temperature in integrable lattice models of Yang-Baxter type. The method is based on an expansion of the correlation functions as a series over matrix elements of a time-dependent quantum transfer matrix rather than the Hamiltonian. In the infinite Trotter-number limit the matrix elements become time independent and turn into the thermal form factors studied previously in the context of static correlation functions. We make this explicit with the example of the XXZ model. We show how the form factors can be summed utilizing certain auxiliary functions solving finite sets of nonlinear integral equations. The case of the XX model is worked out in more detail leading to a novel form-factor series representation of the dynamical transverse two-point function.
Nishida, Jun; Yan, Chang; Fayer, Michael D
2016-10-12
Polarization-selective angle-resolved infrared pump-probe spectroscopy was developed and used to study the orientational dynamics of a planar alkylsiloxane monolayer functionalized with a rhenium metal carbonyl headgroup on an SiO 2 surface. The technique, together with a time-averaged infrared linear dichroism measurement, characterized picosecond orientational relaxation of the headgroup occurring at the monolayer-air interface by employing several sets of incident angles of the infrared pulses relative to the sample surface. By application of this method and using a recently developed theory, it was possible to extract both the out-of-plane and "mainly"-in-plane orientational correlation functions in a model-independent manner. The observed correlation functions were compared with theoretically derived correlation functions based on several dynamical models. The out-of-plane correlation function reveals the highly restricted out-of-plane motions of the head groups and also suggests that the angular distribution of the transition dipole moments is bimodal. The mainly-in-plane correlation function, for the sample studied here with the strongly restricted out-of-plane motions, essentially arises from the purely in-plane dynamics. In contrast to the out-of-plane dynamics, significant in-plane motions occurring over various time scales were observed including an inertial motion, a restricted wobbling motion of ∼3 ps, and complete randomization occurring in ∼25 ps.
Time correlation functions of simple liquids: A new insight on the underlying dynamical processes
NASA Astrophysics Data System (ADS)
Garberoglio, Giovanni; Vallauri, Renzo; Bafile, Ubaldo
2018-05-01
Extensive molecular dynamics simulations of liquid sodium have been carried out to evaluate correlation functions of several dynamical quantities. We report the results of a novel analysis of the longitudinal and transverse correlation functions obtained by evaluating directly their self- and distinct contributions at different wavevectors k. It is easily recognized that the self-contribution remains close to its k → 0 limit, which turns out to be exactly the autocorrelation function of the single particle velocity. The wavevector dependence of the longitudinal and transverse spectra and their self- and distinct parts is also presented. By making use of the decomposition of the velocity autocorrelation spectrum in terms of longitudinal and transverse parts, our analysis is able to recognize the effect of different dynamical processes in different frequency ranges.
Noninvasive measurement of dynamic correlation functions
NASA Astrophysics Data System (ADS)
Uhrich, Philipp; Castrignano, Salvatore; Uys, Hermann; Kastner, Michael
2017-08-01
The measurement of dynamic correlation functions of quantum systems is complicated by measurement backaction. To facilitate such measurements we introduce a protocol, based on weak ancilla-system couplings, that is applicable to arbitrary (pseudo)spin systems and arbitrary equilibrium or nonequilibrium initial states. Different choices of the coupling operator give access to the real and imaginary parts of the dynamic correlation function. This protocol reduces disturbances due to the early-time measurements to a minimum, and we quantify the deviation of the measured correlation functions from the theoretical, unitarily evolved ones. Implementations of the protocol in trapped ions and other experimental platforms are discussed. For spin-1 /2 models and single-site observables we prove that measurement backaction can be avoided altogether, allowing for the use of ancilla-free protocols.
Decomposition of Proteins into Dynamic Units from Atomic Cross-Correlation Functions.
Calligari, Paolo; Gerolin, Marco; Abergel, Daniel; Polimeno, Antonino
2017-01-10
In this article, we present a clustering method of atoms in proteins based on the analysis of the correlation times of interatomic distance correlation functions computed from MD simulations. The goal is to provide a coarse-grained description of the protein in terms of fewer elements that can be treated as dynamically independent subunits. Importantly, this domain decomposition method does not take into account structural properties of the protein. Instead, the clustering of protein residues in terms of networks of dynamically correlated domains is defined on the basis of the effective correlation times of the pair distance correlation functions. For these properties, our method stands as a complementary analysis to the customary protein decomposition in terms of quasi-rigid, structure-based domains. Results obtained for a prototypal protein structure illustrate the approach proposed.
Equilibrium time correlation functions and the dynamics of fluctuations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Luban, Marshall; Luscombe, James H.
1999-12-01
Equilibrium time correlation functions are of great importance because they probe the equilibrium dynamical response to external perturbations. We discuss the properties of time correlation functions for several systems that are simple enough to illustrate the calculational steps involved. The discussion underscores the need for avoiding language which misleadingly suggests that thermal equilibrium is associated with a quiescent or moribund state of the system. (c) 1999 American Association of Physics Teachers.
Smith, Kyle K G; Poulsen, Jens Aage; Nyman, Gunnar; Rossky, Peter J
2015-06-28
We develop two classes of quasi-classical dynamics that are shown to conserve the initial quantum ensemble when used in combination with the Feynman-Kleinert approximation of the density operator. These dynamics are used to improve the Feynman-Kleinert implementation of the classical Wigner approximation for the evaluation of quantum time correlation functions known as Feynman-Kleinert linearized path-integral. As shown, both classes of dynamics are able to recover the exact classical and high temperature limits of the quantum time correlation function, while a subset is able to recover the exact harmonic limit. A comparison of the approximate quantum time correlation functions obtained from both classes of dynamics is made with the exact results for the challenging model problems of the quartic and double-well potentials. It is found that these dynamics provide a great improvement over the classical Wigner approximation, in which purely classical dynamics are used. In a special case, our first method becomes identical to centroid molecular dynamics.
Spatial correlation of the dynamic propensity of a glass-forming liquid
NASA Astrophysics Data System (ADS)
Razul, M. Shajahan G.; Matharoo, Gurpreet S.; Poole, Peter H.
2011-06-01
We present computer simulation results on the dynamic propensity (as defined by Widmer-Cooper et al 2004 Phys. Rev. Lett. 93 135701) in a Kob-Andersen binary Lennard-Jones liquid system consisting of 8788 particles. We compute the spatial correlation function for the dynamic propensity as a function of both the reduced temperature T, and the time scale on which the particle displacements are measured. For T <= 0.6, we find that non-zero correlations occur at the largest length scale accessible in our system. We also show that a cluster-size analysis of particles with extremal values of the dynamic propensity, as well as 3D visualizations, reveal spatially correlated regions that approach the size of our system as T decreases, consistently with the behavior of the spatial correlation function. Next, we define and examine the 'coordination propensity', the isoconfigurational average of the coordination number of the minority B particles around the majority A particles. We show that a significant correlation exists between the spatial fluctuations of the dynamic and coordination propensities. In addition, we find non-zero correlations of the coordination propensity occurring at the largest length scale accessible in our system for all T in the range 0.466 < T < 1.0. We discuss the implications of these results for understanding the length scales of dynamical heterogeneity in glass-forming liquids.
Dynamical Correlation In Some Liquid Alkaline Earth Metals Near Melting
NASA Astrophysics Data System (ADS)
Thakore, B. Y.; Suthar, P. H.; Khambholja, S. G.; Gajjar, P. N.; Jani, A. R.
2010-12-01
The study of dynamical variables: velocity autocorrelation function (VACF) and power spectrum of liquid alkaline earth metals (Ca, Sr, and Ba) have been presented based on the static harmonic well approximation. The effective interatomic potential for liquid metals is computed using our well recognized model potential with the exchange correlation functions due to Hartree, Taylor, Ichimaru and Utsumi, Farid et al. and Sarkar et al. It is observed that the VACF computed using Sarkar et al. gives the good agreement with available molecular dynamics simulation (MD) results [Phys Rev. B 62, 14818 (2000)]. The shoulder of the power spectrum depends upon the type of local field correlation function used.
Cumulants vs correlation functions and the QCD phase diagram at low energies
Bzdak, A.; Koch, V.; Skokov, V.; ...
2017-09-25
We discuss the relation between particle number cumulants and genuine correlation functions. Here, it is argued that measuring multi-particle correlation functions could provide cleaner information on possible non-trivial dynamics in heavy-ion collisions.
Cumulants vs correlation functions and the QCD phase diagram at low energies
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bzdak, A.; Koch, V.; Skokov, V.
We discuss the relation between particle number cumulants and genuine correlation functions. Here, it is argued that measuring multi-particle correlation functions could provide cleaner information on possible non-trivial dynamics in heavy-ion collisions.
Straka, Michal; Lantto, Perttu; Vaara, Juha
2008-03-27
We calculate the 129Xe chemical shift in endohedral Xe@C60 with systematic inclusion of the contributing physical effects to model the real experimental conditions. These are relativistic effects, electron correlation, the temperature-dependent dynamics, and solvent effects. The ultimate task is to obtain the right result for the right reason and to develop a physically justified methodological model for calculations and simulations of endohedral Xe fullerenes and other confined Xe systems. We use the smaller Xe...C6H6 model to calibrate density functional theory approaches against accurate correlated wave function methods. Relativistic effects as well as the coupling of relativity and electron correlation are evaluated using the leading-order Breit-Pauli perturbation theory. The dynamic effects are treated in two ways. In the first approximation, quantum dynamics of the Xe atom in a rigid cage takes advantage of the centrosymmetric potential for Xe within the thermally accessible distance range from the center of the cage. This reduces the problem of obtaining the solution of a diatomic rovibrational problem. In the second approach, first-principles classical molecular dynamics on the density functional potential energy hypersurface is used to produce the dynamical trajectory for the whole system, including the dynamic cage. Snapshots from the trajectory are used for calculations of the dynamic contribution to the absorption 129Xe chemical shift. The calculated nonrelativistic Xe shift is found to be highly sensitive to the optimized molecular structure and to the choice of the exchange-correlation functional. Relativistic and dynamic effects are significant and represent each about 10% of the nonrelativistic static shift at the minimum structure. While the role of the Xe dynamics inside of the rigid cage is negligible, the cage dynamics turns out to be responsible for most of the dynamical correction to the 129Xe shift. Solvent effects evaluated with a polarized continuum model are found to be very small.
Decay of Complex-Time Determinantal and Pfaffian Correlation Functionals in Lattices
NASA Astrophysics Data System (ADS)
Aza, N. J. B.; Bru, J.-B.; de Siqueira Pedra, W.
2018-04-01
We supplement the determinantal and Pfaffian bounds of Sims and Warzel (Commun Math Phys 347:903-931, 2016) for many-body localization of quasi-free fermions, by considering the high dimensional case and complex-time correlations. Our proof uses the analyticity of correlation functions via the Hadamard three-line theorem. We show that the dynamical localization for the one-particle system yields the dynamical localization for the many-point fermionic correlation functions, with respect to the Hausdorff distance in the determinantal case. In Sims and Warzel (2016), a stronger notion of decay for many-particle configurations was used but only at dimension one and for real times. Considering determinantal and Pfaffian correlation functionals for complex times is important in the study of weakly interacting fermions.
Decay of Complex-Time Determinantal and Pfaffian Correlation Functionals in Lattices
NASA Astrophysics Data System (ADS)
Aza, N. J. B.; Bru, J.-B.; de Siqueira Pedra, W.
2018-06-01
We supplement the determinantal and Pfaffian bounds of Sims and Warzel (Commun Math Phys 347:903-931, 2016) for many-body localization of quasi-free fermions, by considering the high dimensional case and complex-time correlations. Our proof uses the analyticity of correlation functions via the Hadamard three-line theorem. We show that the dynamical localization for the one-particle system yields the dynamical localization for the many-point fermionic correlation functions, with respect to the Hausdorff distance in the determinantal case. In Sims and Warzel (2016), a stronger notion of decay for many-particle configurations was used but only at dimension one and for real times. Considering determinantal and Pfaffian correlation functionals for complex times is important in the study of weakly interacting fermions.
Beyond Kohn-Sham Approximation: Hybrid Multistate Wave Function and Density Functional Theory.
Gao, Jiali; Grofe, Adam; Ren, Haisheng; Bao, Peng
2016-12-15
A multistate density functional theory (MSDFT) is presented in which the energies and densities for the ground and excited states are treated on the same footing using multiconfigurational approaches. The method can be applied to systems with strong correlation and to correctly describe the dimensionality of the conical intersections between strongly coupled dissociative potential energy surfaces. A dynamic-then-static framework for treating electron correlation is developed to first incorporate dynamic correlation into contracted state functions through block-localized Kohn-Sham density functional theory (KSDFT), followed by diagonalization of the effective Hamiltonian to include static correlation. MSDFT can be regarded as a hybrid of wave function and density functional theory. The method is built on and makes use of the current approximate density functional developed in KSDFT, yet it retains its computational efficiency to treat strongly correlated systems that are problematic for KSDFT but too large for accurate WFT. The results presented in this work show that MSDFT can be applied to photochemical processes involving conical intersections.
Liu, Jian; Miller, William H
2011-03-14
We show the exact expression of the quantum mechanical time correlation function in the phase space formulation of quantum mechanics. The trajectory-based dynamics that conserves the quantum canonical distribution-equilibrium Liouville dynamics (ELD) proposed in Paper I is then used to approximately evaluate the exact expression. It gives exact thermal correlation functions (of even nonlinear operators, i.e., nonlinear functions of position or momentum operators) in the classical, high temperature, and harmonic limits. Various methods have been presented for the implementation of ELD. Numerical tests of the ELD approach in the Wigner or Husimi phase space have been made for a harmonic oscillator and two strongly anharmonic model problems, for each potential autocorrelation functions of both linear and nonlinear operators have been calculated. It suggests ELD can be a potentially useful approach for describing quantum effects for complex systems in condense phase.
Executive Functions and Prefrontal Cortex: A Matter of Persistence?
Ball, Gareth; Stokes, Paul R.; Rhodes, Rebecca A.; Bose, Subrata K.; Rezek, Iead; Wink, Alle-Meije; Lord, Louis-David; Mehta, Mitul A.; Grasby, Paul M.; Turkheimer, Federico E.
2011-01-01
Executive function is thought to originates from the dynamics of frontal cortical networks. We examined the dynamic properties of the blood oxygen level dependent time-series measured with functional MRI (fMRI) within the prefrontal cortex (PFC) to test the hypothesis that temporally persistent neural activity underlies performance in three tasks of executive function. A numerical estimate of signal persistence, the Hurst exponent, postulated to represent the coherent firing of cortical networks, was determined and correlated with task performance. Increasing persistence in the lateral PFC was shown to correlate with improved performance during an n-back task. Conversely, we observed a correlation between persistence and increasing commission error – indicating a failure to inhibit a prepotent response – during a Go/No-Go task. We propose that persistence within the PFC reflects dynamic network formation and these findings underline the importance of frequency analysis of fMRI time-series in the study of executive functions. PMID:21286223
Lindquist, Martin A.; Xu, Yuting; Nebel, Mary Beth; Caffo, Brain S.
2014-01-01
To date, most functional Magnetic Resonance Imaging (fMRI) studies have assumed that the functional connectivity (FC) between time series from distinct brain regions is constant across time. However, recently, there has been increased interest in quantifying possible dynamic changes in FC during fMRI experiments, as it is thought this may provide insight into the fundamental workings of brain networks. In this work we focus on the specific problem of estimating the dynamic behavior of pair-wise correlations between time courses extracted from two different regions of the brain. We critique the commonly used sliding-windows technique, and discuss some alternative methods used to model volatility in the finance literature that could also prove useful in the neuroimaging setting. In particular, we focus on the Dynamic Conditional Correlation (DCC) model, which provides a model-based approach towards estimating dynamic correlations. We investigate the properties of several techniques in a series of simulation studies and find that DCC achieves the best overall balance between sensitivity and specificity in detecting dynamic changes in correlations. We also investigate its scalability beyond the bivariate case to demonstrate its utility for studying dynamic correlations between more than two brain regions. Finally, we illustrate its performance in an application to test-retest resting state fMRI data. PMID:24993894
From quantum affine groups to the exact dynamical correlation function of the Heisenberg model
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bougourzi, A.H.; Couture, M.; Kacir, M.
1997-01-20
The exact form factors of the Heisenberg models XXX and XXZ have been recently computed through the quantum affine symmetry of XXZ model in the thermodynamic limit. The authors use them to derive an exact formula for the contribution of two spinons to the dynamical correlation function of XXX model at zero temperature.
Detecting subnetwork-level dynamic correlations.
Yan, Yan; Qiu, Shangzhao; Jin, Zhuxuan; Gong, Sihong; Bai, Yun; Lu, Jianwei; Yu, Tianwei
2017-01-15
The biological regulatory system is highly dynamic. The correlations between many functionally related genes change over different biological conditions. Finding dynamic relations on the existing biological network may reveal important regulatory mechanisms. Currently no method is available to detect subnetwork-level dynamic correlations systematically on the genome-scale network. Two major issues hampered the development. The first is gene expression profiling data usually do not contain time course measurements to facilitate the analysis of dynamic relations, which can be partially addressed by using certain genes as indicators of biological conditions. Secondly, it is unclear how to effectively delineate subnetworks, and define dynamic relations between them. Here we propose a new method named LANDD (Liquid Association for Network Dynamics Detection) to find subnetworks that show substantial dynamic correlations, as defined by subnetwork A is concentrated with Liquid Association scouting genes for subnetwork B. The method produces easily interpretable results because of its focus on subnetworks that tend to comprise functionally related genes. Also, the collective behaviour of genes in a subnetwork is a much more reliable indicator of underlying biological conditions compared to using single genes as indicators. We conducted extensive simulations to validate the method's ability to detect subnetwork-level dynamic correlations. Using a real gene expression dataset and the human protein-protein interaction network, we demonstrate the method links subnetworks of distinct biological processes, with both confirmed relations and plausible new functional implications. We also found signal transduction pathways tend to show extensive dynamic relations with other functional groups. The R package is available at https://cran.r-project.org/web/packages/LANDD CONTACTS: yunba@pcom.edu, jwlu33@hotmail.com or tianwei.yu@emory.eduSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
NASA Astrophysics Data System (ADS)
Ono, Junichi; Takada, Shoji; Saito, Shinji
2015-06-01
An analytical method based on a three-time correlation function and the corresponding two-dimensional (2D) lifetime spectrum is developed to elucidate the time-dependent couplings between the multi-timescale (i.e., hierarchical) conformational dynamics in heterogeneous systems such as proteins. In analogy with 2D NMR, IR, electronic, and fluorescence spectroscopies, the waiting-time dependence of the off-diagonal peaks in the 2D lifetime spectra can provide a quantitative description of the dynamical correlations between the conformational motions with different lifetimes. The present method is applied to intrinsic conformational changes of substrate-free adenylate kinase (AKE) using long-time coarse-grained molecular dynamics simulations. It is found that the hierarchical conformational dynamics arise from the intra-domain structural transitions among conformational substates of AKE by analyzing the one-time correlation functions and one-dimensional lifetime spectra for the donor-acceptor distances corresponding to single-molecule Förster resonance energy transfer experiments with the use of the principal component analysis. In addition, the complicated waiting-time dependence of the off-diagonal peaks in the 2D lifetime spectra for the donor-acceptor distances is attributed to the fact that the time evolution of the couplings between the conformational dynamics depends upon both the spatial and temporal characters of the system. The present method is expected to shed light on the biological relationship among the structure, dynamics, and function.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ono, Junichi; Takada, Shoji; Department of Biophysics, Graduate School of Science, Kyoto University, Kyoto 606-8502
2015-06-07
An analytical method based on a three-time correlation function and the corresponding two-dimensional (2D) lifetime spectrum is developed to elucidate the time-dependent couplings between the multi-timescale (i.e., hierarchical) conformational dynamics in heterogeneous systems such as proteins. In analogy with 2D NMR, IR, electronic, and fluorescence spectroscopies, the waiting-time dependence of the off-diagonal peaks in the 2D lifetime spectra can provide a quantitative description of the dynamical correlations between the conformational motions with different lifetimes. The present method is applied to intrinsic conformational changes of substrate-free adenylate kinase (AKE) using long-time coarse-grained molecular dynamics simulations. It is found that the hierarchicalmore » conformational dynamics arise from the intra-domain structural transitions among conformational substates of AKE by analyzing the one-time correlation functions and one-dimensional lifetime spectra for the donor-acceptor distances corresponding to single-molecule Förster resonance energy transfer experiments with the use of the principal component analysis. In addition, the complicated waiting-time dependence of the off-diagonal peaks in the 2D lifetime spectra for the donor-acceptor distances is attributed to the fact that the time evolution of the couplings between the conformational dynamics depends upon both the spatial and temporal characters of the system. The present method is expected to shed light on the biological relationship among the structure, dynamics, and function.« less
Stochastic dynamics of time correlation in complex systems with discrete time
NASA Astrophysics Data System (ADS)
Yulmetyev, Renat; Hänggi, Peter; Gafarov, Fail
2000-11-01
In this paper we present the concept of description of random processes in complex systems with discrete time. It involves the description of kinetics of discrete processes by means of the chain of finite-difference non-Markov equations for time correlation functions (TCFs). We have introduced the dynamic (time dependent) information Shannon entropy Si(t) where i=0,1,2,3,..., as an information measure of stochastic dynamics of time correlation (i=0) and time memory (i=1,2,3,...). The set of functions Si(t) constitute the quantitative measure of time correlation disorder (i=0) and time memory disorder (i=1,2,3,...) in complex system. The theory developed started from the careful analysis of time correlation involving dynamics of vectors set of various chaotic states. We examine two stochastic processes involving the creation and annihilation of time correlation (or time memory) in details. We carry out the analysis of vectors' dynamics employing finite-difference equations for random variables and the evolution operator describing their natural motion. The existence of TCF results in the construction of the set of projection operators by the usage of scalar product operation. Harnessing the infinite set of orthogonal dynamic random variables on a basis of Gram-Shmidt orthogonalization procedure tends to creation of infinite chain of finite-difference non-Markov kinetic equations for discrete TCFs and memory functions (MFs). The solution of the equations above thereof brings to the recurrence relations between the TCF and MF of senior and junior orders. This offers new opportunities for detecting the frequency spectra of power of entropy function Si(t) for time correlation (i=0) and time memory (i=1,2,3,...). The results obtained offer considerable scope for attack on stochastic dynamics of discrete random processes in a complex systems. Application of this technique on the analysis of stochastic dynamics of RR intervals from human ECG's shows convincing evidence for a non-Markovian phenomemena associated with a peculiarities in short- and long-range scaling. This method may be of use in distinguishing healthy from pathologic data sets based in differences in these non-Markovian properties.
NASA Astrophysics Data System (ADS)
Seidu, Azimatu; Marini, Andrea; Gatti, Matteo
2018-03-01
Beryllium is a weakly correlated simple metal. Still we find that dynamical correlation effects, beyond the independent-particle picture, are necessary to successfully interpret the electronic spectra measured by inelastic x-ray scattering (IXS) and photoemission spectroscopies (PES). By combining ab initio time-dependent density-functional theory (TDDFT) and many-body Green's function theory in the G W approximation (G W A ), we calculate the dynamic structure factor, the quasiparticle (QP) properties and PES spectra of bulk Be. We show that band-structure effects (i.e., due to interaction with the crystal potential) and QP lifetimes (LT) are both needed in order to explain the origin of the measured double-peak features in the IXS spectra. A quantitative agreement with experiment is obtained only when LT are supplemented to the adiabatic local-density approximation (ALDA) of TDDFT. Besides the valence band, PES spectra display a satellite, a signature of dynamical correlation due to the coupling of QPs and plasmons, which we are able to reproduce thanks to the combination of the G W A for the self-energy with the cumulant expansion of the Green's function.
Cendagorta, Joseph R; Bačić, Zlatko; Tuckerman, Mark E
2018-03-14
We introduce a scheme for approximating quantum time correlation functions numerically within the Feynman path integral formulation. Starting with the symmetrized version of the correlation function expressed as a discretized path integral, we introduce a change of integration variables often used in the derivation of trajectory-based semiclassical methods. In particular, we transform to sum and difference variables between forward and backward complex-time propagation paths. Once the transformation is performed, the potential energy is expanded in powers of the difference variables, which allows us to perform the integrals over these variables analytically. The manner in which this procedure is carried out results in an open-chain path integral (in the remaining sum variables) with a modified potential that is evaluated using imaginary-time path-integral sampling rather than requiring the generation of a large ensemble of trajectories. Consequently, any number of path integral sampling schemes can be employed to compute the remaining path integral, including Monte Carlo, path-integral molecular dynamics, or enhanced path-integral molecular dynamics. We believe that this approach constitutes a different perspective in semiclassical-type approximations to quantum time correlation functions. Importantly, we argue that our approximation can be systematically improved within a cumulant expansion formalism. We test this approximation on a set of one-dimensional problems that are commonly used to benchmark approximate quantum dynamical schemes. We show that the method is at least as accurate as the popular ring-polymer molecular dynamics technique and linearized semiclassical initial value representation for correlation functions of linear operators in most of these examples and improves the accuracy of correlation functions of nonlinear operators.
NASA Astrophysics Data System (ADS)
Cendagorta, Joseph R.; Bačić, Zlatko; Tuckerman, Mark E.
2018-03-01
We introduce a scheme for approximating quantum time correlation functions numerically within the Feynman path integral formulation. Starting with the symmetrized version of the correlation function expressed as a discretized path integral, we introduce a change of integration variables often used in the derivation of trajectory-based semiclassical methods. In particular, we transform to sum and difference variables between forward and backward complex-time propagation paths. Once the transformation is performed, the potential energy is expanded in powers of the difference variables, which allows us to perform the integrals over these variables analytically. The manner in which this procedure is carried out results in an open-chain path integral (in the remaining sum variables) with a modified potential that is evaluated using imaginary-time path-integral sampling rather than requiring the generation of a large ensemble of trajectories. Consequently, any number of path integral sampling schemes can be employed to compute the remaining path integral, including Monte Carlo, path-integral molecular dynamics, or enhanced path-integral molecular dynamics. We believe that this approach constitutes a different perspective in semiclassical-type approximations to quantum time correlation functions. Importantly, we argue that our approximation can be systematically improved within a cumulant expansion formalism. We test this approximation on a set of one-dimensional problems that are commonly used to benchmark approximate quantum dynamical schemes. We show that the method is at least as accurate as the popular ring-polymer molecular dynamics technique and linearized semiclassical initial value representation for correlation functions of linear operators in most of these examples and improves the accuracy of correlation functions of nonlinear operators.
Temperature dependent structural and dynamical properties of liquid Cu80Si20 binary alloy
NASA Astrophysics Data System (ADS)
Suthar, P. H.; Shah, A. K.; Gajjar, P. N.
2018-05-01
Ashcroft and Langreth binary structure factor have been used to study for pair correlation function and the study of dynamical variable: velocity auto correlation functions, power spectrum and mean square displacement calculated based on the static harmonic well approximation in liquid Cu80Si20 binary alloy at wide temperature range (1140K, 1175K, 1210K, 1250K, 1373K, 1473K.). The effective interaction for the binary alloy is computed by our well established local pseudopotential along with the exchange and correction functions Sarkar et al(S). The negative dip in velocity auto correlation decreases as the various temperature is increases. For power spectrum as temperature increases, the peak of power spectrum shifts toward lower ω. Good agreement with the experiment is observed for the pair correlation functions. Velocity auto correlation showing the transferability of the local pseudopotential used for metallic liquid environment in the case of copper based binary alloys.
Electron Correlation from the Adiabatic Connection for Multireference Wave Functions
NASA Astrophysics Data System (ADS)
Pernal, Katarzyna
2018-01-01
An adiabatic connection (AC) formula for the electron correlation energy is derived for a broad class of multireference wave functions. The AC expression recovers dynamic correlation energy and assures a balanced treatment of the correlation energy. Coupling the AC formalism with the extended random phase approximation allows one to find the correlation energy only from reference one- and two-electron reduced density matrices. If the generalized valence bond perfect pairing model is employed a simple closed-form expression for the approximate AC formula is obtained. This results in the overall M5 scaling of the computation cost making the method one of the most efficient multireference approaches accounting for dynamic electron correlation also for the strongly correlated systems.
Scrambling and thermalization in a diffusive quantum many-body system
Bohrdt, A.; Mendl, C. B.; Endres, M.; ...
2017-06-02
Out-of-time ordered (OTO) correlation functions describe scrambling of information in correlated quantum matter. They are of particular interest in incoherent quantum systems lacking well defined quasi-particles. Thus far, it is largely elusive how OTO correlators spread in incoherent systems with diffusive transport governed by a few globally conserved quantities. Here, we study the dynamical response of such a system using high-performance matrix-product-operator techniques. Specifically, we consider the non-integrable, one-dimensional Bose–Hubbard model in the incoherent high-temperature regime. Our system exhibits diffusive dynamics in time-ordered correlators of globally conserved quantities, whereas OTO correlators display a ballistic, light-cone spreading of quantum information. Themore » slowest process in the global thermalization of the system is thus diffusive, yet information spreading is not inhibited by such slow dynamics. We furthermore develop an experimentally feasible protocol to overcome some challenges faced by existing proposals and to probe time-ordered and OTO correlation functions. As a result, our study opens new avenues for both the theoretical and experimental exploration of thermalization and information scrambling dynamics.« less
Scrambling and thermalization in a diffusive quantum many-body system
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bohrdt, A.; Mendl, C. B.; Endres, M.
Out-of-time ordered (OTO) correlation functions describe scrambling of information in correlated quantum matter. They are of particular interest in incoherent quantum systems lacking well defined quasi-particles. Thus far, it is largely elusive how OTO correlators spread in incoherent systems with diffusive transport governed by a few globally conserved quantities. Here, we study the dynamical response of such a system using high-performance matrix-product-operator techniques. Specifically, we consider the non-integrable, one-dimensional Bose–Hubbard model in the incoherent high-temperature regime. Our system exhibits diffusive dynamics in time-ordered correlators of globally conserved quantities, whereas OTO correlators display a ballistic, light-cone spreading of quantum information. Themore » slowest process in the global thermalization of the system is thus diffusive, yet information spreading is not inhibited by such slow dynamics. We furthermore develop an experimentally feasible protocol to overcome some challenges faced by existing proposals and to probe time-ordered and OTO correlation functions. As a result, our study opens new avenues for both the theoretical and experimental exploration of thermalization and information scrambling dynamics.« less
Kananenka, Alexei A; Zgid, Dominika
2017-11-14
We present a rigorous framework which combines single-particle Green's function theory with density functional theory based on a separation of electron-electron interactions into short- and long-range components. Short-range contribution to the total energy and exchange-correlation potential is provided by a density functional approximation, while the long-range contribution is calculated using an explicit many-body Green's function method. Such a hybrid results in a nonlocal, dynamic, and orbital-dependent exchange-correlation functional of a single-particle Green's function. In particular, we present a range-separated hybrid functional called srSVWN5-lrGF2 which combines the local-density approximation and the second-order Green's function theory. We illustrate that similarly to density functional approximations, the new functional is weakly basis-set dependent. Furthermore, it offers an improved description of the short-range dynamic correlation. The many-body contribution to the functional mitigates the many-electron self-interaction error present in many density functional approximations and provides a better description of molecular properties. Additionally, we illustrate that the new functional can be used to scale down the self-energy and, therefore, introduce an additional sparsity to the self-energy matrix that in the future can be exploited in calculations for large molecules or periodic systems.
NASA Astrophysics Data System (ADS)
Hao, Qing-Hai; You, Yu-Wei; Kong, Xiang-Shan; Liu, C. S.
2013-03-01
The microscopic structure and dynamics of liquid MgxBi1-x(x = 0.5, 0.6, 0.7) alloys together with pure liquid Mg and Bi metals were investigated by means of ab initio molecular dynamics simulations. We present results of structure properties including pair correlation function, structural factor, bond-angle distribution function and bond order parameter, and their composition dependence. The dynamical and electronic properties have also been studied. The structure factor and pair correlation function are in agreement with the available experimental data. The calculated bond-angle distribution function and bond order parameter suggest that the stoichiometric composition Mg3Bi2 exhibits a different local structure order compared with other concentrations, which help us understand the appearance of the minimum electronic conductivity at this composition observed in previous experiments.
Short-range density functional correlation within the restricted active space CI method
NASA Astrophysics Data System (ADS)
Casanova, David
2018-03-01
In the present work, I introduce a hybrid wave function-density functional theory electronic structure method based on the range separation of the electron-electron Coulomb operator in order to recover dynamic electron correlations missed in the restricted active space configuration interaction (RASCI) methodology. The working equations and the computational algorithm for the implementation of the new approach, i.e., RAS-srDFT, are presented, and the method is tested in the calculation of excitation energies of organic molecules. The good performance of the RASCI wave function in combination with different short-range exchange-correlation functionals in the computation of relative energies represents a quantitative improvement with respect to the RASCI results and paves the path for the development of RAS-srDFT as a promising scheme in the computation of the ground and excited states where nondynamic and dynamic electron correlations are important.
Dynamics of a spin-boson model with structured spectral density
NASA Astrophysics Data System (ADS)
Kurt, Arzu; Eryigit, Resul
2018-05-01
We report the results of a study of the dynamics of a two-state system coupled to an environment with peaked spectral density. An exact analytical expression for the bath correlation function is obtained. Validity range of various approximations to the correlation function for calculating the population difference of the system is discussed as function of tunneling splitting, oscillator frequency, coupling constant, damping rate and the temperature of the bath. An exact expression for the population difference, for a limited range of parameters, is derived.
NASA Astrophysics Data System (ADS)
Levashov, Valentin A.; Morris, James R.; Egami, Takeshi
2012-02-01
Temporal and spatial correlations among the local atomic level shear stresses were studied for a model liquid iron by molecular dynamics simulation [PRL 106,115703]. Integration over time and space of the shear stress correlation function F(r,t) yields viscosity via Green-Kubo relation. The stress correlation function in time and space F(r,t) was Fourier transformed to study the dependence on frequency, E, and wave vector, Q. The results, F(Q,E), showed damped shear stress waves propagating in the liquid for small Q at high and low temperatures. We also observed additional diffuse feature that appears as temperature is reduced below crossover temperature of potential energy landscape at relatively low frequencies at small Q. We suggest that this additional feature might be related to dynamic heterogeneity and boson peaks. We also discuss a relation between the time-scale of the stress-stress correlation function and the alpha-relaxation time of the intermediate self-scattering function S(Q,E).
Moustafa, Ibrahim M.; Shen, Hujun; Morton, Brandon; Colina, Coray M.; Cameron, Craig E.
2011-01-01
The viral RNA-dependent RNA polymerase (RdRp) is essential for multiplication of all RNA viruses. The sequence diversity of an RNA virus population contributes to its ability to infect the host. This diversity emanates from errors made by the RdRp during RNA synthesis. The physical basis for RdRp fidelity is unclear but is linked to conformational changes occurring during the nucleotide-addition cycle. To understand RdRp dynamics that might influence RdRp function, we have analyzed all-atom molecular dynamics (MD) simulations on the nanosecond timescale of four RdRps from the picornavirus family that exhibit 30–74% sequence identity. Principal component analysis showed that the major motions observed during the simulations derived from conserved structural motifs and regions of known function. Dynamics of residues participating in the same biochemical property, for example RNA binding, nucleotide binding or catalysis, were correlated even when spatially distant on the RdRp structure. The conserved and correlated dynamics of functional, structural elements suggest co-evolution of dynamics with structure and function of the RdRp. Crystal structures of all picornavirus RdRps exhibit a template-nascent RNA duplex channel too small to fully accommodate duplex RNA. Simulations revealed opening and closing motions of the RNA and NTP channels, which might be relevant to NTP entry, PPi exit and translocation. A role for nanosecond timescale dynamics in RdRp fidelity is supported by altered dynamics of the high-fidelity G64S derivative of PV RdRp relative to wild-type enzyme. PMID:21575642
Signals of dynamical and statistical process from IMF-IMF correlation function
NASA Astrophysics Data System (ADS)
Pagano, E. V.; Acosta, L.; Auditore, L.; Baran, V.; Cap, T.; Cardella, G.; Colonna, M.; De Luca, S.; De Filippo, E.; Dell'Aquila, D.; Francalanza, L.; Gnoffo, B.; Lanzalone, G.; Lombardo, I.; Maiolino, C.; Martorana, N. S.; Norella, S.; Pagano, A.; Papa, M.; Piasecki, E.; Pirrone, S.; Politi, G.; Porto, F.; Quattrocchi, L.; Rizzo, F.; Rosato, E.; Russotto, P.; Siwek-Wilczyńska, K.; Trifiro, A.; Trimarchi, M.; Verde, G.; Vigilante, M.; Wilczyńsky, J.
2017-11-01
In this paper we briefly discuss about a novel application of the IMF-IMF correlation function to the physical case of binary massive projectile-like (PLF) splitting for dynamical and statistical breakup/fission in heavy ion collisions at Fermi energy. Theoretical simulations are also shown for comparisons with the data. These preliminary results have been obtained for the reverse kinematics reaction 124Sn + 64Ni at 35 AMeV that was studied using the forward part of CHIMERA detector. In that reaction a strong competition between a dynamical and a statistical components and its evolution with the charge asymmetry of the binary break up was already shown. In this work we show that the IMF-IMF correlation function can be used to pin down the timescale of the fragments production in binary fission-like phenomena. We also made simulations with the CoMDII model in order to compare to the experimental IMF-IMF correlation function. In future we plan to extend these studies to different reaction mechanisms and nuclear systems and to compare with different theoretical transport simulations.
Biswas, Sohag; Mallik, Bhabani S
2017-04-12
The fluctuation dynamics of amine stretching frequencies, hydrogen bonds, dangling N-D bonds, and the orientation profile of the amine group of methylamine (MA) were investigated under ambient conditions by means of dispersion-corrected density functional theory-based first principles molecular dynamics (FPMD) simulations. Along with the dynamical properties, various equilibrium properties such as radial distribution function, spatial distribution function, combined radial and angular distribution functions and hydrogen bonding were also calculated. The instantaneous stretching frequencies of amine groups were obtained by wavelet transform of the trajectory obtained from FPMD simulations. The frequency-structure correlation reveals that the amine stretching frequency is weakly correlated with the nearest nitrogen-deuterium distance. The frequency-frequency correlation function has a short time scale of around 110 fs and a longer time scale of about 1.15 ps. It was found that the short time scale originates from the underdamped motion of intact hydrogen bonds of MA pairs. However, the long time scale of the vibrational spectral diffusion of N-D modes is determined by the overall dynamics of hydrogen bonds as well as the dangling ND groups and the inertial rotation of the amine group of the molecule.
Stabilization of Polar Nanoregions in Pb-free Ferroelectrics
Pramanick, A.; Dmowski, Wojciech; Egami, Takeshi; ...
2018-05-18
In this study, the formation of polar nanoregions through solid-solution additions is known to enhance significantly the functional properties of ferroelectric materials. Despite considerable progress in characterizing the microscopic behavior of polar nanoregions (PNR), understanding their real-space atomic structure and dynamics of their formation remains a considerable challenge. Here, using the method of dynamic pair distribution function, we provide direct insights into the role of solid-solution additions towards the stabilization of polar nanoregions in the Pb-free ferroelectric of Ba(Zr,Ti)O 3. It is shown that for an optimum level of substitution of Ti by larger Zr ions, the dynamics of atomicmore » displacements for ferroelectric polarization are slowed sufficiently below THz frequencies, which leads to increased local correlation among dipoles within PNRs. The dynamic pair distribution function technique demonstrates a unique capability to obtain insights into locally correlated atomic dynamics in disordered materials, including new Pb-free ferroelectrics, which is necessary to understand and control their functional properties.« less
Stabilization of Polar Nanoregions in Pb-free Ferroelectrics
NASA Astrophysics Data System (ADS)
Pramanick, A.; Dmowski, W.; Egami, T.; Budisuharto, A. Setiadi; Weyland, F.; Novak, N.; Christianson, A. D.; Borreguero, J. M.; Abernathy, D. L.; Jørgensen, M. R. V.
2018-05-01
The formation of polar nanoregions through solid-solution additions is known to enhance significantly the functional properties of ferroelectric materials. Despite considerable progress in characterizing the microscopic behavior of polar nanoregions (PNR), understanding their real-space atomic structure and dynamics of their formation remains a considerable challenge. Here, using the method of dynamic pair distribution function, we provide direct insights into the role of solid-solution additions towards the stabilization of polar nanoregions in the Pb-free ferroelectric of Ba (Zr ,Ti )O3 . It is shown that for an optimum level of substitution of Ti by larger Zr ions, the dynamics of atomic displacements for ferroelectric polarization are slowed sufficiently below THz frequencies, which leads to increased local correlation among dipoles within PNRs. The dynamic pair distribution function technique demonstrates a unique capability to obtain insights into locally correlated atomic dynamics in disordered materials, including new Pb-free ferroelectrics, which is necessary to understand and control their functional properties.
Stabilization of Polar Nanoregions in Pb-free Ferroelectrics
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pramanick, A.; Dmowski, Wojciech; Egami, Takeshi
In this study, the formation of polar nanoregions through solid-solution additions is known to enhance significantly the functional properties of ferroelectric materials. Despite considerable progress in characterizing the microscopic behavior of polar nanoregions (PNR), understanding their real-space atomic structure and dynamics of their formation remains a considerable challenge. Here, using the method of dynamic pair distribution function, we provide direct insights into the role of solid-solution additions towards the stabilization of polar nanoregions in the Pb-free ferroelectric of Ba(Zr,Ti)O 3. It is shown that for an optimum level of substitution of Ti by larger Zr ions, the dynamics of atomicmore » displacements for ferroelectric polarization are slowed sufficiently below THz frequencies, which leads to increased local correlation among dipoles within PNRs. The dynamic pair distribution function technique demonstrates a unique capability to obtain insights into locally correlated atomic dynamics in disordered materials, including new Pb-free ferroelectrics, which is necessary to understand and control their functional properties.« less
Siqueira, Leonardo J A; Ribeiro, Mauro C C
2006-12-07
The dynamical properties of the polymer electrolyte poly(ethylene oxide) (PEO)LiClO(4) have been investigated by molecular dynamics simulations. The effect of changing salt concentration and temperature was evaluated on several time correlation functions. Ionic displacements projected on different directions reveal anisotropy in short-time (rattling) and long-time (diffusive) dynamics of Li(+) cations. It is shown that ionic mobility is coupled to the segmental motion of the polymeric chain. Structural relaxation is probed by the intermediate scattering function F(k,t) at several wave vectors. Good agreement was found between calculated and experimental F(k,t) for pure PEO. A remarkable slowing down of polymer relaxation is observed upon addition of the salt. The ionic conductivity estimated by the Nernst-Einstein equation is approximately ten times higher than the actual conductivity calculated by the time correlation function of charge current.
How Volatilities Nonlocal in Time Affect the Price Dynamics in Complex Financial Systems
Tan, Lei; Zheng, Bo; Chen, Jun-Jie; Jiang, Xiong-Fei
2015-01-01
What is the dominating mechanism of the price dynamics in financial systems is of great interest to scientists. The problem whether and how volatilities affect the price movement draws much attention. Although many efforts have been made, it remains challenging. Physicists usually apply the concepts and methods in statistical physics, such as temporal correlation functions, to study financial dynamics. However, the usual volatility-return correlation function, which is local in time, typically fluctuates around zero. Here we construct dynamic observables nonlocal in time to explore the volatility-return correlation, based on the empirical data of hundreds of individual stocks and 25 stock market indices in different countries. Strikingly, the correlation is discovered to be non-zero, with an amplitude of a few percent and a duration of over two weeks. This result provides compelling evidence that past volatilities nonlocal in time affect future returns. Further, we introduce an agent-based model with a novel mechanism, that is, the asymmetric trading preference in volatile and stable markets, to understand the microscopic origin of the volatility-return correlation nonlocal in time. PMID:25723154
Dynamical potentials for nonequilibrium quantum many-body phases
NASA Astrophysics Data System (ADS)
Roy, Sthitadhi; Lazarides, Achilleas; Heyl, Markus; Moessner, Roderich
2018-05-01
Out of equilibrium phases of matter exhibiting order in individual eigenstates, such as many-body localized spin glasses and discrete time crystals, can be characterized by inherently dynamical quantities such as spatiotemporal correlation functions. In this paper, we introduce dynamical potentials which act as generating functions for such correlations and capture eigenstate phases and order. These potentials show formal similarities to their equilibrium counterparts, namely thermodynamic potentials. We provide three representative examples: a disordered XXZ chain showing many-body localization, a disordered Ising chain exhibiting spin-glass order, and its periodically-driven cousin exhibiting time-crystalline order.
Observation of dynamic atom-atom correlation in liquid helium in real space
Dmowski, W.; Diallo, S. O.; Lokshin, K.; ...
2017-05-04
Liquid 4He becomes superfluid and flows without resistance below temperature 2.17 K. Superfluidity has been a subject of intense studies and notable advances were made in elucidating the phenomenon by experiment and theory. Nevertheless, details of the microscopic state, including dynamic atom–atom correlations in the superfluid state, are not fully understood. Here using a technique of neutron dynamic pair-density function (DPDF) analysis we show that 4He atoms in the Bose–Einstein condensate have environment significantly different from uncondensed atoms, with the interatomic distance larger than the average by about 10%, whereas the average structure changes little through the superfluid transition. DPDFmore » peak not seen in the snap-shot pair-density function is found at 2.3 Å, and is interpreted in terms of atomic tunnelling. The real space picture of dynamic atom–atom correlations presented here reveal characteristics of atomic dynamics not recognized so far, compelling yet another look at the phenomenon.« less
Observation of dynamic atom-atom correlation in liquid helium in real space
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dmowski, W.; Diallo, S. O.; Lokshin, K.
Liquid 4He becomes superfluid and flows without resistance below temperature 2.17 K. Superfluidity has been a subject of intense studies and notable advances were made in elucidating the phenomenon by experiment and theory. Nevertheless, details of the microscopic state, including dynamic atom–atom correlations in the superfluid state, are not fully understood. Here using a technique of neutron dynamic pair-density function (DPDF) analysis we show that 4He atoms in the Bose–Einstein condensate have environment significantly different from uncondensed atoms, with the interatomic distance larger than the average by about 10%, whereas the average structure changes little through the superfluid transition. DPDFmore » peak not seen in the snap-shot pair-density function is found at 2.3 Å, and is interpreted in terms of atomic tunnelling. The real space picture of dynamic atom–atom correlations presented here reveal characteristics of atomic dynamics not recognized so far, compelling yet another look at the phenomenon.« less
Observation of dynamic atom-atom correlation in liquid helium in real space.
Dmowski, W; Diallo, S O; Lokshin, K; Ehlers, G; Ferré, G; Boronat, J; Egami, T
2017-05-04
Liquid 4 He becomes superfluid and flows without resistance below temperature 2.17 K. Superfluidity has been a subject of intense studies and notable advances were made in elucidating the phenomenon by experiment and theory. Nevertheless, details of the microscopic state, including dynamic atom-atom correlations in the superfluid state, are not fully understood. Here using a technique of neutron dynamic pair-density function (DPDF) analysis we show that 4 He atoms in the Bose-Einstein condensate have environment significantly different from uncondensed atoms, with the interatomic distance larger than the average by about 10%, whereas the average structure changes little through the superfluid transition. DPDF peak not seen in the snap-shot pair-density function is found at 2.3 Å, and is interpreted in terms of atomic tunnelling. The real space picture of dynamic atom-atom correlations presented here reveal characteristics of atomic dynamics not recognized so far, compelling yet another look at the phenomenon.
Are Covert Saccade Functionally Relevant in Vestibular Hypofunction?
Hermann, R; Pelisson, D; Dumas, O; Urquizar, Ch; Truy, E; Tilikete, C
2018-06-01
The vestibulo-ocular reflex maintains gaze stabilization during angular or linear head accelerations, allowing adequate dynamic visual acuity. In case of bilateral vestibular hypofunction, patients use saccades to compensate for the reduced vestibulo-ocular reflex function, with covert saccades occurring even during the head displacement. In this study, we questioned whether covert saccades help maintain dynamic visual acuity, and evaluated which characteristic of these saccades are the most relevant to improve visual function. We prospectively included 18 patients with chronic bilateral vestibular hypofunction. Subjects underwent evaluation of dynamic visual acuity in the horizontal plane as well as video recording of their head and eye positions during horizontal head impulse tests in both directions (36 ears tested). Frequency, latency, consistency of covert saccade initiation, and gain of covert saccades as well as residual vestibulo-ocular reflex gain were calculated. We found no correlation between residual vestibulo-ocular reflex gain and dynamic visual acuity. Dynamic visual acuity performance was however positively correlated with the frequency and gain of covert saccades and negatively correlated with covert saccade latency. There was no correlation between consistency of covert saccade initiation and dynamic visual acuity. Even though gaze stabilization in space during covert saccades might be of very short duration, these refixation saccades seem to improve vision in patients with bilateral vestibular hypofunction during angular head impulses. These findings emphasize the need for specific rehabilitation technics that favor the triggering of covert saccades. The physiological origin of covert saccades is discussed.
Thermal quantum time-correlation functions from classical-like dynamics
NASA Astrophysics Data System (ADS)
Hele, Timothy J. H.
2017-07-01
Thermal quantum time-correlation functions are of fundamental importance in quantum dynamics, allowing experimentally measurable properties such as reaction rates, diffusion constants and vibrational spectra to be computed from first principles. Since the exact quantum solution scales exponentially with system size, there has been considerable effort in formulating reliable linear-scaling methods involving exact quantum statistics and approximate quantum dynamics modelled with classical-like trajectories. Here, we review recent progress in the field with the development of methods including centroid molecular dynamics , ring polymer molecular dynamics (RPMD) and thermostatted RPMD (TRPMD). We show how these methods have recently been obtained from 'Matsubara dynamics', a form of semiclassical dynamics which conserves the quantum Boltzmann distribution. We also apply the Matsubara formalism to reaction rate theory, rederiving t → 0+ quantum transition-state theory (QTST) and showing that Matsubara-TST, like RPMD-TST, is equivalent to QTST. We end by surveying areas for future progress.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hedegård, Erik Donovan, E-mail: erik.hedegard@phys.chem.ethz.ch; Knecht, Stefan; Reiher, Markus, E-mail: markus.reiher@phys.chem.ethz.ch
2015-06-14
We present a new hybrid multiconfigurational method based on the concept of range-separation that combines the density matrix renormalization group approach with density functional theory. This new method is designed for the simultaneous description of dynamical and static electron-correlation effects in multiconfigurational electronic structure problems.
Detecting nonlinear dynamics of functional connectivity
NASA Astrophysics Data System (ADS)
LaConte, Stephen M.; Peltier, Scott J.; Kadah, Yasser; Ngan, Shing-Chung; Deshpande, Gopikrishna; Hu, Xiaoping
2004-04-01
Functional magnetic resonance imaging (fMRI) is a technique that is sensitive to correlates of neuronal activity. The application of fMRI to measure functional connectivity of related brain regions across hemispheres (e.g. left and right motor cortices) has great potential for revealing fundamental physiological brain processes. Primarily, functional connectivity has been characterized by linear correlations in resting-state data, which may not provide a complete description of its temporal properties. In this work, we broaden the measure of functional connectivity to study not only linear correlations, but also those arising from deterministic, non-linear dynamics. Here the delta-epsilon approach is extended and applied to fMRI time series. The method of delays is used to reconstruct the joint system defined by a reference pixel and a candidate pixel. The crux of this technique relies on determining whether the candidate pixel provides additional information concerning the time evolution of the reference. As in many correlation-based connectivity studies, we fix the reference pixel. Every brain location is then used as a candidate pixel to estimate the spatial pattern of deterministic coupling with the reference. Our results indicate that measured connectivity is often emphasized in the motor cortex contra-lateral to the reference pixel, demonstrating the suitability of this approach for functional connectivity studies. In addition, discrepancies with traditional correlation analysis provide initial evidence for non-linear dynamical properties of resting-state fMRI data. Consequently, the non-linear characterization provided from our approach may provide a more complete description of the underlying physiology and brain function measured by this type of data.
Arbuznikov, Alexei V; Kaupp, Martin
2012-01-07
Local hybrid functionals with their position-dependent exact-exchange admixture are a conceptually simple and promising extension of the concept of a hybrid functional. Local hybrids based on a simple mixing of the local spin density approximation (LSDA) with exact exchange have been shown to be successful for thermochemistry, reaction barriers, and a range of other properties. So far, the combination of this generation of local hybrids with an LSDA correlation functional has been found to give the most favorable results for atomization energies, for a range of local mixing functions (LMFs) governing the exact-exchange admixture. Here, we show that the choice of correlation functional to be used with local hybrid exchange crucially influences the parameterization also of the exchange part as well as the overall performance. A novel ansatz for the correlation part of local hybrids is suggested based on (i) range-separation of LSDA correlation into short-range (SR) and long-range (LR) parts, and (ii) partial or full elimination of the one-electron self-correlation from the SR part. It is shown that such modified correlation functionals allow overall larger exact exchange admixture in thermochemically competitive local hybrids than before. This results in improvements for reaction barriers and for other properties crucially influenced by self-interaction errors, as demonstrated by a number of examples. Based on the range-separation approach, a fresh view on the breakdown of the correlation energy into dynamical and non-dynamical parts is suggested.
NASA Astrophysics Data System (ADS)
Inoue, Makoto
2017-12-01
Some new formulae of the canonical correlation functions for the one dimensional quantum transverse Ising model are found by the ST-transformation method using a Morita's sum rule and its extensions for the two dimensional classical Ising model. As a consequence we obtain a time-independent term of the dynamical correlation functions. Differences of quantum version and classical version of these formulae are also discussed.
Piccoli, Tommaso; Valente, Giancarlo; Linden, David E J; Re, Marta; Esposito, Fabrizio; Sack, Alexander T; Di Salle, Francesco
2015-01-01
The default mode network and the working memory network are known to be anti-correlated during sustained cognitive processing, in a load-dependent manner. We hypothesized that functional connectivity among nodes of the two networks could be dynamically modulated by task phases across time. To address the dynamic links between default mode network and the working memory network, we used a delayed visuo-spatial working memory paradigm, which allowed us to separate three different phases of working memory (encoding, maintenance, and retrieval), and analyzed the functional connectivity during each phase within and between the default mode network and the working memory network networks. We found that the two networks are anti-correlated only during the maintenance phase of working memory, i.e. when attention is focused on a memorized stimulus in the absence of external input. Conversely, during the encoding and retrieval phases, when the external stimulation is present, the default mode network is positively coupled with the working memory network, suggesting the existence of a dynamically switching of functional connectivity between "task-positive" and "task-negative" brain networks. Our results demonstrate that the well-established dichotomy of the human brain (anti-correlated networks during rest and balanced activation-deactivation during cognition) has a more nuanced organization than previously thought and engages in different patterns of correlation and anti-correlation during specific sub-phases of a cognitive task. This nuanced organization reinforces the hypothesis of a direct involvement of the default mode network in cognitive functions, as represented by a dynamic rather than static interaction with specific task-positive networks, such as the working memory network.
Piccoli, Tommaso; Valente, Giancarlo; Linden, David E. J.; Re, Marta; Esposito, Fabrizio; Sack, Alexander T.; Salle, Francesco Di
2015-01-01
Introduction The default mode network and the working memory network are known to be anti-correlated during sustained cognitive processing, in a load-dependent manner. We hypothesized that functional connectivity among nodes of the two networks could be dynamically modulated by task phases across time. Methods To address the dynamic links between default mode network and the working memory network, we used a delayed visuo-spatial working memory paradigm, which allowed us to separate three different phases of working memory (encoding, maintenance, and retrieval), and analyzed the functional connectivity during each phase within and between the default mode network and the working memory network networks. Results We found that the two networks are anti-correlated only during the maintenance phase of working memory, i.e. when attention is focused on a memorized stimulus in the absence of external input. Conversely, during the encoding and retrieval phases, when the external stimulation is present, the default mode network is positively coupled with the working memory network, suggesting the existence of a dynamically switching of functional connectivity between “task-positive” and “task-negative” brain networks. Conclusions Our results demonstrate that the well-established dichotomy of the human brain (anti-correlated networks during rest and balanced activation-deactivation during cognition) has a more nuanced organization than previously thought and engages in different patterns of correlation and anti-correlation during specific sub-phases of a cognitive task. This nuanced organization reinforces the hypothesis of a direct involvement of the default mode network in cognitive functions, as represented by a dynamic rather than static interaction with specific task-positive networks, such as the working memory network. PMID:25848951
Surface and finite size effect on fluctuations dynamics in nanoparticles with long-range order
NASA Astrophysics Data System (ADS)
Morozovska, A. N.; Eliseev, E. A.
2010-02-01
The influence of surface and finite size on the dynamics of the order parameter fluctuations and critical phenomena in the three-dimensional (3D)-confined systems with long-range order was not considered theoretically. In this paper, we study the influence of surface and finite size on the dynamics of the order parameter fluctuations in the particles of arbitrary shape. We consider concrete examples of the spherical and cylindrical ferroic nanoparticles within Landau-Ginzburg-Devonshire phenomenological approach. Allowing for the strong surface energy contribution in micro and nanoparticles, the analytical expressions derived for the Ornstein-Zernike correlator of the long-range order parameter spatial-temporal fluctuations, dynamic generalized susceptibility, relaxation times, and correlation radii discrete spectra are different from those known for bulk systems. Obtained analytical expressions for the correlation function of the order parameter spatial-temporal fluctuations in micro and nanosized systems can be useful for the quantitative analysis of the dynamical structural factors determined from magnetic resonance diffraction and scattering spectra. Besides the practical importance of the correlation function for the analysis of the experimental data, derived expressions for the fluctuations strength determine the fundamental limits of phenomenological theories applicability for 3D-confined systems.
NASA Astrophysics Data System (ADS)
Betterle, A.; Schirmer, M.; Botter, G.
2017-12-01
Streamflow dynamics strongly influence anthropogenic activities and the ecological functions of riverine and riparian habitats. However, the widespread lack of direct discharge measurements often challenges the set-up of conscious and effective decision-making processes, including droughts and floods protection, water resources management and river restoration practices. By characterizing the spatial correlation of daily streamflow timeseries at two arbitrary locations, this study provides a method to evaluate how spatially variable catchment-scale hydrological process affects the resulting streamflow dynamics along and across river systems. In particular, streamflow spatial correlation is described analytically as a function of morphological, climatic and vegetation properties in the contributing catchments, building on a joint probabilistic description of flow dynamics at pairs of outlets. The approach enables an explicit linkage between similarities of flow dynamics and spatial patterns of hydrologically relevant features of climate and landscape. Therefore, the method is suited to explore spatial patterns of streamflow dynamics across geomorphoclimatic gradients. In particular, we show how the streamflow correlation can be used at the continental scale to individuate catchment pairs with similar hydrological dynamics, thereby providing a useful tool for the estimate of flow duration curves in poorly gauged areas.
Robustness of Oscillatory Behavior in Correlated Networks
Sasai, Takeyuki; Morino, Kai; Tanaka, Gouhei; Almendral, Juan A.; Aihara, Kazuyuki
2015-01-01
Understanding network robustness against failures of network units is useful for preventing large-scale breakdowns and damages in real-world networked systems. The tolerance of networked systems whose functions are maintained by collective dynamical behavior of the network units has recently been analyzed in the framework called dynamical robustness of complex networks. The effect of network structure on the dynamical robustness has been examined with various types of network topology, but the role of network assortativity, or degree–degree correlations, is still unclear. Here we study the dynamical robustness of correlated (assortative and disassortative) networks consisting of diffusively coupled oscillators. Numerical analyses for the correlated networks with Poisson and power-law degree distributions show that network assortativity enhances the dynamical robustness of the oscillator networks but the impact of network disassortativity depends on the detailed network connectivity. Furthermore, we theoretically analyze the dynamical robustness of correlated bimodal networks with two-peak degree distributions and show the positive impact of the network assortativity. PMID:25894574
Nguyen, T B; Cron, G O; Bezzina, K; Perdrizet, K; Torres, C H; Chakraborty, S; Woulfe, J; Jansen, G H; Thornhill, R E; Zanette, B; Cameron, I G
2016-12-01
Tumor CBV is a prognostic and predictive marker for patients with gliomas. Tumor CBV can be measured noninvasively with different MR imaging techniques; however, it is not clear which of these techniques most closely reflects histologically-measured tumor CBV. Our aim was to investigate the correlations between dynamic contrast-enhanced and DSC-MR imaging parameters and immunohistochemistry in patients with gliomas. Forty-three patients with a new diagnosis of glioma underwent a preoperative MR imaging examination with dynamic contrast-enhanced and DSC sequences. Unnormalized and normalized cerebral blood volume was obtained from DSC MR imaging. Two sets of plasma volume and volume transfer constant maps were obtained from dynamic contrast-enhanced MR imaging. Plasma volume obtained from the phase-derived vascular input function and bookend T1 mapping (Vp_Φ) and volume transfer constant obtained from phase-derived vascular input function and bookend T1 mapping (K trans _Φ) were determined. Plasma volume obtained from magnitude-derived vascular input function (Vp_SI) and volume transfer constant obtained from magnitude-derived vascular input function (K trans _SI) were acquired, without T1 mapping. Using CD34 staining, we measured microvessel density and microvessel area within 3 representative areas of the resected tumor specimen. The Mann-Whitney U test was used to test for differences according to grade and degree of enhancement. The Spearman correlation was performed to determine the relationship between dynamic contrast-enhanced and DSC parameters and histopathologic measurements. Microvessel area, microvessel density, dynamic contrast-enhanced, and DSC-MR imaging parameters varied according to the grade and degree of enhancement (P < .05). A strong correlation was found between microvessel area and Vp_Φ and between microvessel area and unnormalized blood volume (r s ≥ 0.61). A moderate correlation was found between microvessel area and normalized blood volume, microvessel area and Vp_SI, microvessel area and K trans _Φ, microvessel area and K trans _SI, microvessel density and Vp_Φ, microvessel density and unnormalized blood volume, and microvessel density and normalized blood volume (0.44 ≤ r s ≤ 0.57). A weaker correlation was found between microvessel density and K trans _Φ and between microvessel density and K trans _SI (r s ≤ 0.41). With dynamic contrast-enhanced MR imaging, use of a phase-derived vascular input function and bookend T1 mapping improves the correlation between immunohistochemistry and plasma volume, but not between immunohistochemistry and the volume transfer constant. With DSC-MR imaging, normalization of tumor CBV could decrease the correlation with microvessel area. © 2016 by American Journal of Neuroradiology.
Scale-Free Neural and Physiological Dynamics in Naturalistic Stimuli Processing
Lin, Amy
2016-01-01
Abstract Neural activity recorded at multiple spatiotemporal scales is dominated by arrhythmic fluctuations without a characteristic temporal periodicity. Such activity often exhibits a 1/f-type power spectrum, in which power falls off with increasing frequency following a power-law function: P(f)∝1/fβ, which is indicative of scale-free dynamics. Two extensively studied forms of scale-free neural dynamics in the human brain are slow cortical potentials (SCPs)—the low-frequency (<5 Hz) component of brain field potentials—and the amplitude fluctuations of α oscillations, both of which have been shown to carry important functional roles. In addition, scale-free dynamics characterize normal human physiology such as heartbeat dynamics. However, the exact relationships among these scale-free neural and physiological dynamics remain unclear. We recorded simultaneous magnetoencephalography and electrocardiography in healthy subjects in the resting state and while performing a discrimination task on scale-free dynamical auditory stimuli that followed different scale-free statistics. We observed that long-range temporal correlation (captured by the power-law exponent β) in SCPs positively correlated with that of heartbeat dynamics across time within an individual and negatively correlated with that of α-amplitude fluctuations across individuals. In addition, across individuals, long-range temporal correlation of both SCP and α-oscillation amplitude predicted subjects’ discrimination performance in the auditory task, albeit through antagonistic relationships. These findings reveal interrelations among different scale-free neural and physiological dynamics and initial evidence for the involvement of scale-free neural dynamics in the processing of natural stimuli, which often exhibit scale-free dynamics. PMID:27822495
Mechanism for subgap optical conductivity in honeycomb Kitaev materials
NASA Astrophysics Data System (ADS)
Bolens, Adrien; Katsura, Hosho; Ogata, Masao; Miyashita, Seiji
2018-04-01
Motivated by recent terahertz absorption measurements in α -RuCl3 , we develop a theory for the electromagnetic absorption of materials described by the Kitaev model on the honeycomb lattice. We derive a mechanism for the polarization operator at second order in the nearest-neighbor hopping Hamiltonian. Using the exact results of the Kitaev honeycomb model, we then calculate the polarization dynamical correlation function corresponding to electric dipole transitions in addition to the spin dynamical correlation function corresponding to magnetic dipole transitions.
NASA Astrophysics Data System (ADS)
Niu, Xiaojie; Sun, Shiyan; Wang, Fujun; Jia, Xiangfu
2017-08-01
The effect of final-state dynamic correlation is investigated for helium single ionization by 75-keV proton impact analyzing fully differential cross sections (FDCS). The final state is represented by a continuum correlated wave (CCW-PT) function which accounts for the interaction between the projectile and the residual target ion (PT interaction). This continuum correlated wave function partially includes the correlation of electron-projectile and electron-target relative motion as coupling terms of the wave equation. The transition matrix is evaluated using the CCW-PT function and the Born initial state. The analytical expression of the transition matrix has been obtained. We have shown that this series is strongly convergent and analyzed the contribution of their different terms to the FDCS within the perturbation method. Illustrative computations are performed in the scattering plane and in the perpendicular plane. Both the correlation effects and the PT interaction are checked by the preset calculations. Our results are compared with absolute experimental data as well as other theoretical models. We have shown that the dynamic correlation plays an important role in the single ionization of atoms by proton impact at intermediate projectile energies, especially at large transverse momentum transfer. While overall agreement between theory and the experimental data is encouraging, detailed agreement is lacking. The need for more theoretical and experimental work is emphasized.
NASA Astrophysics Data System (ADS)
Drachta, Jürgen T.; Kreil, Dominik; Hobbiger, Raphael; Böhm, Helga M.
2018-03-01
Correlations, highly important in low-dimensional systems, are known to decrease the plasmon dispersion of two-dimensional electron liquids. Here we calculate the plasmon properties, applying the 'Dynamic Many-Body Theory', accounting for correlated two-particle-two-hole fluctuations. These dynamic correlations are found to significantly lower the plasmon's energy. For the data obtained numerically, we provide an analytic expression that is valid across a wide range both of densities and of wave vectors. Finally, we demonstrate how this can be invoked in determining the actual electron densities from measurements on an AlGaAs quantum well.
Quenched dynamics and spin-charge separation in an interacting topological lattice
NASA Astrophysics Data System (ADS)
Barbiero, L.; Santos, L.; Goldman, N.
2018-05-01
We analyze the static and dynamical properties of a one-dimensional topological lattice, the fermionic Su-Schrieffer-Heeger model, in the presence of on-site interactions. Based on a study of charge and spin correlation functions, we elucidate the nature of the topological edge modes, which, depending on the sign of the interactions, either display particles of opposite spin on opposite edges, or a pair and a holon. This study of correlation functions also highlights the strong entanglement that exists between the opposite edges of the system. This last feature has remarkable consequences upon subjecting the system to a quench, where an instantaneous edge-to-edge signal appears in the correlation functions characterizing the edge modes. Besides, other correlation functions are shown to propagate in the bulk according to the light cone imposed by the Lieb-Robinson bound. Our study reveals how one-dimensional lattices exhibiting entangled topological edge modes allow for a nontrivial correlation spreading, while providing an accessible platform to detect spin-charge separation using state-of-the-art experimental techniques.
Correlational signatures of time-reversal symmetry breaking in two-dimensional flow
NASA Astrophysics Data System (ADS)
Hogg, Charlie; Ouellette, Nicholas
2015-11-01
Classical turbulence theories posit that broken spatial symmetries should be (statistically) restored at small scales. But since turbulent flows are inherently dissipative, time reversal symmetry is expected to remain broken throughout the cascade. However, the precise dynamical signature of this broken symmetry is not well understood. Recent work has shed new light on this fundamental question by considering the Lagrangian structure functions of power. Here, we take a somewhat different approach by studying the Lagrangian correlation functions of velocity and acceleration. We measured these correlations using particle tracking velocimetry in a quasi-two-dimensional electromagnetically driven flow that displayed net inverse energy transfer. We show that the correlation functions of the velocity and acceleration magnitudes are not symmetric in time, and that the degree of asymmetry can be related to the flux of energy between scales, suggesting that the asymmetry has a dynamical origin.
Pant, Sanjay
2018-05-01
A new class of functions, called the 'information sensitivity functions' (ISFs), which quantify the information gain about the parameters through the measurements/observables of a dynamical system are presented. These functions can be easily computed through classical sensitivity functions alone and are based on Bayesian and information-theoretic approaches. While marginal information gain is quantified by decrease in differential entropy, correlations between arbitrary sets of parameters are assessed through mutual information. For individual parameters, these information gains are also presented as marginal posterior variances, and, to assess the effect of correlations, as conditional variances when other parameters are given. The easy to interpret ISFs can be used to (a) identify time intervals or regions in dynamical system behaviour where information about the parameters is concentrated; (b) assess the effect of measurement noise on the information gain for the parameters; (c) assess whether sufficient information in an experimental protocol (input, measurements and their frequency) is available to identify the parameters; (d) assess correlation in the posterior distribution of the parameters to identify the sets of parameters that are likely to be indistinguishable; and (e) assess identifiability problems for particular sets of parameters. © 2018 The Authors.
Ghosh, Soumen; Cramer, Christopher J; Truhlar, Donald G; Gagliardi, Laura
2017-04-01
Predicting ground- and excited-state properties of open-shell organic molecules by electronic structure theory can be challenging because an accurate treatment has to correctly describe both static and dynamic electron correlation. Strongly correlated systems, i.e. , systems with near-degeneracy correlation effects, are particularly troublesome. Multiconfigurational wave function methods based on an active space are adequate in principle, but it is impractical to capture most of the dynamic correlation in these methods for systems characterized by many active electrons. We recently developed a new method called multiconfiguration pair-density functional theory (MC-PDFT), that combines the advantages of wave function theory and density functional theory to provide a more practical treatment of strongly correlated systems. Here we present calculations of the singlet-triplet gaps in oligoacenes ranging from naphthalene to dodecacene. Calculations were performed for unprecedently large orbitally optimized active spaces of 50 electrons in 50 orbitals, and we test a range of active spaces and active space partitions, including four kinds of frontier orbital partitions. We show that MC-PDFT can predict the singlet-triplet splittings for oligoacenes consistent with the best available and much more expensive methods, and indeed MC-PDFT may constitute the benchmark against which those other models should be compared, given the absence of experimental data.
NASA Astrophysics Data System (ADS)
Levashov, V. A.
2014-11-01
In order to gain insight into the connection between the vibrational dynamics and the atomic-level Green-Kubo stress correlation function in liquids, we consider this connection in a model crystal instead. Of course, vibrational dynamics in liquids and crystals are quite different and it is not expected that the results obtained on a model crystal should be valid for liquids. However, these considerations provide a benchmark to which the results of the previous molecular dynamics simulations can be compared. Thus, assuming that vibrations are plane waves, we derive analytical expressions for the atomic-level stress correlation functions in the classical limit and analyze them. These results provide, in particular, a recipe for analysis of the atomic-level stress correlation functions in Fourier space and extraction of the wave-vector and frequency-dependent information. We also evaluate the energies of the atomic-level stresses. The energies obtained are significantly smaller than the energies previously determined in molecular dynamics simulations of several model liquids. This result suggests that the average energies of the atomic-level stresses in liquids and glasses are largely determined by the structural disorder. We discuss this result in the context of equipartition of the atomic-level stress energies. Analysis of the previously published data suggests that it is possible to speak about configurational and vibrational contributions to the average energies of the atomic-level stresses in a glass state. However, this separation in a liquid state is problematic. We also introduce and briefly consider the atomic-level transverse current correlation function. Finally, we address the broadening of the peaks in the pair distribution function with increase of distance. We find that the peaks' broadening (by ≈40 % ) occurs due to the transverse vibrational modes, while contribution from the longitudinal modes does not change with distance.
Spatial-temporal-spectral EEG patterns of BOLD functional network connectivity dynamics
NASA Astrophysics Data System (ADS)
Lamoš, Martin; Mareček, Radek; Slavíček, Tomáš; Mikl, Michal; Rektor, Ivan; Jan, Jiří
2018-06-01
Objective. Growing interest in the examination of large-scale brain network functional connectivity dynamics is accompanied by an effort to find the electrophysiological correlates. The commonly used constraints applied to spatial and spectral domains during electroencephalogram (EEG) data analysis may leave part of the neural activity unrecognized. We propose an approach that blindly reveals multimodal EEG spectral patterns that are related to the dynamics of the BOLD functional network connectivity. Approach. The blind decomposition of EEG spectrogram by parallel factor analysis has been shown to be a useful technique for uncovering patterns of neural activity. The simultaneously acquired BOLD fMRI data were decomposed by independent component analysis. Dynamic functional connectivity was computed on the component’s time series using a sliding window correlation, and between-network connectivity states were then defined based on the values of the correlation coefficients. ANOVA tests were performed to assess the relationships between the dynamics of between-network connectivity states and the fluctuations of EEG spectral patterns. Main results. We found three patterns related to the dynamics of between-network connectivity states. The first pattern has dominant peaks in the alpha, beta, and gamma bands and is related to the dynamics between the auditory, sensorimotor, and attentional networks. The second pattern, with dominant peaks in the theta and low alpha bands, is related to the visual and default mode network. The third pattern, also with peaks in the theta and low alpha bands, is related to the auditory and frontal network. Significance. Our previous findings revealed a relationship between EEG spectral pattern fluctuations and the hemodynamics of large-scale brain networks. In this study, we suggest that the relationship also exists at the level of functional connectivity dynamics among large-scale brain networks when no standard spatial and spectral constraints are applied on the EEG data.
Phase correlation imaging of unlabeled cell dynamics
NASA Astrophysics Data System (ADS)
Ma, Lihong; Rajshekhar, Gannavarpu; Wang, Ru; Bhaduri, Basanta; Sridharan, Shamira; Mir, Mustafa; Chakraborty, Arindam; Iyer, Rajashekar; Prasanth, Supriya; Millet, Larry; Gillette, Martha U.; Popescu, Gabriel
2016-09-01
We present phase correlation imaging (PCI) as a novel approach to study cell dynamics in a spatially-resolved manner. PCI relies on quantitative phase imaging time-lapse data and, as such, functions in label-free mode, without the limitations associated with exogenous markers. The correlation time map outputted in PCI informs on the dynamics of the intracellular mass transport. Specifically, we show that PCI can extract quantitatively the diffusion coefficient map associated with live cells, as well as standard Brownian particles. Due to its high sensitivity to mass transport, PCI can be applied to studying the integrity of actin polymerization dynamics. Our results indicate that the cyto-D treatment blocking the actin polymerization has a dominant effect at the large spatial scales, in the region surrounding the cell. We found that PCI can distinguish between senescent and quiescent cells, which is extremely difficult without using specific markers currently. We anticipate that PCI will be used alongside established, fluorescence-based techniques to enable valuable new studies of cell function.
Luber, Sandra
2017-03-14
We describe the calculation of Raman optical activity (ROA) tensors from density functional perturbation theory, which has been implemented into the CP2K software package. Using the mixed Gaussian and plane waves method, ROA spectra are evaluated in the double-harmonic approximation. Moreover, an approach for the calculation of ROA spectra by means of density functional theory-based molecular dynamics is derived and used to obtain an ROA spectrum via time correlation functions, which paves the way for the calculation of ROA spectra taking into account anharmonicities and dynamic effects at ambient conditions.
Glerean, Enrico; Salmi, Juha; Lahnakoski, Juha M; Jääskeläinen, Iiro P; Sams, Mikko
2012-01-01
Functional brain activity and connectivity have been studied by calculating intersubject and seed-based correlations of hemodynamic data acquired with functional magnetic resonance imaging (fMRI). To inspect temporal dynamics, these correlation measures have been calculated over sliding time windows with necessary restrictions on the length of the temporal window that compromises the temporal resolution. Here, we show that it is possible to increase temporal resolution by using instantaneous phase synchronization (PS) as a measure of dynamic (time-varying) functional connectivity. We applied PS on an fMRI dataset obtained while 12 healthy volunteers watched a feature film. Narrow frequency band (0.04-0.07 Hz) was used in the PS analysis to avoid artifactual results. We defined three metrics for computing time-varying functional connectivity and time-varying intersubject reliability based on estimation of instantaneous PS across the subjects: (1) seed-based PS, (2) intersubject PS, and (3) intersubject seed-based PS. Our findings show that these PS-based metrics yield results consistent with both seed-based correlation and intersubject correlation methods when inspected over the whole time series, but provide an important advantage of maximal single-TR temporal resolution. These metrics can be applied both in studies with complex naturalistic stimuli (e.g., watching a movie or listening to music in the MRI scanner) and more controlled (e.g., event-related or blocked design) paradigms. A MATLAB toolbox FUNPSY ( http://becs.aalto.fi/bml/software.html ) is openly available for using these metrics in fMRI data analysis.
Spellmon, Nicholas; Sun, Xiaonan; Sirinupong, Nualpun; Edwards, Brian; Li, Chunying; Yang, Zhe
2015-01-01
SMYD proteins are an exciting field of study as they are linked to many types of cancer-related pathways. Cardiac and skeletal muscle development and function also depend on SMYD proteins opening a possible avenue for cardiac-related treatment. Previous crystal structure studies have revealed that this special class of protein lysine methyltransferases have a bilobal structure, and an open-closed motion may regulate substrate specificity. Here we use the molecular dynamics simulation to investigate the still-poorly-understood SMYD2 dynamics. Cross-correlation analysis reveals that SMYD2 exhibits a negative correlated inter-lobe motion. Principle component analysis suggests that this correlated dynamic is contributed to by a twisting motion of the C-lobe with respect to the N-lobe and a clamshell-like motion between the lobes. Dynamical network analysis defines possible allosteric paths for the correlated dynamics. There are nine communities in the dynamical network with six in the N-lobe and three in the C-lobe, and the communication between the lobes is mediated by a lobe-bridging β hairpin. This study provides insight into the dynamical nature of SMYD2 and could facilitate better understanding of SMYD2 substrate specificity.
Reconstructing networks from dynamics with correlated noise
NASA Astrophysics Data System (ADS)
Tam, H. C.; Ching, Emily S. C.; Lai, Pik-Yin
2018-07-01
Reconstructing the structure of complex networks from measurements of the nodes is a challenge in many branches of science. External influences are always present and act as a noise to the networks of interest. In this paper, we present a method for reconstructing networks from measured dynamics of the nodes subjected to correlated noise that cannot be approximated by a white noise. This method can reconstruct the links of both bidirectional and directed networks, the correlation time and strength of the noise, and also the relative coupling strength of the links when the coupling functions have certain properties. Our method is built upon theoretical relations between network structure and measurable quantities from the dynamics that we have derived for systems that have fixed point dynamics in the noise-free limit. Using these theoretical results, we can further explain the shortcomings of two common practices of inferring links for bidirectional networks using the Pearson correlation coefficient and the partial correlation coefficient.
NASA Astrophysics Data System (ADS)
Brugués, Jan; Needleman, Daniel J.
2010-02-01
Metaphase spindles are highly dynamic, nonequilibrium, steady-state structures. We study the internal fluctuations of spindles by computing spatio-temporal correlation functions of movies obtained from quantitative polarized light microscopy. These correlation functions are only physically meaningful if corrections are made for the net motion of the spindle. We describe our image registration algorithm in detail and we explore its robustness. Finally, we discuss the expression used for the estimation of the correlation function in terms of the nematic order of the microtubules which make up the spindle. Ultimately, studying the form of these correlation functions will provide a quantitative test of the validity of coarse-grained models of spindle structure inspired from liquid crystal physics.
Liquid Dynamics from Neutron Spectrometry
DOE R&D Accomplishments Database
Brockhouse, Bertram N.; Bergsma, J.; Dasannacharya, B. A.; Pope, N. K.
1962-10-01
Recent experiments carried out at Chalk River on the dynamics of liquids using neutron inelastic scattering are reviewed, including one by Sakamoto et al., in which the Van Hove self-correlation functions in water at 25 and 75 deg C were determined, and another in which the correlation functions in liquid argon near its triple point were studied. The possible occurrence of short wavelength phonons in classical liquids is discussed, in analogy with their existence in the quantum liquid He4, and in connection with incomplete experiments on liquid tin. (auth)
Microsecond protein dynamics observed at the single-molecule level
NASA Astrophysics Data System (ADS)
Otosu, Takuhiro; Ishii, Kunihiko; Tahara, Tahei
2015-07-01
How polypeptide chains acquire specific conformations to realize unique biological functions is a central problem of protein science. Single-molecule spectroscopy, combined with fluorescence resonance energy transfer, is utilized to study the conformational heterogeneity and the state-to-state transition dynamics of proteins on the submillisecond to second timescales. However, observation of the dynamics on the microsecond timescale is still very challenging. This timescale is important because the elementary processes of protein dynamics take place and direct comparison between experiment and simulation is possible. Here we report a new single-molecule technique to reveal the microsecond structural dynamics of proteins through correlation of the fluorescence lifetime. This method, two-dimensional fluorescence lifetime correlation spectroscopy, is applied to clarify the conformational dynamics of cytochrome c. Three conformational ensembles and the microsecond transitions in each ensemble are indicated from the correlation signal, demonstrating the importance of quantifying microsecond dynamics of proteins on the folding free energy landscape.
Microsecond protein dynamics observed at the single-molecule level
Otosu, Takuhiro; Ishii, Kunihiko; Tahara, Tahei
2015-01-01
How polypeptide chains acquire specific conformations to realize unique biological functions is a central problem of protein science. Single-molecule spectroscopy, combined with fluorescence resonance energy transfer, is utilized to study the conformational heterogeneity and the state-to-state transition dynamics of proteins on the submillisecond to second timescales. However, observation of the dynamics on the microsecond timescale is still very challenging. This timescale is important because the elementary processes of protein dynamics take place and direct comparison between experiment and simulation is possible. Here we report a new single-molecule technique to reveal the microsecond structural dynamics of proteins through correlation of the fluorescence lifetime. This method, two-dimensional fluorescence lifetime correlation spectroscopy, is applied to clarify the conformational dynamics of cytochrome c. Three conformational ensembles and the microsecond transitions in each ensemble are indicated from the correlation signal, demonstrating the importance of quantifying microsecond dynamics of proteins on the folding free energy landscape. PMID:26151767
Pseudorapidity correlations in heavy ion collisions from viscous fluid dynamics
Monnai, A.; Schenke, B.
2015-11-26
We demonstrate by explicit calculations in 3+1 dimensional viscous relativistic fluid dynamics how two-particle pseudorapidity correlation functions in heavy ion collisions at the LHC and RHIC depend on the number of particle producing sources and the transport properties of the produced medium. In particular, we present results for the Legendre coefficients of the two-particle pseudorapidity correlation function, a n,m, in Pb+Pb collisions at 2760 GeV and Au+Au collisions at 200 GeV from viscous hydrodynamics with three dimensionally fluctuating initial conditions. Our results suggest that the a n,m provide important constraints on initial state fluctuations and the transport properties of themore » quark gluon plasma.« less
Towards a formal definition of static and dynamic electronic correlations.
Benavides-Riveros, Carlos L; Lathiotakis, Nektarios N; Marques, Miguel A L
2017-05-24
Some of the most spectacular failures of density-functional and Hartree-Fock theories are related to an incorrect description of the so-called static electron correlation. Motivated by recent progress in the N-representability problem of the one-body density matrix for pure states, we propose a method to quantify the static contribution to the electronic correlation. By studying several molecular systems we show that our proposal correlates well with our intuition of static and dynamic electron correlation. Our results bring out the paramount importance of the occupancy of the highest occupied natural spin-orbital in such quantification.
Coarse-grained hydrodynamics from correlation functions
DOE Office of Scientific and Technical Information (OSTI.GOV)
Palmer, Bruce
This paper will describe a formalism for using correlation functions between different grid cells as the basis for determining coarse-grained hydrodynamic equations for modeling the behavior of mesoscopic fluid systems. Configuration from a molecular dynamics simulation are projected onto basis functions representing grid cells in a continuum hydrodynamic simulation. Equilbrium correlation functions between different grid cells are evaluated from the molecular simulation and used to determine the evolution operator for the coarse-grained hydrodynamic system. The formalism is applied to some simple hydrodynamic cases to determine the feasibility of applying this to realistic nanoscale systems.
NASA Astrophysics Data System (ADS)
Dittmann, Niklas; Splettstoesser, Janine; Helbig, Nicole
2018-04-01
We simulate the dynamics of a single-electron source, modeled as a quantum dot with on-site Coulomb interaction and tunnel coupling to an adjacent lead in time-dependent density-functional theory. Based on this system, we develop a time-nonlocal exchange-correlation potential by exploiting analogies with quantum-transport theory. The time nonlocality manifests itself in a dynamical potential step. We explicitly link the time evolution of the dynamical step to physical relaxation timescales of the electron dynamics. Finally, we discuss prospects for simulations of larger mesoscopic systems.
Dittmann, Niklas; Splettstoesser, Janine; Helbig, Nicole
2018-04-13
We simulate the dynamics of a single-electron source, modeled as a quantum dot with on-site Coulomb interaction and tunnel coupling to an adjacent lead in time-dependent density-functional theory. Based on this system, we develop a time-nonlocal exchange-correlation potential by exploiting analogies with quantum-transport theory. The time nonlocality manifests itself in a dynamical potential step. We explicitly link the time evolution of the dynamical step to physical relaxation timescales of the electron dynamics. Finally, we discuss prospects for simulations of larger mesoscopic systems.
Interaction quantum quenches in the one-dimensional Fermi-Hubbard model
NASA Astrophysics Data System (ADS)
Heidrich-Meisner, Fabian; Bauer, Andreas; Dorfner, Florian; Riegger, Luis; Orso, Giuliano
2016-05-01
We discuss the nonequilibrium dynamics in two interaction quantum quenches in the one-dimensional Fermi-Hubbard model. First, we study the decay of the Néel state as a function of interaction strength. We observe a fast charge dynamics over which double occupancies are built up, while the long-time decay of the staggered moment is controlled by spin excitations, corroborated by the analysis of the entanglement dynamics. Second, we investigate the formation of Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) correlations in a spin-imbalanced system in quenches from the noninteracting case to attractive interactions. Even though the quench puts the system at a finite energy density, peaks at the characteristic FFLO quasimomenta are visible in the quasi-momentum distribution function, albeit with an exponential decay of s-wave pairing correlations. We also discuss the imprinting of FFLO correlations onto repulsively bound pairs and their rapid decay in ramps. Supported by the DFG (Deutsche Forschungsgemeinschaft) via FOR 1807.
NASA Astrophysics Data System (ADS)
Garza, Alejandro J.; Bulik, Ireneusz W.; Alencar, Ana G. Sousa; Sun, Jianwei; Perdew, John P.; Scuseria, Gustavo E.
2016-04-01
Contrary to standard coupled cluster doubles (CCD) and Brueckner doubles (BD), singlet-paired analogues of CCD and BD (denoted here as CCD0 and BD0) do not break down when static correlation is present, but neglect substantial amounts of dynamic correlation. In fact, CCD0 and BD0 do not account for any contributions from multielectron excitations involving only same-spin electrons at all. We exploit this feature to add - without introducing double counting, self-interaction, or increase in cost - the missing correlation to these methods via meta-GGA (generalised gradient approximation) density functionals (Tao-Perdew-Staroverov-Scuseria and strongly constrained and appropriately normed). Furthermore, we improve upon these CCD0+DFT blends by invoking range separation: the short- and long-range correlations absent in CCD0/BD0 are evaluated with density functional theory and the direct random phase approximation, respectively. This corrects the description of long-range van der Waals forces. Comprehensive benchmarking shows that the combinations presented here are very accurate for weakly correlated systems, while also providing a reasonable description of strongly correlated problems without resorting to symmetry breaking.
Coarse-grained hydrodynamics from correlation functions
NASA Astrophysics Data System (ADS)
Palmer, Bruce
2018-02-01
This paper will describe a formalism for using correlation functions between different grid cells as the basis for determining coarse-grained hydrodynamic equations for modeling the behavior of mesoscopic fluid systems. Configurations from a molecular dynamics simulation or other atomistic simulation are projected onto basis functions representing grid cells in a continuum hydrodynamic simulation. Equilibrium correlation functions between different grid cells are evaluated from the molecular simulation and used to determine the evolution operator for the coarse-grained hydrodynamic system. The formalism is demonstrated on a discrete particle simulation of diffusion with a spatially dependent diffusion coefficient. Correlation functions are calculated from the particle simulation and the spatially varying diffusion coefficient is recovered using a fitting procedure.
Quantum currents and pair correlation of electrons in a chain of localized dots
NASA Astrophysics Data System (ADS)
Morawetz, Klaus
2017-03-01
The quantum transport of electrons in a wire of localized dots by hopping, interaction and dissipation is calculated and a representation by an equivalent RCL circuit is found. The exact solution for the electric-field induced currents allows to discuss the role of virtual currents to decay initial correlations and Bloch oscillations. The dynamical response function in random phase approximation (RPA) is calculated analytically with the help of which the static structure function and pair correlation function are determined. The pair correlation function contains a form factor from the Brillouin zone and a structure factor caused by the localized dots in the wire.
Detecting coupled collective motions in protein by independent subspace analysis
NASA Astrophysics Data System (ADS)
Sakuraba, Shun; Joti, Yasumasa; Kitao, Akio
2010-11-01
Protein dynamics evolves in a high-dimensional space, comprising aharmonic, strongly correlated motional modes. Such correlation often plays an important role in analyzing protein function. In order to identify significantly correlated collective motions, here we employ independent subspace analysis based on the subspace joint approximate diagonalization of eigenmatrices algorithm for the analysis of molecular dynamics (MD) simulation trajectories. From the 100 ns MD simulation of T4 lysozyme, we extract several independent subspaces in each of which collective modes are significantly correlated, and identify the other modes as independent. This method successfully detects the modes along which long-tailed non-Gaussian probability distributions are obtained. Based on the time cross-correlation analysis, we identified a series of events among domain motions and more localized motions in the protein, indicating the connection between the functionally relevant phenomena which have been independently revealed by experiments.
NASA Astrophysics Data System (ADS)
Yao, Yi; Kanai, Yosuke
Our ability to correctly model the association of oppositely charged ions in water is fundamental in physical chemistry and essential to various technological and biological applications of molecular dynamics (MD) simulations. MD simulations using classical force fields often show strong clustering of NaCl in the aqueous ionic solutions as a consequence of a deep contact pair minimum in the potential of mean force (PMF) curve. First-Principles Molecular Dynamics (FPMD) based on Density functional theory (DFT) with the popular PBE exchange-correlation approximation, on the other hand, show a different result with a shallow contact pair minimum in the PMF. We employed two of most promising exchange-correlation approximations, ωB97xv by Mardiorossian and Head-Gordon and SCAN by Sun, Ruzsinszky and Perdew, to examine the PMF using FPMD simulations. ωB97xv is highly empirically and optimized in the space of range-separated hybrid functional with a dispersion correction while SCAN is the most recent meta-GGA functional that is constructed by satisfying various known conditions in well-defined physical limits. We will discuss our findings for PMF, charge transfer, water dipoles, etc.
Sojoudi, Alireza; Goodyear, Bradley G
2016-12-01
Spontaneous fluctuations of blood-oxygenation level-dependent functional magnetic resonance imaging (BOLD fMRI) signals are highly synchronous between brain regions that serve similar functions. This provides a means to investigate functional networks; however, most analysis techniques assume functional connections are constant over time. This may be problematic in the case of neurological disease, where functional connections may be highly variable. Recently, several methods have been proposed to determine moment-to-moment changes in the strength of functional connections over an imaging session (so called dynamic connectivity). Here a novel analysis framework based on a hierarchical observation modeling approach was proposed, to permit statistical inference of the presence of dynamic connectivity. A two-level linear model composed of overlapping sliding windows of fMRI signals, incorporating the fact that overlapping windows are not independent was described. To test this approach, datasets were synthesized whereby functional connectivity was either constant (significant or insignificant) or modulated by an external input. The method successfully determines the statistical significance of a functional connection in phase with the modulation, and it exhibits greater sensitivity and specificity in detecting regions with variable connectivity, when compared with sliding-window correlation analysis. For real data, this technique possesses greater reproducibility and provides a more discriminative estimate of dynamic connectivity than sliding-window correlation analysis. Hum Brain Mapp 37:4566-4580, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
The heterogeneity of segmental dynamics of filled EPDM by (1)H transverse relaxation NMR.
Moldovan, D; Fechete, R; Demco, D E; Culea, E; Blümich, B; Herrmann, V; Heinz, M
2011-01-01
Residual second moment of dipolar interactions M(2) and correlation time segmental dynamics distributions were measured by Hahn-echo decays in combination with inverse Laplace transform for a series of unfilled and filled EPDM samples as functions of carbon-black N683 filler content. The fillers-polymer chain interactions which dramatically restrict the mobility of bound rubber modify the dynamics of mobile chains. These changes depend on the filler content and can be evaluated from distributions of M(2). A dipolar filter was applied to eliminate the contribution of bound rubber. In the first approach the Hahn-echo decays were fitted with a theoretical relationship to obtain the average values of the (1)H residual second moment
The heterogeneity of segmental dynamics of filled EPDM by 1H transverse relaxation NMR
NASA Astrophysics Data System (ADS)
Moldovan, D.; Fechete, R.; Demco, D. E.; Culea, E.; Blümich, B.; Herrmann, V.; Heinz, M.
2011-01-01
Residual second moment of dipolar interactions M∼2 and correlation time segmental dynamics distributions were measured by Hahn-echo decays in combination with inverse Laplace transform for a series of unfilled and filled EPDM samples as functions of carbon-black N683 filler content. The fillers-polymer chain interactions which dramatically restrict the mobility of bound rubber modify the dynamics of mobile chains. These changes depend on the filler content and can be evaluated from distributions of M∼2. A dipolar filter was applied to eliminate the contribution of bound rubber. In the first approach the Hahn-echo decays were fitted with a theoretical relationship to obtain the average values of the 1H residual second moment
Probing the triplet correlation function in liquid water by experiments and molecular simulations.
Dhabal, Debdas; Wikfeldt, Kjartan Thor; Skinner, Lawrie B; Chakravarty, Charusita; Kashyap, Hemant K
2017-01-25
Despite very significant developments in scattering experiments like X-ray and neutron diffraction, it has been challenging to elucidate the nature of tetrahedral molecular configurations in liquid water. A key question is whether the pair correlation functions, which can be obtained from scattering experiments, are sufficient to describe the tetrahedral ordering of water molecules. In our previous study (Dhabal et al., J. Chem. Phys., 2014, 141, 174504), using data-sets generated from reverse Monte Carlo and molecular dynamics simulations, we showed that the triplet correlation functions contain important information on the tetrahedrality of water in the liquid state. In the present study, X-ray scattering experiments and molecular dynamics (MD) simulations are used to link the isothermal pressure derivative of the structure factor with the triplet correlation functions for water. Triplet functions are determined for water up to 3.3 kbar at 298 K to display the effect of pressure on the water structure. The results suggest that triplet functions (H[combining tilde](q)) obtained using a rigid-body TIP4P/2005 water model are consistent with the experimental results. The triplet functions obtained in experiment as well as in simulations evince that in the case of tetrahedral liquids, exertion of higher pressure leads to a better agreement with the Kirkwood superposition approximation (KSA). We further validate this observation using the triplet correlation functions (g (3) (r,s,t)) calculated directly from simulation trajectory, revealing that both H[combining tilde](q) in q-space and g (3) (r,s,t) in real-space contain similar information on the tetrahedrality of liquids. This study demonstrates that the structure factor, even though it has only pair correlation information of the liquid structure, can shed light on three-body correlations in liquid water through its isothermal pressure derivative term.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Belyi, V.V.; Kukharenko, Y.A.; Wallenborn, J.
Taking into account the first non-Markovian correction to the Balescu-Lenard equation, we have derived an expression for the pair correlation function and a nonlinear kinetic equation valid for a nonideal polarized classical plasma. This last equation allows for the description of the correlational energy evolution and shows the global conservation of energy with dynamical polarization. {copyright} {ital 1996 The American Physical Society.}
2017-12-06
mechanical response of the azobenzene- functionalized polyimide is correlated to the rotational freedom of the polyimide chains (resulting in extensive... correlated to the rotational freedom of the polyimide chains (resulting in extensive segmental mobility) and fractional free volume (FFV > 0.1...response has been described,34 and a recent simulation study on the stress relaxation dynamics of azo-polyimides has provided insights into the correlation
Instanton effects on CP-violating gluonic correlators
NASA Astrophysics Data System (ADS)
Mori, Shingo; Frison, Julien; Kitano, Ryuichiro; Matsufuru, Hideo; Yamada, Norikazu
2018-03-01
In order to better understand the role played by instantons behind nonperturbative dynamics, we investigate the instanton contributions to the gluonic two point correlation functions in the SU(2) YM theory. Pseudoscalar-scalar gluonic correlation functions are calculated on the lattice at various temperatures and compared with the instanton calculus. We discuss how the instanton effects emerge or disappear with temperature and try to provide the interpretation behind it.
Levashov, V A
2014-09-28
We report on a further investigation of a new method that can be used to address vibrational dynamics and propagation of stress waves in liquids. The method is based on the decomposition of the macroscopic Green-Kubo stress correlation function into the atomic level stress correlation functions. This decomposition, as was demonstrated previously for a model liquid studied in molecular dynamics simulations, reveals the presence of stress waves propagating over large distances and a structure that resembles the pair density function. In this paper, by performing the Fourier transforms of the atomic level stress correlation functions, we elucidate how the lifetimes of the stress waves and the ranges of their propagation depend on their frequency, wavevector, and temperature. These results relate frequency and wavevector dependence of the generalized viscosity to the character of propagation of the shear stress waves. In particular, the results suggest that an increase in the value of the frequency dependent viscosity at low frequencies with decrease of temperature is related to the increase in the ranges of propagation of the stress waves of the corresponding low frequencies. We found that the ranges of propagation of the shear stress waves of frequencies less than half of the Einstein frequency extend well beyond the nearest neighbor shell even above the melting temperature. The results also show that the crossover from quasilocalized to propagating behavior occurs at frequencies usually associated with the Boson peak.
Boltzmann-conserving classical dynamics in quantum time-correlation functions: "Matsubara dynamics".
Hele, Timothy J H; Willatt, Michael J; Muolo, Andrea; Althorpe, Stuart C
2015-04-07
We show that a single change in the derivation of the linearized semiclassical-initial value representation (LSC-IVR or "classical Wigner approximation") results in a classical dynamics which conserves the quantum Boltzmann distribution. We rederive the (standard) LSC-IVR approach by writing the (exact) quantum time-correlation function in terms of the normal modes of a free ring-polymer (i.e., a discrete imaginary-time Feynman path), taking the limit that the number of polymer beads N → ∞, such that the lowest normal-mode frequencies take their "Matsubara" values. The change we propose is to truncate the quantum Liouvillian, not explicitly in powers of ħ(2) at ħ(0) (which gives back the standard LSC-IVR approximation), but in the normal-mode derivatives corresponding to the lowest Matsubara frequencies. The resulting "Matsubara" dynamics is inherently classical (since all terms O(ħ(2)) disappear from the Matsubara Liouvillian in the limit N → ∞) and conserves the quantum Boltzmann distribution because the Matsubara Hamiltonian is symmetric with respect to imaginary-time translation. Numerical tests show that the Matsubara approximation to the quantum time-correlation function converges with respect to the number of modes and gives better agreement than LSC-IVR with the exact quantum result. Matsubara dynamics is too computationally expensive to be applied to complex systems, but its further approximation may lead to practical methods.
Kinetic theory for strongly coupled Coulomb systems
NASA Astrophysics Data System (ADS)
Dufty, James; Wrighton, Jeffrey
2018-01-01
The calculation of dynamical properties for matter under extreme conditions is a challenging task. The popular Kubo-Greenwood model exploits elements from equilibrium density-functional theory (DFT) that allow a detailed treatment of electron correlations, but its origin is largely phenomenological; traditional kinetic theories have a more secure foundation but are limited to weak ion-electron interactions. The objective here is to show how a combination of the two evolves naturally from the short-time limit for the generator of the effective single-electron dynamics governing time correlation functions without such limitations. This provides a theoretical context for the current DFT-related approach, the Kubo-Greenwood model, while showing the nature of its corrections. The method is to calculate the short-time dynamics in the single-electron subspace for a given configuration of the ions. This differs from the usual kinetic theory approach in which an average over the ions is performed as well. In this way the effective ion-electron interaction includes strong Coulomb coupling and is shown to be determined from DFT. The correlation functions have the form of the random-phase approximation for an inhomogeneous system but with renormalized ion-electron and electron-electron potentials. The dynamic structure function, density response function, and electrical conductivity are calculated as examples. The static local field corrections in the dielectric function are identified in this way. The current analysis is limited to semiclassical electrons (quantum statistical potentials), so important quantum conditions are excluded. However, a quantization of the kinetic theory is identified for broader application while awaiting its detailed derivation.
Garg, Hina; Dibble, Leland E; Schubert, Michael C; Sibthorp, Jim; Foreman, K Bo; Gappmaier, Eduard
2018-05-05
Despite the common complaints of dizziness and demyelination of afferent or efferent pathways to and from the vestibular nuclei which may adversely affect the angular Vestibulo-Ocular Reflex (aVOR) and vestibulo-spinal function in persons with Multiple Sclerosis (PwMS), few studies have examined gaze and dynamic balance function in PwMS. 1) Determine the differences in gaze stability, dynamic balance and participation measures between PwMS and controls, 2) Examine the relationships between gaze stability, dynamic balance and participation. Nineteen ambulatory PwMS at fall-risk and 14 age-matched controls were recruited. Outcomes included (a) gaze stability [angular Vestibulo-Ocular Reflex (aVOR) gain (ratio of eye to head velocity); number of Compensatory Saccades (CS) per head rotation; CS latency; gaze position error; Coefficient of Variation (CV) of aVOR gain], (b) dynamic balance [Functional Gait Assessment, FGA; four square step test], and (c) participation [dizziness handicap inventory; activities-specific balance confidence scale]. Separate independent t-tests and Pearson's correlations were calculated. PwMS were age = 53 ± 11.7yrs and had 4.2 ± 3.3 falls/yr. PwMS demonstrated significant (p<0.05) impairments in gaze stability, dynamic balance and participation measures compared to controls. CV of aVOR gain and CS latency were significantly correlated with FGA. Deficits and correlations across a spectrum of disability measures highlight the relevance of gaze and dynamic balance assessment in PwMS. This article is protected by copyright. All rights reserved. © 2018 Wiley Periodicals, Inc.
Kesler, Shelli R; Adams, Marjorie; Packer, Melissa; Rao, Vikram; Henneghan, Ashley M; Blayney, Douglas W; Palesh, Oxana
2017-03-01
Several previous studies have demonstrated that cancer chemotherapy is associated with brain injury and cognitive dysfunction. However, evidence suggests that cancer pathogenesis alone may play a role, even in non-CNS cancers. Using a multimodal neuroimaging approach, we measured structural and functional connectome topology as well as functional network dynamics in newly diagnosed patients with breast cancer. Our study involved a novel, pretreatment assessment that occurred prior to the initiation of any cancer therapies, including surgery with anesthesia. We enrolled 74 patients with breast cancer age 29-65 and 50 frequency-matched healthy female controls who underwent anatomic and resting-state functional MRI as well as cognitive testing. Compared to controls, patients with breast cancer demonstrated significantly lower functional network dynamics ( p = .046) and cognitive functioning ( p < .02, corrected). The breast cancer group also showed subtle alterations in structural local clustering and functional local clustering ( p < .05, uncorrected) as well as significantly increased correlation between structural global clustering and functional global clustering compared to controls ( p = .03). This hyper-correlation between structural and functional topologies was significantly associated with cognitive dysfunction ( p = .005). Our findings could not be accounted for by psychological distress and suggest that non-CNS cancer may directly and/or indirectly affect the brain via mechanisms such as tumor-induced neurogenesis, inflammation, and/or vascular changes, for example. Our results also have broader implications concerning the importance of the balance between structural and functional connectome properties as a potential biomarker of general neurologic deficit.
Heterogeneous dynamics of ionic liquids: A four-point time correlation function approach
NASA Astrophysics Data System (ADS)
Liu, Jiannan; Willcox, Jon A. L.; Kim, Hyung J.
2018-05-01
Many ionic liquids show behavior similar to that of glassy systems, e.g., large and long-lasted deviations from Gaussian dynamics and clustering of "mobile" and "immobile" groups of ions. Herein a time-dependent four-point density correlation function—typically used to characterize glassy systems—is implemented for the ionic liquids, choline acetate, and 1-butyl-3-methylimidazolium acetate. Dynamic correlation beyond the first ionic solvation shell on the time scale of nanoseconds is found in the ionic liquids, revealing the cooperative nature of ion motions. The traditional solvent, acetonitrile, on the other hand, shows a much shorter length-scale that decays after a few picoseconds.
NASA Astrophysics Data System (ADS)
Garza, Alejandro J.
Perhaps the most important approximations to the electronic structure problem in quantum chemistry are those based on coupled cluster and density functional theories. Coupled cluster theory has been called the ``gold standard'' of quantum chemistry due to the high accuracy that it achieves for weakly correlated systems. Kohn-Sham density functionals based on semilocal approximations are, without a doubt, the most widely used methods in chemistry and material science because of their high accuracy/cost ratio. The root of the success of coupled cluster and density functionals is their ability to efficiently describe the dynamic part of the electron correlation. However, both traditional coupled cluster and density functional approximations may fail catastrophically when substantial static correlation is present. This severely limits the applicability of these methods to a plethora of important chemical and physical problems such as, e.g., the description of bond breaking, transition states, transition metal-, lanthanide- and actinide-containing compounds, and superconductivity. In an attempt to tackle this problem, nonstandard (single-reference) coupled cluster-based techniques that aim to describe static correlation have been recently developed: pair coupled cluster doubles (pCCD) and singlet-paired coupled cluster doubles (CCD0). The ability to describe static correlation in pCCD and CCD0 comes, however, at the expense of important amounts of dynamic correlation so that the high accuracy of standard coupled cluster becomes unattainable. Thus, the reliable and efficient description of static and dynamic correlation in a simultaneous manner remains an open problem for quantum chemistry and many-body theory in general. In this thesis, different ways to combine pCCD and CCD0 with density functionals in order to describe static and dynamic correlation simultaneously (and efficiently) are explored. The combination of wavefunction and density functional methods has a long history in quantum chemistry (practical implementations have appeared in the literature since the 1970s). However, this kind of techniques have not achieved widespread use due to problems such as double counting of correlation and the symmetry dilemma--the fact that wavefunction methods respect the symmetries of Hamiltonian, while modern functionals are designed to work with broken symmetry densities. Here, particular mathematical features of pCCD and CCD0 are exploited to avoid these problems in an efficient manner. The two resulting families of approximations, denoted as pCCD+DFT and CCD0+DFT, are shown to be able to describe static and dynamic correlation in standard benchmark calculations. Furthermore, it is also shown that CCD0+DFT lends itself to combination with correlation from the direct random phase approximation (dRPA). Inclusion of dRPA in the long-range via the technique of range-separation allows for the description of dispersion correlation, the remaining part of the correlation. Thus, when combined with the dRPA, CCD0+DFT can account for all three-types of electron correlation that are necessary to accurately describe molecular systems. Lastly, applications of CCD0+DFT to actinide chemistry are considered in this work. The accuracy of CCD0+DFT for predicting equilibrium geometries and vibrational frequencies of actinide molecules and ions is assessed and compared to that of well-established quantum chemical methods. For this purpose, the f0 actinyl series (UO2 2+, NpO 23+, PuO24+, the isoelectronic NUN, and Thorium (ThO, ThO2+) and Nobelium (NoO, NoO2) oxides are studied. It is shown that the CCD0+DFT description of these species agrees with available experimental data and is comparable with the results given by the highest-level calculations that are possible for such heavy compounds while being, at least, an order of magnitude lower in computational cost.
Electron correlation by polarization of interacting densities
NASA Astrophysics Data System (ADS)
Whitten, Jerry L.
2017-02-01
Coulomb interactions that occur in electronic structure calculations are correlated by allowing basis function components of the interacting densities to polarize dynamically, thereby reducing the magnitude of the interaction. Exchange integrals of molecular orbitals are not correlated. The modified Coulomb interactions are used in single-determinant or configuration interaction calculations. The objective is to account for dynamical correlation effects without explicitly introducing higher spherical harmonic functions into the molecular orbital basis. Molecular orbital densities are decomposed into a distribution of spherical components that conserve the charge and each of the interacting components is considered as a two-electron wavefunction embedded in the system acted on by an average field Hamiltonian plus r12-1. A method of avoiding redundancy is described. Applications to atoms, negative ions, and molecules representing different types of bonding and spin states are discussed.
Function Package for Computing Quantum Resource Measures
NASA Astrophysics Data System (ADS)
Huang, Zhiming
2018-05-01
In this paper, we present a function package for to calculate quantum resource measures and dynamics of open systems. Our package includes common operators and operator lists, frequently-used functions for computing quantum entanglement, quantum correlation, quantum coherence, quantum Fisher information and dynamics in noisy environments. We briefly explain the functions of the package and illustrate how to use the package with several typical examples. We expect that this package is a useful tool for future research and education.
A time-correlation function approach to nuclear dynamical effects in X-ray spectroscopy
NASA Astrophysics Data System (ADS)
Karsten, Sven; Bokarev, Sergey I.; Aziz, Saadullah G.; Ivanov, Sergei D.; Kühn, Oliver
2017-06-01
Modern X-ray spectroscopy has proven itself as a robust tool for probing the electronic structure of atoms in complex environments. Despite working on energy scales that are much larger than those corresponding to nuclear motions, taking nuclear dynamics and the associated nuclear correlations into account may be of importance for X-ray spectroscopy. Recently, we have developed an efficient protocol to account for nuclear dynamics in X-ray absorption and resonant inelastic X-ray scattering spectra [Karsten et al., J. Phys. Chem. Lett. 8, 992 (2017)], based on ground state molecular dynamics accompanied with state-of-the-art calculations of electronic excitation energies and transition dipoles. Here, we present an alternative derivation of the formalism and elaborate on the developed simulation protocol using gas phase and bulk water as examples. The specific spectroscopic features stemming from the nuclear motions are analyzed and traced down to the dynamics of electronic energy gaps and transition dipole correlation functions. The observed tendencies are explained on the basis of a simple harmonic model, and the involved approximations are discussed. The method represents a step forward over the conventional approaches that treat the system in full complexity and provides a reasonable starting point for further improvements.
A time-correlation function approach to nuclear dynamical effects in X-ray spectroscopy.
Karsten, Sven; Bokarev, Sergey I; Aziz, Saadullah G; Ivanov, Sergei D; Kühn, Oliver
2017-06-14
Modern X-ray spectroscopy has proven itself as a robust tool for probing the electronic structure of atoms in complex environments. Despite working on energy scales that are much larger than those corresponding to nuclear motions, taking nuclear dynamics and the associated nuclear correlations into account may be of importance for X-ray spectroscopy. Recently, we have developed an efficient protocol to account for nuclear dynamics in X-ray absorption and resonant inelastic X-ray scattering spectra [Karsten et al., J. Phys. Chem. Lett. 8, 992 (2017)], based on ground state molecular dynamics accompanied with state-of-the-art calculations of electronic excitation energies and transition dipoles. Here, we present an alternative derivation of the formalism and elaborate on the developed simulation protocol using gas phase and bulk water as examples. The specific spectroscopic features stemming from the nuclear motions are analyzed and traced down to the dynamics of electronic energy gaps and transition dipole correlation functions. The observed tendencies are explained on the basis of a simple harmonic model, and the involved approximations are discussed. The method represents a step forward over the conventional approaches that treat the system in full complexity and provides a reasonable starting point for further improvements.
NASA Astrophysics Data System (ADS)
Fedosov, I. V.; Tuchin, Valerii V.; Galanzha, E. I.; Solov'eva, A. V.; Stepanova, T. V.
2002-11-01
The direction-sensitive method of microflow velocity measurements based on the space — time correlation properties of the dynamic speckle field is described and used for in vivo monitoring of lymph flow in the vessels of rat mesentery. The results of measurements are compared with the data obtained from functional video microscopy of the microvessel region.
A diagnostic for determining the quality of single-reference electron correlation methods
NASA Technical Reports Server (NTRS)
Lee, Timothy J.; Taylor, Peter R.
1989-01-01
It was recently proposed that the Euclidian norm of the t(sub 1) vector of the coupled cluster wave function (normalized by the number of electrons included in the correlation procedure) could be used to determine whether a single-reference-based electron correlation procedure is appopriate. This diagnostic, T(sub 1) is defined for use with self-consistent-field molecular orbitals and is invariant to the same orbital rotations as the coupled cluster energy. T(sub 1) is investigated for several different chemical systems which exhibit a range of multireference behavior, and is shown to be an excellent measure of the importance of non-dynamical electron correlation and is far superior to C(sub 0) from a singles and doubles configuration interaction wave function. It is further suggested that when the aim is to recover a large fraction of the dynamical electron correlation energy, a large T(sub 1) (i.e., greater than 0.02) probably indicates the need for a multireference electron correlation procedure.
Storek, M; Tilly, J F; Jeffrey, K R; Böhmer, R
2017-09-01
To study the nature of the nonexponential ionic hopping in solids a pulse sequence was developed that yields four-time stimulated-echo functions of previously inaccessible spin-3/2-nuclei such as 7 Li. It exploits combined Zeeman and octupolar order as longitudinal carrier state. Higher-order correlation functions were successfully generated for natural-abundance and isotopically-enriched lithium diborate glasses. Four-time 7 Li measurements are presented and compared with two-time correlation functions. The results are discussed with reference to approaches devised to quantify the degree of nonexponentiality in glass forming systems and evidence for the occurrence of dynamic heterogeneities and dynamic exchange were found. Additional experiments using the 6 Li species illustrate the challenge posed by subensemble selection when the dipolar interactions are not very much smaller than the quadrupolar ones. Copyright © 2017 Elsevier Inc. All rights reserved.
Quantum Critical Point revisited by the Dynamical Mean Field Theory
NASA Astrophysics Data System (ADS)
Xu, Wenhu; Kotliar, Gabriel; Tsvelik, Alexei
Dynamical mean field theory is used to study the quantum critical point (QCP) in the doped Hubbard model on a square lattice. The QCP is characterized by a universal scaling form of the self energy and a spin density wave instability at an incommensurate wave vector. The scaling form unifies the low energy kink and the high energy waterfall feature in the spectral function, while the spin dynamics includes both the critical incommensurate and high energy antiferromagnetic paramagnons. We use the frequency dependent four-point correlation function of spin operators to calculate the momentum dependent correction to the electron self energy. Our results reveal a substantial difference with the calculations based on the Spin-Fermion model which indicates that the frequency dependence of the the quasiparitcle-paramagnon vertices is an important factor. The authors are supported by Center for Computational Design of Functional Strongly Correlated Materials and Theoretical Spectroscopy under DOE Grant DE-FOA-0001276.
NASA Astrophysics Data System (ADS)
Garza, Alejandro J.; Sousa Alencar, Ana G.; Scuseria, Gustavo E.
2015-12-01
Singlet-paired coupled cluster doubles (CCD0) is a simplification of CCD that relinquishes a fraction of dynamic correlation in order to be able to describe static correlation. Combinations of CCD0 with density functionals that recover specifically the dynamic correlation missing in the former have also been developed recently. Here, we assess the accuracy of CCD0 and CCD0+DFT (and variants of these using Brueckner orbitals) as compared to well-established quantum chemical methods for describing ground-state properties of singlet actinide molecules. The f0 actinyl series (UO22+, NpO23+, PuO24+), the isoelectronic NUN, and thorium (ThO, ThO2+) and nobelium (NoO, NoO2) oxides are studied.
Large Deviations in Weakly Interacting Boundary Driven Lattice Gases
NASA Astrophysics Data System (ADS)
van Wijland, Frédéric; Rácz, Zoltán
2005-01-01
One-dimensional, boundary-driven lattice gases with local interactions are studied in the weakly interacting limit. The density profiles and the correlation functions are calculated to first order in the interaction strength for zero-range and short-range processes differing only in the specifics of the detailed-balance dynamics. Furthermore, the effective free-energy (large-deviation function) and the integrated current distribution are also found to this order. From the former, we find that the boundary drive generates long-range correlations only for the short-range dynamics while the latter provides support to an additivity principle recently proposed by Bodineau and Derrida.
NASA Astrophysics Data System (ADS)
Levashov, Valentin A.; Egami, Takeshi; Morris, James R.
2009-03-01
We present a new approach to the issue of correlation range in supercooled liquids based on Green-Kubo expression for viscosity. The integrand of this expression is the average stress-stress autocorrelation function. This correlation function could be rewritten in terms of correlations among local atomic stresses at different times and distances. The features of the autocorrelation function decay with time depend on temperature and correlation range. Through this approach we can study the development of spatial correlation with time, thus directly addressing the question of dynamic heterogeneity. We performed MD simulations on a single component system of particles interacting through short range pair potential. Our results indicate that even above the crossover temperature correlations extend well beyond the nearest neighbors. Surprisingly we found that the system size effects exist even on relatively large systems. We also address the role of diffusion in decay of stress-stress correlation function.
NASA Astrophysics Data System (ADS)
Pathak, Arup Kumar
2018-05-01
Despite the knowledge that the influenza protein, hemagglutinin, undergoes a large conformational change at low pH during the process of fusion with the host cell, its molecular mechanism remains elusive. The present constant pH molecular dynamics (CpHMD) study identifies the residues responsible for large conformational change in acidic condition. Based on the pKa calculations, it is predicted that His-106 is much more responsible for the large conformational change than any other residues in the hinge region of hemagglutinin protein. Potential of mean force profile from well-tempered meta-dynamics (WT-MtD) simulation is also generated along the folding pathway by considering radius of gyration (R gyr) as a collective variable (CV). It is very clear from the present WT-MtD study, that the initial bending starts at that hinge region, which may trigger other conformational changes. Both the protein–protein and protein–water HB time correlation functions are monitored along the folding pathway. The protein–protein (full or hinge region) HB time correlation functions are always found to be stronger than those of the protein–water time correlation functions. The dynamical balance between protein–protein and protein–water HB interactions favors the stabilization of the folded state.
Thermal noise model of antiferromagnetic dynamics: A macroscopic approach
NASA Astrophysics Data System (ADS)
Li, Xilai; Semenov, Yuriy; Kim, Ki Wook
In the search for post-silicon technologies, antiferromagnetic (AFM) spintronics is receiving widespread attention. Due to faster dynamics when compared with its ferromagnetic counterpart, AFM enables ultra-fast magnetization switching and THz oscillations. A crucial factor that affects the stability of antiferromagnetic dynamics is the thermal fluctuation, rarely considered in AFM research. Here, we derive from theory both stochastic dynamic equations for the macroscopic AFM Neel vector (L-vector) and the corresponding Fokker-Plank equation for the L-vector distribution function. For the dynamic equation approach, thermal noise is modeled by a stochastic fluctuating magnetic field that affects the AFM dynamics. The field is correlated within the correlation time and the amplitude is derived from the energy dissipation theory. For the distribution function approach, the inertial behavior of AFM dynamics forces consideration of the generalized space, including both coordinates and velocities. Finally, applying the proposed thermal noise model, we analyze a particular case of L-vector reversal of AFM nanoparticles by voltage controlled perpendicular magnetic anisotropy (PMA) with a tailored pulse width. This work was supported, in part, by SRC/NRI SWAN.
Triplet correlation functions in liquid water
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dhabal, Debdas; Chakravarty, Charusita, E-mail: charus@chemistry.iitd.ac.in; Singh, Murari
Triplet correlations have been shown to play a crucial role in the transformation of simple liquids to anomalous tetrahedral fluids [M. Singh, D. Dhabal, A. H. Nguyen, V. Molinero, and C. Chakravarty, Phys. Rev. Lett. 112, 147801 (2014)]. Here we examine triplet correlation functions for water, arguably the most important tetrahedral liquid, under ambient conditions, using configurational ensembles derived from molecular dynamics (MD) simulations and reverse Monte Carlo (RMC) datasets fitted to experimental scattering data. Four different RMC data sets with widely varying hydrogen-bond topologies fitted to neutron and x-ray scattering data are considered [K. T. Wikfeldt, M. Leetmaa, M.more » P. Ljungberg, A. Nilsson, and L. G. M. Pettersson, J. Phys. Chem. B 113, 6246 (2009)]. Molecular dynamics simulations are performed for two rigid-body effective pair potentials (SPC/E and TIP4P/2005) and the monatomic water (mW) model. Triplet correlation functions are compared with other structural measures for tetrahedrality, such as the O–O–O angular distribution function and the local tetrahedral order distributions. In contrast to the pair correlation functions, which are identical for all the RMC ensembles, the O–O–O triplet correlation function can discriminate between ensembles with different degrees of tetrahedral network formation with the maximally symmetric, tetrahedral SYM dataset displaying distinct signatures of tetrahedrality similar to those obtained from atomistic simulations of the SPC/E model. Triplet correlations from the RMC datasets conform closely to the Kirkwood superposition approximation, while those from MD simulations show deviations within the first two neighbour shells. The possibilities for experimental estimation of triplet correlations of water and other tetrahedral liquids are discussed.« less
NASA Astrophysics Data System (ADS)
Pagano, E. V.; Acosta, L.; Auditore, L.; Cap, T.; Cardella, G.; Colonna, M.; De Filippo, E.; Geraci, E.; Gnoffo, B.; Lanzalone, G.; Maiolino, C.; Martorana, N.; Pagano, A.; Papa, M.; Piasecki, E.; Pirrone, S.; Politi, G.; Porto, F.; Quattrocchi, L.; Rizzo, F.; Russotto, P.; Trifiro’, A.; Trimarchi, M.; Siwek-Wilczynska, K.
2018-05-01
In nuclear reactions at Fermi energies two and multi particles intensity interferometry correlation methods are powerful tools in order to pin down the characteristic time scale of the emission processes. In this paper we summarize an improved application of the fragment-fragment correlation function in the specific physics case of heavy projectile-like (PLF) binary massive splitting in two fragments of intermediate mass(IMF). Results are shown for the reverse kinematics reaction 124 Sn+64 Ni at 35 AMeV that has been investigated by using the forward part of CHIMERA multi-detector. The analysis was performed as a function of the charge asymmetry of the observed couples of IMF. We show a coexistence of dynamical and statistical components as a function of the charge asymmetry. Transport CoMD simulations are compared with the data in order to pin down the timescale of the fragments production and the relevant ingredients of the in medium effective interaction used in the transport calculations.
Investigation of the 9B nucleus and its cluster-nucleon correlations
NASA Astrophysics Data System (ADS)
Zhao, Qing; Ren, Zhongzhou; Lyu, Mengjiao; Horiuchi, Hisashi; Funaki, Yasuro; Röpke, Gerd; Schuck, Peter; Tohsaki, Akihiro; Xu, Chang; Yamada, Taiichi; Zhou, Bo
2018-05-01
In order to study the correlations between clusters and nucleons in light nuclei, we formulate a new superposed Tohsaki-Horiuchi-Schuck-Röpke (THSR) wave function which describes both spatially large spreading and cluster-correlated dynamics of valence nucleons. Using this new THSR wave function, the binding energy of 9B is significantly improved in comparison with our previous studies. We calculate the excited states of 9B and obtain an energy spectrum of 9B which is consistent with the experimental results. This includes the prediction of the first 1 /2+ excited state of 9B which is not yet fixed experimentally. We study the proton dynamics in 9B and find that the cluster-proton correlation plays an essential role for the proton dynamics in the ground state of 9B. Furthermore, we discuss the density distribution of the valence proton with special attention to its tail structure. Finally, the resonance nature of excited states of 9B is illustrated comparing root-mean-square radii between the ground and excited states.
Multiconfigurational short-range density-functional theory for open-shell systems
NASA Astrophysics Data System (ADS)
Hedegârd, Erik Donovan; Toulouse, Julien; Jensen, Hans Jørgen Aagaard
2018-06-01
Many chemical systems cannot be described by quantum chemistry methods based on a single-reference wave function. Accurate predictions of energetic and spectroscopic properties require a delicate balance between describing the most important configurations (static correlation) and obtaining dynamical correlation efficiently. The former is most naturally done through a multiconfigurational (MC) wave function, whereas the latter can be done by, e.g., perturbation theory. We have employed a different strategy, namely, a hybrid between multiconfigurational wave functions and density-functional theory (DFT) based on range separation. The method is denoted by MC short-range DFT (MC-srDFT) and is more efficient than perturbative approaches as it capitalizes on the efficient treatment of the (short-range) dynamical correlation by DFT approximations. In turn, the method also improves DFT with standard approximations through the ability of multiconfigurational wave functions to recover large parts of the static correlation. Until now, our implementation was restricted to closed-shell systems, and to lift this restriction, we present here the generalization of MC-srDFT to open-shell cases. The additional terms required to treat open-shell systems are derived and implemented in the DALTON program. This new method for open-shell systems is illustrated on dioxygen and [Fe(H2O)6]3+.
Generalized hydrodynamic correlations and fractional memory functions
NASA Astrophysics Data System (ADS)
Rodríguez, Rosalio F.; Fujioka, Jorge
2015-12-01
A fractional generalized hydrodynamic (GH) model of the longitudinal velocity fluctuations correlation, and its associated memory function, for a complex fluid is analyzed. The adiabatic elimination of fast variables introduces memory effects in the transport equations, and the dynamic of the fluctuations is described by a generalized Langevin equation with long-range noise correlations. These features motivate the introduction of Caputo time fractional derivatives and allows us to calculate analytic expressions for the fractional longitudinal velocity correlation function and its associated memory function. Our analysis eliminates a spurious constant term in the non-fractional memory function found in the non-fractional description. It also produces a significantly slower power-law decay of the memory function in the GH regime that reduces to the well-known exponential decay in the non-fractional Navier-Stokes limit.
Pham, Tuan Anh; Ogitsu, Tadashi; Lau, Edmond Y; Schwegler, Eric
2016-10-21
Establishing an accurate and predictive computational framework for the description of complex aqueous solutions is an ongoing challenge for density functional theory based first-principles molecular dynamics (FPMD) simulations. In this context, important advances have been made in recent years, including the development of sophisticated exchange-correlation functionals. On the other hand, simulations based on simple generalized gradient approximation (GGA) functionals remain an active field, particularly in the study of complex aqueous solutions due to a good balance between the accuracy, computational expense, and the applicability to a wide range of systems. Such simulations are often performed at elevated temperatures to artificially "correct" for GGA inaccuracies in the description of liquid water; however, a detailed understanding of how the choice of temperature affects the structure and dynamics of other components, such as solvated ions, is largely unknown. To address this question, we carried out a series of FPMD simulations at temperatures ranging from 300 to 460 K for liquid water and three representative aqueous solutions containing solvated Na + , K + , and Cl - ions. We show that simulations at 390-400 K with the Perdew-Burke-Ernzerhof (PBE) exchange-correlation functional yield water structure and dynamics in good agreement with experiments at ambient conditions. Simultaneously, this computational setup provides ion solvation structures and ion effects on water dynamics consistent with experiments. Our results suggest that an elevated temperature around 390-400 K with the PBE functional can be used for the description of structural and dynamical properties of liquid water and complex solutions with solvated ions at ambient conditions.
Tiwari, Sandhya P.; Reuter, Nathalie
2016-01-01
The conservation of the intrinsic dynamics of proteins emerges as we attempt to understand the relationship between sequence, structure and functional conservation. We characterise the conservation of such dynamics in a case where the structure is conserved but function differs greatly. The triosephosphate isomerase barrel fold (TBF), renowned for its 8 β-strand-α-helix repeats that close to form a barrel, is one of the most diverse and abundant folds found in known protein structures. Proteins with this fold have diverse enzymatic functions spanning five of six Enzyme Commission classes, and we have picked five different superfamily candidates for our analysis using elastic network models. We find that the overall shape is a large determinant in the similarity of the intrinsic dynamics, regardless of function. In particular, the β-barrel core is highly rigid, while the α-helices that flank the β-strands have greater relative mobility, allowing for the many possibilities for placement of catalytic residues. We find that these elements correlate with each other via the loops that link them, as opposed to being directly correlated. We are also able to analyse the types of motions encoded by the normal mode vectors of the α-helices. We suggest that the global conservation of the intrinsic dynamics in the TBF contributes greatly to its success as an enzymatic scaffold both through evolution and enzyme design. PMID:27015412
van Megen, W; Martinez, V A; Bryant, G
2009-12-18
The current correlation function is determined from dynamic light scattering measurements of a suspension of particles with hard spherelike interactions. For suspensions in thermodynamic equilibrium we find scaling of the space and time variables of the current correlation function. This finding supports the notion that the movement of suspended particles can be described in terms of uncorrelated Brownian encounters. However, in the metastable fluid, at volume fractions above freezing, this scaling fails.
NASA Astrophysics Data System (ADS)
Stopper, Daniel; Thorneywork, Alice L.; Dullens, Roel P. A.; Roth, Roland
2018-03-01
Using dynamical density functional theory (DDFT), we theoretically study Brownian self-diffusion and structural relaxation of hard disks and compare to experimental results on quasi two-dimensional colloidal hard spheres. To this end, we calculate the self-van Hove correlation function and distinct van Hove correlation function by extending a recently proposed DDFT-approach for three-dimensional systems to two dimensions. We find that the theoretical results for both self-part and distinct part of the van Hove function are in very good quantitative agreement with the experiments up to relatively high fluid packing fractions of roughly 0.60. However, at even higher densities, deviations between the experiment and the theoretical approach become clearly visible. Upon increasing packing fraction, in experiments, the short-time self-diffusive behavior is strongly affected by hydrodynamic effects and leads to a significant decrease in the respective mean-squared displacement. By contrast, and in accordance with previous simulation studies, the present DDFT, which neglects hydrodynamic effects, shows no dependence on the particle density for this quantity.
Using a pseudo-dynamic source inversion approach to improve earthquake source imaging
NASA Astrophysics Data System (ADS)
Zhang, Y.; Song, S. G.; Dalguer, L. A.; Clinton, J. F.
2014-12-01
Imaging a high-resolution spatio-temporal slip distribution of an earthquake rupture is a core research goal in seismology. In general we expect to obtain a higher quality source image by improving the observational input data (e.g. using more higher quality near-source stations). However, recent studies show that increasing the surface station density alone does not significantly improve source inversion results (Custodio et al. 2005; Zhang et al. 2014). We introduce correlation structures between the kinematic source parameters: slip, rupture velocity, and peak slip velocity (Song et al. 2009; Song and Dalguer 2013) in the non-linear source inversion. The correlation structures are physical constraints derived from rupture dynamics that effectively regularize the model space and may improve source imaging. We name this approach pseudo-dynamic source inversion. We investigate the effectiveness of this pseudo-dynamic source inversion method by inverting low frequency velocity waveforms from a synthetic dynamic rupture model of a buried vertical strike-slip event (Mw 6.5) in a homogeneous half space. In the inversion, we use a genetic algorithm in a Bayesian framework (Moneli et al. 2008), and a dynamically consistent regularized Yoffe function (Tinti, et al. 2005) was used for a single-window slip velocity function. We search for local rupture velocity directly in the inversion, and calculate the rupture time using a ray-tracing technique. We implement both auto- and cross-correlation of slip, rupture velocity, and peak slip velocity in the prior distribution. Our results suggest that kinematic source model estimates capture the major features of the target dynamic model. The estimated rupture velocity closely matches the target distribution from the dynamic rupture model, and the derived rupture time is smoother than the one we searched directly. By implementing both auto- and cross-correlation of kinematic source parameters, in comparison to traditional smoothing constraints, we are in effect regularizing the model space in a more physics-based manner without loosing resolution of the source image. Further investigation is needed to tune the related parameters of pseudo-dynamic source inversion and relative weighting between the prior and the likelihood function in the Bayesian inversion.
Modeling of Momentum Correlations in Heavy Ion Collisions
NASA Astrophysics Data System (ADS)
Pruneau, Claude; Sharma, Monika
2010-02-01
Measurements of transverse momentum (pt) correlations and fluctuations in heavy ion collisions (HIC) are of interest because they provide information on the collision dynamics not readily available from number correlations. For instance, pt fluctuations are expected to diverge for a system near its tri-critical point [1]. Integral momentum correlations may also be used to estimate the shear viscosity of the quark gluon plasma produced in HIC [2]. Integral correlations measured over large fractions of the particle phase space average out several dynamical contributions and as such may be difficult to interpret. It is thus of interest to seek extensions of integral correlation variables that may provide more detailed information about the collision dynamics. We introduce a variety of differential momentum correlations and discuss their basic properties in the light of simple toy models. We also present theoretical predictions based on the PYTHIA, HIJING, AMPT, and EPOS models. Finally, we discuss the interplay of various dynamical effects that may play a role in the determination of the shear viscosity based on the broadening of momentum correlations measured as function of collision centrality. [1] L. Stodolsky, Phys. Rev. Lett. 75 (1995) 1044. [2] S. Gavin and M. A. Aziz, Phys. Rev. Lett. 97 (2006) 162302. )
Shear banding leads to accelerated aging dynamics in a metallic glass
NASA Astrophysics Data System (ADS)
Küchemann, Stefan; Liu, Chaoyang; Dufresne, Eric M.; Shin, Jeremy; Maaß, Robert
2018-01-01
Traditionally, strain localization in metallic glasses is related to the thickness of the shear defect, which is confined to the nanometer scale. Using site-specific x-ray photon correlation spectroscopy, we reveal significantly accelerated relaxation dynamics around a shear band in a metallic glass at a length scale that is orders of magnitude larger than the defect itself. The relaxation time in the shear-band vicinity is up to ten times smaller compared to the as-cast matrix, and the relaxation dynamics occurs in a characteristic three-stage aging response that manifests itself in the temperature-dependent shape parameter known from classical stretched exponential relaxation dynamics of disordered materials. We demonstrate that the time-dependent correlation functions describing the aging at different temperatures can be captured and collapsed using simple scaling functions. These insights highlight how a ubiquitous nanoscale strain-localization mechanism in metallic glasses leads to a fundamental change of the relaxation dynamics at the mesoscale.
Sotiropoulos, Stamatios N.; Brookes, Matthew J.; Woolrich, Mark W.
2018-01-01
Over long timescales, neuronal dynamics can be robust to quite large perturbations, such as changes in white matter connectivity and grey matter structure through processes including learning, aging, development and certain disease processes. One possible explanation is that robust dynamics are facilitated by homeostatic mechanisms that can dynamically rebalance brain networks. In this study, we simulate a cortical brain network using the Wilson-Cowan neural mass model with conduction delays and noise, and use inhibitory synaptic plasticity (ISP) to dynamically achieve a spatially local balance between excitation and inhibition. Using MEG data from 55 subjects we find that ISP enables us to simultaneously achieve high correlation with multiple measures of functional connectivity, including amplitude envelope correlation and phase locking. Further, we find that ISP successfully achieves local E/I balance, and can consistently predict the functional connectivity computed from real MEG data, for a much wider range of model parameters than is possible with a model without ISP. PMID:29474352
Shear banding leads to accelerated aging dynamics in a metallic glass
DOE Office of Scientific and Technical Information (OSTI.GOV)
Küchemann, Stefan; Liu, Chaoyang; Dufresne, Eric M.
Traditionally, strain localization in metallic glasses is related to the thickness of the shear defect, which is confined to the nanometer scale. In this study, using site-specific x-ray photon correlation spectroscopy (XPCS), we reveal significantly accelerated relaxation dynamics around a shear band in a metallic glass at a length scale that is orders of magnitude larger than the defect itself. The relaxation time in the shear-band vicinity is up to ten-times smaller compared to the as-cast matrix, and the relaxation dynamics occurs in a characteristic three-stage aging response that manifests itself in the temperature-dependent shape parameter known from classical stretchedmore » exponential relaxation dynamics of disordered materials. We demonstrate that the time-dependent correlation functions describing the aging at different temperatures can be captured and collapsed using simple scaling functions. Finally, these insights highlight how an ubiquitous nano-scale strain-localization mechanism in metallic glasses leads to a fundamental change of the relaxation dynamics at the mesoscale.« less
Shear banding leads to accelerated aging dynamics in a metallic glass
Küchemann, Stefan; Liu, Chaoyang; Dufresne, Eric M.; ...
2018-01-11
Traditionally, strain localization in metallic glasses is related to the thickness of the shear defect, which is confined to the nanometer scale. In this study, using site-specific x-ray photon correlation spectroscopy (XPCS), we reveal significantly accelerated relaxation dynamics around a shear band in a metallic glass at a length scale that is orders of magnitude larger than the defect itself. The relaxation time in the shear-band vicinity is up to ten-times smaller compared to the as-cast matrix, and the relaxation dynamics occurs in a characteristic three-stage aging response that manifests itself in the temperature-dependent shape parameter known from classical stretchedmore » exponential relaxation dynamics of disordered materials. We demonstrate that the time-dependent correlation functions describing the aging at different temperatures can be captured and collapsed using simple scaling functions. Finally, these insights highlight how an ubiquitous nano-scale strain-localization mechanism in metallic glasses leads to a fundamental change of the relaxation dynamics at the mesoscale.« less
Modeling of two-particle femtoscopic correlations at top RHIC energy
NASA Astrophysics Data System (ADS)
Ermakov, N.; Nigmatkulov, G.
2017-01-01
The spatial and temporal characteristics of particle emitting source produced in particle and/or nuclear collisions can be measured by using two-particle femtoscopic correlations. These correlations arise due to quantum statistics, Coulomb and strong final state interactions. In this paper we report on the calculations of like-sign pion femtoscopic correlations produced in p+p, p+Au, d+Au, Au+Au at top RHIC energy using Ultra Relativistic Quantum Molecular Dynamics Model (UrQMD). Three-dimensional correlation functions are constructed using the Bertsch-Pratt parametrization of the two-particle relative momentum. The correlation functions are studied in several transverse mass ranges. The emitting source radii of charged pions, Rout, Rside, Rlong , are obtained from Gaussian fit to the correlation functions and compared to data from the STAR and PHENIX experiments.
Zhuang, Katie Z.; Lebedev, Mikhail A.
2014-01-01
Correlation between cortical activity and electromyographic (EMG) activity of limb muscles has long been a subject of neurophysiological studies, especially in terms of corticospinal connectivity. Interest in this issue has recently increased due to the development of brain-machine interfaces with output signals that mimic muscle force. For this study, three monkeys were implanted with multielectrode arrays in multiple cortical areas. One monkey performed self-timed touch pad presses, whereas the other two executed arm reaching movements. We analyzed the dynamic relationship between cortical neuronal activity and arm EMGs using a joint cross-correlation (JCC) analysis that evaluated trial-by-trial correlation as a function of time intervals within a trial. JCCs revealed transient correlations between the EMGs of multiple muscles and neural activity in motor, premotor and somatosensory cortical areas. Matching results were obtained using spike-triggered averages corrected by subtracting trial-shuffled data. Compared with spike-triggered averages, JCCs more readily revealed dynamic changes in cortico-EMG correlations. JCCs showed that correlation peaks often sharpened around movement times and broadened during delay intervals. Furthermore, JCC patterns were directionally selective for the arm-reaching task. We propose that such highly dynamic, task-dependent and distributed relationships between cortical activity and EMGs should be taken into consideration for future brain-machine interfaces that generate EMG-like signals. PMID:25210153
Grabowski, Ireneusz; Teale, Andrew M; Śmiga, Szymon; Bartlett, Rodney J
2011-09-21
The framework of ab initio density-functional theory (DFT) has been introduced as a way to provide a seamless connection between the Kohn-Sham (KS) formulation of DFT and wave-function based ab initio approaches [R. J. Bartlett, I. Grabowski, S. Hirata, and S. Ivanov, J. Chem. Phys. 122, 034104 (2005)]. Recently, an analysis of the impact of dynamical correlation effects on the density of the neon atom was presented [K. Jankowski, K. Nowakowski, I. Grabowski, and J. Wasilewski, J. Chem. Phys. 130, 164102 (2009)], contrasting the behaviour for a variety of standard density functionals with that of ab initio approaches based on second-order Møller-Plesset (MP2) and coupled cluster theories at the singles-doubles (CCSD) and singles-doubles perturbative triples [CCSD(T)] levels. In the present work, we consider ab initio density functionals based on second-order many-body perturbation theory and coupled cluster perturbation theory in a similar manner, for a range of small atomic and molecular systems. For comparison, we also consider results obtained from MP2, CCSD, and CCSD(T) calculations. In addition to this density based analysis, we determine the KS correlation potentials corresponding to these densities and compare them with those obtained for a range of ab initio density functionals via the optimized effective potential method. The correlation energies, densities, and potentials calculated using ab initio DFT display a similar systematic behaviour to those derived from electronic densities calculated using ab initio wave function theories. In contrast, typical explicit density functionals for the correlation energy, such as VWN5 and LYP, do not show behaviour consistent with this picture of dynamical correlation, although they may provide some degree of correction for already erroneous explicitly density-dependent exchange-only functionals. The results presented here using orbital dependent ab initio density functionals show that they provide a treatment of exchange and correlation contributions within the KS framework that is more consistent with traditional ab initio wave function based methods.
Phase transitions in the first-passage time of scale-invariant correlated processes
Carretero-Campos, Concepción; Bernaola-Galván, Pedro; Ch. Ivanov, Plamen
2012-01-01
A key quantity describing the dynamics of complex systems is the first-passage time (FPT). The statistical properties of FPT depend on the specifics of the underlying system dynamics. We present a unified approach to account for the diversity of statistical behaviors of FPT observed in real-world systems. We find three distinct regimes, separated by two transition points, with fundamentally different behavior for FPT as a function of increasing strength of the correlations in the system dynamics: stretched exponential, power-law, and saturation regimes. In the saturation regime, the average length of FPT diverges proportionally to the system size, with important implications for understanding electronic delocalization in one-dimensional correlated-disordered systems. PMID:22400544
A stochastic-dynamic model for global atmospheric mass field statistics
NASA Technical Reports Server (NTRS)
Ghil, M.; Balgovind, R.; Kalnay-Rivas, E.
1981-01-01
A model that yields the spatial correlation structure of atmospheric mass field forecast errors was developed. The model is governed by the potential vorticity equation forced by random noise. Expansion in spherical harmonics and correlation function was computed analytically using the expansion coefficients. The finite difference equivalent was solved using a fast Poisson solver and the correlation function was computed using stratified sampling of the individual realization of F(omega) and hence of phi(omega). A higher order equation for gamma was derived and solved directly in finite differences by two successive applications of the fast Poisson solver. The methods were compared for accuracy and efficiency and the third method was chosen as clearly superior. The results agree well with the latitude dependence of observed atmospheric correlation data. The value of the parameter c sub o which gives the best fit to the data is close to the value expected from dynamical considerations.
NASA Astrophysics Data System (ADS)
Hollett, Joshua W.; Pegoretti, Nicholas
2018-04-01
Separate, one-parameter, on-top density functionals are derived for the short-range dynamic correlation between opposite and parallel-spin electrons, in which the electron-electron cusp is represented by an exponential function. The combination of both functionals is referred to as the Opposite-spin exponential-cusp and Fermi-hole correction (OF) functional. The two parameters of the OF functional are set by fitting the ionization energies and electron affinities, of the atoms He to Ar, predicted by ROHF in combination with the OF functional to the experimental values. For ionization energies, the overall performance of ROHF-OF is better than completely renormalized coupled-cluster [CR-CC(2,3)] and better than, or as good as, conventional density functional methods. For electron affinities, the overall performance of ROHF-OF is less impressive. However, for both ionization energies and electron affinities of third row atoms, the mean absolute error of ROHF-OF is only 3 kJ mol-1.
Thompson, William H; Fransson, Peter
2015-01-01
When studying brain connectivity using fMRI, signal intensity time-series are typically correlated with each other in time to compute estimates of the degree of interaction between different brain regions and/or networks. In the static connectivity case, the problem of defining which connections that should be considered significant in the analysis can be addressed in a rather straightforward manner by a statistical thresholding that is based on the magnitude of the correlation coefficients. More recently, interest has come to focus on the dynamical aspects of brain connectivity and the problem of deciding which brain connections that are to be considered relevant in the context of dynamical changes in connectivity provides further options. Since we, in the dynamical case, are interested in changes in connectivity over time, the variance of the correlation time-series becomes a relevant parameter. In this study, we discuss the relationship between the mean and variance of brain connectivity time-series and show that by studying the relation between them, two conceptually different strategies to analyze dynamic functional brain connectivity become available. Using resting-state fMRI data from a cohort of 46 subjects, we show that the mean of fMRI connectivity time-series scales negatively with its variance. This finding leads to the suggestion that magnitude- versus variance-based thresholding strategies will induce different results in studies of dynamic functional brain connectivity. Our assertion is exemplified by showing that the magnitude-based strategy is more sensitive to within-resting-state network (RSN) connectivity compared to between-RSN connectivity whereas the opposite holds true for a variance-based analysis strategy. The implications of our findings for dynamical functional brain connectivity studies are discussed.
Erukhimovich, I Ya; Kudryavtsev, Ya V
2003-08-01
An extended generalization of the dynamic random phase approximation (DRPA) for L-component polymer systems is presented. Unlike the original version of the DRPA, which relates the (LxL) matrices of the collective density-density time correlation functions and the corresponding susceptibilities of concentrated polymer systems to those of the tracer macromolecules and so-called broken-links system (BLS), our generalized DRPA solves this problem for the (5xL) x (5xL) matrices of the coupled susceptibilities and time correlation functions of the component number, kinetic energy and flux densities. The presented technique is used to study propagation of sound and dynamic form-factor in disentangled (Rouse) monodisperse homopolymer melt. The calculated ultrasonic velocity and absorption coefficient reveal substantial frequency dispersion. The relaxation time tau is proportional to the degree of polymerization N, which is N times less than the Rouse time and evidences strong dynamic screening because of interchain interaction. We discuss also some peculiarities of the Brillouin scattering in polymer melts. Besides, a new convenient expression for the dynamic structure function of the single Rouse chain in (q,p) representation is found.
On Stabilizing the Variance of Dynamic Functional Brain Connectivity Time Series
Fransson, Peter
2016-01-01
Abstract Assessment of dynamic functional brain connectivity based on functional magnetic resonance imaging (fMRI) data is an increasingly popular strategy to investigate temporal dynamics of the brain's large-scale network architecture. Current practice when deriving connectivity estimates over time is to use the Fisher transformation, which aims to stabilize the variance of correlation values that fluctuate around varying true correlation values. It is, however, unclear how well the stabilization of signal variance performed by the Fisher transformation works for each connectivity time series, when the true correlation is assumed to be fluctuating. This is of importance because many subsequent analyses either assume or perform better when the time series have stable variance or adheres to an approximate Gaussian distribution. In this article, using simulations and analysis of resting-state fMRI data, we analyze the effect of applying different variance stabilization strategies on connectivity time series. We focus our investigation on the Fisher transformation, the Box–Cox (BC) transformation and an approach that combines both transformations. Our results show that, if the intention of stabilizing the variance is to use metrics on the time series, where stable variance or a Gaussian distribution is desired (e.g., clustering), the Fisher transformation is not optimal and may even skew connectivity time series away from being Gaussian. Furthermore, we show that the suboptimal performance of the Fisher transformation can be substantially improved by including an additional BC transformation after the dynamic functional connectivity time series has been Fisher transformed. PMID:27784176
On Stabilizing the Variance of Dynamic Functional Brain Connectivity Time Series.
Thompson, William Hedley; Fransson, Peter
2016-12-01
Assessment of dynamic functional brain connectivity based on functional magnetic resonance imaging (fMRI) data is an increasingly popular strategy to investigate temporal dynamics of the brain's large-scale network architecture. Current practice when deriving connectivity estimates over time is to use the Fisher transformation, which aims to stabilize the variance of correlation values that fluctuate around varying true correlation values. It is, however, unclear how well the stabilization of signal variance performed by the Fisher transformation works for each connectivity time series, when the true correlation is assumed to be fluctuating. This is of importance because many subsequent analyses either assume or perform better when the time series have stable variance or adheres to an approximate Gaussian distribution. In this article, using simulations and analysis of resting-state fMRI data, we analyze the effect of applying different variance stabilization strategies on connectivity time series. We focus our investigation on the Fisher transformation, the Box-Cox (BC) transformation and an approach that combines both transformations. Our results show that, if the intention of stabilizing the variance is to use metrics on the time series, where stable variance or a Gaussian distribution is desired (e.g., clustering), the Fisher transformation is not optimal and may even skew connectivity time series away from being Gaussian. Furthermore, we show that the suboptimal performance of the Fisher transformation can be substantially improved by including an additional BC transformation after the dynamic functional connectivity time series has been Fisher transformed.
NASA Astrophysics Data System (ADS)
Paust, Nathaniel E. Q.; Reid, I. Neill; Piotto, Giampaolo; Aparicio, Antonio; Anderson, Jay; Sarajedini, Ata; Bedin, Luigi R.; Chaboyer, Brian; Dotter, Aaron; Hempel, Maren; Majewski, Steven; Marín-Franch, A.; Milone, Antonino; Rosenberg, Alfred; Siegel, Michael
2010-02-01
We have used observations obtained as part of the Hubble Space Telescope/ACS Survey of Galactic Globular Clusters to construct global present-day mass functions for 17 globular clusters utilizing multi-mass King models to extrapolate from our observations to the global cluster behavior. The global present-day mass functions for these clusters are well matched by power laws from the turnoff, ≈0.8 M sun, to 0.2-0.3 M sun on the lower main sequence. The slopes of those power-law fits, α, have been correlated with an extensive set of intrinsic and extrinsic cluster properties to investigate which parameters may influence the form of the present-day mass function. We do not confirm previous suggestions of correlations between α and either metallicity or Galactic location. However, we do find a strong statistical correlation with the related parameters central surface brightness, μ V , and inferred central density, ρ0. The correlation is such that clusters with denser cores (stronger binding energy) tend to have steeper mass functions (a higher proportion of low-mass stars), suggesting that dynamical evolution due to external interactions may have played a key role in determining α. Thus, the present-day mass function may owe more to nurture than to nature. Detailed modeling of external dynamical effects is therefore a requisite for determining the initial mass function for Galactic globular clusters.
Emergent behaviors of the Schrödinger-Lohe model on cooperative-competitive networks
NASA Astrophysics Data System (ADS)
Huh, Hyungjin; Ha, Seung-Yeal; Kim, Dohyun
2017-12-01
We present several sufficient frameworks leading to the emergent behaviors of the coupled Schrödinger-Lohe (S-L) model under the same one-body external potential on cooperative-competitive networks. The S-L model was first introduced as a possible phenomenological model exhibiting quantum synchronization and its emergent dynamics on all-to-all cooperative networks has been treated via two distinct approaches, Lyapunov functional approach and the finite-dimensional reduction based on pairwise correlations. In this paper, we further generalize the finite-dimensional dynamical systems approach for pairwise correlation functions on cooperative-competitive networks and provide several sufficient frameworks leading to the collective exponential synchronization. For small systems consisting of three and four quantum subsystem, we also show that the system for pairwise correlations can be reduced to the Lotka-Volterra model with cooperative and competitive interactions, in which lots of interesting dynamical patterns appear, e.g., existence of closed orbits and limit-cycles.
Ghosh, Soumen; Cramer, Christopher J.; Truhlar, Donald G.; ...
2017-01-19
Predicting ground- and excited-state properties of open-shell organic molecules by electronic structure theory can be challenging because an accurate treatment has to correctly describe both static and dynamic electron correlation. Strongly correlated systems, i.e., systems with near-degeneracy correlation effects, are particularly troublesome. Multiconfigurational wave function methods based on an active space are adequate in principle, but it is impractical to capture most of the dynamic correlation in these methods for systems characterized by many active electrons. Here, we recently developed a new method called multiconfiguration pair-density functional theory (MC-PDFT), that combines the advantages of wave function theory and density functionalmore » theory to provide a more practical treatment of strongly correlated systems. Here we present calculations of the singlet–triplet gaps in oligoacenes ranging from naphthalene to dodecacene. Calculations were performed for unprecedently large orbitally optimized active spaces of 50 electrons in 50 orbitals, and we test a range of active spaces and active space partitions, including four kinds of frontier orbital partitions. We show that MC-PDFT can predict the singlet–triplet splittings for oligoacenes consistent with the best available and much more expensive methods, and indeed MC-PDFT may constitute the benchmark against which those other models should be compared, given the absence of experimental data.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ghosh, Soumen; Cramer, Christopher J.; Truhlar, Donald G.
Predicting ground- and excited-state properties of open-shell organic molecules by electronic structure theory can be challenging because an accurate treatment has to correctly describe both static and dynamic electron correlation. Strongly correlated systems, i.e., systems with near-degeneracy correlation effects, are particularly troublesome. Multiconfigurational wave function methods based on an active space are adequate in principle, but it is impractical to capture most of the dynamic correlation in these methods for systems characterized by many active electrons. Here, we recently developed a new method called multiconfiguration pair-density functional theory (MC-PDFT), that combines the advantages of wave function theory and density functionalmore » theory to provide a more practical treatment of strongly correlated systems. Here we present calculations of the singlet–triplet gaps in oligoacenes ranging from naphthalene to dodecacene. Calculations were performed for unprecedently large orbitally optimized active spaces of 50 electrons in 50 orbitals, and we test a range of active spaces and active space partitions, including four kinds of frontier orbital partitions. We show that MC-PDFT can predict the singlet–triplet splittings for oligoacenes consistent with the best available and much more expensive methods, and indeed MC-PDFT may constitute the benchmark against which those other models should be compared, given the absence of experimental data.« less
NASA Technical Reports Server (NTRS)
Syroid, Noah (Inventor); Westinskow, Dwayne (Inventor); Agutter, James (Inventor); Albert, Robert (Inventor); Strayer, David (Inventor); Wachter, S. Blake (Inventor); Drews, Frank (Inventor)
2010-01-01
A method, system, apparatus and device for the monitoring, diagnosis and evaluation of the state of a dynamic pulmonary system is disclosed. This method and system provides the processing means for receiving sensed and/or simulated data, converting such data into a displayable object format and displaying such objects in a manner such that the interrelationships between the respective variables can be correlated and identified by a user. This invention provides for the rapid cognitive grasp of the overall state of a pulmonary critical function with respect to a dynamic system.
Nonequilibrium Green's functions and atom-surface dynamics: Simple views from a simple model system
NASA Astrophysics Data System (ADS)
Boström, E.; Hopjan, M.; Kartsev, A.; Verdozzi, C.; Almbladh, C.-O.
2016-03-01
We employ Non-equilibrium Green's functions (NEGF) to describe the real-time dynamics of an adsorbate-surface model system exposed to ultrafast laser pulses. For a finite number of electronic orbitals, the system is solved exactly and within different levels of approximation. Specifically i) the full exact quantum mechanical solution for electron and nuclear degrees of freedom is used to benchmark ii) the Ehrenfest approximation (EA) for the nuclei, with the electron dynamics still treated exactly. Then, using the EA, electronic correlations are treated with NEGF within iii) 2nd Born and with iv) a recently introduced hybrid scheme, which mixes 2nd Born self-energies with non-perturbative, local exchange- correlation potentials of Density Functional Theory (DFT). Finally, the effect of a semi-infinite substrate is considered: we observe that a macroscopic number of de-excitation channels can hinder desorption. While very preliminary in character and based on a simple and rather specific model system, our results clearly illustrate the large potential of NEGF to investigate atomic desorption, and more generally, the non equilibrium dynamics of material surfaces subject to ultrafast laser fields.
The Dynamical Balance of the Brain at Rest
Deco, Gustavo; Corbetta, Maurizio
2014-01-01
We review evidence that spontaneous, i.e. not stimulus- or task-driven, activity in the brain is not noise, but orderly organized at the level of large scale systems in a series of functional networks that maintain at all times a high level of coherence. These networks of spontaneous activity correlation or resting state networks (RSN) are closely related to the underlying anatomical connectivity, but their topography is also gated by the history of prior task activation. Network coherence does not depend on covert cognitive activity, but its strength and integrity relates to behavioral performance. Some RSN are functionally organized as dynamically competing systems both at rest and during tasks. Computational studies show that one of such dynamics, the anti-correlation between networks, depends on noise driven transitions between different multi-stable cluster synchronization states. These multi-stable states emerge because of transmission delays between regions that are modeled as coupled oscillators systems. Large-scale systems dynamics are useful for keeping different functional sub-networks in a state of heightened competition, which can be stabilized and fired by even small modulations of either sensory or internal signals. PMID:21196530
Spatio-temporal coordination among functional residues in protein
NASA Astrophysics Data System (ADS)
Dutta, Sutapa; Ghosh, Mahua; Chakrabarti, J.
2017-01-01
The microscopic basis of communication among the functional sites in bio-macromolecules is a fundamental challenge in uncovering their functions. We study the communication through temporal cross-correlation among the binding sites. We illustrate via Molecular Dynamics simulations the properties of the temporal cross-correlation between the dihedrals of a small protein, ubiquitin which participates in protein degradation in eukaryotes. We show that the dihedral angles of the residues possess non-trivial temporal cross-correlations with asymmetry with respect to exchange of the dihedrals, having peaks at low frequencies with time scales in nano-seconds and an algebraic tail with a universal exponent for large frequencies. We show the existence of path for temporally correlated degrees of freedom among the functional residues. We explain the qualitative features of the cross-correlations through a general mathematical model. The generality of our analysis suggests that temporal cross-correlation functions may provide convenient theoretical framework to understand bio-molecular functions on microscopic basis.
NASA Astrophysics Data System (ADS)
Turi, László; Hantal, György; Rossky, Peter J.; Borgis, Daniel
2009-07-01
A general formalism for introducing nuclear quantum effects in the expression of the quantum time correlation function of an operator in a multilevel electronic system is presented in the adiabatic limit. The final formula includes the nuclear quantum time correlation functions of the operator matrix elements, of the energy gap, and their cross terms. These quantities can be inferred and evaluated from their classical analogs obtained by mixed quantum-classical molecular dynamics simulations. The formalism is applied to the absorption spectrum of a hydrated electron, expressed in terms of the time correlation function of the dipole operator in the ground electronic state. We find that both static and dynamic nuclear quantum effects distinctly influence the shape of the absorption spectrum, especially its high energy tail related to transitions to delocalized electron states. Their inclusion does improve significantly the agreement between theory and experiment for both the low and high frequency edges of the spectrum. It does not appear sufficient, however, to resolve persistent deviations in the slow Lorentzian-like decay part of the spectrum in the intermediate 2-3 eV region.
Veis, Libor; Antalík, Andrej; Brabec, Jiří; Neese, Frank; Legeza, Örs; Pittner, Jiří
2016-10-03
In the past decade, the quantum chemical version of the density matrix renormalization group (DMRG) method has established itself as the method of choice for calculations of strongly correlated molecular systems. Despite its favorable scaling, it is in practice not suitable for computations of dynamic correlation. We present a novel method for accurate "post-DMRG" treatment of dynamic correlation based on the tailored coupled cluster (CC) theory in which the DMRG method is responsible for the proper description of nondynamic correlation, whereas dynamic correlation is incorporated through the framework of the CC theory. We illustrate the potential of this method on prominent multireference systems, in particular, N 2 and Cr 2 molecules and also oxo-Mn(Salen), for which we have performed the first post-DMRG computations in order to shed light on the energy ordering of the lowest spin states.
Dynamics of the functional link between area MT LFPs and motion detection
Smith, Jackson E. T.; Beliveau, Vincent; Schoen, Alan; Remz, Jordana; Zhan, Chang'an A.
2015-01-01
The evolution of a visually guided perceptual decision results from multiple neural processes, and recent work suggests that signals with different neural origins are reflected in separate frequency bands of the cortical local field potential (LFP). Spike activity and LFPs in the middle temporal area (MT) have a functional link with the perception of motion stimuli (referred to as neural-behavioral correlation). To cast light on the different neural origins that underlie this functional link, we compared the temporal dynamics of the neural-behavioral correlations of MT spikes and LFPs. Wide-band activity was simultaneously recorded from two locations of MT from monkeys performing a threshold, two-stimuli, motion pulse detection task. Shortly after the motion pulse occurred, we found that high-gamma (100–200 Hz) LFPs had a fast, positive correlation with detection performance that was similar to that of the spike response. Beta (10–30 Hz) LFPs were negatively correlated with detection performance, but their dynamics were much slower, peaked late, and did not depend on stimulus configuration or reaction time. A late change in the correlation of all LFPs across the two recording electrodes suggests that a common input arrived at both MT locations prior to the behavioral response. Our results support a framework in which early high-gamma LFPs likely reflected fast, bottom-up, sensory processing that was causally linked to perception of the motion pulse. In comparison, late-arriving beta and high-gamma LFPs likely reflected slower, top-down, sources of neural-behavioral correlation that originated after the perception of the motion pulse. PMID:25948867
NASA Astrophysics Data System (ADS)
Haule, Kristjan
2018-04-01
The Dynamical Mean Field Theory (DMFT) in combination with the band structure methods has been able to address reach physics of correlated materials, such as the fluctuating local moments, spin and orbital fluctuations, atomic multiplet physics and band formation on equal footing. Recently it is getting increasingly recognized that more predictive ab-initio theory of correlated systems needs to also address the feedback effect of the correlated electronic structure on the ionic positions, as the metal-insulator transition is almost always accompanied with considerable structural distortions. We will review recently developed extension of merger between the Density Functional Theory (DFT) and DMFT method, dubbed DFT+ embedded DMFT (DFT+eDMFT), whichsuccessfully addresses this challenge. It is based on the stationary Luttinger-Ward functional to minimize the numerical error, it subtracts the exact double-counting of DFT and DMFT, and implements self-consistent forces on all atoms in the unit cell. In a few examples, we will also show how the method elucidated the important feedback effect of correlations on crystal structure in rare earth nickelates to explain the mechanism of the metal-insulator transition. The method showed that such feedback effect is also essential to understand the dynamic stability of the high-temperature body-centered cubic phase of elemental iron, and in particular it predicted strong enhancement of the electron-phonon coupling over DFT values in FeSe, which was very recently verified by pioneering time-domain experiment.
Accurate Structural Correlations from Maximum Likelihood Superpositions
Theobald, Douglas L; Wuttke, Deborah S
2008-01-01
The cores of globular proteins are densely packed, resulting in complicated networks of structural interactions. These interactions in turn give rise to dynamic structural correlations over a wide range of time scales. Accurate analysis of these complex correlations is crucial for understanding biomolecular mechanisms and for relating structure to function. Here we report a highly accurate technique for inferring the major modes of structural correlation in macromolecules using likelihood-based statistical analysis of sets of structures. This method is generally applicable to any ensemble of related molecules, including families of nuclear magnetic resonance (NMR) models, different crystal forms of a protein, and structural alignments of homologous proteins, as well as molecular dynamics trajectories. Dominant modes of structural correlation are determined using principal components analysis (PCA) of the maximum likelihood estimate of the correlation matrix. The correlations we identify are inherently independent of the statistical uncertainty and dynamic heterogeneity associated with the structural coordinates. We additionally present an easily interpretable method (“PCA plots”) for displaying these positional correlations by color-coding them onto a macromolecular structure. Maximum likelihood PCA of structural superpositions, and the structural PCA plots that illustrate the results, will facilitate the accurate determination of dynamic structural correlations analyzed in diverse fields of structural biology. PMID:18282091
Family dynamics and psychosocial functioning in children with SCI/D from Colombia, South America
Nicolais, Christina J.; Perrin, Paul B.; Panyavin, Ivan; Nicholls, Elizabeth G.; Olivera Plaza, Silvia Leonor; Quintero, Lorena Medina; Arango-Lasprilla, Juan Carlos
2016-01-01
Objective The purpose of this study was to examine the connections between family dynamics and the psychosocial functioning of children with spinal cord injuries and disorders (SCI/D). Design Cross-sectional. Setting Participants were recruited from communities in Neiva, Colombia. Participants Thirty children with SCI/D and their primary caregiver participated. Children were between 8 and 17 years of age, and had sustained their injury at least six months prior to data collection. Interventions NA. Outcome measures Participating children completed measures assessing their own psychosocial functioning (Children's Depression Inventory, Revised Children's Manifest Anxiety Scale-2, Pediatric Quality of Life Inventory), and their primary caregiver completed measures of family dynamics (Family Adaptability and Cohesion Evaluation Scale- Fourth Edition, Family Communication Scale, Family Assessment Device- General Functioning, Family Satisfaction Scale, Relationship-Focused Coping Scale). Results A correlation matrix showed a number of significant bivariate correlations between child and family variables, and three multiple regressions showed that family satisfaction, empathy, and flexibility significantly explained 27% of the variance in child worry; family satisfaction and communication explained 18% of the variance in child social anxiety; and family cohesion and communication explained 23% of the variance in child emotional functioning. Conclusions These findings highlight the importance of rehabilitation professionals considering the association between family dynamics and the psychosocial functioning of children with SCI/D when working with this population. PMID:25582185
Structural connectome topology relates to regional BOLD signal dynamics in the mouse brain
NASA Astrophysics Data System (ADS)
Sethi, Sarab S.; Zerbi, Valerio; Wenderoth, Nicole; Fornito, Alex; Fulcher, Ben D.
2017-04-01
Brain dynamics are thought to unfold on a network determined by the pattern of axonal connections linking pairs of neuronal elements; the so-called connectome. Prior work has indicated that structural brain connectivity constrains pairwise correlations of brain dynamics ("functional connectivity"), but it is not known whether inter-regional axonal connectivity is related to the intrinsic dynamics of individual brain areas. Here we investigate this relationship using a weighted, directed mesoscale mouse connectome from the Allen Mouse Brain Connectivity Atlas and resting state functional MRI (rs-fMRI) time-series data measured in 184 brain regions in eighteen anesthetized mice. For each brain region, we measured degree, betweenness, and clustering coefficient from weighted and unweighted, and directed and undirected versions of the connectome. We then characterized the univariate rs-fMRI dynamics in each brain region by computing 6930 time-series properties using the time-series analysis toolbox, hctsa. After correcting for regional volume variations, strong and robust correlations between structural connectivity properties and rs-fMRI dynamics were found only when edge weights were accounted for, and were associated with variations in the autocorrelation properties of the rs-fMRI signal. The strongest relationships were found for weighted in-degree, which was positively correlated to the autocorrelation of fMRI time series at time lag τ = 34 s (partial Spearman correlation ρ = 0.58 ), as well as a range of related measures such as relative high frequency power (f > 0.4 Hz: ρ = - 0.43 ). Our results indicate that the topology of inter-regional axonal connections of the mouse brain is closely related to intrinsic, spontaneous dynamics such that regions with a greater aggregate strength of incoming projections display longer timescales of activity fluctuations.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pham, Tuan Anh; Ogitsu, Tadashi; Lau, Edmond Y.
Establishing an accurate and predictive computational framework for the description of complex aqueous solutions is an ongoing challenge for density functional theory based first-principles molecular dynamics (FPMD) simulations. In this context, important advances have been made in recent years, including the development of sophisticated exchange-correlation functionals. On the other hand, simulations based on simple generalized gradient approximation (GGA) functionals remain an active field, particularly in the study of complex aqueous solutions due to a good balance between the accuracy, computational expense, and the applicability to a wide range of systems. In such simulations we often perform them at elevated temperaturesmore » to artificially “correct” for GGA inaccuracies in the description of liquid water; however, a detailed understanding of how the choice of temperature affects the structure and dynamics of other components, such as solvated ions, is largely unknown. In order to address this question, we carried out a series of FPMD simulations at temperatures ranging from 300 to 460 K for liquid water and three representative aqueous solutions containing solvated Na +, K +, and Cl - ions. We show that simulations at 390–400 K with the Perdew-Burke-Ernzerhof (PBE) exchange-correlation functional yield water structure and dynamics in good agreement with experiments at ambient conditions. Simultaneously, this computational setup provides ion solvation structures and ion effects on water dynamics consistent with experiments. These results suggest that an elevated temperature around 390–400 K with the PBE functional can be used for the description of structural and dynamical properties of liquid water and complex solutions with solvated ions at ambient conditions.« less
Pham, Tuan Anh; Ogitsu, Tadashi; Lau, Edmond Y.; ...
2016-10-17
Establishing an accurate and predictive computational framework for the description of complex aqueous solutions is an ongoing challenge for density functional theory based first-principles molecular dynamics (FPMD) simulations. In this context, important advances have been made in recent years, including the development of sophisticated exchange-correlation functionals. On the other hand, simulations based on simple generalized gradient approximation (GGA) functionals remain an active field, particularly in the study of complex aqueous solutions due to a good balance between the accuracy, computational expense, and the applicability to a wide range of systems. In such simulations we often perform them at elevated temperaturesmore » to artificially “correct” for GGA inaccuracies in the description of liquid water; however, a detailed understanding of how the choice of temperature affects the structure and dynamics of other components, such as solvated ions, is largely unknown. In order to address this question, we carried out a series of FPMD simulations at temperatures ranging from 300 to 460 K for liquid water and three representative aqueous solutions containing solvated Na +, K +, and Cl - ions. We show that simulations at 390–400 K with the Perdew-Burke-Ernzerhof (PBE) exchange-correlation functional yield water structure and dynamics in good agreement with experiments at ambient conditions. Simultaneously, this computational setup provides ion solvation structures and ion effects on water dynamics consistent with experiments. These results suggest that an elevated temperature around 390–400 K with the PBE functional can be used for the description of structural and dynamical properties of liquid water and complex solutions with solvated ions at ambient conditions.« less
Kurashige, Yuki; Yanai, Takeshi
2011-09-07
We present a second-order perturbation theory based on a density matrix renormalization group self-consistent field (DMRG-SCF) reference function. The method reproduces the solution of the complete active space with second-order perturbation theory (CASPT2) when the DMRG reference function is represented by a sufficiently large number of renormalized many-body basis, thereby being named DMRG-CASPT2 method. The DMRG-SCF is able to describe non-dynamical correlation with large active space that is insurmountable to the conventional CASSCF method, while the second-order perturbation theory provides an efficient description of dynamical correlation effects. The capability of our implementation is demonstrated for an application to the potential energy curve of the chromium dimer, which is one of the most demanding multireference systems that require best electronic structure treatment for non-dynamical and dynamical correlation as well as large basis sets. The DMRG-CASPT2/cc-pwCV5Z calculations were performed with a large (3d double-shell) active space consisting of 28 orbitals. Our approach using large-size DMRG reference addressed the problems of why the dissociation energy is largely overestimated by CASPT2 with the small active space consisting of 12 orbitals (3d4s), and also is oversensitive to the choice of the zeroth-order Hamiltonian. © 2011 American Institute of Physics
NASA Astrophysics Data System (ADS)
Tahmassebi, Amirhessam; Pinker-Domenig, Katja; Wengert, Georg; Lobbes, Marc; Stadlbauer, Andreas; Romero, Francisco J.; Morales, Diego P.; Castillo, Encarnacion; Garcia, Antonio; Botella, Guillermo; Meyer-Bäse, Anke
2017-05-01
Graph network models in dementia have become an important computational technique in neuroscience to study fundamental organizational principles of brain structure and function of neurodegenerative diseases such as dementia. The graph connectivity is reflected in the connectome, the complete set of structural and functional connections of the graph network, which is mostly based on simple Pearson correlation links. In contrast to simple Pearson correlation networks, the partial correlations (PC) only identify direct correlations while indirect associations are eliminated. In addition to this, the state-of-the-art techniques in brain research are based on static graph theory, which is unable to capture the dynamic behavior of the brain connectivity, as it alters with disease evolution. We propose a new research avenue in neuroimaging connectomics based on combining dynamic graph network theory and modeling strategies at different time scales. We present the theoretical framework for area aggregation and time-scale modeling in brain networks as they pertain to disease evolution in dementia. This novel paradigm is extremely powerful, since we can derive both static parameters pertaining to node and area parameters, as well as dynamic parameters, such as system's eigenvalues. By implementing and analyzing dynamically both disease driven PC-networks and regular concentration networks, we reveal differences in the structure of these network that play an important role in the temporal evolution of this disease. The described research is key to advance biomedical research on novel disease prediction trajectories and dementia therapies.
Desdouits, Nathan; Nilges, Michael; Blondel, Arnaud
2015-02-01
Protein conformation has been recognized as the key feature determining biological function, as it determines the position of the essential groups specifically interacting with substrates. Hence, the shape of the cavities or grooves at the protein surface appears to drive those functions. However, only a few studies describe the geometrical evolution of protein cavities during molecular dynamics simulations (MD), usually with a crude representation. To unveil the dynamics of cavity geometry evolution, we developed an approach combining cavity detection and Principal Component Analysis (PCA). This approach was applied to four systems subjected to MD (lysozyme, sperm whale myoglobin, Dengue envelope protein and EF-CaM complex). PCA on cavities allows us to perform efficient analysis and classification of the geometry diversity explored by a cavity. Additionally, it reveals correlations between the evolutions of the cavities and structures, and can even suggest how to modify the protein conformation to induce a given cavity geometry. It also helps to perform fast and consensual clustering of conformations according to cavity geometry. Finally, using this approach, we show that both carbon monoxide (CO) location and transfer among the different xenon sites of myoglobin are correlated with few cavity evolution modes of high amplitude. This correlation illustrates the link between ligand diffusion and the dynamic network of internal cavities. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.
Li, Huahui; Kong, Lingzhi; Wu, Xihong; Li, Liang
2013-01-01
In reverberant rooms with multiple-people talking, spatial separation between speech sources improves recognition of attended speech, even though both the head-shadowing and interaural-interaction unmasking cues are limited by numerous reflections. It is the perceptual integration between the direct wave and its reflections that bridges the direct-reflection temporal gaps and results in the spatial unmasking under reverberant conditions. This study further investigated (1) the temporal dynamic of the direct-reflection-integration-based spatial unmasking as a function of the reflection delay, and (2) whether this temporal dynamic is correlated with the listeners’ auditory ability to temporally retain raw acoustic signals (i.e., the fast decaying primitive auditory memory, PAM). The results showed that recognition of the target speech against the speech-masker background is a descending exponential function of the delay of the simulated target reflection. In addition, the temporal extent of PAM is frequency dependent and markedly longer than that for perceptual fusion. More importantly, the temporal dynamic of the speech-recognition function is significantly correlated with the temporal extent of the PAM of low-frequency raw signals. Thus, we propose that a chain process, which links the earlier-stage PAM with the later-stage correlation computation, perceptual integration, and attention facilitation, plays a role in spatially unmasking target speech under reverberant conditions. PMID:23658664
NASA Astrophysics Data System (ADS)
Wang, Ting-Ting; Ma, Yu-Gang; Zhang, Chun-Jian; Zhang, Zheng-Qiao
2018-03-01
The proton-proton momentum correlation function from different rapidity regions is systematically investigated for the Au + Au collisions at different impact parameters and different energies from 400 A MeV to 1500 A MeV in the framework of the isospin-dependent quantum molecular dynamics model complemented by the Lednický-Lyuboshitz analytical method. In particular, the in-medium nucleon-nucleon cross-section dependence of the correlation function is brought into focus, while the impact parameter and energy dependence of the momentum correlation function are also explored. The sizes of the emission source are extracted by fitting the momentum correlation functions using the Gaussian source method. We find that the in-medium nucleon-nucleon cross section obviously influences the proton-proton momentum correlation function, which is from the whole-rapidity or projectile or target rapidity region at smaller impact parameters, but there is no effect on the mid-rapidity proton-proton momentum correlation function, which indicates that the emission mechanism differs between projectile or target rapidity and mid-rapidity protons.
Optimized "detectors" for dynamics analysis in solid-state NMR
NASA Astrophysics Data System (ADS)
Smith, Albert A.; Ernst, Matthias; Meier, Beat H.
2018-01-01
Relaxation in nuclear magnetic resonance (NMR) results from stochastic motions that modulate anisotropic NMR interactions. Therefore, measurement of relaxation-rate constants can be used to characterize molecular-dynamic processes. The motion is often characterized by Markov processes using an auto-correlation function, which is assumed to be a sum of multiple decaying exponentials. We have recently shown that such a model can lead to severe misrepresentation of the real motion, when the real correlation function is more complex than the model. Furthermore, multiple distributions of motion may yield the same set of dynamics data. Therefore, we introduce optimized dynamics "detectors" to characterize motions which are linear combinations of relaxation-rate constants. A detector estimates the average or total amplitude of motion for a range of motional correlation times. The information obtained through the detectors is less specific than information obtained using an explicit model, but this is necessary because the information contained in the relaxation data is ambiguous, if one does not know the correct motional model. On the other hand, if one has a molecular dynamics trajectory, one may calculate the corresponding detector responses, allowing direct comparison to experimental NMR dynamics analysis. We describe how to construct a set of optimized detectors for a given set of relaxation measurements. We then investigate the properties of detectors for a number of different data sets, thus gaining an insight into the actual information content of the NMR data. Finally, we show an example analysis of ubiquitin dynamics data using detectors, using the DIFRATE software.
NASA Astrophysics Data System (ADS)
Chakraborty, Ahana; Sensarma, Rajdeep
2018-03-01
The Born-Markov approximation is widely used to study the dynamics of open quantum systems coupled to external baths. Using Keldysh formalism, we show that the dynamics of a system of bosons (fermions) linearly coupled to a noninteracting bosonic (fermionic) bath falls outside this paradigm if the bath spectral function has nonanalyticities as a function of frequency. In this case, we show that the dissipative and noise kernels governing the dynamics have distinct power-law tails. The Green's functions show a short-time "quasi"-Markovian exponential decay before crossing over to a power-law tail governed by the nonanalyticity of the spectral function. We study a system of bosons (fermions) hopping on a one-dimensional lattice, where each site is coupled linearly to an independent bath of noninteracting bosons (fermions). We obtain exact expressions for the Green's functions of this system, which show power-law decay ˜|t - t'|-3 /2 . We use these to calculate the density and current profile, as well as unequal-time current-current correlators. While the density and current profiles show interesting quantitative deviations from Markovian results, the current-current correlators show qualitatively distinct long-time power-law tails |t - t'|-3 characteristic of non-Markovian dynamics. We show that the power-law decays survive in the presence of interparticle interaction in the system, but the crossover time scale is shifted to larger values with increasing interaction strength.
Siqueira, Leonardo J A; Ribeiro, Mauro C C
2007-10-11
Thermodynamics, structure, and dynamics of an ionic liquid based on a quaternary ammonium salt with ether side chain, namely, N-ethyl-N,N-dimethyl-N-(2-methoxyethyl)ammonium bis(trifluoromethanesulfonyl)imide, MOENM2E TFSI, are investigated by molecular dynamics (MD) simulations. Average density and configurational energy of simulated MOENM2E TFSI are interpreted with models that take into account empirical ionic volumes. A throughout comparison of the equilibrium structure of MOENM2E TFSI with previous results for the more common ionic liquids based on imidazolium cations is provided. Several time correlation functions are used to reveal the microscopic dynamics of MOENM2E TFSI. Structural relaxation is discussed by the calculation of simultaneous space-time correlation functions. Temperature effects on transport coefficients (diffusion, conductivity, and viscosity) are investigated. The ratio between the actual conductivity and the estimate from ionic diffusion by the Nernst-Einstein equation indicates that correlated motion of neighboring ions in MOENM2E TFSI is similar to imidazolium ionic liquids. In line with experiment, Walden plot of conductivity and viscosity indicates that simulated MOENM2E TFSI should be classified as a poor ionic liquid.
Lee, Hwang-Jae; Chang, Won Hyuk; Hwang, Sun Hee; Choi, Byung-Ok; Ryu, Gyu-Ha; Kim, Yun-Hee
2017-04-01
The purpose of this study was to examine age-related gait characteristics and their associations with balance function in older adults. A total of 51 adult volunteers participated. All subjects underwent locomotion analysis using a 3D motion analysis and 12-channel dynamic electromyography system. Dynamic balance function was assessed by the Berg Balance Scale. Older adults showed a higher level of muscle activation than young adults, and there were significant positive correlations between increased age and activation of the trunk and thigh muscles in the stance and swing phase of the gait cycle. In particular, back extensor muscle activity was mostly correlated with the dynamic balance in older adults. Thus, back extensor muscle activity in walking may provide a clue for higher falling risk in older adults. This study demonstrates that the back extensor muscles play very important roles with potential for rehabilitation training to improve balance and gait in older adults.
Molteni, Matteo; Weigel, Udo M; Remiro, Francisco; Durduran, Turgut; Ferri, Fabio
2014-11-17
We present a new hardware simulator (HS) for characterization, testing and benchmarking of digital correlators used in various optical correlation spectroscopy experiments where the photon statistics is Gaussian and the corresponding time correlation function can have any arbitrary shape. Starting from the HS developed in [Rev. Sci. Instrum. 74, 4273 (2003)], and using the same I/O board (PCI-6534 National Instrument) mounted on a modern PC (Intel Core i7-CPU, 3.07GHz, 12GB RAM), we have realized an instrument capable of delivering continuous streams of TTL pulses over two channels, with a time resolution of Δt = 50ns, up to a maximum count rate of 〈I〉 ∼ 5MHz. Pulse streams, typically detected in dynamic light scattering and diffuse correlation spectroscopy experiments were generated and measured with a commercial hardware correlator obtaining measured correlation functions that match accurately the expected ones.
Atomic Dynamics in Simple Liquid: de Gennes Narrowing Revisited
NASA Astrophysics Data System (ADS)
Wu, Bin; Iwashita, Takuya; Egami, Takeshi
2018-03-01
The de Gennes narrowing phenomenon is frequently observed by neutron or x -ray scattering measurements of the dynamics of complex systems, such as liquids, proteins, colloids, and polymers. The characteristic slowing down of dynamics in the vicinity of the maximum of the total scattering intensity is commonly attributed to enhanced cooperativity. In this Letter, we present an alternative view on its origin through the examination of the time-dependent pair correlation function, the van Hove correlation function, for a model liquid in two, three, and four dimensions. We find that the relaxation time increases monotonically with distance and the dependence on distance varies with dimension. We propose a heuristic explanation of this dependence based on a simple geometrical model. This finding sheds new light on the interpretation of the de Gennes narrowing phenomenon and the α -relaxation time.
Memory Effects and Nonequilibrium Correlations in the Dynamics of Open Quantum Systems
NASA Astrophysics Data System (ADS)
Morozov, V. G.
2018-01-01
We propose a systematic approach to the dynamics of open quantum systems in the framework of Zubarev's nonequilibrium statistical operator method. The approach is based on the relation between ensemble means of the Hubbard operators and the matrix elements of the reduced statistical operator of an open quantum system. This key relation allows deriving master equations for open systems following a scheme conceptually identical to the scheme used to derive kinetic equations for distribution functions. The advantage of the proposed formalism is that some relevant dynamical correlations between an open system and its environment can be taken into account. To illustrate the method, we derive a non-Markovian master equation containing the contribution of nonequilibrium correlations associated with energy conservation.
Determination of split renal function using dynamic CT-angiography: preliminary results.
Helck, Andreas; Schönermarck, Ulf; Habicht, Antje; Notohamiprodjo, Mike; Stangl, Manfred; Klotz, Ernst; Nikolaou, Konstantin; la Fougère, Christian; Clevert, Dirk Andrè; Reiser, Maximilian; Becker, Christoph
2014-01-01
To determine the feasibility of a dynamic CT angiography-protocol with regard to simultaneous assessment of renal anatomy and function. 7 healthy potential kidney donors (58 ± 7 years) underwent a dynamic computed tomography angiography (CTA) using a 128-slice CT-scanner with continuous bi-directional table movement, allowing the coverage of a scan range of 18 cm within 1.75 sec. Twelve scans of the kidneys (n = 14) were acquired every 3.5 seconds with the aim to simultaneously obtain CTA and renal function data. Image quality was assessed quantitatively (HU-measurements) and qualitatively (grade 1-4, 1 = best). The glomerular filtration rate (GFR) was calculated by a modified Patlak method and compared with the split renal function obtained with renal scintigraphy. Mean maximum attenuation was 464 ± 58 HU, 435 ± 48 HU and 277 ± 29 HU in the aorta, renal arteries, and renal veins, respectively. The abdominal aorta and all renal vessels were depicted excellently (grade 1.0). The image quality score for cortex differentiation was 1.6 ± 0.49, for the renal parenchyma 2.4 ± 0.49. GFR obtained from dynamic CTA correlated well with renal scintigraphy with a correlation coefficient of r = 0.84; P = 0.0002 (n = 14). The average absolute deviation was 1.6 mL/min. The average effective dose was 8.96 mSv. Comprehensive assessment of renal anatomy and function is feasible using a single dynamic CT angiography examination. The proposed protocol may help to improve management in case of asymmetric kidney function as well as to simplify evaluation of potential living kidney donors.
Short-time vibrational dynamics of metaphosphate glasses
NASA Astrophysics Data System (ADS)
Kalampounias, Angelos G.
2012-02-01
In this paper we present the picosecond vibrational dynamics of a series of binary metaphosphate glasses, namely Na2O-P2O5, MO-P2O5 (M=Ba, Sr, Ca, Mg) and Al2O3-3P2O5 by means of Raman spectroscopy. We studied the vibrational dephasing and vibrational frequency modulation by calculating time correlation functions of vibrational relaxation by fits in the frequency domain. The fitting method used enables one to model the real line profiles intermediate between Lorentzian and Gaussian by an analytical function, which has an analytical counterpart in the time domain. The symmetric stretching modes νs(PO2-) and νs(P-O-P) of the PO2- entity of PØ2O2- units and of P-O-P bridges in metaphosphate arrangements have been investigated by Raman spectroscopy and we used them as probes of the dynamics of these glasses. The vibrational time correlation functions of both modes studied are rather adequately interpreted within the assumption of exponential modulation function in the context of Kubo-Rothschield theory and indicate that the system experiences an intermediate dynamical regime that gets only slower with an increase in the ionic radius of the cation-modifier. We found that the vibrational correlation functions of all glasses studied comply with the Rothschild approach assuming that the environmental modulation is described by a stretched exponential decay. The evolution of the dispersion parameter α with increasing ionic radius of the cation indicates the deviation from the model simple liquid indicating the reduction of the coherence decay in the perturbation potential as a result of local short lived aggregates. The results are discussed in the framework of the current phenomenological status of the field.
NASA Astrophysics Data System (ADS)
Stramaglia, S.; Pellicoro, M.; Angelini, L.; Amico, E.; Aerts, H.; Cortés, J. M.; Laureys, S.; Marinazzo, D.
2017-04-01
Dynamical models implemented on the large scale architecture of the human brain may shed light on how a function arises from the underlying structure. This is the case notably for simple abstract models, such as the Ising model. We compare the spin correlations of the Ising model and the empirical functional brain correlations, both at the single link level and at the modular level, and show that their match increases at the modular level in anesthesia, in line with recent results and theories. Moreover, we show that at the peak of the specific heat (the critical state), the spin correlations are minimally shaped by the underlying structural network, explaining how the best match between the structure and function is obtained at the onset of criticality, as previously observed. These findings confirm that brain dynamics under anesthesia shows a departure from criticality and could open the way to novel perspectives when the conserved magnetization is interpreted in terms of a homeostatic principle imposed to neural activity.
Multiple Point Dynamic Gas Density Measurements Using Molecular Rayleigh Scattering
NASA Technical Reports Server (NTRS)
Seasholtz, Richard; Panda, Jayanta
1999-01-01
A nonintrusive technique for measuring dynamic gas density properties is described. Molecular Rayleigh scattering is used to measure the time-history of gas density simultaneously at eight spatial locations at a 50 kHz sampling rate. The data are analyzed using the Welch method of modified periodograms to reduce measurement uncertainty. Cross-correlations, power spectral density functions, cross-spectral density functions, and coherence functions may be obtained from the data. The technique is demonstrated using low speed co-flowing jets with a heated inner jet.
Optical observation of correlated motions in dihydrofolate reductase
NASA Astrophysics Data System (ADS)
Xu, Mengyang; Niessen, Katherine; Pace, James; Cody, Vivian; Markelz, Andrea
2015-03-01
Enzyme function relies on its structural flexibility to make conformational changes for substrate binding and product release. An example of a metabolic enzyme where such structural changes are vital is dihydrofolate reductase (DHFR). DHFR is essential in both prokaryotes and eukaryotes for the nucleotide biosynthesis by catalyzing the reduction of dihydrofolate to tetrahydrofolate. NMR dynamical measurements found large amplitude fast dynamics that could indicate rigid-body, twisting-hinge motion for ecDHFR that may mediate flux. The role of such long-range correlated motions in function was suggested by the observed sharp decrease in enzyme activity for the single point mutation G121V, which is remote from active sites. This decrease in activity may be caused by the mutation interfering with the long-range intramolecular vibrations necessary for rapid access to functional configurations. We use our new technique of crystal anisotropy terahertz microscopy (CATM), to observe correlated motions in ecDHFR crystals with the bonding of NADPH and methotrexate. We compare the measured intramolecular vibrational spectrum with calculations using normal mode analysis.
NASA Astrophysics Data System (ADS)
Suzuki, Yosuke; Ebina, Kuniyoshi; Tanaka, Shigenori
2016-08-01
A computational scheme to describe the coherent dynamics of excitation energy transfer (EET) in molecular systems is proposed on the basis of generalized master equations with memory kernels. This formalism takes into account those physical effects in electron-bath coupling system such as the spin symmetry of excitons, the inelastic electron tunneling and the quantum features of nuclear motions, thus providing a theoretical framework to perform an ab initio description of EET through molecular simulations for evaluating the spectral density and the temporal correlation function of electronic coupling. Some test calculations have then been carried out to investigate the dependence of exciton population dynamics on coherence memory, inelastic tunneling correlation time, magnitude of electronic coupling, quantum correction to temporal correlation function, reorganization energy and energy gap.
Spectral fingerprints of large-scale cortical dynamics during ambiguous motion perception.
Helfrich, Randolph F; Knepper, Hannah; Nolte, Guido; Sengelmann, Malte; König, Peter; Schneider, Till R; Engel, Andreas K
2016-11-01
Ambiguous stimuli have been widely used to study the neuronal correlates of consciousness. Recently, it has been suggested that conscious perception might arise from the dynamic interplay of functionally specialized but widely distributed cortical areas. While previous research mainly focused on phase coupling as a correlate of cortical communication, more recent findings indicated that additional coupling modes might coexist and possibly subserve distinct cortical functions. Here, we studied two coupling modes, namely phase and envelope coupling, which might differ in their origins, putative functions and dynamics. Therefore, we recorded 128-channel EEG while participants performed a bistable motion task and utilized state-of-the-art source-space connectivity analysis techniques to study the functional relevance of different coupling modes for cortical communication. Our results indicate that gamma-band phase coupling in extrastriate visual cortex might mediate the integration of visual tokens into a moving stimulus during ambiguous visual stimulation. Furthermore, our results suggest that long-range fronto-occipital gamma-band envelope coupling sustains the horizontal percept during ambiguous motion perception. Additionally, our results support the idea that local parieto-occipital alpha-band phase coupling controls the inter-hemispheric information transfer. These findings provide correlative evidence for the notion that synchronized oscillatory brain activity reflects the processing of sensory input as well as the information integration across several spatiotemporal scales. The results indicate that distinct coupling modes are involved in different cortical computations and that the rich spatiotemporal correlation structure of the brain might constitute the functional architecture for cortical processing and specific multi-site communication. Hum Brain Mapp 37:4099-4111, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Interplay between Functional Connectivity and Scale-Free Dynamics in Intrinsic fMRI Networks
Ciuciu, Philippe; Abry, Patrice; He, Biyu J.
2014-01-01
Studies employing functional connectivity-type analyses have established that spontaneous fluctuations in functional magnetic resonance imaging (fMRI) signals are organized within large-scale brain networks. Meanwhile, fMRI signals have been shown to exhibit 1/f-type power spectra – a hallmark of scale-free dynamics. We studied the interplay between functional connectivity and scale-free dynamics in fMRI signals, utilizing the fractal connectivity framework – a multivariate extension of the univariate fractional Gaussian noise model, which relies on a wavelet formulation for robust parameter estimation. We applied this framework to fMRI data acquired from healthy young adults at rest and performing a visual detection task. First, we found that scale-invariance existed beyond univariate dynamics, being present also in bivariate cross-temporal dynamics. Second, we observed that frequencies within the scale-free range do not contribute evenly to inter-regional connectivity, with a systematically stronger contribution of the lowest frequencies, both at rest and during task. Third, in addition to a decrease of the Hurst exponent and inter-regional correlations, task performance modified cross-temporal dynamics, inducing a larger contribution of the highest frequencies within the scale-free range to global correlation. Lastly, we found that across individuals, a weaker task modulation of the frequency contribution to inter-regional connectivity was associated with better task performance manifesting as shorter and less variable reaction times. These findings bring together two related fields that have hitherto been studied separately – resting-state networks and scale-free dynamics, and show that scale-free dynamics of human brain activity manifest in cross-regional interactions as well. PMID:24675649
Morphological dynamics of mitochondria--a special emphasis on cardiac muscle cells.
Hom, Jennifer; Sheu, Shey-Shing
2009-06-01
Mitochondria play a critical role in cellular energy metabolism, Ca(2+) homeostasis, reactive oxygen species generation, apoptosis, aging, and development. Many recent publications have shown that a continuous balance of fusion and fission of these organelles is important in maintaining their proper function. Therefore, there is a steep correlation between the form and function of mitochondria. Many major proteins involved in mitochondrial fusion and fission have been identified in different cell types, including heart. However, the functional role of mitochondrial dynamics in the heart remains, for the most part, unexplored. In this review we will cover the recent field of mitochondrial dynamics and its physiological and pathological implications, with a particular emphasis on the experimental and theoretical basis of mitochondrial dynamics in the heart.
Functional correlation approach to operational risk in banking organizations
NASA Astrophysics Data System (ADS)
Kühn, Reimer; Neu, Peter
2003-05-01
A Value-at-Risk-based model is proposed to compute the adequate equity capital necessary to cover potential losses due to operational risks, such as human and system process failures, in banking organizations. Exploring the analogy to a lattice gas model from physics, correlations between sequential failures are modeled by as functionally defined, heterogeneous couplings between mutually supportive processes. In contrast to traditional risk models for market and credit risk, where correlations are described as equal-time-correlations by a covariance matrix, the dynamics of the model shows collective phenomena such as bursts and avalanches of process failures.
Dynamic functional connectivity of the default mode network tracks daydreaming.
Kucyi, Aaron; Davis, Karen D
2014-10-15
Humans spend much of their time engaged in stimulus-independent thoughts, colloquially known as "daydreaming" or "mind-wandering." A fundamental question concerns how awake, spontaneous brain activity represents the ongoing cognition of daydreaming versus unconscious processes characterized as "intrinsic." Since daydreaming involves brief cognitive events that spontaneously fluctuate, we tested the hypothesis that the dynamics of brain network functional connectivity (FC) are linked with daydreaming. We determined the general tendency to daydream in healthy adults based on a daydreaming frequency scale (DDF). Subjects then underwent both resting state functional magnetic resonance imaging (rs-fMRI) and fMRI during sensory stimulation with intermittent thought probes to determine the occurrences of mind-wandering events. Brain regions within the default mode network (DMN), purported to be involved in daydreaming, were assessed for 1) static FC across the entire fMRI scans, and 2) dynamic FC based on FC variability (FCV) across 30s progressively sliding windows of 2s increments within each scan. We found that during both resting and sensory stimulation states, individual differences in DDF were negatively correlated with static FC between the posterior cingulate cortex and a ventral DMN subsystem involved in future-oriented thought. Dynamic FC analysis revealed that DDF was positively correlated with FCV within the same DMN subsystem in the resting state but not during stimulation. However, dynamic but not static FC, in this subsystem, was positively correlated with an individual's degree of self-reported mind-wandering during sensory stimulation. These findings identify temporal aspects of spontaneous DMN activity that reflect conscious and unconscious processes. Copyright © 2014 Elsevier Inc. All rights reserved.
Varughese, Jayson F; Chalovich, Joseph M; Li, Yumin
2010-10-01
Mutations of any subunit of the troponin complex may lead to serious disorders. Rational approaches to managing these disorders require knowledge of the complex interactions among the three subunits that are required for proper function. Molecular dynamics (MD) simulations were performed for both skeletal (sTn) and cardiac (cTn) troponin. The interactions and correlated motions among the three components of the troponin complex were analyzed using both Molecular Mechanics-Generalized Born Surface Area (MMGBSA) and cross-correlation techniques. The TnTH2 helix was strongly positively correlated with the two long helices of TnI. The C domain of TnC was positively correlated with TnI and TnT. The N domain of TnC was negatively correlated with TnI and TnT in cTn, but not in sTn. The two C-domain calcium-binding sites of TnC were dynamically correlated. The two regulatory N-domain calcium-binding sites of TnC were dynamically correlated, even though the calcium-binding site I is dysfunctional. The strong interaction residue pairs and the strong dynamically correlated residues pairs among the three components of troponin complexes were identified. These correlated motions are consistent with the idea that there is a high degree of cooperativity among the components of the regulatory complex in response to Ca(2+) and other effectors. This approach may give insight into the mechanism by which mutations of troponin cause disease. It is interesting that some observed disease causing mutations fall within regions of troponin that are strongly correlated or interacted.
Depressor septi nasi modifications in rhinoplasty: a review of anatomy and surgical techniques.
Benlier, Erol; Balta, Serkan; Tas, Suleyman
2014-08-01
The anatomy of the nasal muscles contributes a social harmony in aesthetic rhinoplasty because these muscles coordinate the nose and the upper lip while smiling. Sometimes this coordination can be interrupted by the hyperactivity or variations of these muscles and may result as a deformity because of their dynamic functions and relations with the nose. In our daily practice, we usually perform the rhinoplasty without considering the dynamic functions. When the patients recover the muscle functions after operation and start to use their mimics, such as smiling, the undamaged dynamic forces may start to rotate the tip of the nose inferiorly in a long-term period, correlated with their preoperative function. To avoid this unexpected rotation it is essential to remember preoperative examination of the smile patterns. To manage this functional part of rhinoplasty, we aimed to clarify the smiling patterns or deformities mainly focused on depressor septi nasi muscle in this article. This muscle creates downward movement of the nasal tip and shortens the upper lip during smiling. The overactivity of this muscle can aggravate the smiling deformity in some patients by a sharper nasolabial angle correlated with levator labii superioris alaeque nasi and orbicularis oris muscle activities. The article not only stresses the correction of this deformity, but also aims to guide their treatment alternatives for correlation of postoperative results and applicability in rhinoplasty. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.
Quantum regression theorem and non-Markovianity of quantum dynamics
NASA Astrophysics Data System (ADS)
Guarnieri, Giacomo; Smirne, Andrea; Vacchini, Bassano
2014-08-01
We explore the connection between two recently introduced notions of non-Markovian quantum dynamics and the validity of the so-called quantum regression theorem. While non-Markovianity of a quantum dynamics has been defined looking at the behavior in time of the statistical operator, which determines the evolution of mean values, the quantum regression theorem makes statements about the behavior of system correlation functions of order two and higher. The comparison relies on an estimate of the validity of the quantum regression hypothesis, which can be obtained exactly evaluating two-point correlation functions. To this aim we consider a qubit undergoing dephasing due to interaction with a bosonic bath, comparing the exact evaluation of the non-Markovianity measures with the violation of the quantum regression theorem for a class of spectral densities. We further study a photonic dephasing model, recently exploited for the experimental measurement of non-Markovianity. It appears that while a non-Markovian dynamics according to either definition brings with itself violation of the regression hypothesis, even Markovian dynamics can lead to a failure of the regression relation.
Stadler, A M; Digel, I; Embs, J P; Unruh, T; Tehei, M; Zaccai, G; Büldt, G; Artmann, G M
2009-06-17
A transition in hemoglobin (Hb), involving partial unfolding and aggregation, has been shown previously by various biophysical methods. The correlation between the transition temperature and body temperature for Hb from different species, suggested that it might be significant for biological function. To focus on such biologically relevant human Hb dynamics, we studied the protein internal picosecond motions as a response to hydration, by elastic and quasielastic neutron scattering. Rates of fast diffusive motions were found to be significantly enhanced with increasing hydration from fully hydrated powder to concentrated Hb solution. In concentrated protein solution, the data showed that amino acid side chains can explore larger volumes above body temperature than expected from normal temperature dependence. The body temperature transition in protein dynamics was absent in fully hydrated powder, indicating that picosecond protein dynamics responsible for the transition is activated only at a sufficient level of hydration. A collateral result from the study is that fully hydrated protein powder samples do not accurately describe all aspects of protein picosecond dynamics that might be necessary for biological function.
Dynamic functional connectivity: Promise, issues, and interpretations
Hutchison, R. Matthew; Womelsdorf, Thilo; Allen, Elena A.; Bandettini, Peter A.; Calhoun, Vince D.; Corbetta, Maurizio; Penna, Stefania Della; Duyn, Jeff H.; Glover, Gary H.; Gonzalez-Castillo, Javier; Handwerker, Daniel A.; Keilholz, Shella; Kiviniemi, Vesa; Leopold, David A.; de Pasquale, Francesco; Sporns, Olaf; Walter, Martin; Chang, Catie
2013-01-01
The brain must dynamically integrate, coordinate, and respond to internal and external stimuli across multiple time scales. Non-invasive measurements of brain activity with fMRI have greatly advanced our understanding of the large-scale functional organization supporting these fundamental features of brain function. Conclusions from previous resting-state fMRI investigations were based upon static descriptions of functional connectivity (FC), and only recently studies have begun to capitalize on the wealth of information contained within the temporal features of spontaneous BOLD FC. Emerging evidence suggests that dynamic FC metrics may index changes in macroscopic neural activity patterns underlying critical aspects of cognition and behavior, though limitations with regard to analysis and interpretation remain. Here, we review recent findings, methodological considerations, neural and behavioral correlates, and future directions in the emerging field of dynamic FC investigations. PMID:23707587
Nilsson, Henrik; Blomqvist, Lennart; Douglas, Lena; Nordell, Anders; Jacobsson, Hans; Hagen, Karin; Bergquist, Annika; Jonas, Eduard
2014-04-01
To evaluate dynamic hepatocyte-specific contrast-enhanced MRI (DHCE-MRI) for the assessment of global and segmental liver volume and function in patients with primary sclerosing cholangitis (PSC), and to explore the heterogeneous distribution of liver function in this patient group. Twelve patients with primary sclerosing cholangitis (PSC) and 20 healthy volunteers were examined using DHCE-MRI with Gd-EOB-DTPA. Segmental and total liver volume were calculated, and functional parameters (hepatic extraction fraction [HEF], input relative blood-flow [irBF], and mean transit time [MTT]) were calculated in each liver voxel using deconvolutional analysis. In each study subject, and incongruence score (IS) was constructed to describe the mismatch between segmental function and volume. Among patients, the liver function parameters were correlated to bile duct obstruction and to established scoring models for liver disease. Liver function was significantly more heterogeneously distributed in the patient group (IS 1.0 versus 0.4). There were significant correlations between biliary obstruction and segmental functional parameters (HEF rho -0.24; irBF rho -0.45), and the Mayo risk score correlated significantly with the total liver extraction capacity of Gd-EOB-DTPA (rho -0.85). The study demonstrates a new method to quantify total and segmental liver function using DHCE-MRI in patients with PSC. Copyright © 2013 Wiley Periodicals, Inc.
Nonlinear dynamic analysis of voices before and after surgical excision of vocal polyps
NASA Astrophysics Data System (ADS)
Zhang, Yu; McGilligan, Clancy; Zhou, Liang; Vig, Mark; Jiang, Jack J.
2004-05-01
Phase space reconstruction, correlation dimension, and second-order entropy, methods from nonlinear dynamics, are used to analyze sustained vowels generated by patients before and after surgical excision of vocal polyps. Two conventional acoustic perturbation parameters, jitter and shimmer, are also employed to analyze voices before and after surgery. Presurgical and postsurgical analyses of jitter, shimmer, correlation dimension, and second-order entropy are statistically compared. Correlation dimension and second-order entropy show a statistically significant decrease after surgery, indicating reduced complexity and higher predictability of postsurgical voice dynamics. There is not a significant postsurgical difference in shimmer, although jitter shows a significant postsurgical decrease. The results suggest that jitter and shimmer should be applied to analyze disordered voices with caution; however, nonlinear dynamic methods may be useful for analyzing abnormal vocal function and quantitatively evaluating the effects of surgical excision of vocal polyps.
RNA Polymerase II cluster dynamics predict mRNA output in living cells
Cho, Won-Ki; Jayanth, Namrata; English, Brian P; Inoue, Takuma; Andrews, J Owen; Conway, William; Grimm, Jonathan B; Spille, Jan-Hendrik; Lavis, Luke D; Lionnet, Timothée; Cisse, Ibrahim I
2016-01-01
Protein clustering is a hallmark of genome regulation in mammalian cells. However, the dynamic molecular processes involved make it difficult to correlate clustering with functional consequences in vivo. We developed a live-cell super-resolution approach to uncover the correlation between mRNA synthesis and the dynamics of RNA Polymerase II (Pol II) clusters at a gene locus. For endogenous β-actin genes in mouse embryonic fibroblasts, we observe that short-lived (~8 s) Pol II clusters correlate with basal mRNA output. During serum stimulation, a stereotyped increase in Pol II cluster lifetime correlates with a proportionate increase in the number of mRNAs synthesized. Our findings suggest that transient clustering of Pol II may constitute a pre-transcriptional regulatory event that predictably modulates nascent mRNA output. DOI: http://dx.doi.org/10.7554/eLife.13617.001 PMID:27138339
Liu, Jian; Miller, William H
2008-09-28
The maximum entropy analytic continuation (MEAC) method is used to extend the range of accuracy of the linearized semiclassical initial value representation (LSC-IVR)/classical Wigner approximation for real time correlation functions. LSC-IVR provides a very effective "prior" for the MEAC procedure since it is very good for short times, exact for all time and temperature for harmonic potentials (even for correlation functions of nonlinear operators), and becomes exact in the classical high temperature limit. This combined MEAC+LSC/IVR approach is applied here to two highly nonlinear dynamical systems, a pure quartic potential in one dimensional and liquid para-hydrogen at two thermal state points (25 and 14 K under nearly zero external pressure). The former example shows the MEAC procedure to be a very significant enhancement of the LSC-IVR for correlation functions of both linear and nonlinear operators, and especially at low temperature where semiclassical approximations are least accurate. For liquid para-hydrogen, the LSC-IVR is seen already to be excellent at T=25 K, but the MEAC procedure produces a significant correction at the lower temperature (T=14 K). Comparisons are also made as to how the MEAC procedure is able to provide corrections for other trajectory-based dynamical approximations when used as priors.
Dephasing dynamics in confined myoglobin
NASA Astrophysics Data System (ADS)
Goj, Anne; Loring, Roger F.
2007-11-01
Confinement of a solution can slow solvent dynamics and in turn influence the reactivity and structure of the solute. Encapsulating a protein in an aqueous pore affects its binding properties, stability to degradation, interconversion between conformational states, and energy relaxation. We perform molecular dynamics simulations of H64V-CO mutant myoglobin solvated by varying amounts of liquid water, and in turn enclosed by a matrix of immobilized solvent, to mimic differing degrees of confinement of H64V-CO in a glass. We calculate the three-pulse vibrational echo signal of the CO ligand from the autocorrelation function of fluctuations in the CO vibrational frequency. When the first solvation layer alone is free to relax, the correlation function displays only fast relaxation reminiscent of the case of a protein in a fixed, immobilized solvent matrix. However the vibrational echo signal in this case decays significantly more rapidly than for a static solvent. With two solvation layers mobile, the correlation function displays long time relaxation characteristic of the unconfined protein and the echo signal decays rapidly. The echo signal of the protein with two mobile solvation layers is nearly identical to that of the unconfined protein, despite the substantially constrained solvent dynamics in the confined case.
Johnson, Erin R; Contreras-García, Julia
2011-08-28
We develop a new density-functional approach combining physical insight from chemical structure with treatment of multi-reference character by real-space modeling of the exchange-correlation hole. We are able to recover, for the first time, correct fractional-charge and fractional-spin behaviour for atoms of groups 1 and 2. Based on Becke's non-dynamical correlation functional [A. D. Becke, J. Chem. Phys. 119, 2972 (2003)] and explicitly accounting for core-valence separation and pairing effects, this method is able to accurately describe dissociation and strong correlation in s-shell many-electron systems. © 2011 American Institute of Physics
NASA Astrophysics Data System (ADS)
Jana, Biman; Adkar, Bharat V.; Biswas, Rajib; Bagchi, Biman
2011-01-01
The catalytic conversion of adenosine triphosphate (ATP) and adenosine monophosphate (AMP) to adenosine diphosphate (ADP) by adenylate kinase (ADK) involves large amplitude, ligand induced domain motions, involving the opening and the closing of ATP binding domain (LID) and AMP binding domain (NMP) domains, during the repeated catalytic cycle. We discover and analyze an interesting dynamical coupling between the motion of the two domains during the opening, using large scale atomistic molecular dynamics trajectory analysis, covariance analysis, and multidimensional free energy calculations with explicit water. Initially, the LID domain must open by a certain amount before the NMP domain can begin to open. Dynamical correlation map shows interesting cross-peak between LID and NMP domain which suggests the presence of correlated motion between them. This is also reflected in our calculated two-dimensional free energy surface contour diagram which has an interesting elliptic shape, revealing a strong correlation between the opening of the LID domain and that of the NMP domain. Our free energy surface of the LID domain motion is rugged due to interaction with water and the signature of ruggedness is evident in the observed root mean square deviation variation and its fluctuation time correlation functions. We develop a correlated dynamical disorder-type theoretical model to explain the observed dynamic coupling between the motion of the two domains in ADK. Our model correctly reproduces several features of the cross-correlation observed in simulations.
Atomic Dynamics in Simple Liquid: de Gennes Narrowing Revisited
Wu, Bin; Iwashita, Takuya; Egami, Takeshi
2018-03-27
The de Gennes narrowing phenomenon is frequently observed by neutron or x-ray scattering measurements of the dynamics of complex systems, such as liquids, proteins, colloids, and polymers. The characteristic slowing down of dynamics in the vicinity of the maximum of the total scattering intensity is commonly attributed to enhanced cooperativity. In this Letter, we present an alternative view on its origin through the examination of the time-dependent pair correlation function, the van Hove correlation function, for a model liquid in two, three, and four dimensions. We find that the relaxation time increases monotonically with distance and the dependence on distancemore » varies with dimension. We propose a heuristic explanation of this dependence based on a simple geometrical model. Furthermore, this finding sheds new light on the interpretation of the de Gennes narrowing phenomenon and the α-relaxation time.« less
Atomic Dynamics in Simple Liquid: de Gennes Narrowing Revisited
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wu, Bin; Iwashita, Takuya; Egami, Takeshi
The de Gennes narrowing phenomenon is frequently observed by neutron or x-ray scattering measurements of the dynamics of complex systems, such as liquids, proteins, colloids, and polymers. The characteristic slowing down of dynamics in the vicinity of the maximum of the total scattering intensity is commonly attributed to enhanced cooperativity. In this Letter, we present an alternative view on its origin through the examination of the time-dependent pair correlation function, the van Hove correlation function, for a model liquid in two, three, and four dimensions. We find that the relaxation time increases monotonically with distance and the dependence on distancemore » varies with dimension. We propose a heuristic explanation of this dependence based on a simple geometrical model. Furthermore, this finding sheds new light on the interpretation of the de Gennes narrowing phenomenon and the α-relaxation time.« less
Transition from lognormal to χ2-superstatistics for financial time series
NASA Astrophysics Data System (ADS)
Xu, Dan; Beck, Christian
2016-07-01
Share price returns on different time scales can be well modelled by a superstatistical dynamics. Here we provide an investigation which type of superstatistics is most suitable to properly describe share price dynamics on various time scales. It is shown that while χ2-superstatistics works well on a time scale of days, on a much smaller time scale of minutes the price changes are better described by lognormal superstatistics. The system dynamics thus exhibits a transition from lognormal to χ2 superstatistics as a function of time scale. We discuss a more general model interpolating between both statistics which fits the observed data very well. We also present results on correlation functions of the extracted superstatistical volatility parameter, which exhibits exponential decay for returns on large time scales, whereas for returns on small time scales there are long-range correlations and power-law decay.
Probabilistic density function method for nonlinear dynamical systems driven by colored noise
DOE Office of Scientific and Technical Information (OSTI.GOV)
Barajas-Solano, David A.; Tartakovsky, Alexandre M.
2016-05-01
We present a probability density function (PDF) method for a system of nonlinear stochastic ordinary differential equations driven by colored noise. The method provides an integro-differential equation for the temporal evolution of the joint PDF of the system's state, which we close by means of a modified Large-Eddy-Diffusivity-type closure. Additionally, we introduce the generalized local linearization (LL) approximation for deriving a computable PDF equation in the form of the second-order partial differential equation (PDE). We demonstrate the proposed closure and localization accurately describe the dynamics of the PDF in phase space for systems driven by noise with arbitrary auto-correlation time.more » We apply the proposed PDF method to the analysis of a set of Kramers equations driven by exponentially auto-correlated Gaussian colored noise to study the dynamics and stability of a power grid.« less
Roy, S; Gruenbaum, S M; Skinner, J L
2014-12-14
The structural stability and function of biomolecules is strongly influenced by the dynamics and hydrogen bonding of interfacial water. Understanding and characterizing the dynamics of these water molecules require a surface-sensitive technique such as two-dimensional vibrational sum-frequency generation (2DSFG) spectroscopy. We have combined theoretical 2DSFG calculations with molecular dynamics simulations in order to investigate the dynamics of water near different lipid and surfactant monolayer surfaces. We show that 2DSFG can distinguish the dynamics of interfacial water as a function of the lipid charge and headgroup chemistry. The dynamics of water is slow compared to the bulk near water-zwitterionic and water-anionic interfaces due to conformational constraints on interfacial water imposed by strong phosphate-water hydrogen bonding. The dynamics of water is somewhat faster near water-cationic lipid interfaces as no such constraint is present. Using hydrogen bonding and rotational correlation functions, we characterize the dynamics of water as a function of the distance from the interface between water and zwitterionic lipids. We find that there is a transition from bulk-like to interface-like dynamics approximately 7 Å away from a zwitterionic phosphatidylcholine monolayer surface.
Stereotypical modulations in dynamic functional connectivity explained by changes in BOLD variance.
Glomb, Katharina; Ponce-Alvarez, Adrián; Gilson, Matthieu; Ritter, Petra; Deco, Gustavo
2018-05-01
Spontaneous activity measured in human subject under the absence of any task exhibits complex patterns of correlation that largely correspond to large-scale functional topographies obtained with a wide variety of cognitive and perceptual tasks. These "resting state networks" (RSNs) fluctuate over time, forming and dissolving on the scale of seconds to minutes. While these fluctuations, most prominently those of the default mode network, have been linked to cognitive function, it remains unclear whether they result from random noise or whether they index a nonstationary process which could be described as state switching. In this study, we use a sliding windows-approach to relate temporal dynamics of RSNs to global modulations in correlation and BOLD variance. We compare empirical data, phase-randomized surrogate data, and data simulated with a stationary model. We find that RSN time courses exhibit a large amount of coactivation in all three cases, and that the modulations in their activity are closely linked to global dynamics of the underlying BOLD signal. We find that many properties of the observed fluctuations in FC and BOLD, including their ranges and their correlations amongst each other, are explained by fluctuations around the average FC structure. However, we also report some interesting characteristics that clearly support nonstationary features in the data. In particular, we find that the brain spends more time in the troughs of modulations than can be expected from stationary dynamics. Copyright © 2018 Elsevier Inc. All rights reserved.
Virji-Babul, Naznin
2018-01-01
Sports-related concussion in youth is a major public health issue. Evaluating the diffuse and often subtle changes in structure and function that occur in the brain, particularly in this population, remains a significant challenge. The goal of this pilot study was to evaluate the relationship between the intrinsic dynamics of the brain using resting-state functional magnetic resonance imaging (rs-fMRI) and relate these findings to structural brain correlates from diffusion tensor imaging in a group of adolescents with sports-related concussions (n = 6) and a group of healthy adolescent athletes (n = 6). We analyzed rs-fMRI data using a sliding windows approach and related the functional findings to structural brain correlates by applying graph theory analysis to the diffusion tensor imaging data. Within the resting-state condition, we extracted three separate brain states in both groups. Our analysis revealed that the brain dynamics in healthy adolescents was characterized by a dynamic pattern, shifting equally between three brain states; however, in adolescents with concussion, the pattern was more static with a longer time spent in one brain state. Importantly, this lack of dynamic flexibility in the concussed group was associated with increased nodal strength in the left middle frontal gyrus, suggesting reorganization in a region related to attention. This preliminary report shows that both the intrinsic brain dynamics and structural organization are altered in networks related to attention in adolescents with concussion. This first report in adolescents will be used to inform future studies in a larger cohort. PMID:29357675
Muller, Angela M; Virji-Babul, Naznin
2018-01-01
Sports-related concussion in youth is a major public health issue. Evaluating the diffuse and often subtle changes in structure and function that occur in the brain, particularly in this population, remains a significant challenge. The goal of this pilot study was to evaluate the relationship between the intrinsic dynamics of the brain using resting-state functional magnetic resonance imaging (rs-fMRI) and relate these findings to structural brain correlates from diffusion tensor imaging in a group of adolescents with sports-related concussions ( n = 6) and a group of healthy adolescent athletes ( n = 6). We analyzed rs-fMRI data using a sliding windows approach and related the functional findings to structural brain correlates by applying graph theory analysis to the diffusion tensor imaging data. Within the resting-state condition, we extracted three separate brain states in both groups. Our analysis revealed that the brain dynamics in healthy adolescents was characterized by a dynamic pattern, shifting equally between three brain states; however, in adolescents with concussion, the pattern was more static with a longer time spent in one brain state. Importantly, this lack of dynamic flexibility in the concussed group was associated with increased nodal strength in the left middle frontal gyrus, suggesting reorganization in a region related to attention. This preliminary report shows that both the intrinsic brain dynamics and structural organization are altered in networks related to attention in adolescents with concussion. This first report in adolescents will be used to inform future studies in a larger cohort.
Dynamic 68Ga-DOTATOC PET/CT and static image in NET patients. Correlation of parameters during PRRT.
Van Binnebeek, Sofie; Koole, Michel; Terwinghe, Christelle; Baete, Kristof; Vanbilloen, Bert; Haustermans, Karine; Clement, Paul M; Bogaerts, Kris; Verbruggen, Alfons; Nackaerts, Kris; Van Cutsem, Eric; Verslype, Chris; Mottaghy, Felix M; Deroose, Christophe M
2016-06-28
To investigate the relationship between the dynamic parameters (Ki) and static image-derived parameters of 68Ga-DOTATOC-PET, to determine which static parameter best reflects underlying somatostatin-receptor-expression (SSR) levels on neuroendocrine tumours (NETs). 20 patients with metastasized NETs underwent a dynamic and static 68Ga-DOTATOC-PET before PRRT and at 7 and 40 weeks after the first administration of 90Y-DOTATOC (in total 4 cycles were planned); 175 lesions were defined and analyzed on the dynamic as well as static scans. Quantitative analysis was performed using the software PMOD. One to five target lesions per patient were chosen and delineated manually on the baseline dynamic scan and further, on the corresponding static 68Ga-DOTATOC-PET and the dynamic and static 68Ga-DOTATOC-PET at the other time-points; SUVmax and SUVmean of the lesions was assessed on the other six scans. The input function was retrieved from the abdominal aorta on the images. Further on, Ki was calculated using the Patlak-Plot. At last, 5 reference regions for normalization of SUVtumour were delineated on the static scans resulting in 5 ratios (SUVratio). SUVmax and SUVmean of the tumoural lesions on the dynamic 68Ga-DOTATOC-PET had a very strong correlation with the corresponding parameters in the static scan (R²: 0.94 and 0.95 respectively). SUVmax, SUVmean and Ki of the lesions showed a good linear correlation; the SUVratios correlated poorly with Ki. A significantly better correlation was noticed between Ki and SUVtumour(max and mean) (p < 0.0001). As the dynamic parameter Ki correlates best with the absolute SUVtumour, SUVtumour best reflects underlying SSR-levels in NETs.
Dynamic electronic correlation effects in NbO 2 as compared to VO 2
Brito, W. H.; Aguiar, M. C. O.; Haule, K.; ...
2017-11-01
In this study we present a comparative investigation of the electronic structures of NbO 2 and VO 2 obtained within a combination of density functional theory and cluster-dynamical mean-field theory calculations. We investigate the role of dynamic electronic correlations on the electronic structure of the metallic and insulating phases of NbO 2 and VO 2, with a focus on the mechanism responsible for the gap opening in the insulating phases. For the rutile metallic phases of both oxides, we obtain that electronic correlations lead to a strong renormalization of the t 2g subbands, as well as the emergence of incoherentmore » Hubbard subbands, signaling that electronic correlations are also important in the metallic phase of NbO 2. Interestingly, we find that nonlocal dynamic correlations do play a role in the gap formation of the [body-centered-tetragonal (bct)] insulating phase of NbO 2, by a similar physical mechanism as that recently proposed by us in the case of the monoclinic (M 1) dimerized phase of VO 2. Finally, although the effect of nonlocal dynamic correlations in the gap opening of bct phase is less important than in the (M 1 and M 2) monoclinic phases of VO 2, their presence indicates that the former is not a purely Peierls-type insulator, as it was recently proposed.« less
Hepatic function imaging using dynamic Gd-EOB-DTPA enhanced MRI and pharmacokinetic modeling.
Ning, Jia; Yang, Zhiying; Xie, Sheng; Sun, Yongliang; Yuan, Chun; Chen, Huijun
2017-10-01
To determine whether pharmacokinetic modeling parameters with different output assumptions of dynamic contrast-enhanced MRI (DCE-MRI) using Gd-EOB-DTPA correlate with serum-based liver function tests, and compare the goodness of fit of the different output assumptions. A 6-min DCE-MRI protocol was performed in 38 patients. Four dual-input two-compartment models with different output assumptions and a published one-compartment model were used to calculate hepatic function parameters. The Akaike information criterion fitting error was used to evaluate the goodness of fit. Imaging-based hepatic function parameters were compared with blood chemistry using correlation with multiple comparison correction. The dual-input two-compartment model assuming venous flow equals arterial flow plus portal venous flow and no bile duct output better described the liver tissue enhancement with low fitting error and high correlation with blood chemistry. The relative uptake rate Kir derived from this model was found to be significantly correlated with direct bilirubin (r = -0.52, P = 0.015), prealbumin concentration (r = 0.58, P = 0.015), and prothrombin time (r = -0.51, P = 0.026). It is feasible to evaluate hepatic function by proper output assumptions. The relative uptake rate has the potential to serve as a biomarker of function. Magn Reson Med 78:1488-1495, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.
Spectral mapping of brain functional connectivity from diffusion imaging.
Becker, Cassiano O; Pequito, Sérgio; Pappas, George J; Miller, Michael B; Grafton, Scott T; Bassett, Danielle S; Preciado, Victor M
2018-01-23
Understanding the relationship between the dynamics of neural processes and the anatomical substrate of the brain is a central question in neuroscience. On the one hand, modern neuroimaging technologies, such as diffusion tensor imaging, can be used to construct structural graphs representing the architecture of white matter streamlines linking cortical and subcortical structures. On the other hand, temporal patterns of neural activity can be used to construct functional graphs representing temporal correlations between brain regions. Although some studies provide evidence that whole-brain functional connectivity is shaped by the underlying anatomy, the observed relationship between function and structure is weak, and the rules by which anatomy constrains brain dynamics remain elusive. In this article, we introduce a methodology to map the functional connectivity of a subject at rest from his or her structural graph. Using our methodology, we are able to systematically account for the role of structural walks in the formation of functional correlations. Furthermore, in our empirical evaluations, we observe that the eigenmodes of the mapped functional connectivity are associated with activity patterns associated with different cognitive systems.
NASA Technical Reports Server (NTRS)
Hausdorff, J. M.; Mitchell, S. L.; Firtion, R.; Peng, C. K.; Cudkowicz, M. E.; Wei, J. Y.; Goldberger, A. L.
1997-01-01
Fluctuations in the duration of the gait cycle (the stride interval) display fractal dynamics and long-range correlations in healthy young adults. We hypothesized that these stride-interval correlations would be altered by changes in neurological function associated with aging and certain disease states. To test this hypothesis, we compared the stride-interval time series of 1) healthy elderly subjects and young controls and of 2) subjects with Huntington's disease and healthy controls. Using detrended fluctuation analysis we computed alpha, a measure of the degree to which one stride interval is correlated with previous and subsequent intervals over different time scales. The scaling exponent alpha was significantly lower in elderly subjects compared with young subjects (elderly: 0.68 +/- 0.14; young: 0.87 +/- 0.15; P < 0.003). The scaling exponent alpha was also smaller in the subjects with Huntington's disease compared with disease-free controls (Huntington's disease: 0.60 +/- 0.24; controls: 0.88 +/-0.17; P < 0.005). Moreover, alpha was linearly related to degree of functional impairment in subjects with Huntington's disease (r = 0.78, P < 0.0005). These findings demonstrate that strike-interval fluctuations are more random (i.e., less correlated) in elderly subjects and in subjects with Huntington's disease. Abnormal alterations in the fractal properties of gait dynamics are apparently associated with changes in central nervous system control.
Morphological Dynamics of Mitochondria – A Special Emphasis on Cardiac Muscle Cells
Hom, Jennifer; Sheu, Shey-Shing
2010-01-01
Mitochondria play a critical role in cellular energy metabolism, Ca2+ homeostasis, reactive oxygen species generation, apoptosis, aging, and development. Many recent publications have shown that a continuous balance of fusion and fission of these organelles is important in maintaining their proper function. Therefore, there is a steep correlation between the form and function of mitochondria. Many major proteins involved in mitochondrial fusion and fission have been identified in different cell types, including heart. However, the functional role of mitochondrial dynamics in the heart remains, for the most part, unexplored. In this review we will cover the recent field of mitochondrial dynamics and its physiological and pathological implications, with a particular emphasis on the experimental and theoretical basis of mitochondrial dynamics in the heart. PMID:19281816
Quantitative fluorescence correlation spectroscopy on DNA in living cells
NASA Astrophysics Data System (ADS)
Hodges, Cameron; Kafle, Rudra P.; Meiners, Jens-Christian
2017-02-01
FCS is a fluorescence technique conventionally used to study the kinetics of fluorescent molecules in a dilute solution. Being a non-invasive technique, it is now drawing increasing interest for the study of more complex systems like the dynamics of DNA or proteins in living cells. Unlike an ordinary dye solution, the dynamics of macromolecules like proteins or entangled DNA in crowded environments is often slow and subdiffusive in nature. This in turn leads to longer residence times of the attached fluorophores in the excitation volume of the microscope and artifacts from photobleaching abound that can easily obscure the signature of the molecular dynamics of interest and make quantitative analysis challenging.We discuss methods and procedures to make FCS applicable to quantitative studies of the dynamics of DNA in live prokaryotic and eukaryotic cells. The intensity autocorrelation is computed function from weighted arrival times of the photons on the detector that maximizes the information content while simultaneously correcting for the effect of photobleaching to yield an autocorrelation function that reflects only the underlying dynamics of the sample. This autocorrelation function in turn is used to calculate the mean square displacement of the fluorophores attached to DNA. The displacement data is more amenable to further quantitative analysis than the raw correlation functions. By using a suitable integral transform of the mean square displacement, we can then determine the viscoelastic moduli of the DNA in its cellular environment. The entire analysis procedure is extensively calibrated and validated using model systems and computational simulations.
Collaborative Signaling of Informational Structures by Dynamic Speech Rate.
ERIC Educational Resources Information Center
Koiso, Hanae; Shimojima, Atsushi; Katagiri, Yasuhiro
1998-01-01
Investigated the functions of dynamic speech rates as contextualization cues in conversational Japanese, examining five spontaneous task-oriented dialogs and analyzing the potential of speech-rate changes in signaling the structure of the information being exchanged. Results found a correlation between speech decelerations and the openings of new…
Wavepacket dynamics in one-dimensional system with long-range correlated disorder
NASA Astrophysics Data System (ADS)
Yamada, Hiroaki S.
2018-03-01
We numerically investigate dynamical property in the one-dimensional tight-binding model with long-range correlated disorder having power spectrum 1 /fα (α: spectrum exponent) generated by Fourier filtering method. For relatively small α <αc (=2) time-dependence of mean square displacement (MSD) of the initially localized wavepacket shows ballistic spread and localizes as time elapses. It is shown that α-dependence of the dynamical localization length determined by the MSD exhibits a simple scaling law in the localization regime for the relatively weak disorder strength W. Furthermore, scaled MSD by the dynamical localization length almost obeys an universal function from the ballistic to the localization regime in the various combinations of the parameters α and W.
Observations of non-linear plasmon damping in dense plasmas
NASA Astrophysics Data System (ADS)
Witte, B. B. L.; Sperling, P.; French, M.; Recoules, V.; Glenzer, S. H.; Redmer, R.
2018-05-01
We present simulations using finite-temperature density-functional-theory molecular-dynamics to calculate dynamic dielectric properties in warm dense aluminum. The comparison between exchange-correlation functionals in the Perdew, Burke, Ernzerhof approximation, Strongly Constrained and Appropriately Normed Semilocal Density Functional, and Heyd, Scuseria, Ernzerhof (HSE) approximation indicates evident differences in the electron transition energies, dc conductivity, and Lorenz number. The HSE calculations show excellent agreement with x-ray scattering data [Witte et al., Phys. Rev. Lett. 118, 225001 (2017)] as well as dc conductivity and absorption measurements. These findings demonstrate non-Drude behavior of the dynamic conductivity above the Cooper minimum that needs to be taken into account to determine optical properties in the warm dense matter regime.
Communication: Time-dependent optimized coupled-cluster method for multielectron dynamics
NASA Astrophysics Data System (ADS)
Sato, Takeshi; Pathak, Himadri; Orimo, Yuki; Ishikawa, Kenichi L.
2018-02-01
Time-dependent coupled-cluster method with time-varying orbital functions, called time-dependent optimized coupled-cluster (TD-OCC) method, is formulated for multielectron dynamics in an intense laser field. We have successfully derived the equations of motion for CC amplitudes and orthonormal orbital functions based on the real action functional, and implemented the method including double excitations (TD-OCCD) and double and triple excitations (TD-OCCDT) within the optimized active orbitals. The present method is size extensive and gauge invariant, a polynomial cost-scaling alternative to the time-dependent multiconfiguration self-consistent-field method. The first application of the TD-OCC method of intense-laser driven correlated electron dynamics in Ar atom is reported.
Communication: Time-dependent optimized coupled-cluster method for multielectron dynamics.
Sato, Takeshi; Pathak, Himadri; Orimo, Yuki; Ishikawa, Kenichi L
2018-02-07
Time-dependent coupled-cluster method with time-varying orbital functions, called time-dependent optimized coupled-cluster (TD-OCC) method, is formulated for multielectron dynamics in an intense laser field. We have successfully derived the equations of motion for CC amplitudes and orthonormal orbital functions based on the real action functional, and implemented the method including double excitations (TD-OCCD) and double and triple excitations (TD-OCCDT) within the optimized active orbitals. The present method is size extensive and gauge invariant, a polynomial cost-scaling alternative to the time-dependent multiconfiguration self-consistent-field method. The first application of the TD-OCC method of intense-laser driven correlated electron dynamics in Ar atom is reported.
Global Dynamics of Proteins: Bridging Between Structure and Function
Bahar, Ivet; Lezon, Timothy R.; Yang, Lee-Wei; Eyal, Eran
2010-01-01
Biomolecular systems possess unique, structure-encoded dynamic properties that underlie their biological functions. Recent studies indicate that these dynamic properties are determined to a large extent by the topology of native contacts. In recent years, elastic network models used in conjunction with normal mode analyses have proven to be useful for elucidating the collective dynamics intrinsically accessible under native state conditions, including in particular the global modes of motions that are robustly defined by the overall architecture. With increasing availability of structural data for well-studied proteins in different forms (liganded, complexed, or free), there is increasing evidence in support of the correspondence between functional changes in structures observed in experiments and the global motions predicted by these coarse-grained analyses. These observed correlations suggest that computational methods may be advantageously employed for assessing functional changes in structure and allosteric mechanisms intrinsically favored by the native fold. PMID:20192781
Global dynamics of proteins: bridging between structure and function.
Bahar, Ivet; Lezon, Timothy R; Yang, Lee-Wei; Eyal, Eran
2010-01-01
Biomolecular systems possess unique, structure-encoded dynamic properties that underlie their biological functions. Recent studies indicate that these dynamic properties are determined to a large extent by the topology of native contacts. In recent years, elastic network models used in conjunction with normal mode analyses have proven to be useful for elucidating the collective dynamics intrinsically accessible under native state conditions, including in particular the global modes of motions that are robustly defined by the overall architecture. With increasing availability of structural data for well-studied proteins in different forms (liganded, complexed, or free), there is increasing evidence in support of the correspondence between functional changes in structures observed in experiments and the global motions predicted by these coarse-grained analyses. These observed correlations suggest that computational methods may be advantageously employed for assessing functional changes in structure and allosteric mechanisms intrinsically favored by the native fold.
Matching-pursuit/split-operator-Fourier-transform computations of thermal correlation functions.
Chen, Xin; Wu, Yinghua; Batista, Victor S
2005-02-08
A rigorous and practical methodology for evaluating thermal-equilibrium density matrices, finite-temperature time-dependent expectation values, and time-correlation functions is described. The method involves an extension of the matching-pursuit/split-operator-Fourier-transform method to the solution of the Bloch equation via imaginary-time propagation of the density matrix and the evaluation of Heisenberg time-evolution operators through real-time propagation in dynamically adaptive coherent-state representations.
NASA Astrophysics Data System (ADS)
Cui, S. T.
The stress-stress correlation function and the viscosity of a united-atom model of liquid decane are studied by equilibrium molecular dynamics simulation using two different formalisms for the stress tensor: the atomic and the molecular formalisms. The atomic and molecular correlation functions show dramatic difference in short-time behaviour. The integrals of the two correlation functions, however, become identical after a short transient period whichis significantly shorter than the rotational relaxation time of the molecule. Both reach the same plateau value in a time period corresponding to this relaxation time. These results provide a convenient guide for the choice of the upper integral time limit in calculating the viscosity by the Green-Kubo formula.
Dynamic Structure Factor: An Introduction
NASA Astrophysics Data System (ADS)
Sturm, K.
1993-02-01
The doubly differential cross-section for weak inelastic scattering of waves or particles by manybody systems is derived in Born approximation and expressed in terms of the dynamic structure factor according to van Hove. The application of this very general scheme to scattering of neutrons, x-rays and high-energy electrons is discussed briefly. The dynamic structure factor, which is the space and time Fourier transform of the density-density correlation function, is a property of the many-body system independent of the external probe and carries information on the excitation spectrum of the system. The relation of the electronic structure factor to the density-density response function defined in linear-response theory is shown using the fluctuation-dissipation theorem. This is important for calculations, since the response function can be calculated approximately from the independent-particle response function in self-consistent field approximations, such as the random-phase approximation or the local-density approximation of the density functional theory. Since the density-density response function also determines the dielectric function, the dynamic structure can be expressed by the dielectric function.
Elastic constants and dynamics in nematic liquid crystals
NASA Astrophysics Data System (ADS)
Humpert, Anja; Allen, Michael P.
2015-09-01
In this paper, we present molecular dynamics calculations of the Frank elastic constants, and associated time correlation functions, in nematic liquid crystals. We study two variants of the Gay-Berne potential, and use system sizes of half a million molecules, significantly larger than in previous studies of elastic behaviour. Equilibrium orientational fluctuations in reciprocal (k-) space were calculated, to determine the elastic constants by fitting at low |k|; our results indicate that small system size may be a source of inaccuracy in previous work. Furthermore, the dynamics of the Gay-Berne nematic were studied by calculating time correlation functions of components of the order tensor, together with associated components of the velocity field, for a set of wave vectors k. Confirming our earlier work, we found exponential decay for splay and twist correlations, and oscillatory exponential decay for the bend correlation. In this work, we confirm similar behaviour for the corresponding velocity components. In all cases, the decay rates, and oscillation frequencies, were found to be accurately proportional to k2 for small k, as predicted by the equations of nematodynamics. However, the observation of oscillatory bend fluctuations, and corresponding oscillatory shear flow decay, is in contradiction to the usual assumptions appearing in the literature, and in standard texts. We discuss the advantages and drawbacks of using large systems in these calculations.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yu, Y.; Pang, N.; Halpin-Healy, T.
1994-12-01
The linear Langevin equation proposed by Edwards and Wilkinson [Proc. R. Soc. London A 381, 17 (1982)] is solved in closed form for noise of arbitrary space and time correlation. Furthermore, the temporal development of the full probability functional describing the height fluctuations is derived exactly, exhibiting an interesting evolution between two distinct Gaussian forms. We determine explicitly the dynamic scaling function for the interfacial width for any given initial condition, isolate the early-time behavior, and discover an invariance that was unsuspected in this problem of arbitrary spatiotemporal noise.
Palva, J. Matias; Zhigalov, Alexander; Hirvonen, Jonni; Korhonen, Onerva; Linkenkaer-Hansen, Klaus; Palva, Satu
2013-01-01
Scale-free fluctuations are ubiquitous in behavioral performance and neuronal activity. In time scales from seconds to hundreds of seconds, psychophysical dynamics and the amplitude fluctuations of neuronal oscillations are governed by power-law-form long-range temporal correlations (LRTCs). In millisecond time scales, neuronal activity comprises cascade-like neuronal avalanches that exhibit power-law size and lifetime distributions. However, it remains unknown whether these neuronal scaling laws are correlated with those characterizing behavioral performance or whether neuronal LRTCs and avalanches are related. Here, we show that the neuronal scaling laws are strongly correlated both with each other and with behavioral scaling laws. We used source reconstructed magneto- and electroencephalographic recordings to characterize the dynamics of ongoing cortical activity. We found robust power-law scaling in neuronal LRTCs and avalanches in resting-state data and during the performance of audiovisual threshold stimulus detection tasks. The LRTC scaling exponents of the behavioral performance fluctuations were correlated with those of concurrent neuronal avalanches and LRTCs in anatomically identified brain systems. The behavioral exponents also were correlated with neuronal scaling laws derived from a resting-state condition and with a similar anatomical topography. Finally, despite the difference in time scales, the scaling exponents of neuronal LRTCs and avalanches were strongly correlated during both rest and task performance. Thus, long and short time-scale neuronal dynamics are related and functionally significant at the behavioral level. These data suggest that the temporal structures of human cognitive fluctuations and behavioral variability stem from the scaling laws of individual and intrinsic brain dynamics. PMID:23401536
Solute rotational dynamics at the water liquid/vapor interface.
Benjamin, Ilan
2007-11-28
The rotational dynamics of a number of diatomic molecules adsorbed at different locations at the interface between water and its own vapors are studied using classical molecular dynamics computer simulations. Both equilibrium orientational and energy correlations and nonequilibrium orientational and energy relaxation correlations are calculated. By varying the dipole moment of the molecule and its location, and by comparing the results with those in bulk water, the effects of dielectric and mechanical frictions on reorientation dynamics and on rotational energy relaxation can be studied. It is shown that for nonpolar and weekly polar solutes, the equilibrium orientational relaxation is much slower in the bulk than at the interface. As the solute becomes more polar, the rotation slows down and the surface and bulk dynamics become similar. The energy relaxation (both equilibrium and nonequilibrium) has the opposite trend with the solute dipole (larger dipoles relax faster), but here again the bulk and surface results converge as the solute dipole is increased. It is shown that these behaviors correlate with the peak value of the solvent-solute radial distribution function, which demonstrates the importance of the first hydration shell structure in determining the rotational dynamics and dependence of these dynamics on the solute dipole and location.
WASP (Write a Scientific Paper) using Excel - 13: Correlation and Regression.
Grech, Victor
2018-07-01
Correlation and regression measure the closeness of association between two continuous variables. This paper explains how to perform these tests in Microsoft Excel and their interpretation, as well as how to apply these tests dynamically using Excel's functions. Copyright © 2018 Elsevier B.V. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lu, Fengbin, E-mail: fblu@amss.ac.cn
This paper proposes a new time-varying coefficient vector autoregressions (VAR) model, in which the coefficient is a linear function of dynamic lagged correlation. The proposed model allows for flexibility in choices of dynamic correlation models (e.g. dynamic conditional correlation generalized autoregressive conditional heteroskedasticity (GARCH) models, Markov-switching GARCH models and multivariate stochastic volatility models), which indicates that it can describe many types of time-varying causal effects. Time-varying causal relations between West Texas Intermediate (WTI) crude oil and the US Standard and Poor’s 500 (S&P 500) stock markets are examined by the proposed model. The empirical results show that their causal relationsmore » evolve with time and display complex characters. Both positive and negative causal effects of the WTI on the S&P 500 in the subperiods have been found and confirmed by the traditional VAR models. Similar results have been obtained in the causal effects of S&P 500 on WTI. In addition, the proposed model outperforms the traditional VAR model.« less
Lu, Fengbin; Qiao, Han; Wang, Shouyang; Lai, Kin Keung; Li, Yuze
2017-01-01
This paper proposes a new time-varying coefficient vector autoregressions (VAR) model, in which the coefficient is a linear function of dynamic lagged correlation. The proposed model allows for flexibility in choices of dynamic correlation models (e.g. dynamic conditional correlation generalized autoregressive conditional heteroskedasticity (GARCH) models, Markov-switching GARCH models and multivariate stochastic volatility models), which indicates that it can describe many types of time-varying causal effects. Time-varying causal relations between West Texas Intermediate (WTI) crude oil and the US Standard and Poor's 500 (S&P 500) stock markets are examined by the proposed model. The empirical results show that their causal relations evolve with time and display complex characters. Both positive and negative causal effects of the WTI on the S&P 500 in the subperiods have been found and confirmed by the traditional VAR models. Similar results have been obtained in the causal effects of S&P 500 on WTI. In addition, the proposed model outperforms the traditional VAR model. Copyright © 2016 Elsevier Ltd. All rights reserved.
Evidence of three-body correlation functions in Rb+ and Sr2+ acetonitrile solutions
NASA Astrophysics Data System (ADS)
D'Angelo, P.; Pavel, N. V.
1999-09-01
The local structure of Sr2+ and Rb+ ions in acetonitrile has been investigated by x-ray absorption spectroscopy (XAS) and molecular dynamics simulations. The extended x-ray absorption fine structure above the Sr and Rb K edges has been interpreted in the framework of multiple scattering (MS) formalism and, for the first time, clear evidence of MS contributions has been found in noncomplexing ion solutions. Molecular dynamics has been used to generate the partial pair and triangular distribution functions from which model χ(k) signals have been constructed. The Sr2+ and Rb+ acetonitrile pair distribution functions show very sharp and well-defined first peaks indicating the presence of a well organized first solvation shell. Most of the linear acetonitrile molecules have been found to be distributed like hedgehog spines around the Sr2+ and Rb+ ions. The presence of three-body correlations has been singled out by the existence of well-defined peaks in the triangular configurations. Excellent agreement has been found between the theoretical and experimental data enforcing the reliability of the interatomic potentials used in the simulations. These results demonstrate the ability of the XAS technique in probing the higher-order correlation functions in solution.
Pattern, growth, and aging in aggregation kinetics of a Vicsek-like active matter model
NASA Astrophysics Data System (ADS)
Das, Subir K.
2017-01-01
Via molecular dynamics simulations, we study kinetics in a Vicsek-like phase-separating active matter model. Quantitative results, for isotropic bicontinuous pattern, are presented on the structure, growth, and aging. These are obtained via the two-point equal-time density-density correlation function, the average domain length, and the two-time density autocorrelation function. Both the correlation functions exhibit basic scaling properties, implying self-similarity in the pattern dynamics, for which the average domain size exhibits a power-law growth in time. The equal-time correlation has a short distance behavior that provides reasonable agreement between the corresponding structure factor tail and the Porod law. The autocorrelation decay is a power-law in the average domain size. Apart from these basic similarities, the overall quantitative behavior of the above-mentioned observables is found to be vastly different from those of the corresponding passive limit of the model which also undergoes phase separation. The functional forms of these have been quantified. An exceptionally rapid growth in the active system occurs due to fast coherent motion of the particles, mean-squared-displacements of which exhibit multiple scaling regimes, including a long time ballistic one.
Gibson, William S.; Jo, Hang Joon; Testini, Paola; Cho, Shinho; Felmlee, Joel P.; Welker, Kirk M.; Klassen, Bryan T.; Min, Hoon-Ki
2016-01-01
Deep brain stimulation is an established neurosurgical therapy for movement disorders including essential tremor and Parkinson’s disease. While typically highly effective, deep brain stimulation can sometimes yield suboptimal therapeutic benefit and can cause adverse effects. In this study, we tested the hypothesis that intraoperative functional magnetic resonance imaging could be used to detect deep brain stimulation-evoked changes in functional and effective connectivity that would correlate with the therapeutic and adverse effects of stimulation. Ten patients receiving deep brain stimulation of the ventralis intermedius thalamic nucleus for essential tremor underwent functional magnetic resonance imaging during stimulation applied at a series of stimulation localizations, followed by evaluation of deep brain stimulation-evoked therapeutic and adverse effects. Correlations between the therapeutic effectiveness of deep brain stimulation (3 months postoperatively) and deep brain stimulation-evoked changes in functional and effective connectivity were assessed using region of interest-based correlation analysis and dynamic causal modelling, respectively. Further, we investigated whether brain regions might exist in which activation resulting from deep brain stimulation might correlate with the presence of paraesthesias, the most common deep brain stimulation-evoked adverse effect. Thalamic deep brain stimulation resulted in activation within established nodes of the tremor circuit: sensorimotor cortex, thalamus, contralateral cerebellar cortex and deep cerebellar nuclei (FDR q < 0.05). Stimulation-evoked activation in all these regions of interest, as well as activation within the supplementary motor area, brainstem, and inferior frontal gyrus, exhibited significant correlations with the long-term therapeutic effectiveness of deep brain stimulation (P < 0.05), with the strongest correlation (P < 0.001) observed within the contralateral cerebellum. Dynamic causal modelling revealed a correlation between therapeutic effectiveness and attenuated within-region inhibitory connectivity in cerebellum. Finally, specific subregions of sensorimotor cortex were identified in which deep brain stimulation-evoked activation correlated with the presence of unwanted paraesthesias. These results suggest that thalamic deep brain stimulation in tremor likely exerts its effects through modulation of both olivocerebellar and thalamocortical circuits. In addition, our findings indicate that deep brain stimulation-evoked functional activation maps obtained intraoperatively may contain predictive information pertaining to the therapeutic and adverse effects induced by deep brain stimulation. PMID:27329768
Hydration dynamics of a lipid membrane: Hydrogen bond networks and lipid-lipid associations
NASA Astrophysics Data System (ADS)
Srivastava, Abhinav; Debnath, Ananya
2018-03-01
Dynamics of hydration layers of a dimyristoylphosphatidylcholine (DMPC) bilayer are investigated using an all atom molecular dynamics simulation. Based upon the geometric criteria, continuously residing interface water molecules which form hydrogen bonds solely among themselves and then concertedly hydrogen bonded to carbonyl, phosphate, and glycerol head groups of DMPC are identified. The interface water hydrogen bonded to lipids shows slower relaxation rates for translational and rotational dynamics compared to that of the bulk water and is found to follow sub-diffusive and non-diffusive behaviors, respectively. The mean square displacements and the reorientational auto-correlation functions are slowest for the interfacial waters hydrogen bonded to the carbonyl oxygen since these are buried deep in the hydrophobic core among all interfacial water studied. The intermittent hydrogen bond auto-correlation functions are calculated, which allows breaking and reformations of the hydrogen bonds. The auto-correlation functions for interfacial hydrogen bonded networks develop humps during a transition from cage-like motion to eventual power law behavior of t-3/2. The asymptotic t-3/2 behavior indicates translational diffusion dictated dynamics during hydrogen bond breaking and formation irrespective of the nature of the chemical confinement. Employing reactive flux correlation analysis, the forward rate constant of hydrogen bond breaking and formation is calculated which is used to obtain Gibbs energy of activation of the hydrogen bond breaking. The relaxation rates of the networks buried in the hydrophobic core are slower than the networks near the lipid-water interface which is again slower than bulk due to the higher Gibbs energy of activation. Since hydrogen bond breakage follows a translational diffusion dictated mechanism, chemically confined hydrogen bond networks need an activation energy to diffuse through water depleted hydrophobic environments. Our calculations reveal that the slow relaxation rates of interfacial waters in the vicinity of lipids are originated from the chemical confinement of concerted hydrogen bond networks. The analysis suggests that the networks in the hydration layer of membranes dynamically facilitate the water mediated lipid-lipid associations which can provide insights on the thermodynamic stability of soft interfaces relevant to biological systems in the future.
Ohto, Tatsuhiko; Usui, Kota; Hasegawa, Taisuke; Bonn, Mischa; Nagata, Yuki
2015-09-28
Interfacial water structures have been studied intensively by probing the O-H stretch mode of water molecules using sum-frequency generation (SFG) spectroscopy. This surface-specific technique is finding increasingly widespread use, and accordingly, computational approaches to calculate SFG spectra using molecular dynamics (MD) trajectories of interfacial water molecules have been developed and employed to correlate specific spectral signatures with distinct interfacial water structures. Such simulations typically require relatively long (several nanoseconds) MD trajectories to allow reliable calculation of the SFG response functions through the dipole moment-polarizability time correlation function. These long trajectories limit the use of computationally expensive MD techniques such as ab initio MD and centroid MD simulations. Here, we present an efficient algorithm determining the SFG response from the surface-specific velocity-velocity correlation function (ssVVCF). This ssVVCF formalism allows us to calculate SFG spectra using a MD trajectory of only ∼100 ps, resulting in the substantial reduction of the computational costs, by almost an order of magnitude. We demonstrate that the O-H stretch SFG spectra at the water-air interface calculated by using the ssVVCF formalism well reproduce those calculated by using the dipole moment-polarizability time correlation function. Furthermore, we applied this ssVVCF technique for computing the SFG spectra from the ab initio MD trajectories with various density functionals. We report that the SFG responses computed from both ab initio MD simulations and MD simulations with an ab initio based force field model do not show a positive feature in its imaginary component at 3100 cm(-1).
Seeing real-space dynamics of liquid water through inelastic x-ray scattering.
Iwashita, Takuya; Wu, Bin; Chen, Wei-Ren; Tsutsui, Satoshi; Baron, Alfred Q R; Egami, Takeshi
2017-12-01
Water is ubiquitous on earth, but we know little about the real-space motion of molecules in liquid water. We demonstrate that high-resolution inelastic x-ray scattering measurement over a wide range of momentum and energy transfer makes it possible to probe real-space, real-time dynamics of water molecules through the so-called Van Hove function. Water molecules are found to be strongly correlated in space and time with coupling between the first and second nearest-neighbor molecules. The local dynamic correlation of molecules observed here is crucial to a fundamental understanding of the origin of the physical properties of water, including viscosity. The results also suggest that the quantum-mechanical nature of hydrogen bonds could influence its dynamics. The approach used here offers a powerful experimental method for investigating real-space dynamics of liquids.
Course 4: Density Functional Theory, Methods, Techniques, and Applications
NASA Astrophysics Data System (ADS)
Chrétien, S.; Salahub, D. R.
Contents 1 Introduction 2 Density functional theory 2.1 Hohenberg and Kohn theorems 2.2 Levy's constrained search 2.3 Kohn-Sham method 3 Density matrices and pair correlation functions 4 Adiabatic connection or coupling strength integration 5 Comparing and constrasting KS-DFT and HF-CI 6 Preparing new functionals 7 Approximate exchange and correlation functionals 7.1 The Local Spin Density Approximation (LSDA) 7.2 Gradient Expansion Approximation (GEA) 7.3 Generalized Gradient Approximation (GGA) 7.4 meta-Generalized Gradient Approximation (meta-GGA) 7.5 Hybrid functionals 7.6 The Optimized Effective Potential method (OEP) 7.7 Comparison between various approximate functionals 8 LAP correlation functional 9 Solving the Kohn-Sham equations 9.1 The Kohn-Sham orbitals 9.2 Coulomb potential 9.3 Exchange-correlation potential 9.4 Core potential 9.5 Other choices and sources of error 9.6 Functionality 10 Applications 10.1 Ab initio molecular dynamics for an alanine dipeptide model 10.2 Transition metal clusters: The ecstasy, and the agony... 10.3 The conversion of acetylene to benzene on Fe clusters 11 Conclusions
Fraiman, Daniel; Chialvo, Dante R.
2012-01-01
The study of spontaneous fluctuations of brain activity, often referred as brain noise, is getting increasing attention in functional magnetic resonance imaging (fMRI) studies. Despite important efforts, much of the statistical properties of such fluctuations remain largely unknown. This work scrutinizes these fluctuations looking at specific statistical properties which are relevant to clarify its dynamical origins. Here, three statistical features which clearly differentiate brain data from naive expectations for random processes are uncovered: First, the variance of the fMRI mean signal as a function of the number of averaged voxels remains constant across a wide range of observed clusters sizes. Second, the anomalous behavior of the variance is originated by bursts of synchronized activity across regions, regardless of their widely different sizes. Finally, the correlation length (i.e., the length at which the correlation strength between two regions vanishes) as well as mutual information diverges with the cluster's size considered, such that arbitrarily large clusters exhibit the same collective dynamics than smaller ones. These three properties are known to be exclusive of complex systems exhibiting critical dynamics, where the spatio-temporal dynamics show these peculiar type of fluctuations. Thus, these findings are fully consistent with previous reports of brain critical dynamics, and are relevant for the interpretation of the role of fluctuations and variability in brain function in health and disease. PMID:22934058
Vibrational Relaxation and Dynamical Transitions in Atactic Polystyrene
NASA Astrophysics Data System (ADS)
Zhao, Hanqing; Park, Yung; Painter, Paul
2009-03-01
Infrared bands and Raman lines recorded in the frequency domain have a counterpart in the time domain in the form of time-correlation functions, which are sensitive to molecular dynamics on the picosecond time scale. This is explored by calculating time correlation functions and their variation with temperature for the conformationally insensitive modes observed near 1601 cm-1 and 1583 cm-1 in the infrared spectrum of atactic polystyrene. The correlation functions were modeled by assuming that there is a fast relaxation process characterized by a single relaxation time that is inhomogeneously broadened by a slower process, also characterized by a single relaxation time. The fundamental mode, near 1583 cm-1, is inhomogeneously broadened, but the relaxation time calculated for this mode is sensitive to temperature as a result of anharmonic coupling to a combination mode. A change in the modulation of the 1583 cm-1 band becomes apparent about 10--20 degrees below the thermally measured Tg. Relaxation times at first increase then decrease and becomes negligible at temperatures near 180 degrees. These results are consistent with theories of the glass transition.
Dong, Zheng; Zhou, Hongyu; Tao, Peng
2018-02-01
PAS domains are widespread in archaea, bacteria, and eukaryota, and play important roles in various functions. In this study, we aim to explore functional evolutionary relationship among proteins in the PAS domain superfamily in view of the sequence-structure-dynamics-function relationship. We collected protein sequences and crystal structure data from RCSB Protein Data Bank of the PAS domain superfamily belonging to three biological functions (nucleotide binding, photoreceptor activity, and transferase activity). Protein sequences were aligned and then used to select sequence-conserved residues and build phylogenetic tree. Three-dimensional structure alignment was also applied to obtain structure-conserved residues. The protein dynamics were analyzed using elastic network model (ENM) and validated by molecular dynamics (MD) simulation. The result showed that the proteins with same function could be grouped by sequence similarity, and proteins in different functional groups displayed statistically significant difference in their vibrational patterns. Interestingly, in all three functional groups, conserved amino acid residues identified by sequence and structure conservation analysis generally have a lower fluctuation than other residues. In addition, the fluctuation of conserved residues in each biological function group was strongly correlated with the corresponding biological function. This research suggested a direct connection in which the protein sequences were related to various functions through structural dynamics. This is a new attempt to delineate functional evolution of proteins using the integrated information of sequence, structure, and dynamics. © 2017 The Protein Society.
Jaiswal, Abhishek; Egami, Takeshi; Zhang, Yang
2015-04-01
The phase behavior of multi-component metallic liquids is exceedingly complex because of the convoluted many-body and many-elemental interactions. Herein, we present systematic studies of the dynamic aspects of such a model ternary metallic liquid Cu 40Zr 51Al 9 using molecular dynamics simulation with embedded atom method. We observed a dynamical crossover from Arrhenius to super-Arrhenius behavior in the transport properties (diffusion coefficient, relaxation times, and shear viscosity) bordered at T x ~1300K. Unlike in many molecular and macromolecular liquids, this crossover phenomenon occurs in the equilibrium liquid state well above the melting temperature of the system (T m ~ 900K),more » and the crossover temperature is roughly twice of the glass-transition temperature (T g). Below T x, we found the elemental dynamics decoupled and the Stokes-Einstein relation broke down, indicating the onset of heterogeneous spatially correlated dynamics in the system mediated by dynamic communications among local configurational excitations. To directly characterize and visualize the correlated dynamics, we employed a non-parametric, unsupervised machine learning technique and identified dynamical clusters of atoms with similar atomic mobility. The revealed average dynamical cluster size shows an accelerated increase below T x and mimics the trend observed in other ensemble averaged quantities that are commonly used to quantify the spatially heterogeneous dynamics such as the non-Gaussian parameter and the four-point correlation function.« less
NASA Technical Reports Server (NTRS)
Waegell, Mordecai J.; Palacios, David M.
2011-01-01
Jitter_Correct.m is a MATLAB function that automatically measures and corrects inter-frame jitter in an image sequence to a user-specified precision. In addition, the algorithm dynamically adjusts the image sample size to increase the accuracy of the measurement. The Jitter_Correct.m function takes an image sequence with unknown frame-to-frame jitter and computes the translations of each frame (column and row, in pixels) relative to a chosen reference frame with sub-pixel accuracy. The translations are measured using a Cross Correlation Fourier transformation method in which the relative phase of the two transformed images is fit to a plane. The measured translations are then used to correct the inter-frame jitter of the image sequence. The function also dynamically expands the image sample size over which the cross-correlation is measured to increase the accuracy of the measurement. This increases the robustness of the measurement to variable magnitudes of inter-frame jitter
Kinetic theory molecular dynamics and hot dense matter: theoretical foundations.
Graziani, F R; Bauer, J D; Murillo, M S
2014-09-01
Electrons are weakly coupled in hot, dense matter that is created in high-energy-density experiments. They are also mildly quantum mechanical and the ions associated with them are classical and may be strongly coupled. In addition, the dynamical evolution of plasmas under these hot, dense matter conditions involve a variety of transport and energy exchange processes. Quantum kinetic theory is an ideal tool for treating the electrons but it is not adequate for treating the ions. Molecular dynamics is perfectly suited to describe the classical, strongly coupled ions but not the electrons. We develop a method that combines a Wigner kinetic treatment of the electrons with classical molecular dynamics for the ions. We refer to this hybrid method as "kinetic theory molecular dynamics," or KTMD. The purpose of this paper is to derive KTMD from first principles and place it on a firm theoretical foundation. The framework that KTMD provides for simulating plasmas in the hot, dense regime is particularly useful since current computational methods are generally limited by their inability to treat the dynamical quantum evolution of the electronic component. Using the N-body von Neumann equation for the electron-proton plasma, three variations of KTMD are obtained. Each variant is determined by the physical state of the plasma (e.g., collisional versus collisionless). The first variant of KTMD yields a closed set of equations consisting of a mean-field quantum kinetic equation for the electron one-particle distribution function coupled to a classical Liouville equation for the protons. The latter equation includes both proton-proton Coulombic interactions and an effective electron-proton interaction that involves the convolution of the electron density with the electron-proton Coulomb potential. The mean-field approach is then extended to incorporate equilibrium electron-proton correlations through the Singwi-Tosi-Land-Sjolander (STLS) ansatz. This is the second variant of KTMD. The STLS contribution produces an effective electron-proton interaction that involves the electron-proton structure factor, thereby extending the usual mean-field theory to correlated but near equilibrium systems. Finally, a third variant of KTMD is derived. It includes dynamical electrons and their correlations coupled to a MD description for the ions. A set of coupled equations for the one-particle electron Wigner function and the electron-electron and electron-proton correlation functions are coupled to a classical Liouville equation for the protons. This latter variation has both time and momentum dependent correlations.
Mathematical modelling and linear stability analysis of laser fusion cutting
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hermanns, Torsten; Schulz, Wolfgang; Vossen, Georg
A model for laser fusion cutting is presented and investigated by linear stability analysis in order to study the tendency for dynamic behavior and subsequent ripple formation. The result is a so called stability function that describes the correlation of the setting values of the process and the process’ amount of dynamic behavior.
Role of Dynamically Frustrated Bond Disorder in a Li + Superionic Solid Electrolyte
Adelstein, Nicole; Wood, Brandon C.
2016-09-16
Inorganic lithium solid electrolytes are critical components in next-generation solid-state batteries, yet the fundamental nature of the cation-anion interactions and their relevance for ionic conductivity in these materials remains enigmatic. Here, we employ first-principles molecular dynamics simulations to explore the interplay between chemistry, structure, and functionality of a highly conductive Li + solid electrolyte, Li3InBr6. Using local-orbital projections to dynamically track the evolution of the electronic charge density, the simulations reveal rapid, correlated fluctuations between cation-anion interactions with different degrees of directional covalent character. These chemical bond dynamics are shown to correlate with Li + mobility, and are enabled thermallymore » by intrinsic frustration between the preferred geometries of chemical bonding and lattice symmetry. We suggest that the fluctuating chemical environment from the polarizable anions functions similar to a solvent, contributing to the superionic behavior of Li 3InBr 6 by temporarily stabilizing configurations favorable for migrating Li +. The generality of these conclusions for understanding solid electrolytes and key factors governing the superionic phase transition is discussed.« less
NASA Astrophysics Data System (ADS)
Del Ben, Mauro; Hutter, Jürg; VandeVondele, Joost
2015-08-01
Water is a ubiquitous liquid that displays a wide range of anomalous properties and has a delicate structure that challenges experiment and simulation alike. The various intermolecular interactions that play an important role, such as repulsion, polarization, hydrogen bonding, and van der Waals interactions, are often difficult to reproduce faithfully in atomistic models. Here, electronic structure theories including all these interactions at equal footing, which requires the inclusion of non-local electron correlation, are used to describe structure and dynamics of bulk liquid water. Isobaric-isothermal (NpT) ensemble simulations based on the Random Phase Approximation (RPA) yield excellent density (0.994 g/ml) and fair radial distribution functions, while various other density functional approximations produce scattered results (0.8-1.2 g/ml). Molecular dynamics simulation in the microcanonical (NVE) ensemble based on Møller-Plesset perturbation theory (MP2) yields dynamical properties in the condensed phase, namely, the infrared spectrum and diffusion constant. At the MP2 and RPA levels of theory, ice is correctly predicted to float on water, resolving one of the anomalies as resulting from a delicate balance between van der Waals and hydrogen bonding interactions. For several properties, obtaining quantitative agreement with experiment requires correction for nuclear quantum effects (NQEs), highlighting their importance, for structure, dynamics, and electronic properties. A computed NQE shift of 0.6 eV for the band gap and absorption spectrum illustrates the latter. Giving access to both structure and dynamics of condensed phase systems, non-local electron correlation will increasingly be used to study systems where weak interactions are of paramount importance.
Giesbertz, Klaas J H; van Leeuwen, Robert
2014-05-14
Electron correlations in molecules can be divided in short range dynamical correlations, long range Van der Waals type interactions, and near degeneracy static correlations. In this work, we analyze for a one-dimensional model of a two-electron system how these three types of correlations can be incorporated in a simple wave function of restricted functional form consisting of an orbital product multiplied by a single correlation function f (r12) depending on the interelectronic distance r12. Since the three types of correlations mentioned lead to different signatures in terms of the natural orbital (NO) amplitudes in two-electron systems, we make an analysis of the wave function in terms of the NO amplitudes for a model system of a diatomic molecule. In our numerical implementation, we fully optimize the orbitals and the correlation function on a spatial grid without restrictions on their functional form. Due to this particular form of the wave function, we can prove that none of the amplitudes vanishes and moreover that it displays a distinct sign pattern and a series of avoided crossings as a function of the bond distance in agreement with the exact solution. This shows that the wave function ansatz correctly incorporates the long range Van der Waals interactions. We further show that the approximate wave function gives an excellent binding curve and is able to describe static correlations. We show that in order to do this the correlation function f (r12) needs to diverge for large r12 at large internuclear distances while for shorter bond distances it increases as a function of r12 to a maximum value after which it decays exponentially. We further give a physical interpretation of this behavior.
Dynamics of Intersubject Brain Networks during Anxious Anticipation
Najafi, Mahshid; Kinnison, Joshua; Pessoa, Luiz
2017-01-01
How do large-scale brain networks reorganize during the waxing and waning of anxious anticipation? Here, threat was dynamically modulated during human functional MRI as two circles slowly meandered on the screen; if they touched, an unpleasant shock was delivered. We employed intersubject correlation analysis, which allowed the investigation of network-level functional connectivity across brains, and sought to determine how network connectivity changed during periods of approach (circles moving closer) and periods of retreat (circles moving apart). Analysis of positive connection weights revealed that dynamic threat altered connectivity within and between the salience, executive, and task-negative networks. For example, dynamic functional connectivity increased within the salience network during approach and decreased during retreat. The opposite pattern was found for the functional connectivity between the salience and task-negative networks: decreases during approach and increases during approach. Functional connections between subcortical regions and the salience network also changed dynamically during approach and retreat periods. Subcortical regions exhibiting such changes included the putative periaqueductal gray, putative habenula, and putative bed nucleus of the stria terminalis. Additional analysis of negative functional connections revealed dynamic changes, too. For example, negative weights within the salience network decreased during approach and increased during retreat, opposite what was found for positive weights. Together, our findings unraveled dynamic features of functional connectivity of large-scale networks and subcortical regions across participants while threat levels varied continuously, and demonstrate the potential of characterizing emotional processing at the level of dynamic networks. PMID:29209184
BINARY CORRELATIONS IN IONIZED GASES
DOE Office of Scientific and Technical Information (OSTI.GOV)
Balescu, R.; Taylor, H.S.
1961-01-01
An equation of evolution for the binary distribution function in a classical homogeneous, nonequilibrium plasma was derived. It is shown that the asymptotic (long-time) solution of this equation is the Debye distribution, thus providing a rigorous dynamical derivation of the equilibrium distribution. This proof is free from the fundamental conceptual difficulties of conventional equilibrium derivations. Out of equilibrium, a closed formula was obtained for the long living correlations, in terms of the momentum distribution function. These results should form an appropriate starting point for a rigorous theory of transport phenomena in plasmas, including the effect of molecular correlations. (auth)
Fractal Dynamics of Heartbeat Interval Fluctuations in Health and Disease
NASA Astrophysics Data System (ADS)
Meyer, M.; Marconi, C.; Rahmel, A.; Grassi, B.; Ferretti, G.; Skinner, J. E.; Cerretelli, P.
The dynamics of heartbeat interval time series were studied by a modified random walk analysis recently introduced as Detrended Fluctuation Analysis. In this analysis, the intrinsic fractal long-range power-law correlation properties of beat-to-beat fluctuations generated by the dynamical system (i.e. cardiac rhythm generator), after decomposition from extrinsic uncorrelated sources, can be quantified by the scaling exponent which, in healthy subjects, is about 1.0. The finding of a scaling coefficient of 1.0, indicating scale-invariant long-range power-law correlations (1/ƒnoise) of heartbeat fluctuations, would reflect a genuinely self-similar fractal process that typically generates fluctuations on a wide range of time scales. Lack of a characteristic time scale suggests that the neuroautonomic system underlying the control of heart rate dynamics helps prevent excessive mode-locking (error tolerance) that would restrict its functional responsiveness (plasticity) to environmental stimuli. The 1/ƒ dynamics of heartbeat interval fluctuations are unaffected by exposure to chronic hypoxia suggesting that the neuroautonomic cardiac control system is preadapted to hypoxia. Functional (hypothermia, cardiac disease) and/or structural (cardiac transplantation, early cardiac development) inactivation of neuroautonomic control is associated with the breakdown or absence of fractal complexity reflected by anticorrelated random walk-like dynamics, indicating that in these conditions the heart is unadapted to its environment.
Measuring and comparing structural fluctuation patterns in large protein datasets.
Fuglebakk, Edvin; Echave, Julián; Reuter, Nathalie
2012-10-01
The function of a protein depends not only on its structure but also on its dynamics. This is at the basis of a large body of experimental and theoretical work on protein dynamics. Further insight into the dynamics-function relationship can be gained by studying the evolutionary divergence of protein motions. To investigate this, we need appropriate comparative dynamics methods. The most used dynamical similarity score is the correlation between the root mean square fluctuations (RMSF) of aligned residues. Despite its usefulness, RMSF is in general less evolutionarily conserved than the native structure. A fundamental issue is whether RMSF is not as conserved as structure because dynamics is less conserved or because RMSF is not the best property to use to study its conservation. We performed a systematic assessment of several scores that quantify the (dis)similarity between protein fluctuation patterns. We show that the best scores perform as well as or better than structural dissimilarity, as assessed by their consistency with the SCOP classification. We conclude that to uncover the full extent of the evolutionary conservation of protein fluctuation patterns, it is important to measure the directions of fluctuations and their correlations between sites. Nathalie.Reuter@mbi.uib.no Supplementary data are available at Bioinformatics Online.
Groen, Thomas A; L'Ambert, Gregory; Bellini, Romeo; Chaskopoulou, Alexandra; Petric, Dusan; Zgomba, Marija; Marrama, Laurence; Bicout, Dominique J
2017-10-26
Culex pipiens is the major vector of West Nile virus in Europe, and is causing frequent outbreaks throughout the southern part of the continent. Proper empirical modelling of the population dynamics of this species can help in understanding West Nile virus epidemiology, optimizing vector surveillance and mosquito control efforts. But modelling results may differ from place to place. In this study we look at which type of models and weather variables can be consistently used across different locations. Weekly mosquito trap collections from eight functional units located in France, Greece, Italy and Serbia for several years were combined. Additionally, rainfall, relative humidity and temperature were recorded. Correlations between lagged weather conditions and Cx. pipiens dynamics were analysed. Also seasonal autoregressive integrated moving-average (SARIMA) models were fitted to describe the temporal dynamics of Cx. pipiens and to check whether the weather variables could improve these models. Correlations were strongest between mean temperatures at short time lags, followed by relative humidity, most likely due to collinearity. Precipitation alone had weak correlations and inconsistent patterns across sites. SARIMA models could also make reasonable predictions, especially when longer time series of Cx. pipiens observations are available. Average temperature was a consistently good predictor across sites. When only short time series (~ < 4 years) of observations are available, average temperature can therefore be used to model Cx. pipiens dynamics. When longer time series (~ > 4 years) are available, SARIMAs can provide better statistical descriptions of Cx. pipiens dynamics, without the need for further weather variables. This suggests that density dependence is also an important determinant of Cx. pipiens dynamics.
NASA Astrophysics Data System (ADS)
Noah, Joyce E.
Time correlation functions of density fluctuations of liquids at equilibrium can be used to relate the microscopic dynamics of a liquid to its macroscopic transport properties. Time correlation functions are especially useful since they can be generated in a variety of ways, from scattering experiments to computer simulation to analytic theory. The kinetic theory of fluctuations in equilibrium liquids is an analytic theory for calculating correlation functions using memory functions. In this work, we use a diagrammatic formulation of the kinetic theory to develop a series of binary collision approximations for the collisional part of the memory function. We define binary collisions as collisions between two distinct density fluctuations whose identities are fixed during the duration of a collsion. R approximations are for the short time part of the memory function, and build upon the work of Ranganathan and Andersen. These approximations have purely repulsive interactions between the fluctuations. The second type of approximation, RA approximations, is for the longer time part of the memory function, where the density fluctuations now interact via repulsive and attractive forces. Although RA approximations are a natural extension of R approximations, they permit two density fluctuations to become trapped in the wells of the interaction potential, leading to long-lived oscillatory behavior, which is unphysical. Therefore we consider S approximations which describe binary particles which experience the random effect of the surroundings while interacting via repulsive or repulsive and attractive interactions. For each of these approximations for the memory function we numerically solve the kinetic equation to generate correlation functions. These results are compared to molecular dynamics results for the correlation functions. Comparing the successes and failures of the different approximations, we conclude that R approximations give more accurate intermediate and long time results while RA and S approximations do particularly well at predicting the short time behavior. Lastly, we also develop a series of non-graphically derived approximations and use an optimization procedure to determine the underlying memory function from the simulation data. These approaches provide valuable information about the memory function that will be used in the development of future kinetic theories.
Photon statistics and speckle visibility spectroscopy with partially coherent X-rays.
Li, Luxi; Kwaśniewski, Paweł; Orsi, Davide; Wiegart, Lutz; Cristofolini, Luigi; Caronna, Chiara; Fluerasu, Andrei
2014-11-01
A new approach is proposed for measuring structural dynamics in materials from multi-speckle scattering patterns obtained with partially coherent X-rays. Coherent X-ray scattering is already widely used at high-brightness synchrotron lightsources to measure dynamics using X-ray photon correlation spectroscopy, but in many situations this experimental approach based on recording long series of images (i.e. movies) is either not adequate or not practical. Following the development of visible-light speckle visibility spectroscopy, the dynamic information is obtained instead by analyzing the photon statistics and calculating the speckle contrast in single scattering patterns. This quantity, also referred to as the speckle visibility, is determined by the properties of the partially coherent beam and other experimental parameters, as well as the internal motions in the sample (dynamics). As a case study, Brownian dynamics in a low-density colloidal suspension is measured and an excellent agreement is found between correlation functions measured by X-ray photon correlation spectroscopy and the decay in speckle visibility with integration time obtained from the analysis presented here.
Group entropies, correlation laws, and zeta functions.
Tempesta, Piergiulio
2011-08-01
The notion of group entropy is proposed. It enables the unification and generaliztion of many different definitions of entropy known in the literature, such as those of Boltzmann-Gibbs, Tsallis, Abe, and Kaniadakis. Other entropic functionals are introduced, related to nontrivial correlation laws characterizing universality classes of systems out of equilibrium when the dynamics is weakly chaotic. The associated thermostatistics are discussed. The mathematical structure underlying our construction is that of formal group theory, which provides the general structure of the correlations among particles and dictates the associated entropic functionals. As an example of application, the role of group entropies in information theory is illustrated and generalizations of the Kullback-Leibler divergence are proposed. A new connection between statistical mechanics and zeta functions is established. In particular, Tsallis entropy is related to the classical Riemann zeta function.
Noise-induced polarization switching in complex networks
NASA Astrophysics Data System (ADS)
Haerter, Jan O.; Díaz-Guilera, Albert; Serrano, M. Ángeles
2017-04-01
The combination of bistability and noise is ubiquitous in complex systems, from biology to social interactions, and has important implications for their functioning and resilience. Here we use a simple three-state dynamical process, in which nodes go from one pole to another through an intermediate state, to show that noise can induce polarization switching in bistable systems if dynamical correlations are significant. In large, fully connected networks, where dynamical correlations can be neglected, increasing noise yields a collapse of bistability to an unpolarized configuration where the three possible states of the nodes are equally likely. In contrast, increased noise induces abrupt and irreversible polarization switching in sparsely connected networks. In multiplexes, where each layer can have a different polarization tendency, one layer is dominant and progressively imposes its polarization state on the other, offsetting or promoting the ability of noise to switch its polarization. Overall, we show that the interplay of noise and dynamical correlations can yield discontinuous transitions between extremes, which cannot be explained by a simple mean-field description.
Functional Connectivity in Islets of Langerhans from Mouse Pancreas Tissue Slices
Stožer, Andraž; Gosak, Marko; Dolenšek, Jurij; Perc, Matjaž; Marhl, Marko; Rupnik, Marjan Slak; Korošak, Dean
2013-01-01
We propose a network representation of electrically coupled beta cells in islets of Langerhans. Beta cells are functionally connected on the basis of correlations between calcium dynamics of individual cells, obtained by means of confocal laser-scanning calcium imaging in islets from acute mouse pancreas tissue slices. Obtained functional networks are analyzed in the light of known structural and physiological properties of islets. Focusing on the temporal evolution of the network under stimulation with glucose, we show that the dynamics are more correlated under stimulation than under non-stimulated conditions and that the highest overall correlation, largely independent of Euclidean distances between cells, is observed in the activation and deactivation phases when cells are driven by the external stimulus. Moreover, we find that the range of interactions in networks during activity shows a clear dependence on the Euclidean distance, lending support to previous observations that beta cells are synchronized via calcium waves spreading throughout islets. Most interestingly, the functional connectivity patterns between beta cells exhibit small-world properties, suggesting that beta cells do not form a homogeneous geometric network but are connected in a functionally more efficient way. Presented results provide support for the existing knowledge of beta cell physiology from a network perspective and shed important new light on the functional organization of beta cell syncitia whose structural topology is probably not as trivial as believed so far. PMID:23468610
Short-time microscopic dynamics of aqueous methanol solutions
NASA Astrophysics Data System (ADS)
Kalampounias, A. G.; Tsilomelekis, G.; Boghosian, S.
2012-12-01
In this paper we present the picosecond vibrational dynamics of a series of methanol aqueous solutions over a wide concentration range from dense to dilute solutions. We studied the vibrational dephasing and vibrational frequency modulation by calculating the time correlation functions of vibrational relaxation by fits in the frequency domain. This method is applied to aqueous methanol solutions xMeOH-(1 - x)H2O, where x = 0, 0.2, 0.4, 0.6, 0.8 and 1. The important finding is that the vibrational dynamics of the system become slower with increasing methanol concentration. The removal of many-body effects by having the molecules in less-crowded environments seems to be the key factor. The interpretation of the vibrational correlation function in the context of Kubo theory, which is based on the assumption that the environmental modulation arises from a single relaxation process and applied to simple liquids, is inadequate for all solutions studied. We found that the vibrational correlation functions of the solutions over the whole concentration range comply with the Rothschild approach, assuming that the environmental modulation is described by a stretched exponential decay. The evolution of the dispersion parameter α with dilution indicates the deviation of the solutions from the model simple liquid and the results are discussed in the framework of the current phenomenological status of the field.
Abdelnour, Farras; Voss, Henning U.; Raj, Ashish
2014-01-01
The relationship between anatomic connectivity of large-scale brain networks and their functional connectivity is of immense importance and an area of active research. Previous attempts have required complex simulations which model the dynamics of each cortical region, and explore the coupling between regions as derived by anatomic connections. While much insight is gained from these non-linear simulations, they can be computationally taxing tools for predicting functional from anatomic connectivities. Little attention has been paid to linear models. Here we show that a properly designed linear model appears to be superior to previous non-linear approaches in capturing the brain’s long-range second order correlation structure that governs the relationship between anatomic and functional connectivities. We derive a linear network of brain dynamics based on graph diffusion, whereby the diffusing quantity undergoes a random walk on a graph. We test our model using subjects who underwent diffusion MRI and resting state fMRI. The network diffusion model applied to the structural networks largely predicts the correlation structures derived from their fMRI data, to a greater extent than other approaches. The utility of the proposed approach is that it can routinely be used to infer functional correlation from anatomic connectivity. And since it is linear, anatomic connectivity can also be inferred from functional data. The success of our model confirms the linearity of ensemble average signals in the brain, and implies that their long-range correlation structure may percolate within the brain via purely mechanistic processes enacted on its structural connectivity pathways. PMID:24384152
Tree-level correlations in the strong field regime
NASA Astrophysics Data System (ADS)
Gelis, François
2017-09-01
We consider the correlation function of an arbitrary number of local observables in quantum field theory, in situations where the field amplitude is large. Using a quasi-classical approximation (valid for a highly occupied initial mixed state, or for a coherent initial state if the classical dynamics has instabilities), we show that at tree level these correlations are dominated by fluctuations at the initial time. We obtain a general expression of the correlation functions in terms of the classical solution of the field equation of motion and its derivatives with respect to its initial conditions, that can be arranged graphically as the sum of labeled trees where the nodes are the individual observables, and the links are pairs of derivatives acting on them. For 3-point (and higher) correlation functions, there are additional tree-level terms beyond the quasi-classical approximation, generated by fluctuations in the bulk.
Fu, Zening; Tu, Yiheng; Di, Xin; Du, Yuhui; Pearlson, G D; Turner, J A; Biswal, Bharat B; Zhang, Zhiguo; Calhoun, V D
2017-09-20
The human brain is a highly dynamic system with non-stationary neural activity and rapidly-changing neural interaction. Resting-state dynamic functional connectivity (dFC) has been widely studied during recent years, and the emerging aberrant dFC patterns have been identified as important features of many mental disorders such as schizophrenia (SZ). However, only focusing on the time-varying patterns in FC is not enough, since the local neural activity itself (in contrast to the inter-connectivity) is also found to be highly fluctuating from research using high-temporal-resolution imaging techniques. Exploring the time-varying patterns in brain activity and their relationships with time-varying brain connectivity is important for advancing our understanding of the co-evolutionary property of brain network and the underlying mechanism of brain dynamics. In this study, we introduced a framework for characterizing time-varying brain activity and exploring its associations with time-varying brain connectivity, and applied this framework to a resting-state fMRI dataset including 151 SZ patients and 163 age- and gender matched healthy controls (HCs). In this framework, 48 brain regions were first identified as intrinsic connectivity networks (ICNs) using group independent component analysis (GICA). A sliding window approach was then adopted for the estimation of dynamic amplitude of low-frequency fluctuation (dALFF) and dFC, which were used to measure time-varying brain activity and time-varying brain connectivity respectively. The dALFF was further clustered into six reoccurring states by the k-means clustering method and the group difference in occurrences of dALFF states was explored. Lastly, correlation coefficients between dALFF and dFC were calculated and the group difference in these dALFF-dFC correlations was explored. Our results suggested that 1) ALFF of brain regions was highly fluctuating during the resting-state and such dynamic patterns are altered in SZ, 2) dALFF and dFC were correlated in time and their correlations are altered in SZ. The overall results support and expand prior work on abnormalities of brain activity, static FC (sFC) and dFC in SZ, and provide new evidence on aberrant time-varying brain activity and its associations with brain connectivity in SZ, which might underscore the disrupted brain cognitive functions in this mental disorder. Copyright © 2017 Elsevier Inc. All rights reserved.
Nematode grazing promotes bacterial community dynamics in soil at the aggregate level
Jiang, Yuji; Liu, Manqiang; Zhang, Jiabao; Chen, Yan; Chen, Xiaoyun; Chen, Lijun; Li, Huixin; Zhang, Xue-Xian; Sun, Bo
2017-01-01
Nematode predation has important roles in determining bacterial community composition and dynamics, but the extent of the effects remains largely rudimentary, particularly in natural environment settings. Here, we investigated the complex microbial–microfaunal interactions in the rhizosphere of maize grown in red soils, which were derived from four long-term fertilization regimes. Root-free rhizosphere soil samples were separated into three aggregate fractions whereby the abundance and community composition were examined for nematode and total bacterial communities. A functional group of alkaline phosphomonoesterase (ALP) producing bacteria was included to test the hypothesis that nematode grazing may significantly affect specific bacteria-mediated ecological functions, that is, organic phosphate cycling in soil. Results of correlation analysis, structural equation modeling and interaction networks combined with laboratory microcosm experiments consistently indicated that bacterivorous nematodes enhanced bacterial diversity, and the abundance of bacterivores was positively correlated with bacterial biomass, including ALP-producing bacterial abundance. Significantly, such effects were more pronounced in large macroaggregates than in microaggregates. There was a positive correlation between the most dominant bacterivores Protorhabditis and the ALP-producing keystone 'species' Mesorhizobium. Taken together, these findings implicate important roles of nematodes in stimulating bacterial dynamics in a spatially dependent manner. PMID:28742069
Nematode grazing promotes bacterial community dynamics in soil at the aggregate level.
Jiang, Yuji; Liu, Manqiang; Zhang, Jiabao; Chen, Yan; Chen, Xiaoyun; Chen, Lijun; Li, Huixin; Zhang, Xue-Xian; Sun, Bo
2017-12-01
Nematode predation has important roles in determining bacterial community composition and dynamics, but the extent of the effects remains largely rudimentary, particularly in natural environment settings. Here, we investigated the complex microbial-microfaunal interactions in the rhizosphere of maize grown in red soils, which were derived from four long-term fertilization regimes. Root-free rhizosphere soil samples were separated into three aggregate fractions whereby the abundance and community composition were examined for nematode and total bacterial communities. A functional group of alkaline phosphomonoesterase (ALP) producing bacteria was included to test the hypothesis that nematode grazing may significantly affect specific bacteria-mediated ecological functions, that is, organic phosphate cycling in soil. Results of correlation analysis, structural equation modeling and interaction networks combined with laboratory microcosm experiments consistently indicated that bacterivorous nematodes enhanced bacterial diversity, and the abundance of bacterivores was positively correlated with bacterial biomass, including ALP-producing bacterial abundance. Significantly, such effects were more pronounced in large macroaggregates than in microaggregates. There was a positive correlation between the most dominant bacterivores Protorhabditis and the ALP-producing keystone 'species' Mesorhizobium. Taken together, these findings implicate important roles of nematodes in stimulating bacterial dynamics in a spatially dependent manner.
Space-time modeling of soil moisture
NASA Astrophysics Data System (ADS)
Chen, Zijuan; Mohanty, Binayak P.; Rodriguez-Iturbe, Ignacio
2017-11-01
A physically derived space-time mathematical representation of the soil moisture field is carried out via the soil moisture balance equation driven by stochastic rainfall forcing. The model incorporates spatial diffusion and in its original version, it is shown to be unable to reproduce the relative fast decay in the spatial correlation functions observed in empirical data. This decay resulting from variations in local topography as well as in local soil and vegetation conditions is well reproduced via a jitter process acting multiplicatively over the space-time soil moisture field. The jitter is a multiplicative noise acting on the soil moisture dynamics with the objective to deflate its correlation structure at small spatial scales which are not embedded in the probabilistic structure of the rainfall process that drives the dynamics. These scales of order of several meters to several hundred meters are of great importance in ecohydrologic dynamics. Properties of space-time correlation functions and spectral densities of the model with jitter are explored analytically, and the influence of the jitter parameters, reflecting variabilities of soil moisture at different spatial and temporal scales, is investigated. A case study fitting the derived model to a soil moisture dataset is presented in detail.
Anero, Jesús G; Español, Pep; Tarazona, Pedro
2013-07-21
We present a generalization of Density Functional Theory (DFT) to non-equilibrium non-isothermal situations. By using the original approach set forth by Gibbs in his consideration of Macroscopic Thermodynamics (MT), we consider a Functional Thermo-Dynamics (FTD) description based on the density field and the energy density field. A crucial ingredient of the theory is an entropy functional, which is a concave functional. Therefore, there is a one to one connection between the density and energy fields with the conjugate thermodynamic fields. The connection between the three levels of description (MT, DFT, FTD) is clarified through a bridge theorem that relates the entropy of different levels of description and that constitutes a generalization of Mermin's theorem to arbitrary levels of description whose relevant variables are connected linearly. Although the FTD level of description does not provide any new information about averages and correlations at equilibrium, it is a crucial ingredient for the dynamics in non-equilibrium states. We obtain with the technique of projection operators the set of dynamic equations that describe the evolution of the density and energy density fields from an initial non-equilibrium state towards equilibrium. These equations generalize time dependent density functional theory to non-isothermal situations. We also present an explicit model for the entropy functional for hard spheres.
Exact solution for a non-Markovian dissipative quantum dynamics.
Ferialdi, Luca; Bassi, Angelo
2012-04-27
We provide the exact analytic solution of the stochastic Schrödinger equation describing a harmonic oscillator interacting with a non-Markovian and dissipative environment. This result represents an arrival point in the study of non-Markovian dynamics via stochastic differential equations. It is also one of the few exactly solvable models for infinite-dimensional systems. We compute the Green's function; in the case of a free particle and with an exponentially correlated noise, we discuss the evolution of Gaussian wave functions.
Diffusion in Colocation Contact Networks: The Impact of Nodal Spatiotemporal Dynamics.
Thomas, Bryce; Jurdak, Raja; Zhao, Kun; Atkinson, Ian
2016-01-01
Temporal contact networks are studied to understand dynamic spreading phenomena such as communicable diseases or information dissemination. To establish how spatiotemporal dynamics of nodes impact spreading potential in colocation contact networks, we propose "inducement-shuffling" null models which break one or more correlations between times, locations and nodes. By reconfiguring the time and/or location of each node's presence in the network, these models induce alternative sets of colocation events giving rise to contact networks with varying spreading potential. This enables second-order causal reasoning about how correlations in nodes' spatiotemporal preferences not only lead to a given contact network but ultimately influence the network's spreading potential. We find the correlation between nodes and times to be the greatest impediment to spreading, while the correlation between times and locations slightly catalyzes spreading. Under each of the presented null models we measure both the number of contacts and infection prevalence as a function of time, with the surprising finding that the two have no direct causality.
NASA Astrophysics Data System (ADS)
Galler, Anna; Gunacker, Patrik; Tomczak, Jan; Thunström, Patrik; Held, Karsten
Recently, approaches such as the dynamical vertex approximation (D ΓA) or the dual-fermion method have been developed. These diagrammatic approaches are going beyond dynamical mean field theory (DMFT) by including nonlocal electronic correlations on all length scales as well as the local DMFT correlations. Here we present our efforts to extend the D ΓA methodology to ab-initio materials calculations (ab-initio D ΓA). Our approach is a unifying framework which includes both GW and DMFT-type of diagrams, but also important nonlocal correlations beyond, e.g. nonlocal spin fluctuations. In our multi-band implementation we are using a worm sampling technique within continuous-time quantum Monte Carlo in the hybridization expansion to obtain the DMFT vertex, from which we construct the reducible vertex function using the two particle-hole ladders. As a first application we show results for transition metal oxides. Support by the ERC project AbinitioDGA (306447) is acknowledged.
Fankhauser, Franz Ii; Ott, Maria; Munteanu, Mihnea
2016-01-01
Photon-correlation spectroscopy (PCS) (quasi-elastic light scattering spectroscopy, dynamic light scattering spectroscopy) allows the non-invasively reveal of local dynamics and local heterogeneities of macromolecular systems. The capability of this technique to diagnose the retinal pathologies by in-vivo investigations of spatial anomalies of retinas displaying non-exudative senile macular degeneration was evaluated. Further, the potential use of the technique for the diagnosis of the macular degeneration was analyzed and displayed by the Receiver Operating Curve (ROC). The maculae and the peripheral retina of 73 normal eyes and of 26 eyes afflicted by an early stage of non-exudative senile macular degeneration were characterized by time-correlation functions and analyzed in terms of characteristic decay times and apparent size distributions. The characteristics of the obtained time-correlation functions of the eyes afflicted with nonexudative macular degeneration and of normal eyes differed significantly, which could be referred to a significant change of the nano- and microstructure of the investigated pathologic maculas. Photon-correlation spectroscopy is able to assess the macromolecular and microstructural aberrations in the macula afflicted by non-exudative, senile macular degeneration. It has been demonstrated that macromolecules of this disease show a characteristic abnormal behavior in the macula.
Universality of long-range correlations in expansion randomization systems
NASA Astrophysics Data System (ADS)
Messer, P. W.; Lässig, M.; Arndt, P. F.
2005-10-01
We study the stochastic dynamics of sequences evolving by single-site mutations, segmental duplications, deletions, and random insertions. These processes are relevant for the evolution of genomic DNA. They define a universality class of non-equilibrium 1D expansion-randomization systems with generic stationary long-range correlations in a regime of growing sequence length. We obtain explicitly the two-point correlation function of the sequence composition and the distribution function of the composition bias in sequences of finite length. The characteristic exponent χ of these quantities is determined by the ratio of two effective rates, which are explicitly calculated for several specific sequence evolution dynamics of the universality class. Depending on the value of χ, we find two different scaling regimes, which are distinguished by the detectability of the initial composition bias. All analytic results are accurately verified by numerical simulations. We also discuss the non-stationary build-up and decay of correlations, as well as more complex evolutionary scenarios, where the rates of the processes vary in time. Our findings provide a possible example for the emergence of universality in molecular biology.
The effects of resonances on time delay estimation for water leak detection in plastic pipes
NASA Astrophysics Data System (ADS)
Almeida, Fabrício C. L.; Brennan, Michael J.; Joseph, Phillip F.; Gao, Yan; Paschoalini, Amarildo T.
2018-04-01
In the use of acoustic correlation methods for water leak detection, sensors are placed at pipe access points either side of a suspected leak, and the peak in the cross-correlation function of the measured signals gives the time difference (delay) between the arrival times of the leak noise at the sensors. Combining this information with the speed at which the leak noise propagates along the pipe, gives an estimate for the location of the leak with respect to one of the measurement positions. It is possible for the structural dynamics of the pipe system to corrupt the time delay estimate, which results in the leak being incorrectly located. In this paper, data from test-rigs in the United Kingdom and Canada are used to demonstrate this phenomenon, and analytical models of resonators are coupled with a pipe model to replicate the experimental results. The model is then used to investigate which of the two commonly used correlation algorithms, the Basic Cross-Correlation (BCC) function or the Phase Transform (PHAT), is more robust to the undesirable structural dynamics of the pipe system. It is found that time delay estimation is highly sensitive to the frequency bandwidth over which the analysis is conducted. Moreover, it is found that the PHAT is particularly sensitive to the presence of resonances and can give an incorrect time delay estimate, whereas the BCC function is found to be much more robust, giving a consistently accurate time delay estimate for a range of dynamic conditions.
Magnetic properties and core electron binding energies of liquid water
NASA Astrophysics Data System (ADS)
Galamba, N.; Cabral, Benedito J. C.
2018-01-01
The magnetic properties and the core and inner valence electron binding energies of liquid water are investigated. The adopted methodology relies on the combination of molecular dynamics and electronic structure calculations. Born-Oppenheimer molecular dynamics with the Becke and Lee-Yang-Parr functionals for exchange and correlation, respectively, and includes an empirical correction (BLYP-D3) functional and classical molecular dynamics with the TIP4P/2005-F model were carried out. The Keal-Tozer functional was applied for predicting magnetic shielding and spin-spin coupling constants. Core and inner valence electron binding energies in liquid water were calculated with symmetry adapted cluster-configuration interaction. The relationship between the magnetic shielding constant σ(17O), the role played by the oxygen atom as a proton acceptor and donor, and the tetrahedral organisation of liquid water are investigated. The results indicate that the deshielding of the oxygen atom in water is very dependent on the order parameter (q) describing the tetrahedral organisation of the hydrogen bond network. The strong sensitivity of magnetic properties on changes of the electronic density in the nuclei environment is illustrated by a correlation between σ(17O) and the energy gap between the 1a1[O1s] (core) and the 2a1 (inner valence) orbitals of water. Although several studies discussed the eventual connection between magnetic properties and core electron binding energies, such a correlation could not be clearly established. Here, we demonstrate that for liquid water this correlation exists although involving the gap between electron binding energies of core and inner valence orbitals.
Fetterhoff, Dustin; Opris, Ioan; Simpson, Sean L.; Deadwyler, Sam A.; Hampson, Robert E.; Kraft, Robert A.
2014-01-01
Background Multifractal analysis quantifies the time-scale-invariant properties in data by describing the structure of variability over time. By applying this analysis to hippocampal interspike interval sequences recorded during performance of a working memory task, a measure of long-range temporal correlations and multifractal dynamics can reveal single neuron correlates of information processing. New method Wavelet leaders-based multifractal analysis (WLMA) was applied to hippocampal interspike intervals recorded during a working memory task. WLMA can be used to identify neurons likely to exhibit information processing relevant to operation of brain–computer interfaces and nonlinear neuronal models. Results Neurons involved in memory processing (“Functional Cell Types” or FCTs) showed a greater degree of multifractal firing properties than neurons without task-relevant firing characteristics. In addition, previously unidentified FCTs were revealed because multifractal analysis suggested further functional classification. The cannabinoid-type 1 receptor partial agonist, tetrahydrocannabinol (THC), selectively reduced multifractal dynamics in FCT neurons compared to non-FCT neurons. Comparison with existing methods WLMA is an objective tool for quantifying the memory-correlated complexity represented by FCTs that reveals additional information compared to classification of FCTs using traditional z-scores to identify neuronal correlates of behavioral events. Conclusion z-Score-based FCT classification provides limited information about the dynamical range of neuronal activity characterized by WLMA. Increased complexity, as measured with multifractal analysis, may be a marker of functional involvement in memory processing. The level of multifractal attributes can be used to differentially emphasize neural signals to improve computational models and algorithms underlying brain–computer interfaces. PMID:25086297
NASA Astrophysics Data System (ADS)
Strate, Anne; Neumann, Jan; Overbeck, Viviane; Bonsa, Anne-Marie; Michalik, Dirk; Paschek, Dietmar; Ludwig, Ralf
2018-05-01
We report a concerted theoretical and experimental effort to determine the reorientational dynamics as well as hydrogen bond lifetimes for the doubly ionic hydrogen bond +OH⋯O- in the ionic liquid (2-hydroxyethyl)trimethylammonium bis(trifluoromethylsulfonyl)imide [Ch][NTf2] by using a combination of NMR relaxation time experiments, density functional theory (DFT) calculations, and molecular dynamics (MD) simulations. Due to fast proton exchange, the determination of rotational correlation times is challenging. For molecular liquids, 17O-enhanced proton relaxation time experiments have been used to determine the rotational correlation times for the OH vectors in water or alcohols. As an alternative to those expensive isotopic substitution experiments, we employed a recently introduced approach which is providing access to the rotational dynamics from a single NMR deuteron quadrupolar relaxation time experiment. Here, the deuteron quadrupole coupling constants (DQCCs) are obtained from a relation between the DQCC and the δ1H proton chemical shifts determined from a set of DFT calculated clusters in combination with experimentally determined proton chemical shifts. The NMR-obtained rotational correlation times were compared to those obtained from MD simulations and then related to viscosities for testing the applicability of popular hydrodynamic models. In addition, hydrogen bond lifetimes were derived, using hydrogen bond population correlation functions computed from MD simulations. Here, two different time domains were observed: The short-time contributions to the hydrogen lifetimes and the reorientational correlation times have roughly the same size and are located in the picosecond range, whereas the long-time contributions decay with relaxation times in the nanosecond regime and are related to rather slow diffusion processes. The computed average hydrogen bond lifetime is dominated by the long-time process, highlighting the importance and longevity of hydrogen-bonded ion pairs in these ionic liquids.
Correlation functions from a unified variational principle: Trial Lie groups
NASA Astrophysics Data System (ADS)
Balian, R.; Vénéroni, M.
2015-11-01
Time-dependent expectation values and correlation functions for many-body quantum systems are evaluated by means of a unified variational principle. It optimizes a generating functional depending on sources associated with the observables of interest. It is built by imposing through Lagrange multipliers constraints that account for the initial state (at equilibrium or off equilibrium) and for the backward Heisenberg evolution of the observables. The trial objects are respectively akin to a density operator and to an operator involving the observables of interest and the sources. We work out here the case where trial spaces constitute Lie groups. This choice reduces the original degrees of freedom to those of the underlying Lie algebra, consisting of simple observables; the resulting objects are labeled by the indices of a basis of this algebra. Explicit results are obtained by expanding in powers of the sources. Zeroth and first orders provide thermodynamic quantities and expectation values in the form of mean-field approximations, with dynamical equations having a classical Lie-Poisson structure. At second order, the variational expression for two-time correlation functions separates-as does its exact counterpart-the approximate dynamics of the observables from the approximate correlations in the initial state. Two building blocks are involved: (i) a commutation matrix which stems from the structure constants of the Lie algebra; and (ii) the second-derivative matrix of a free-energy function. The diagonalization of both matrices, required for practical calculations, is worked out, in a way analogous to the standard RPA. The ensuing structure of the variational formulae is the same as for a system of non-interacting bosons (or of harmonic oscillators) plus, at non-zero temperature, classical Gaussian variables. This property is explained by mapping the original Lie algebra onto a simpler Lie algebra. The results, valid for any trial Lie group, fulfill consistency properties and encompass several special cases: linear responses, static and time-dependent fluctuations, zero- and high-temperature limits, static and dynamic stability of small deviations.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Galan, Roberto F.; Urban, Nathaniel N.; Center for the Neural Basis of Cognition, Mellon Institute, Pittsburgh, Pennsylvania 15213
We have investigated the effect of the phase response curve on the dynamics of oscillators driven by noise in two limit cases that are especially relevant for neuroscience. Using the finite element method to solve the Fokker-Planck equation we have studied (i) the impact of noise on the regularity of the oscillations quantified as the coefficient of variation, (ii) stochastic synchronization of two uncoupled phase oscillators driven by correlated noise, and (iii) their cross-correlation function. We show that, in general, the limit of type II oscillators is more robust to noise and more efficient at synchronizing by correlated noise thanmore » type I.« less
Age-related changes in the ease of dynamical transitions in human brain activity.
Ezaki, Takahiro; Sakaki, Michiko; Watanabe, Takamitsu; Masuda, Naoki
2018-06-01
Executive functions, a set of cognitive processes that enable flexible behavioral control, are known to decay with aging. Because such complex mental functions are considered to rely on the dynamic coordination of functionally different neural systems, the age-related decline in executive functions should be underpinned by alteration of large-scale neural dynamics. However, the effects of age on brain dynamics have not been firmly formulated. Here, we investigate such age-related changes in brain dynamics by applying "energy landscape analysis" to publicly available functional magnetic resonance imaging data from healthy younger and older human adults. We quantified the ease of dynamical transitions between different major patterns of brain activity, and estimated it for the default mode network (DMN) and the cingulo-opercular network (CON) separately. We found that the two age groups shared qualitatively the same trajectories of brain dynamics in both the DMN and CON. However, in both of networks, the ease of transitions was significantly smaller in the older than the younger group. Moreover, the ease of transitions was associated with the performance in executive function tasks in a doubly dissociated manner: for the younger adults, the ability of executive functions was mainly correlated with the ease of transitions in the CON, whereas that for the older adults was specifically associated with the ease of transitions in the DMN. These results provide direct biological evidence for age-related changes in macroscopic brain dynamics and suggest that such neural dynamics play key roles when individuals carry out cognitively demanding tasks. © 2018 Wiley Periodicals, Inc.
Theory of nonstationary Hawkes processes
NASA Astrophysics Data System (ADS)
Tannenbaum, Neta Ravid; Burak, Yoram
2017-12-01
We expand the theory of Hawkes processes to the nonstationary case, in which the mutually exciting point processes receive time-dependent inputs. We derive an analytical expression for the time-dependent correlations, which can be applied to networks with arbitrary connectivity, and inputs with arbitrary statistics. The expression shows how the network correlations are determined by the interplay between the network topology, the transfer functions relating units within the network, and the pattern and statistics of the external inputs. We illustrate the correlation structure using several examples in which neural network dynamics are modeled as a Hawkes process. In particular, we focus on the interplay between internally and externally generated oscillations and their signatures in the spike and rate correlation functions.
NASA Astrophysics Data System (ADS)
Bogolubov, Nikolai N.; Soldatov, Andrey V.
2017-12-01
Exact and approximate master equations were derived by the projection operator method for the reduced statistical operator of a multi-level quantum system with finite number N of quantum eigenstates interacting with arbitrary external classical fields and dissipative environment simultaneously. It was shown that the structure of these equations can be simplified significantly if the free Hamiltonian driven dynamics of an arbitrary quantum multi-level system under the influence of the external driving fields as well as its Markovian and non-Markovian evolution, stipulated by the interaction with the environment, are described in terms of the SU(N) algebra representation. As a consequence, efficient numerical methods can be developed and employed to analyze these master equations for real problems in various fields of theoretical and applied physics. It was also shown that literally the same master equations hold not only for the reduced density operator but also for arbitrary nonequilibrium multi-time correlation functions as well under the only assumption that the system and the environment are uncorrelated at some initial moment of time. A calculational scheme was proposed to account for these lost correlations in a regular perturbative way, thus providing additional computable terms to the correspondent master equations for the correlation functions.
Xu, Enhua; Zhao, Dongbo; Li, Shuhua
2015-10-13
A multireference second order perturbation theory based on a complete active space configuration interaction (CASCI) function or density matrix renormalized group (DMRG) function has been proposed. This method may be considered as an approximation to the CAS/A approach with the same reference, in which the dynamical correlation is simplified with blocked correlated second order perturbation theory based on the generalized valence bond (GVB) reference (GVB-BCPT2). This method, denoted as CASCI-BCPT2/GVB or DMRG-BCPT2/GVB, is size consistent and has a similar computational cost as the conventional second order perturbation theory (MP2). We have applied it to investigate a number of problems of chemical interest. These problems include bond-breaking potential energy surfaces in four molecules, the spectroscopic constants of six diatomic molecules, the reaction barrier for the automerization of cyclobutadiene, and the energy difference between the monocyclic and bicyclic forms of 2,6-pyridyne. Our test applications demonstrate that CASCI-BCPT2/GVB can provide comparable results with CASPT2 (second order perturbation theory based on the complete active space self-consistent-field wave function) for systems under study. Furthermore, the DMRG-BCPT2/GVB method is applicable to treat strongly correlated systems with large active spaces, which are beyond the capability of CASPT2.
Seeing real-space dynamics of liquid water through inelastic x-ray scattering
DOE Office of Scientific and Technical Information (OSTI.GOV)
Iwashita, Takuya; Wu, Bin; Chen, Wei-Ren
Water is ubiquitous on earth, but we know little about the real-space motion of molecules in liquid water. We demonstrate that high-resolution inelastic x-ray scattering measurement over a wide range of momentum and energy transfer makes it possible to probe real-space, real-time dynamics of water molecules through the so-called Van Hove function. Water molecules are found to be strongly correlated in space and time with coupling between the first and second nearest-neighbor molecules. The local dynamic correlation of molecules observed here is crucial to a fundamental understanding of the origin of the physical properties of water, including viscosity. The resultsmore » also suggest that the quantum-mechanical nature of hydrogen bonds could influence its dynamics. Finally, the approach used here offers a powerful experimental method for investigating real-space dynamics of liquids.« less
Seeing real-space dynamics of liquid water through inelastic x-ray scattering
Iwashita, Takuya; Wu, Bin; Chen, Wei-Ren; ...
2017-12-22
Water is ubiquitous on earth, but we know little about the real-space motion of molecules in liquid water. We demonstrate that high-resolution inelastic x-ray scattering measurement over a wide range of momentum and energy transfer makes it possible to probe real-space, real-time dynamics of water molecules through the so-called Van Hove function. Water molecules are found to be strongly correlated in space and time with coupling between the first and second nearest-neighbor molecules. The local dynamic correlation of molecules observed here is crucial to a fundamental understanding of the origin of the physical properties of water, including viscosity. The resultsmore » also suggest that the quantum-mechanical nature of hydrogen bonds could influence its dynamics. Finally, the approach used here offers a powerful experimental method for investigating real-space dynamics of liquids.« less
Zhou, Yunyi; Tao, Chenyang; Lu, Wenlian; Feng, Jianfeng
2018-04-20
Functional connectivity is among the most important tools to study brain. The correlation coefficient, between time series of different brain areas, is the most popular method to quantify functional connectivity. Correlation coefficient in practical use assumes the data to be temporally independent. However, the time series data of brain can manifest significant temporal auto-correlation. A widely applicable method is proposed for correcting temporal auto-correlation. We considered two types of time series models: (1) auto-regressive-moving-average model, (2) nonlinear dynamical system model with noisy fluctuations, and derived their respective asymptotic distributions of correlation coefficient. These two types of models are most commonly used in neuroscience studies. We show the respective asymptotic distributions share a unified expression. We have verified the validity of our method, and shown our method exhibited sufficient statistical power for detecting true correlation on numerical experiments. Employing our method on real dataset yields more robust functional network and higher classification accuracy than conventional methods. Our method robustly controls the type I error while maintaining sufficient statistical power for detecting true correlation in numerical experiments, where existing methods measuring association (linear and nonlinear) fail. In this work, we proposed a widely applicable approach for correcting the effect of temporal auto-correlation on functional connectivity. Empirical results favor the use of our method in functional network analysis. Copyright © 2018. Published by Elsevier B.V.
Molecular dynamics study of naturally existing cavity couplings in proteins.
Barbany, Montserrat; Meyer, Tim; Hospital, Adam; Faustino, Ignacio; D'Abramo, Marco; Morata, Jordi; Orozco, Modesto; de la Cruz, Xavier
2015-01-01
Couplings between protein sub-structures are a common property of protein dynamics. Some of these couplings are especially interesting since they relate to function and its regulation. In this article we have studied the case of cavity couplings because cavities can host functional sites, allosteric sites, and are the locus of interactions with the cell milieu. We have divided this problem into two parts. In the first part, we have explored the presence of cavity couplings in the natural dynamics of 75 proteins, using 20 ns molecular dynamics simulations. For each of these proteins, we have obtained two trajectories around their native state. After applying a stringent filtering procedure, we found significant cavity correlations in 60% of the proteins. We analyze and discuss the structure origins of these correlations, including neighbourhood, cavity distance, etc. In the second part of our study, we have used longer simulations (≥100 ns) from the MoDEL project, to obtain a broader view of cavity couplings, particularly about their dependence on time. Using moving window computations we explored the fluctuations of cavity couplings along time, finding that these couplings could fluctuate substantially during the trajectory, reaching in several cases correlations above 0.25/0.5. In summary, we describe the structural origin and the variations with time of cavity couplings. We complete our work with a brief discussion of the biological implications of these results.
Molecular Dynamics Study of Naturally Existing Cavity Couplings in Proteins
Barbany, Montserrat; Meyer, Tim; Hospital, Adam; Faustino, Ignacio; D'Abramo, Marco; Morata, Jordi; Orozco, Modesto; de la Cruz, Xavier
2015-01-01
Couplings between protein sub-structures are a common property of protein dynamics. Some of these couplings are especially interesting since they relate to function and its regulation. In this article we have studied the case of cavity couplings because cavities can host functional sites, allosteric sites, and are the locus of interactions with the cell milieu. We have divided this problem into two parts. In the first part, we have explored the presence of cavity couplings in the natural dynamics of 75 proteins, using 20 ns molecular dynamics simulations. For each of these proteins, we have obtained two trajectories around their native state. After applying a stringent filtering procedure, we found significant cavity correlations in 60% of the proteins. We analyze and discuss the structure origins of these correlations, including neighbourhood, cavity distance, etc. In the second part of our study, we have used longer simulations (≥100ns) from the MoDEL project, to obtain a broader view of cavity couplings, particularly about their dependence on time. Using moving window computations we explored the fluctuations of cavity couplings along time, finding that these couplings could fluctuate substantially during the trajectory, reaching in several cases correlations above 0.25/0.5. In summary, we describe the structural origin and the variations with time of cavity couplings. We complete our work with a brief discussion of the biological implications of these results. PMID:25816327
Lanczos algorithm with matrix product states for dynamical correlation functions
NASA Astrophysics Data System (ADS)
Dargel, P. E.; Wöllert, A.; Honecker, A.; McCulloch, I. P.; Schollwöck, U.; Pruschke, T.
2012-05-01
The density-matrix renormalization group (DMRG) algorithm can be adapted to the calculation of dynamical correlation functions in various ways which all represent compromises between computational efficiency and physical accuracy. In this paper we reconsider the oldest approach based on a suitable Lanczos-generated approximate basis and implement it using matrix product states (MPS) for the representation of the basis states. The direct use of matrix product states combined with an ex post reorthogonalization method allows us to avoid several shortcomings of the original approach, namely the multitargeting and the approximate representation of the Hamiltonian inherent in earlier Lanczos-method implementations in the DMRG framework, and to deal with the ghost problem of Lanczos methods, leading to a much better convergence of the spectral weights and poles. We present results for the dynamic spin structure factor of the spin-1/2 antiferromagnetic Heisenberg chain. A comparison to Bethe ansatz results in the thermodynamic limit reveals that the MPS-based Lanczos approach is much more accurate than earlier approaches at minor additional numerical cost.
NASA Astrophysics Data System (ADS)
Witte, B. B. L.; Fletcher, L. B.; Galtier, E.; Gamboa, E.; Lee, H. J.; Zastrau, U.; Redmer, R.; Glenzer, S. H.; Sperling, P.
2017-06-01
We present simulations using finite-temperature density-functional-theory molecular dynamics to calculate the dynamic electrical conductivity in warm dense aluminum. The comparison between exchange-correlation functionals in the Perdew-Burke-Enzerhof and Heyd-Scuseria-Enzerhof (HSE) approximation indicates evident differences in the density of states and the dc conductivity. The HSE calculations show excellent agreement with experimental Linac Coherent Light Source x-ray plasmon scattering spectra revealing plasmon damping below the widely used random phase approximation. These findings demonstrate non-Drude-like behavior of the dynamic conductivity that needs to be taken into account to determine the optical properties of warm dense matter.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Brito, W. H.; Aguiar, M. C. O.; Haule, K.
In this study we present a comparative investigation of the electronic structures of NbO 2 and VO 2 obtained within a combination of density functional theory and cluster-dynamical mean-field theory calculations. We investigate the role of dynamic electronic correlations on the electronic structure of the metallic and insulating phases of NbO 2 and VO 2, with a focus on the mechanism responsible for the gap opening in the insulating phases. For the rutile metallic phases of both oxides, we obtain that electronic correlations lead to a strong renormalization of the t 2g subbands, as well as the emergence of incoherentmore » Hubbard subbands, signaling that electronic correlations are also important in the metallic phase of NbO 2. Interestingly, we find that nonlocal dynamic correlations do play a role in the gap formation of the [body-centered-tetragonal (bct)] insulating phase of NbO 2, by a similar physical mechanism as that recently proposed by us in the case of the monoclinic (M 1) dimerized phase of VO 2. Finally, although the effect of nonlocal dynamic correlations in the gap opening of bct phase is less important than in the (M 1 and M 2) monoclinic phases of VO 2, their presence indicates that the former is not a purely Peierls-type insulator, as it was recently proposed.« less
NASA Astrophysics Data System (ADS)
Kähler, Sven; Olsen, Jeppe
2017-11-01
A computational method is presented for systems that require high-level treatments of static and dynamic electron correlation but cannot be treated using conventional complete active space self-consistent field-based methods due to the required size of the active space. Our method introduces an efficient algorithm for perturbative dynamic correlation corrections for compact non-orthogonal MCSCF calculations. In the algorithm, biorthonormal expansions of orbitals and CI-wave functions are used to reduce the scaling of the performance determining step from quadratic to linear in the number of configurations. We describe a hierarchy of configuration spaces that can be chosen for the active space. Potential curves for the nitrogen molecule and the chromium dimer are compared for different configuration spaces. Already the most compact spaces yield qualitatively correct potentials that with increasing size of configuration spaces systematically approach complete active space results.
NASA Astrophysics Data System (ADS)
Hopkins, Paul; Fortini, Andrea; Archer, Andrew J.; Schmidt, Matthias
2010-12-01
We describe a test particle approach based on dynamical density functional theory (DDFT) for studying the correlated time evolution of the particles that constitute a fluid. Our theory provides a means of calculating the van Hove distribution function by treating its self and distinct parts as the two components of a binary fluid mixture, with the "self " component having only one particle, the "distinct" component consisting of all the other particles, and using DDFT to calculate the time evolution of the density profiles for the two components. We apply this approach to a bulk fluid of Brownian hard spheres and compare to results for the van Hove function and the intermediate scattering function from Brownian dynamics computer simulations. We find good agreement at low and intermediate densities using the very simple Ramakrishnan-Yussouff [Phys. Rev. B 19, 2775 (1979)] approximation for the excess free energy functional. Since the DDFT is based on the equilibrium Helmholtz free energy functional, we can probe a free energy landscape that underlies the dynamics. Within the mean-field approximation we find that as the particle density increases, this landscape develops a minimum, while an exact treatment of a model confined situation shows that for an ergodic fluid this landscape should be monotonic. We discuss possible implications for slow, glassy, and arrested dynamics at high densities.
NASA Astrophysics Data System (ADS)
Walter, Nathan P.; Jaiswal, Abhishek; Cai, Zhikun; Zhang, Yang
2018-07-01
Neutron scattering is a powerful experimental technique for characterizing the structure and dynamics of materials on the atomic or molecular scale. However, the interpretation of experimental data from neutron scattering is oftentimes not trivial, partly because scattering methods probe ensemble-averaged information in the reciprocal space. Therefore, computer simulations, such as classical and ab initio molecular dynamics, are frequently used to unravel the time-dependent atomistic configurations that can reproduce the scattering patterns and thus assist in the understanding of the microscopic origin of certain properties of materials. LiquidLib is a post-processing package for analyzing the trajectory of atomistic simulations of liquids and liquid-like matter with application to neutron scattering experiments. From an atomistic simulation, LiquidLib provides the computation of various statistical quantities including the pair distribution function, the weighted and unweighted structure factors, the mean squared displacement, the non-Gaussian parameter, the four-point correlation function, the velocity auto correlation function, the self and collective van Hove correlation functions, the self and collective intermediate scattering functions, and the bond orientational order parameter. LiquidLib analyzes atomistic trajectories generated from packages such as LAMMPS, GROMACS, and VASP. It also offers an extendable platform to conveniently integrate new quantities into the library and integrate simulation trajectories of other file formats for analysis. Weighting the quantities by element-specific neutron-scattering lengths provides results directly comparable to neutron scattering measurements. Lastly, LiquidLib is independent of dimensionality, which allows analysis of trajectories in two, three, and higher dimensions. The code is beginning to find worldwide use.
Relativistic diffusive motion in random electromagnetic fields
NASA Astrophysics Data System (ADS)
Haba, Z.
2011-08-01
We show that the relativistic dynamics in a Gaussian random electromagnetic field can be approximated by the relativistic diffusion of Schay and Dudley. Lorentz invariant dynamics in the proper time leads to the diffusion in the proper time. The dynamics in the laboratory time gives the diffusive transport equation corresponding to the Jüttner equilibrium at the inverse temperature β-1 = mc2. The diffusion constant is expressed by the field strength correlation function (Kubo's formula).
Active motion assisted by correlated stochastic torques.
Weber, Christian; Radtke, Paul K; Schimansky-Geier, Lutz; Hänggi, Peter
2011-07-01
The stochastic dynamics of an active particle undergoing a constant speed and additionally driven by an overall fluctuating torque is investigated. The random torque forces are expressed by a stochastic differential equation for the angular dynamics of the particle determining the orientation of motion. In addition to a constant torque, the particle is supplemented by random torques, which are modeled as an Ornstein-Uhlenbeck process with given correlation time τ(c). These nonvanishing correlations cause a persistence of the particles' trajectories and a change of the effective spatial diffusion coefficient. We discuss the mean square displacement as a function of the correlation time and the noise intensity and detect a nonmonotonic dependence of the effective diffusion coefficient with respect to both correlation time and noise strength. A maximal diffusion behavior is obtained if the correlated angular noise straightens the curved trajectories, interrupted by small pirouettes, whereby the correlated noise amplifies a straightening of the curved trajectories caused by the constant torque.
Hensen, Ulf; Meyer, Tim; Haas, Jürgen; Rex, René; Vriend, Gert; Grubmüller, Helmut
2012-01-01
Proteins are usually described and classified according to amino acid sequence, structure or function. Here, we develop a minimally biased scheme to compare and classify proteins according to their internal mobility patterns. This approach is based on the notion that proteins not only fold into recurring structural motifs but might also be carrying out only a limited set of recurring mobility motifs. The complete set of these patterns, which we tentatively call the dynasome, spans a multi-dimensional space with axes, the dynasome descriptors, characterizing different aspects of protein dynamics. The unique dynamic fingerprint of each protein is represented as a vector in the dynasome space. The difference between any two vectors, consequently, gives a reliable measure of the difference between the corresponding protein dynamics. We characterize the properties of the dynasome by comparing the dynamics fingerprints obtained from molecular dynamics simulations of 112 proteins but our approach is, in principle, not restricted to any specific source of data of protein dynamics. We conclude that: 1. the dynasome consists of a continuum of proteins, rather than well separated classes. 2. For the majority of proteins we observe strong correlations between structure and dynamics. 3. Proteins with similar function carry out similar dynamics, which suggests a new method to improve protein function annotation based on protein dynamics. PMID:22606222
Bolton, Thomas A W; Jochaut, Delphine; Giraud, Anne-Lise; Van De Ville, Dimitri
2018-06-01
To refine our understanding of autism spectrum disorders (ASD), studies of the brain in dynamic, multimodal and ecological experimental settings are required. One way to achieve this is to compare the neural responses of ASD and typically developing (TD) individuals when viewing a naturalistic movie, but the temporal complexity of the stimulus hampers this task, and the presence of intrinsic functional connectivity (FC) may overshadow movie-driven fluctuations. Here, we detected inter-subject functional correlation (ISFC) transients to disentangle movie-induced functional changes from underlying resting-state activity while probing FC dynamically. When considering the number of significant ISFC excursions triggered by the movie across the brain, connections between remote functional modules were more heterogeneously engaged in the ASD population. Dynamically tracking the temporal profiles of those ISFC changes and tying them to specific movie subparts, this idiosyncrasy in ASD responses was then shown to involve functional integration and segregation mechanisms such as response inhibition, background suppression, or multisensory integration, while low-level visual processing was spared. Through the application of a new framework for the study of dynamic experimental paradigms, our results reveal a temporally localized idiosyncrasy in ASD responses, specific to short-lived episodes of long-range functional interplays. © 2018 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.
Equilibrium properties and phase diagram of two-dimensional Yukawa systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hartmann, P.; Donko, Z.; Kutasi, K.
Properties of two-dimensional strongly coupled Yukawa systems are explored through molecular dynamics simulations. An effective coupling coefficient {gamma}{sup *} for the liquid phase is introduced on the basis of the constancy of the first peak amplitude of the pair-correlation functions. Thermodynamic quantities are calculated from the pair-correlation function. The solid-liquid transition of the system is investigated through the analysis of the bond-angular order parameter. The static structure function satisfies consistency relation, attesting to the reliability of the computational method. The response is shown to be governed by the correlational part of the inverse compressibility. An analysis of the velocity autocorrelationmore » demonstrates that this latter also exhibits a universal behavior.« less
Intrinsic Multi-Scale Dynamic Behaviors of Complex Financial Systems.
Ouyang, Fang-Yan; Zheng, Bo; Jiang, Xiong-Fei
2015-01-01
The empirical mode decomposition is applied to analyze the intrinsic multi-scale dynamic behaviors of complex financial systems. In this approach, the time series of the price returns of each stock is decomposed into a small number of intrinsic mode functions, which represent the price motion from high frequency to low frequency. These intrinsic mode functions are then grouped into three modes, i.e., the fast mode, medium mode and slow mode. The probability distribution of returns and auto-correlation of volatilities for the fast and medium modes exhibit similar behaviors as those of the full time series, i.e., these characteristics are rather robust in multi time scale. However, the cross-correlation between individual stocks and the return-volatility correlation are time scale dependent. The structure of business sectors is mainly governed by the fast mode when returns are sampled at a couple of days, while by the medium mode when returns are sampled at dozens of days. More importantly, the leverage and anti-leverage effects are dominated by the medium mode.
A secure image encryption method based on dynamic harmony search (DHS) combined with chaotic map
NASA Astrophysics Data System (ADS)
Mirzaei Talarposhti, Khadijeh; Khaki Jamei, Mehrzad
2016-06-01
In recent years, there has been increasing interest in the security of digital images. This study focuses on the gray scale image encryption using dynamic harmony search (DHS). In this research, first, a chaotic map is used to create cipher images, and then the maximum entropy and minimum correlation coefficient is obtained by applying a harmony search algorithm on them. This process is divided into two steps. In the first step, the diffusion of a plain image using DHS to maximize the entropy as a fitness function will be performed. However, in the second step, a horizontal and vertical permutation will be applied on the best cipher image, which is obtained in the previous step. Additionally, DHS has been used to minimize the correlation coefficient as a fitness function in the second step. The simulation results have shown that by using the proposed method, the maximum entropy and the minimum correlation coefficient, which are approximately 7.9998 and 0.0001, respectively, have been obtained.
NASA Astrophysics Data System (ADS)
Buttgereit, R.; Roths, T.; Honerkamp, J.; Aberle, L. B.
2001-10-01
Dynamic light scattering experiments have become a powerful tool in order to investigate the dynamical properties of complex fluids. In many applications in both soft matter research and industry so-called ``real world'' systems are subject of great interest. Here, the dilution of the investigated system often cannot be changed without getting measurement artifacts, so that one often has to deal with highly concentrated and turbid media. The investigation of such systems requires techniques that suppress the influence of multiple scattering, e.g., cross correlation techniques. However, measurements at turbid as well as highly diluted media lead to data with low signal-to-noise ratio, which complicates data analysis and leads to unreliable results. In this article a multiangle regularization method is discussed, which copes with the difficulties arising from such samples and enhances enormously the quality of the estimated solution. In order to demonstrate the efficiency of this multiangle regularization method we applied it to cross correlation functions measured at highly turbid samples.
Shock probes in a one-dimensional Katz-Lebowitz-Spohn model
NASA Astrophysics Data System (ADS)
Chatterjee, Sakuntala; Barma, Mustansir
2008-06-01
We consider shock probes in a one-dimensional driven diffusive medium with nearest-neighbor Ising interaction (KLS model). Earlier studies based on an approximate mapping of the present system to an effective zero-range process concluded that the exponents characterizing the decays of several static and dynamical correlation functions of the probes depend continuously on the strength of the Ising interaction. On the contrary, our numerical simulations indicate that over a substantial range of the interaction strength, these exponents remain constant and their values are the same as in the case of no interaction (when the medium executes an ASEP). We demonstrate this by numerical studies of several dynamical correlation functions for two probes and also for a macroscopic number of probes. Our results are consistent with the expectation that the short-ranged correlations induced by the Ising interaction should not affect the large time and large distance properties of the system, implying that scaling forms remain the same as in the medium with no interactions present.
Shakil, Sadia; Lee, Chin-Hui; Keilholz, Shella Dawn
2016-01-01
A promising recent development in the study of brain function is the dynamic analysis of resting-state functional MRI scans, which can enhance understanding of normal cognition and alterations that result from brain disorders. One widely used method of capturing the dynamics of functional connectivity is sliding window correlation (SWC). However, in the absence of a “gold standard” for comparison, evaluating the performance of the SWC in typical resting-state data is challenging. This study uses simulated networks (SNs) with known transitions to examine the effects of parameters such as window length, window offset, window type, noise, filtering, and sampling rate on the SWC performance. The SWC time course was calculated for all node pairs of each SN and then clustered using the k-means algorithm to determine how resulting brain states match known configurations and transitions in the SNs. The outcomes show that the detection of state transitions and durations in the SWC is most strongly influenced by the window length and offset, followed by noise and filtering parameters. The effect of the image sampling rate was relatively insignificant. Tapered windows provide less sensitivity to state transitions than rectangular windows, which could be the result of the sharp transitions in the SNs. Overall, the SWC gave poor estimates of correlation for each brain state. Clustering based on the SWC time course did not reliably reflect the underlying state transitions unless the window length was comparable to the state duration, highlighting the need for new adaptive window analysis techniques. PMID:26952197
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bytautas, Laimutis; Scuseria, Gustavo E.; Chemistry Department, Faculty of Science, King Abdulaziz University, Jeddah 21589
2015-09-07
The present study further explores the concept of the seniority number (Ω) by examining different configuration interaction (CI) truncation strategies in generating compact wave functions in a systematic way. While the role of Ω in addressing static (strong) correlation problem has been addressed in numerous previous studies, the usefulness of seniority number in describing weak (dynamic) correlation has not been investigated in a systematic way. Thus, the overall objective in the present work is to investigate the role of Ω in addressing also dynamic electron correlation in addition to the static correlation. Two systematic CI truncation strategies are compared beyondmore » minimal basis sets and full valence active spaces. One approach is based on the seniority number (defined as the total number of singly occupied orbitals in a determinant) and another is based on an excitation-level limitation. In addition, molecular orbitals are energy-optimized using multiconfigurational-self-consistent-field procedure for all these wave functions. The test cases include the symmetric dissociation of water (6-31G), N{sub 2} (6-31G), C{sub 2} (6-31G), and Be{sub 2} (cc-pVTZ). We find that the potential energy profile for H{sub 2}O dissociation can be reasonably well described using only the Ω = 0 sector of the CI wave function. For the Be{sub 2} case, we show that the full CI potential energy curve (cc-pVTZ) is almost exactly reproduced using either Ω-based (including configurations having up to Ω = 2 in the virtual-orbital-space) or excitation-based (up to single-plus-double-substitutions) selection methods, both out of a full-valence-reference function. Finally, in dissociation cases of N{sub 2} and C{sub 2}, we shall also consider novel hybrid wave functions obtained by a union of a set of CI configurations representing the full valence space and a set of CI configurations where seniority-number restriction is imposed for a complete set (full-valence-space and virtual) of correlated molecular orbitals, simultaneously. We discuss the usefulness of the seniority number concept in addressing both static and dynamic electron correlation problems along dissociation paths.« less
Correlated Fluctuations in Strongly Coupled Binary Networks Beyond Equilibrium
NASA Astrophysics Data System (ADS)
Dahmen, David; Bos, Hannah; Helias, Moritz
2016-07-01
Randomly coupled Ising spins constitute the classical model of collective phenomena in disordered systems, with applications covering glassy magnetism and frustration, combinatorial optimization, protein folding, stock market dynamics, and social dynamics. The phase diagram of these systems is obtained in the thermodynamic limit by averaging over the quenched randomness of the couplings. However, many applications require the statistics of activity for a single realization of the possibly asymmetric couplings in finite-sized networks. Examples include reconstruction of couplings from the observed dynamics, representation of probability distributions for sampling-based inference, and learning in the central nervous system based on the dynamic and correlation-dependent modification of synaptic connections. The systematic cumulant expansion for kinetic binary (Ising) threshold units with strong, random, and asymmetric couplings presented here goes beyond mean-field theory and is applicable outside thermodynamic equilibrium; a system of approximate nonlinear equations predicts average activities and pairwise covariances in quantitative agreement with full simulations down to hundreds of units. The linearized theory yields an expansion of the correlation and response functions in collective eigenmodes, leads to an efficient algorithm solving the inverse problem, and shows that correlations are invariant under scaling of the interaction strengths.
Dynamical correlation functions of the quadratic coupling spin-Boson model
NASA Astrophysics Data System (ADS)
Zheng, Da-Chuan; Tong, Ning-Hua
2017-06-01
The spin-boson model with quadratic coupling is studied using the bosonic numerical renormalization group method. We focus on the dynamical auto-correlation functions {C}O(ω ), with the operator \\hat{O} taken as {\\hat{{{σ }}}}x, {\\hat{{{σ }}}}z, and \\hat{X}, respectively. In the weak-coupling regime α < {α }{{c}}, these functions show power law ω-dependence in the small frequency limit, with the powers 1+2s, 1+2s, and s, respectively. At the critical point α ={α }{{c}} of the boson-unstable quantum phase transition, the critical exponents y O of these correlation functions are obtained as {y}{{{σ }}x}={y}{{{σ }}z}=1-2s and {y}X=-s, respectively. Here s is the bath index and X is the boson displacement operator. Close to the spin flip point, the high frequency peak of {C}{{{σ }}x}(ω ) is broadened significantly and the line shape changes qualitatively, showing enhanced dephasing at the spin flip point. Project supported by the National Key Basic Research Program of China (Grant No. 2012CB921704), the National Natural Science Foundation of China (Grant No. 11374362), the Fundamental Research Funds for the Central Universities, China, and the Research Funds of Renmin University of China (Grant No. 15XNLQ03).
Parametrically coupled fermionic oscillators: Correlation functions and phase-space description
NASA Astrophysics Data System (ADS)
Ghosh, Arnab
2015-01-01
A fermionic analog of a parametric amplifier is used to describe the joint quantum state of the two interacting fermionic modes. Based on a two-mode generalization of the time-dependent density operator, time evolution of the fermionic density operator is determined in terms of its two-mode Wigner and P function. It is shown that the equation of motion of the Wigner function corresponds to a fermionic analog of Liouville's equation. The equilibrium density operator for fermionic fields developed by Cahill and Glauber is thus extended to a dynamical context to show that the mathematical structures of both the correlation functions and the weight factors closely resemble their bosonic counterpart. It has been shown that the fermionic correlation functions are marked by a characteristic upper bound due to Fermi statistics, which can be verified in the matter wave counterpart of photon down-conversion experiments.
Zhao, Linjie; Sun, Tanlin; Pei, Jianfeng; Ouyang, Qi
2015-01-01
It has been a consensus in cancer research that cancer is a disease caused primarily by genomic alterations, especially somatic mutations. However, the mechanism of mutation-induced oncogenesis is not fully understood. Here, we used the mitochondrial apoptotic pathway as a case study and performed a systematic analysis of integrating pathway dynamics with protein interaction kinetics to quantitatively investigate the causal molecular mechanism of mutation-induced oncogenesis. A mathematical model of the regulatory network was constructed to establish the functional role of dynamic bifurcation in the apoptotic process. The oncogenic mutation enrichment of each of the protein functional domains involved was found strongly correlated with the parameter sensitivity of the bifurcation point. We further dissected the causal mechanism underlying this correlation by evaluating the mutational influence on protein interaction kinetics using molecular dynamics simulation. We analyzed 29 matched mutant–wild-type and 16 matched SNP—wild-type protein systems. We found that the binding kinetics changes reflected by the changes of free energy changes induced by protein interaction mutations, which induce variations in the sensitive parameters of the bifurcation point, were a major cause of apoptosis pathway dysfunction, and mutations involved in sensitive interaction domains show high oncogenic potential. Our analysis provided a molecular basis for connecting protein mutations, protein interaction kinetics, network dynamics properties, and physiological function of a regulatory network. These insights provide a framework for coupling mutation genotype to tumorigenesis phenotype and help elucidate the logic of cancer initiation. PMID:26170328
Boguslawski, Katharina; Tecmer, Paweł
2017-12-12
Wave functions restricted to electron-pair states are promising models to describe static/nondynamic electron correlation effects encountered, for instance, in bond-dissociation processes and transition-metal and actinide chemistry. To reach spectroscopic accuracy, however, the missing dynamic electron correlation effects that cannot be described by electron-pair states need to be included a posteriori. In this Article, we extend the previously presented perturbation theory models with an Antisymmetric Product of 1-reference orbital Geminal (AP1roG) reference function that allows us to describe both static/nondynamic and dynamic electron correlation effects. Specifically, our perturbation theory models combine a diagonal and off-diagonal zero-order Hamiltonian, a single-reference and multireference dual state, and different excitation operators used to construct the projection manifold. We benchmark all proposed models as well as an a posteriori Linearized Coupled Cluster correction on top of AP1roG against CR-CC(2,3) reference data for reaction energies of several closed-shell molecules that are extrapolated to the basis set limit. Moreover, we test the performance of our new methods for multiple bond breaking processes in the homonuclear N 2 , C 2 , and F 2 dimers as well as the heteronuclear BN, CO, and CN + dimers against MRCI-SD, MRCI-SD+Q, and CR-CC(2,3) reference data. Our numerical results indicate that the best performance is obtained from a Linearized Coupled Cluster correction as well as second-order perturbation theory corrections employing a diagonal and off-diagonal zero-order Hamiltonian and a single-determinant dual state. These dynamic corrections on top of AP1roG provide substantial improvements for binding energies and spectroscopic properties obtained with the AP1roG approach, while allowing us to approach chemical accuracy for reaction energies involving closed-shell species.
Roos, Matthias; Hofmann, Marius; Link, Susanne; Ott, Maria; Balbach, Jochen; Rössler, Ernst; Saalwächter, Kay; Krushelnitsky, Alexey
2015-12-01
Inter-protein interactions in solution affect the auto-correlation function of Brownian tumbling not only in terms of a simple increase of the correlation time, they also lead to the appearance of a weak slow component ("long tail") of the correlation function due to a slowly changing local anisotropy of the microenvironment. The conventional protocol of correlation time estimation from the relaxation rate ratio R1/R2 assumes a single-component tumbling correlation function, and thus can provide incorrect results as soon as the "long tail" is of relevance. This effect, however, has been underestimated in many instances. In this work we present a detailed systematic study of the tumbling correlation function of two proteins, lysozyme and bovine serum albumin, at different concentrations and temperatures using proton field-cycling relaxometry combined with R1ρ and R2 measurements. Unlike high-field NMR relaxation methods, these techniques enable a detailed study of dynamics on a time scale longer than the normal protein tumbling correlation time and, thus, a reliable estimate of the parameters of the "long tail". In this work we analyze the concentration dependence of the intensity and correlation time of the slow component and perform simulations of high-field (15)N NMR relaxation data demonstrating the importance of taking the "long tail" in the analysis into account.
Ramasesha, Krupa; De Marco, Luigi; Horning, Andrew D; Mandal, Aritra; Tokmakoff, Andrei
2012-04-07
We present an approach for calculating nonlinear spectroscopic observables, which overcomes the approximations inherent to current phenomenological models without requiring the computational cost of performing molecular dynamics simulations. The trajectory mapping method uses the semi-classical approximation to linear and nonlinear response functions, and calculates spectra from trajectories of the system's transition frequencies and transition dipole moments. It rests on identifying dynamical variables important to the problem, treating the dynamics of these variables stochastically, and then generating correlated trajectories of spectroscopic quantities by mapping from the dynamical variables. This approach allows one to describe non-Gaussian dynamics, correlated dynamics between variables of the system, and nonlinear relationships between spectroscopic variables of the system and the bath such as non-Condon effects. We illustrate the approach by applying it to three examples that are often not adequately treated by existing analytical models--the non-Condon effect in the nonlinear infrared spectra of water, non-Gaussian dynamics inherent to strongly hydrogen bonded systems, and chemical exchange processes in barrier crossing reactions. The methods described are generally applicable to nonlinear spectroscopy throughout the optical, infrared and terahertz regions.
Impact of 36 h of total sleep deprivation on resting-state dynamic functional connectivity.
Xu, Huaze; Shen, Hui; Wang, Lubin; Zhong, Qi; Lei, Yu; Yang, Liu; Zeng, Ling-Li; Zhou, Zongtan; Hu, Dewen; Yang, Zheng
2018-06-01
Resting-state functional magnetic resonance imaging (fMRI) studies using static functional connectivity (sFC) measures have shown that the brain function is severely disrupted after long-term sleep deprivation (SD). However, increasing evidence has suggested that resting-state functional connectivity (FC) is dynamic and exhibits spontaneous fluctuation on a smaller timescale. The process by which long-term SD can influence dynamic functional connectivity (dFC) remains unclear. In this study, 37 healthy subjects participated in the SD experiment, and they were scanned both during rested wakefulness (RW) and after 36 h of SD. A sliding-window based approach and a spectral clustering algorithm were used to evaluate the effects of SD on dFC based on the 26 qualified subjects' data. The outcomes showed that time-averaging FC across specific regions as well as temporal properties of the FC states, such as the dwell time and transition probability, was strongly influenced after SD in contrast to the RW condition. Based on the occurrences of FC states, we further identified some RW-dominant states characterized by anti-correlation between the default mode network (DMN) and other cortices, and some SD-dominant states marked by significantly decreased thalamocortical connectivity. In particular, the temporal features of these FC states were negatively correlated with the correlation coefficients between the DMN and dorsal attention network (dATN) and demonstrated high potential in classification of sleep state (with 10-fold cross-validation accuracy of 88.6% for dwell time and 88.1% for transition probability). Collectively, our results suggested that the temporal properties of the FC states greatly account for changes in the resting-state brain networks following SD, which provides new insights into the impact of SD on the resting-state functional organization in the human brain. Copyright © 2017. Published by Elsevier B.V.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li, Minjing; Gao, Yuqian; Qian, Wei-Jun
Microbially mediated biogeochemical processes are catalyzed by enzymes that control the transformation of carbon, nitrogen, and other elements in environment. The dynamic linkage between enzymes and biogeochemical species transformation has, however, rarely been investigated because of the lack of analytical approaches to efficiently and reliably quantify enzymes and their dynamics in soils and sediments. Herein, we developed a signature peptide-based technique for sensitively quantifying dissimilatory and assimilatory enzymes using nitrate-reducing enzymes in a hyporheic zone sediment as an example. Moreover, the measured changes in enzyme concentration were found to correlate with the nitrate reduction rate in a way different frommore » that inferred from biogeochemical models based on biomass or functional genes as surrogates for functional enzymes. This phenomenon has important implications for understanding and modeling the dynamics of microbial community functions and biogeochemical processes in environments. Our results also demonstrate the importance of enzyme quantification for the identification and interrogation of those biogeochemical processes with low metabolite concentrations as a result of faster enzyme-catalyzed consumption of metabolites than their production. The dynamic enzyme behaviors provide a basis for the development of enzyme-based models to describe the relationship between the microbial community and biogeochemical processes.« less
Cuetos, Alejandro; Patti, Alessandro
2015-08-01
We propose a simple but powerful theoretical framework to quantitatively compare Brownian dynamics (BD) and dynamic Monte Carlo (DMC) simulations of multicomponent colloidal suspensions. By extending our previous study focusing on monodisperse systems of rodlike colloids, here we generalize the formalism described there to multicomponent colloidal mixtures and validate it by investigating the dynamics in isotropic and liquid crystalline phases containing spherical and rodlike particles. In order to investigate the dynamics of multicomponent colloidal systems by DMC simulations, it is key to determine the elementary time step of each species and establish a unique timescale. This is crucial to consistently study the dynamics of colloidal particles with different geometry. By analyzing the mean-square displacement, the orientation autocorrelation functions, and the self part of the van Hove correlation functions, we show that DMC simulation is a very convenient and reliable technique to describe the stochastic dynamics of any multicomponent colloidal system. Our theoretical formalism can be easily extended to any colloidal system containing size and/or shape polydisperse particles.
Andrews, Ross N; Narayanan, Suresh; Zhang, Fan; Kuzmenko, Ivan; Ilavsky, Jan
2018-02-01
X-ray photon correlation spectroscopy (XPCS), an extension of dynamic light scattering (DLS) in the X-ray regime, detects temporal intensity fluctuations of coherent speckles and provides scattering vector-dependent sample dynamics at length scales smaller than DLS. The penetrating power of X-rays enables probing dynamics in a broad array of materials with XPCS, including polymers, glasses and metal alloys, where attempts to describe the dynamics with a simple exponential fit usually fails. In these cases, the prevailing XPCS data analysis approach employs stretched or compressed exponential decay functions (Kohlrausch functions), which implicitly assume homogeneous dynamics. In this paper, we propose an alternative analysis scheme based upon inverse Laplace or Gaussian transformation for elucidating heterogeneous distributions of dynamic time scales in XPCS, an approach analogous to the CONTIN algorithm widely accepted in the analysis of DLS from polydisperse and multimodal systems. Using XPCS data measured from colloidal gels, we demonstrate the inverse transform approach reveals hidden multimodal dynamics in materials, unleashing the full potential of XPCS.
Andrews, Ross N.; Narayanan, Suresh; Zhang, Fan; Kuzmenko, Ivan; Ilavsky, Jan
2018-01-01
X-ray photon correlation spectroscopy (XPCS), an extension of dynamic light scattering (DLS) in the X-ray regime, detects temporal intensity fluctuations of coherent speckles and provides scattering vector-dependent sample dynamics at length scales smaller than DLS. The penetrating power of X-rays enables probing dynamics in a broad array of materials with XPCS, including polymers, glasses and metal alloys, where attempts to describe the dynamics with a simple exponential fit usually fails. In these cases, the prevailing XPCS data analysis approach employs stretched or compressed exponential decay functions (Kohlrausch functions), which implicitly assume homogeneous dynamics. In this paper, we propose an alternative analysis scheme based upon inverse Laplace or Gaussian transformation for elucidating heterogeneous distributions of dynamic time scales in XPCS, an approach analogous to the CONTIN algorithm widely accepted in the analysis of DLS from polydisperse and multimodal systems. Using XPCS data measured from colloidal gels, we demonstrate the inverse transform approach reveals hidden multimodal dynamics in materials, unleashing the full potential of XPCS. PMID:29875506
Dynamics of Lithium Polymer Electrolytes using X-ray Photon Correlation Spectroscopy and Rheology
NASA Astrophysics Data System (ADS)
Oparaji, Onyekachi; Narayanan, Suresh; Sandy, Alec; Hallinan, Daniel, Jr.
Polymer electrolytes are promising materials for high energy density rechargeable batteries. Battery fade can be caused by structural evolution in the battery electrode and loss of electrode/electrolyte adhesion during cycling. Both of these effects are dependent on polymer mechanical properties. In addition, cycling rate is dictated by the ion mobility of the polymer electrolyte. Lithium ion mobility is expected to be strongly coupled to polymer dynamics. Therefore, we investigate polymer dynamics as a function of salt concentration using X-ray Photon Correlation Spectroscopy (XPCS) and rheology. We report the influence of lithium salt concentration on the structural relaxation time (XPCS) and stress relaxation time (rheology) of high molecular weight poly(styrene - ethylene oxide) block copolymer membranes.
Image correlation microscopy for uniform illumination.
Gaborski, T R; Sealander, M N; Ehrenberg, M; Waugh, R E; McGrath, J L
2010-01-01
Image cross-correlation microscopy is a technique that quantifies the motion of fluorescent features in an image by measuring the temporal autocorrelation function decay in a time-lapse image sequence. Image cross-correlation microscopy has traditionally employed laser-scanning microscopes because the technique emerged as an extension of laser-based fluorescence correlation spectroscopy. In this work, we show that image correlation can also be used to measure fluorescence dynamics in uniform illumination or wide-field imaging systems and we call our new approach uniform illumination image correlation microscopy. Wide-field microscopy is not only a simpler, less expensive imaging modality, but it offers the capability of greater temporal resolution over laser-scanning systems. In traditional laser-scanning image cross-correlation microscopy, lateral mobility is calculated from the temporal de-correlation of an image, where the characteristic length is the illuminating laser beam width. In wide-field microscopy, the diffusion length is defined by the feature size using the spatial autocorrelation function. Correlation function decay in time occurs as an object diffuses from its original position. We show that theoretical and simulated comparisons between Gaussian and uniform features indicate the temporal autocorrelation function depends strongly on particle size and not particle shape. In this report, we establish the relationships between the spatial autocorrelation function feature size, temporal autocorrelation function characteristic time and the diffusion coefficient for uniform illumination image correlation microscopy using analytical, Monte Carlo and experimental validation with particle tracking algorithms. Additionally, we demonstrate uniform illumination image correlation microscopy analysis of adhesion molecule domain aggregation and diffusion on the surface of human neutrophils.
Recent advances in multidimensional ultrafast spectroscopy
NASA Astrophysics Data System (ADS)
Oliver, Thomas A. A.
2018-01-01
Multidimensional ultrafast spectroscopies are one of the premier tools to investigate condensed phase dynamics of biological, chemical and functional nanomaterial systems. As they reach maturity, the variety of frequency domains that can be explored has vastly increased, with experimental techniques capable of correlating excitation and emission frequencies from the terahertz through to the ultraviolet. Some of the most recent innovations also include extreme cross-peak spectroscopies that directly correlate the dynamics of electronic and vibrational states. This review article summarizes the key technological advances that have permitted these recent advances, and the insights gained from new multidimensional spectroscopic probes.
Recent advances in multidimensional ultrafast spectroscopy
2018-01-01
Multidimensional ultrafast spectroscopies are one of the premier tools to investigate condensed phase dynamics of biological, chemical and functional nanomaterial systems. As they reach maturity, the variety of frequency domains that can be explored has vastly increased, with experimental techniques capable of correlating excitation and emission frequencies from the terahertz through to the ultraviolet. Some of the most recent innovations also include extreme cross-peak spectroscopies that directly correlate the dynamics of electronic and vibrational states. This review article summarizes the key technological advances that have permitted these recent advances, and the insights gained from new multidimensional spectroscopic probes. PMID:29410844
Collective excitations and ultrafast dipolar solvation dynamics in water-ethanol binary mixture
NASA Astrophysics Data System (ADS)
Hazra, Milan K.; Bagchi, Biman
2018-03-01
In order to understand the intermolecular vibrational spectrum and the collective excitations of water-ethanol binary mixture, we investigate the density of states and the power spectrum using computer simulations aided by theory. We investigate in particular the spectra at intermediate to low frequencies (a few hundreds to few tens of cm-1) by calculating (i) the density of states from quenched normal modes, (ii) the power spectrum from velocity time correlation function, and (iii) the far infrared and dielectric spectra (that is, the Cole-Cole plot) from the total dipole moment time correlation function. The different spectra are in broad agreement with each other and at the same time reveal unique characteristics of the water-ethanol mixture. Inverse participation ratio reveals several interesting features. Libration of pure ethanol is more localized than that of pure water. With increasing ethanol content, we observe localization of the collective libration mode as well as of the hindered translational and rotational mode. An interesting mixing between the libration of water and ethanol is observed. Solvation dynamics of tryptophan measured by equilibrium energy fluctuation time correlation function show surprisingly strong non-linear dependence on composition that can be tested against experiments.
Collective excitations and ultrafast dipolar solvation dynamics in water-ethanol binary mixture.
Hazra, Milan K; Bagchi, Biman
2018-03-21
In order to understand the intermolecular vibrational spectrum and the collective excitations of water-ethanol binary mixture, we investigate the density of states and the power spectrum using computer simulations aided by theory. We investigate in particular the spectra at intermediate to low frequencies (a few hundreds to few tens of cm -1 ) by calculating (i) the density of states from quenched normal modes, (ii) the power spectrum from velocity time correlation function, and (iii) the far infrared and dielectric spectra (that is, the Cole-Cole plot) from the total dipole moment time correlation function. The different spectra are in broad agreement with each other and at the same time reveal unique characteristics of the water-ethanol mixture. Inverse participation ratio reveals several interesting features. Libration of pure ethanol is more localized than that of pure water. With increasing ethanol content, we observe localization of the collective libration mode as well as of the hindered translational and rotational mode. An interesting mixing between the libration of water and ethanol is observed. Solvation dynamics of tryptophan measured by equilibrium energy fluctuation time correlation function show surprisingly strong non-linear dependence on composition that can be tested against experiments.
Response properties in the adsorption-desorption model on a triangular lattice
NASA Astrophysics Data System (ADS)
Šćepanović, J. R.; Stojiljković, D.; Jakšić, Z. M.; Budinski-Petković, Lj.; Vrhovac, S. B.
2016-06-01
The out-of-equilibrium dynamical processes during the reversible random sequential adsorption (RSA) of objects of various shapes on a two-dimensional triangular lattice are studied numerically by means of Monte Carlo simulations. We focused on the influence of the order of symmetry axis of the shape on the response of the reversible RSA model to sudden perturbations of the desorption probability Pd. We provide a detailed discussion of the significance of collective events for governing the time coverage behavior of shapes with different rotational symmetries. We calculate the two-time density-density correlation function C(t ,tw) for various waiting times tw and show that longer memory of the initial state persists for the more symmetrical shapes. Our model displays nonequilibrium dynamical effects such as aging. We find that the correlation function C(t ,tw) for all objects scales as a function of single variable ln(tw) / ln(t) . We also study the short-term memory effects in two-component mixtures of extended objects and give a detailed analysis of the contribution to the densification kinetics coming from each mixture component. We observe the weakening of correlation features for the deposition processes in multicomponent systems.
Internal dynamics of semiflexible polymers with active noise
NASA Astrophysics Data System (ADS)
Eisenstecken, Thomas; Gompper, Gerhard; Winkler, Roland G.
2017-04-01
The intramolecular dynamics of flexible and semiflexible polymers in response to active noise is studied theoretically. The active noise may either originate from interactions of a passive polymer with a bath of active Brownian particles or the polymer itself is comprised of active Brownian particles. We describe the polymer by the continuous Gaussian semiflexible-polymer model, taking into account the finite polymer extensibility. Our analytical calculations predict a strong dependence of the polymer dynamics on the activity. In particular, active semiflexible polymers exhibit a crossover from a bending elasticity-dominated dynamics at weak activity to that of flexible polymers at strong activity. The end-to-end vector correlation function decays exponentially for times longer than the longest polymer relaxation time. Thereby, the polymer relaxation determines the decay of the correlation function for long and flexible polymers. For shorter and stiffer polymers, the relaxation behavior of individual active Brownian particles dominates the decay above a certain activity. The diffusive dynamics of a polymer is substantially enhanced by the activity. Three regimes can be identified in the mean square displacement for sufficiently strong activities: an activity-induced ballistic regime at short times, followed by a Rouse-type polymer-specific regime for any polymer stiffness, and free diffusion at long times, again determined by the activity.
Hydration and vibrational dynamics of betaine (N,N,N-trimethylglycine)
NASA Astrophysics Data System (ADS)
Li, Tanping; Cui, Yaowen; Mathaga, John; Kumar, Revati; Kuroda, Daniel G.
2015-06-01
Zwitterions are naturally occurring molecules that have a positive and a negative charge group in its structure and are of great importance in many areas of science. Here, the vibrational and hydration dynamics of the zwitterionic system betaine (N,N,N-trimethylglycine) is reported. The linear infrared spectrum of aqueous betaine exhibits an asymmetric band in the 1550-1700 cm-1 region of the spectrum. This band is attributed to the carboxylate asymmetric stretch of betaine. The potential of mean force computed from ab initio molecular dynamic simulations confirms that the two observed transitions of the linear spectrum are related to two different betaine conformers present in solution. A model of the experimental data using non-linear response theory agrees very well with a vibrational model comprising of two vibrational transitions. In addition, our modeling shows that spectral parameters such as the slope of the zeroth contour plot and central line slope are both sensitive to the presence of overlapping transitions. The vibrational dynamics of the system reveals an ultrafast decay of the vibrational population relaxation as well as the correlation of frequency-frequency correlation function (FFCF). A decay of ˜0.5 ps is observed for the FFCF correlation time and is attributed to the frequency fluctuations caused by the motions of water molecules in the solvation shell. The comparison of the experimental observations with simulations of the FFCF from ab initio molecular dynamics and a density functional theory frequency map shows a very good agreement corroborating the correct characterization and assignment of the derived parameters.
Hydration and vibrational dynamics of betaine (N,N,N-trimethylglycine)
Li, Tanping; Cui, Yaowen; Mathaga, John; Kumar, Revati; Kuroda, Daniel G.
2015-01-01
Zwitterions are naturally occurring molecules that have a positive and a negative charge group in its structure and are of great importance in many areas of science. Here, the vibrational and hydration dynamics of the zwitterionic system betaine (N,N,N-trimethylglycine) is reported. The linear infrared spectrum of aqueous betaine exhibits an asymmetric band in the 1550-1700 cm−1 region of the spectrum. This band is attributed to the carboxylate asymmetric stretch of betaine. The potential of mean force computed from ab initio molecular dynamic simulations confirms that the two observed transitions of the linear spectrum are related to two different betaine conformers present in solution. A model of the experimental data using non-linear response theory agrees very well with a vibrational model comprising of two vibrational transitions. In addition, our modeling shows that spectral parameters such as the slope of the zeroth contour plot and central line slope are both sensitive to the presence of overlapping transitions. The vibrational dynamics of the system reveals an ultrafast decay of the vibrational population relaxation as well as the correlation of frequency-frequency correlation function (FFCF). A decay of ∼0.5 ps is observed for the FFCF correlation time and is attributed to the frequency fluctuations caused by the motions of water molecules in the solvation shell. The comparison of the experimental observations with simulations of the FFCF from ab initio molecular dynamics and a density functional theory frequency map shows a very good agreement corroborating the correct characterization and assignment of the derived parameters. PMID:26049458
NASA Astrophysics Data System (ADS)
Zimnyakov, Dmitry A.; Tuchin, Valery V.; Yodh, Arjun G.; Mishin, Alexey A.; Peretochkin, Igor S.
1998-04-01
Relationships between decorrelation and depolarization of coherent light scattered by disordered media are examined by using the conception of the photon paths distribution functions. Analysis of behavior of the autocorrelation functions of the scattered field fluctuations and their polarization properties allows us to introduce generalized parameter of scattering media such as specific correlation time. Determination of specific correlation time has been carried out for phantom scattering media (water suspensions of polystyrene spheres). Results of statistical, correlation and polarization analysis of static and dynamic speckle patterns carried out in the experiments with human sclera with artificially controlled optical transmittance are presented. Some possibilities of applications of such polarization- correlation technique for monitoring and visualization of non- single scattering tissue structures are discussed.
Vorberger, J; Chapman, D A
2018-01-01
We present a quantum theory for the dynamic structure factors in nonequilibrium, correlated, two-component systems such as plasmas or warm dense matter. The polarization function, which is needed as the input for the calculation of the structure factors, is calculated in nonequilibrium based on a perturbation expansion in the interaction strength. To make our theory applicable for x-ray scattering, a generalized Chihara decomposition for the total electron structure factor in nonequilibrium is derived. Examples are given and the influence of correlations and exchange on the structure and the x-ray-scattering spectrum are discussed for a model nonequilibrium distribution, as often encountered during laser heating of materials, as well as for two-temperature systems.
NASA Astrophysics Data System (ADS)
Vorberger, J.; Chapman, D. A.
2018-01-01
We present a quantum theory for the dynamic structure factors in nonequilibrium, correlated, two-component systems such as plasmas or warm dense matter. The polarization function, which is needed as the input for the calculation of the structure factors, is calculated in nonequilibrium based on a perturbation expansion in the interaction strength. To make our theory applicable for x-ray scattering, a generalized Chihara decomposition for the total electron structure factor in nonequilibrium is derived. Examples are given and the influence of correlations and exchange on the structure and the x-ray-scattering spectrum are discussed for a model nonequilibrium distribution, as often encountered during laser heating of materials, as well as for two-temperature systems.
Exact results for quench dynamics and defect production in a two-dimensional model.
Sengupta, K; Sen, Diptiman; Mondal, Shreyoshi
2008-02-22
We show that for a d-dimensional model in which a quench with a rate tau(-1) takes the system across a (d-m)-dimensional critical surface, the defect density scales as n approximately 1/tau(mnu/(znu+1)), where nu and z are the correlation length and dynamical critical exponents characterizing the critical surface. We explicitly demonstrate that the Kitaev model provides an example of such a scaling with d = 2 and m = nu = z = 1. We also provide the first example of an exact calculation of some multispin correlation functions for a two-dimensional model that can be used to determine the correlation between the defects. We suggest possible experiments to test our theory.
Chiacchiaretta, Piero; Cerritelli, Francesco; Bubbico, Giovanna; Perrucci, Mauro Gianni; Ferretti, Antonio
2018-01-01
Measurement of the dynamic coupling between spontaneous Blood Oxygenation Level Dependent (BOLD) and cerebral blood flow (CBF) fluctuations has been recently proposed as a method to probe resting-state brain physiology. Here we investigated how the dynamic BOLD-CBF coupling during resting-state is affected by aging. Fifteen young subjects and 17 healthy elderlies were studied using a dual-echo pCASL sequence. We found that the dynamic BOLD-CBF coupling was markedly reduced in elderlies, in particular in the left supramarginal gyrus, an area known to be involved in verbal working memory and episodic memory. Moreover, correcting for temporal shift between BOLD and CBF timecourses resulted in an increased correlation of the two signals for both groups, but with a larger increase for elderlies. However, even after temporal shift correction, a significantly decreased correlation was still observed for elderlies in the left supramarginal gyrus, indicating that the age-related dynamic BOLD-CBF uncoupling in this region is more pronounced and can be only partially explained with a simple time-shift between the two signals. Interestingly, these results were observed in a group of elderlies with normal cognitive functions, suggesting that the study of dynamic BOLD-CBF coupling during resting-state is a promising technique, potentially able to provide early biomarkers of functional changes in the aging brain.
Lynch, Michael S; Slenkamp, Karla M; Cheng, Mark; Khalil, Munira
2012-07-05
Obtaining a detailed description of photochemical reactions in solution requires measuring time-evolving structural dynamics of transient chemical species on ultrafast time scales. Time-resolved vibrational spectroscopies are sensitive probes of molecular structure and dynamics in solution. In this work, we develop doubly resonant fifth-order nonlinear visible-infrared spectroscopies to probe nonequilibrium vibrational dynamics among coupled high-frequency vibrations during an ultrafast charge transfer process using a heterodyne detection scheme. The method enables the simultaneous collection of third- and fifth-order signals, which respectively measure vibrational dynamics occurring on electronic ground and excited states on a femtosecond time scale. Our data collection and analysis strategy allows transient dispersed vibrational echo (t-DVE) and dispersed pump-probe (t-DPP) spectra to be extracted as a function of electronic and vibrational population periods with high signal-to-noise ratio (S/N > 25). We discuss how fifth-order experiments can measure (i) time-dependent anharmonic vibrational couplings, (ii) nonequilibrium frequency-frequency correlation functions, (iii) incoherent and coherent vibrational relaxation and transfer dynamics, and (iv) coherent vibrational and electronic (vibronic) coupling as a function of a photochemical reaction.
Response Functions for the Two-Dimensional Ultracold Fermi Gas: Dynamical BCS Theory and Beyond
NASA Astrophysics Data System (ADS)
Vitali, Ettore; Shi, Hao; Qin, Mingpu; Zhang, Shiwei
2017-12-01
Response functions are central objects in physics. They provide crucial information about the behavior of physical systems, and they can be directly compared with scattering experiments involving particles such as neutrons or photons. Calculations of such functions starting from the many-body Hamiltonian of a physical system are challenging and extremely valuable. In this paper, we focus on the two-dimensional (2D) ultracold Fermi atomic gas which has been realized experimentally. We present an application of the dynamical BCS theory to obtain response functions for different regimes of interaction strengths in the 2D gas with zero-range attractive interaction. We also discuss auxiliary-field quantum Monte Carlo (AFQMC) methods for the calculation of imaginary time correlations in these dilute Fermi gas systems. Illustrative results are given and comparisons are made between AFQMC and dynamical BCS theory results to assess the accuracy of the latter.
NASA Astrophysics Data System (ADS)
Schmitz, R.; Yordanov, S.; Butt, H. J.; Koynov, K.; Dünweg, B.
2011-12-01
Total internal reflection fluorescence cross-correlation spectroscopy (TIR-FCCS) has recently [S. Yordanov , Optics ExpressOPEXFF1094-408710.1364/OE.17.021149 17, 21149 (2009)] been established as an experimental method to probe hydrodynamic flows near surfaces, on length scales of tens of nanometers. Its main advantage is that fluorescence occurs only for tracer particles close to the surface, thus resulting in high sensitivity. However, the measured correlation functions provide only rather indirect information about the flow parameters of interest, such as the shear rate and the slip length. In the present paper, we show how to combine detailed and fairly realistic theoretical modeling of the phenomena by Brownian dynamics simulations with accurate measurements of the correlation functions, in order to establish a quantitative method to retrieve the flow properties from the experiments. First, Brownian dynamics is used to sample highly accurate correlation functions for a fixed set of model parameters. Second, these parameters are varied systematically by means of an importance-sampling Monte Carlo procedure in order to fit the experiments. This provides the optimum parameter values together with their statistical error bars. The approach is well suited for massively parallel computers, which allows us to do the data analysis within moderate computing times. The method is applied to flow near a hydrophilic surface, where the slip length is observed to be smaller than 10nm, and, within the limitations of the experiments and the model, indistinguishable from zero.
Troitzsch, R Z; Vass, H; Hossack, W J; Martyna, G J; Crain, J
2008-04-10
Free proline amino acid is a natural cryoprotectant expressed by numerous organisms under low-temperature stress. Previous reports have suggested that complex assemblies underlie its functional properties. We investigate here aqueous proline solutions as a function of temperature using combinations of Raman spectroscopy, Rayleigh-Brillouin light scattering, and molecular dynamics simulations with the view to revealing the molecular origins of the mixtures' functionality as a cryoprotectant. The evolution of the Brillouin frequency shifts and line widths with temperature shows that, above a critical proline concentration, the water-like dynamics is suppressed and viscoelastic behavior emerges: Here, the Landau-Placzek ratio also shows a temperature-independent maximum arising from concentration fluctuations. Molecular dynamics simulations reveal that the water-water correlations in the mixtures depend much more weakly on temperature than does bulk water. By contrast, the water OH Raman bands exhibit strong red-shifts on cooling similar to those seen in ices; however, no evidence of ice lattice phonons is observed in the low-frequency spectrum. We attribute this primarily to enhanced proline-water hydrogen bonding. In general, the picture that emerges is that aqueous proline is a heterogeneous mixture on molecular length scales (characterized by significant concentration fluctuations rather than well-defined aggregates). Simulations reveal that proline also appears to suppress the normal dependence of water structure on temperature and preserves the ambient-temperature correlations even in very cold solutions. The water structure in cold proline solutions therefore appears to be similar to that at a higher effective temperature. This, coupled with the emergence of glassy dynamics offers a molecular explanation for the functional properties of proline as a cryoprotectant without the need to invoke previously proposed complex aggregates.
Ohno, Yoshiharu; Seki, Shinichiro; Koyama, Hisanobu; Yoshikawa, Takeshi; Matsumoto, Sumiaki; Takenaka, Daisuke; Kassai, Yoshimori; Yui, Masao; Sugimura, Kazuro
2015-08-01
To compare predictive capabilities of non-contrast-enhanced (CE)- and dynamic CE-perfusion MRIs, thin-section multidetector computed tomography (CT) (MDCT), and perfusion scan for postoperative lung function in non-small cell lung cancer (NSCLC) patients. Sixty consecutive pathologically diagnosed NSCLC patients were included and prospectively underwent thin-section MDCT, non-CE-, and dynamic CE-perfusion MRIs and perfusion scan, and had their pre- and postoperative forced expiratory volume in one second (FEV1 ) measured. Postoperative percent FEV1 (po%FEV1 ) was then predicted from the fractional lung volume determined on semiquantitatively assessed non-CE- and dynamic CE-perfusion MRIs, from the functional lung volumes determined on quantitative CT, from the number of segments observed on qualitative CT, and from uptakes detected on perfusion scans within total and resected lungs. Predicted po%FEV1 s were then correlated with actual po%FEV1 s, which were %FEV1 s measured postoperatively. The limits of agreement were also determined. All predicted po%FEV1 s showed significant correlation (0.73 ≤ r ≤ 0.93, P < 0.0001) and limits of agreement with actual po%FEV1 (non-CE-perfusion MRI: 0.3 ± 10.0%, dynamic CE-perfusion MRI: 1.0 ± 10.8%, perfusion scan: 2.2 ± 14.1%, quantitative CT: 1.2 ± 9.0%, qualitative CT: 1.5 ± 10.2%). Non-CE-perfusion MRI may be able to predict postoperative lung function more accurately than qualitatively assessed MDCT and perfusion scan. © 2014 Wiley Periodicals, Inc.
NASA Astrophysics Data System (ADS)
Bora, Ram Prasad; Prabhakar, Rajeev
2009-10-01
In this study, diffusion constants [translational (DT) and rotational (DR)], correlation times [rotational (τrot) and internal (τint)], and the intramolecular order parameters (S2) of the Alzheimer amyloid-β peptides Aβ40 and Aβ42 have been calculated from 150 ns molecular dynamics simulations in aqueous solution. The computed parameters have been compared with the experimentally measured values. The calculated DT of 1.61×10-6 cm2/s and 1.43×10-6 cm2/s for Aβ40 and Aβ42, respectively, at 300 K was found to follow the correct trend defined by the Debye-Stokes-Einstein relation that its value should decrease with the increase in the molecular weight. The estimated DR for Aβ40 and Aβ42 at 300 K are 0.085 and 0.071 ns-1, respectively. The rotational (Crot(t)) and internal (Cint(t)) correlation functions of Aβ40 and Aβ42 were observed to decay at nano- and picosecond time scales, respectively. The significantly different time decays of these functions validate the factorization of the total correlation function (Ctot(t)) of Aβ peptides into Crot(t) and Cint(t). At both short and long time scales, the Clore-Szabo model that was used as Cint(t) provided the best behavior of Ctot(t) for both Aβ40 and Aβ42. In addition, an effective rotational correlation time of Aβ40 is also computed at 18 °C and the computed value (2.30 ns) is in close agreement with the experimental value of 2.45 ns. The computed S2 parameters for the central hydrophobic core, the loop region, and C-terminal domains of Aβ40 and Aβ42 are in accord with the previous studies.
Thermal dynamics on the lattice with exponentially improved accuracy
NASA Astrophysics Data System (ADS)
Pawlowski, Jan M.; Rothkopf, Alexander
2018-03-01
We present a novel simulation prescription for thermal quantum fields on a lattice that operates directly in imaginary frequency space. By distinguishing initial conditions from quantum dynamics it provides access to correlation functions also outside of the conventional Matsubara frequencies ωn = 2 πnT. In particular it resolves their frequency dependence between ω = 0 and ω1 = 2 πT, where the thermal physics ω ∼ T of e.g. transport phenomena is dominantly encoded. Real-time spectral functions are related to these correlators via an integral transform with rational kernel, so that their unfolding from the novel simulation data is exponentially improved compared to standard Euclidean simulations. We demonstrate this improvement within a non-trivial 0 + 1-dimensional quantum mechanical toy-model and show that spectral features inaccessible in standard Euclidean simulations are quantitatively captured.
Lasky, Jesse R; Uriarte, María; Boukili, Vanessa K; Chazdon, Robin L
2014-04-15
Interspecific differences in relative fitness can cause local dominance by a single species. However, stabilizing interspecific niche differences can promote local diversity. Understanding these mechanisms requires that we simultaneously quantify their effects on demography and link these effects to community dynamics. Successional forests are ideal systems for testing assembly theory because they exhibit rapid community assembly. Here, we leverage functional trait and long-term demographic data to build spatially explicit models of successional community dynamics of lowland rainforests in Costa Rica. First, we ask what the effects and relative importance of four trait-mediated community assembly processes are on tree survival, a major component of fitness. We model trait correlations with relative fitness differences that are both density-independent and -dependent in addition to trait correlations with stabilizing niche differences. Second, we ask how the relative importance of these trait-mediated processes relates to successional changes in functional diversity. Tree dynamics were more strongly influenced by trait-related interspecific variation in average survival than trait-related responses to neighbors, with wood specific gravity (WSG) positively correlated with greater survival. Our findings also suggest that competition was mediated by stabilizing niche differences associated with specific leaf area (SLA) and leaf dry matter content (LDMC). These drivers of individual-level survival were reflected in successional shifts to higher SLA and LDMC diversity but lower WSG diversity. Our study makes significant advances to identifying the links between individual tree performance, species functional traits, and mechanisms of tropical forest succession.
Nonequilibrium dynamic critical scaling of the quantum Ising chain.
Kolodrubetz, Michael; Clark, Bryan K; Huse, David A
2012-07-06
We solve for the time-dependent finite-size scaling functions of the one-dimensional transverse-field Ising chain during a linear-in-time ramp of the field through the quantum critical point. We then simulate Mott-insulating bosons in a tilted potential, an experimentally studied system in the same equilibrium universality class, and demonstrate that universality holds for the dynamics as well. We find qualitatively athermal features of the scaling functions, such as negative spin correlations, and we show that they should be robustly observable within present cold atom experiments.
Molecular dynamics simulations of dense plasmas
DOE Office of Scientific and Technical Information (OSTI.GOV)
Collins, L.A.; Kress, J.D.; Kwon, I.
1993-12-31
We have performed quantum molecular dynamics simulations of hot, dense plasmas of hydrogen over a range of temperatures(0.1-5eV) and densities(0.0625-5g/cc). We determine the forces quantum mechanically from density functional, extended Huckel, and tight binding techniques and move the nuclei according to the classical equations of motion. We determine pair-correlation functions, diffusion coefficients, and electrical conductivities. We find that many-body effects predominate in this regime. We begin to obtain agreement with the OCP and Thomas-Fermi models only at the higher temperatures and densities.
Temporal cross-correlation asymmetry and departure from equilibrium in a bistable chemical system.
Bianca, C; Lemarchand, A
2014-06-14
This paper aims at determining sustained reaction fluxes in a nonlinear chemical system driven in a nonequilibrium steady state. The method relies on the computation of cross-correlation functions for the internal fluctuations of chemical species concentrations. By employing Langevin-type equations, we derive approximate analytical formulas for the cross-correlation functions associated with nonlinear dynamics. Kinetic Monte Carlo simulations of the chemical master equation are performed in order to check the validity of the Langevin equations for a bistable chemical system. The two approaches are found in excellent agreement, except for critical parameter values where the bifurcation between monostability and bistability occurs. From the theoretical point of view, the results imply that the behavior of cross-correlation functions cannot be exploited to measure sustained reaction fluxes in a specific nonlinear system without the prior knowledge of the associated chemical mechanism and the rate constants.
Maraga, Anna; Chiocchetta, Alessio; Mitra, Aditi; Gambassi, Andrea
2015-10-01
The nonequilibrium dynamics of an isolated quantum system after a sudden quench to a dynamical critical point is expected to be characterized by scaling and universal exponents due to the absence of time scales. We explore these features for a quench of the parameters of a Hamiltonian with O(N) symmetry, starting from a ground state in the disordered phase. In the limit of infinite N, the exponents and scaling forms of the relevant two-time correlation functions can be calculated exactly. Our analytical predictions are confirmed by the numerical solution of the corresponding equations. Moreover, we find that the same scaling functions, yet with different exponents, also describe the coarsening dynamics for quenches below the dynamical critical point.
NASA Astrophysics Data System (ADS)
Giorgini, Maria Grazia; Arcioni, Alberto; Polizzi, Ciro; Musso, Maurizio; Ottaviani, Paolo
2004-03-01
We have investigated the Raman profiles of the ν(C≡N) and ν(C=O) vibrational modes of the nematic liquid crystal ME6N (4-cyanophenyl-4'-hexylbenzoate) in the isotropic phase at different temperatures and used them as probes of the dynamics and structural organization of this liquid. The vibrational time correlation functions of the ν(C≡N) mode, rather adequately interpreted within the assumption of exponential modulation function (the Kubo-Rothschild theory), indicate that the system experiences an intermediate dynamical regime that gets only slightly faster with increasing temperature. However, this theory fails in predicting the non-exponential behavior that the time correlation functions manifest in the long time range (t>3 ps). For this reason we have additionally approached the interpretation of vibrational correlation functions in terms of the theory formulated by Rothschild and co-workers for locally structured liquids. The application of this theory reveals that the molecular dynamics in this liquid crystal in the isotropic phase is that deriving from a distribution of differently sized clusters, which narrows as the temperature increases. Even at the highest temperature reached in this study (87 °C above the nematic-isotropic transition), the liquid has not yet achieved the structure of the simple liquid and the dynamics has not reached the limit of the single channel process. The vibrational and orientational relaxations occur in very different time scales. The temperature independence of the orientational dynamics in the whole range from 55 °C to 135 °C has been referred to the nonhydrodynamic behavior of the system, arising when local pseudonematic structures persist for times longer than the orientational relaxation. The occurrence of the process of resonant vibrational energy transfer between the C=O groups of adjacent molecules has been revealed in the isotropic phase by a slightly positive Raman noncoincidence effect in the band associated with the ν(C=O) mode. A qualitative interpretation is tentatively given in terms of partial cancellation of contributions deriving from structures having opposite orientations of their C=O groups.
Quantum dynamics modeled by interacting trajectories
NASA Astrophysics Data System (ADS)
Cruz-Rodríguez, L.; Uranga-Piña, L.; Martínez-Mesa, A.; Meier, C.
2018-03-01
We present quantum dynamical simulations based on the propagation of interacting trajectories where the effect of the quantum potential is mimicked by effective pseudo-particle interactions. The method is applied to several quantum systems, both for bound and scattering problems. For the bound systems, the quantum ground state density and zero point energy are shown to be perfectly obtained by the interacting trajectories. In the case of time-dependent quantum scattering, the Eckart barrier and uphill ramp are considered, with transmission coefficients in very good agreement with standard quantum calculations. Finally, we show that via wave function synthesis along the trajectories, correlation functions and energy spectra can be obtained based on the dynamics of interacting trajectories.
NASA Astrophysics Data System (ADS)
van Roekeghem, Ambroise; Richard, Pierre; Shi, Xun; Wu, Shangfei; Zeng, Lingkun; Saparov, Bayrammurad; Ohtsubo, Yoshiyuki; Qian, Tian; Sefat, Athena S.; Biermann, Silke; Ding, Hong
2016-06-01
We present a study of the tetragonal to collapsed-tetragonal transition of CaFe2As2 using angle-resolved photoemission spectroscopy and dynamical mean field theory-based electronic structure calculations. We observe that the collapsed-tetragonal phase exhibits reduced correlations and a higher coherence temperature due to the stronger Fe-As hybridization. Furthermore, a comparison of measured photoemission spectra and theoretical spectral functions shows that momentum-dependent corrections to the density functional band structure are essential for the description of low-energy quasiparticle dispersions. We introduce those using the recently proposed combined "screened exchange + dynamical mean field theory" scheme.
Zecchin, Chiara; Facchinetti, Andrea; Sparacino, Giovanni; Dalla Man, Chiara; Manohar, Chinmay; Levine, James A; Basu, Ananda; Kudva, Yogish C; Cobelli, Claudio
2013-10-01
In type 1 diabetes mellitus (T1DM), physical activity (PA) lowers the risk of cardiovascular complications but hinders the achievement of optimal glycemic control, transiently boosting insulin action and increasing hypoglycemia risk. Quantitative investigation of relationships between PA-related signals and glucose dynamics, tracked using, for example, continuous glucose monitoring (CGM) sensors, have been barely explored. In the clinic, 20 control and 19 T1DM subjects were studied for 4 consecutive days. They underwent low-intensity PA sessions daily. PA was tracked by the PA monitoring system (PAMS), a system comprising accelerometers and inclinometers. Variations on glucose dynamics were tracked estimating first- and second-order time derivatives of glucose concentration from CGM via Bayesian smoothing. Short-time effects of PA on glucose dynamics were quantified through the partial correlation function in the interval (0, 60 min) after starting PA. Correlation of PA with glucose time derivatives is evident. In T1DM, the negative correlation with the first-order glucose time derivative is maximal (absolute value) after 15 min of PA, whereas the positive correlation is maximal after 40-45 min. The negative correlation between the second-order time derivative and PA is maximal after 5 min, whereas the positive correlation is maximal after 35-40 min. Control subjects provided similar results but with positive and negative correlation peaks anticipated of 5 min. Quantitative information on correlation between mild PA and short-term glucose dynamics was obtained. This represents a preliminary important step toward incorporation of PA information in more realistic physiological models of the glucose-insulin system usable in T1DM simulators, in development of closed-loop artificial pancreas control algorithms, and in CGM-based prediction algorithms for generation of hypoglycemic alerts.
Bhadra, Pratiti; Pal, Debnath
2017-04-01
Dynamics is integral to the function of proteins, yet the use of molecular dynamics (MD) simulation as a technique remains under-explored for molecular function inference. This is more important in the context of genomics projects where novel proteins are determined with limited evolutionary information. Recently we developed a method to match the query protein's flexible segments to infer function using a novel approach combining analysis of residue fluctuation-graphs and auto-correlation vectors derived from coarse-grained (CG) MD trajectory. The method was validated on a diverse dataset with sequence identity between proteins as low as 3%, with high function-recall rates. Here we share its implementation as a publicly accessible web service, named DynFunc (Dynamics Match for Function) to query protein function from ≥1 µs long CG dynamics trajectory information of protein subunits. Users are provided with the custom-developed coarse-grained molecular mechanics (CGMM) forcefield to generate the MD trajectories for their protein of interest. On upload of trajectory information, the DynFunc web server identifies specific flexible regions of the protein linked to putative molecular function. Our unique application does not use evolutionary information to infer molecular function from MD information and can, therefore, work for all proteins, including moonlighting and the novel ones, whenever structural information is available. Our pipeline is expected to be of utility to all structural biologists working with novel proteins and interested in moonlighting functions. Copyright © 2017 Elsevier Ltd. All rights reserved.
Exploring the Dynamics of Cell Processes through Simulations of Fluorescence Microscopy Experiments
Angiolini, Juan; Plachta, Nicolas; Mocskos, Esteban; Levi, Valeria
2015-01-01
Fluorescence correlation spectroscopy (FCS) methods are powerful tools for unveiling the dynamical organization of cells. For simple cases, such as molecules passively moving in a homogeneous media, FCS analysis yields analytical functions that can be fitted to the experimental data to recover the phenomenological rate parameters. Unfortunately, many dynamical processes in cells do not follow these simple models, and in many instances it is not possible to obtain an analytical function through a theoretical analysis of a more complex model. In such cases, experimental analysis can be combined with Monte Carlo simulations to aid in interpretation of the data. In response to this need, we developed a method called FERNET (Fluorescence Emission Recipes and Numerical routines Toolkit) based on Monte Carlo simulations and the MCell-Blender platform, which was designed to treat the reaction-diffusion problem under realistic scenarios. This method enables us to set complex geometries of the simulation space, distribute molecules among different compartments, and define interspecies reactions with selected kinetic constants, diffusion coefficients, and species brightness. We apply this method to simulate single- and multiple-point FCS, photon-counting histogram analysis, raster image correlation spectroscopy, and two-color fluorescence cross-correlation spectroscopy. We believe that this new program could be very useful for predicting and understanding the output of fluorescence microscopy experiments. PMID:26039162
NASA Astrophysics Data System (ADS)
Majka, M.; Góra, P. F.
2016-10-01
While the origins of temporal correlations in Langevin dynamics have been thoroughly researched, the understanding of spatially correlated noise (SCN) is rather incomplete. In particular, very little is known about the relation between friction and SCN. In this article, starting from the microscopic, deterministic model, we derive the analytical formula for the spatial correlation function in the particle-bath interactions. This expression shows that SCN is the inherent component of binary mixtures, originating from the effective (entropic) interactions. Further, employing this spatial correlation function, we postulate the thermodynamically consistent Langevin equation driven by the Gaussian SCN and calculate the adequate fluctuation-dissipation relation. The thermodynamical consistency is achieved by introducing the spatially variant friction coefficient, which can be also derived analytically. This coefficient exhibits a number of intriguing properties, e.g., the singular behavior for certain types of interactions. Eventually, we apply this new theory to the system of two charged particles in the presence of counter-ions. Such particles interact via the screened-charge Yukawa potential and the inclusion of SCN leads to the emergence of the anomalous frictionless regime. In this regime the particles can experience active propulsion leading to the transient attraction effect. This effect suggests a nonequilibrium mechanism facilitating the molecular binding of the like-charged particles.
Dielectric Properties of Poly(ethylene oxide) from Molecular Dynamics Simulations
NASA Technical Reports Server (NTRS)
Smith, Grant D.
1994-01-01
The order, conformations and dynamics of poly(oxyethylene) (POE) melts have been investigated through molecular dynamics simulations. The potential energy functions were determined from detailed ab initio electronic structure calculations of the conformational energies of the model molecules 1,2-dimethoxyethane (DME) and diethylether. The x-ray structure factor for POE from simulation will be compared to experiment. In terms of conformation, simulations reveal that chains are extended in the melt relative to isolated chains due to the presence of strong intermolecular O...H interactions, which occur at the expense of intramolecular O...H interactions. Conformational dynamics about the C-C bond were found to be significantly faster than in polymethylene, while conformational dynamics about the C-O bond even faster than the C-C dynamics. The faster local dynamics in POE relative to polymethylene is consistent with C-13 NMR spin-lattice relaxation experiments. Conformational transitions showed significant second-neighbor correlation, as was found for polymethylene. This correlation of transitions with C-C neighbors was found to be reduced relative to C-O neighbors. Dielectric relaxation from simulation will also be compared with experiment.
Dynamics of a magnetic active Brownian particle under a uniform magnetic field.
Vidal-Urquiza, Glenn C; Córdova-Figueroa, Ubaldo M
2017-11-01
The dynamics of a magnetic active Brownian particle undergoing three-dimensional Brownian motion, both translation and rotation, under the influence of a uniform magnetic field is investigated. The particle self-propels at a constant speed along its magnetic dipole moment, which reorients due to the interplay between Brownian and magnetic torques, quantified by the Langevin parameter α. In this work, the time-dependent active diffusivity and the crossover time (τ^{cross})-from ballistic to diffusive regimes-are calculated through the time-dependent correlation function of the fluctuations of the propulsion direction. The results reveal that, for any value of α, the particle undergoes a directional (or ballistic) propulsive motion at very short times (t≪τ^{cross}). In this regime, the correlation function decreases linearly with time, and the active diffusivity increases with it. It the opposite time limit (t≫τ^{cross}), the particle moves in a purely diffusive regime with a correlation function that decays asymptotically to zero and an active diffusivity that reaches a constant value equal to the long-time active diffusivity of the particle. As expected in the absence of a magnetic field (α=0), the crossover time is equal to the characteristic time scale for rotational diffusion, τ_{rot}. In the presence of a magnetic field (α>0), the correlation function, the active diffusivity, and the crossover time decrease with increasing α. The magnetic field regulates the regimes of propulsion of the particle. Here, the field reduces the period of time at which the active particle undergoes a directional motion. Consequently, the active particle rapidly reaches a diffusive regime at τ^{cross}≪τ_{rot}. In the limit of weak fields (α≪1), the crossover time decreases quadratically with α, while in the limit of strong fields (α≫1) it decays asymptotically as α^{-1}. The results are in excellent agreement with those obtained by Brownian dynamics simulations.
Dynamics of a magnetic active Brownian particle under a uniform magnetic field
NASA Astrophysics Data System (ADS)
Vidal-Urquiza, Glenn C.; Córdova-Figueroa, Ubaldo M.
2017-11-01
The dynamics of a magnetic active Brownian particle undergoing three-dimensional Brownian motion, both translation and rotation, under the influence of a uniform magnetic field is investigated. The particle self-propels at a constant speed along its magnetic dipole moment, which reorients due to the interplay between Brownian and magnetic torques, quantified by the Langevin parameter α . In this work, the time-dependent active diffusivity and the crossover time (τcross)—from ballistic to diffusive regimes—are calculated through the time-dependent correlation function of the fluctuations of the propulsion direction. The results reveal that, for any value of α , the particle undergoes a directional (or ballistic) propulsive motion at very short times (t ≪τcross ). In this regime, the correlation function decreases linearly with time, and the active diffusivity increases with it. It the opposite time limit (t ≫τcross ), the particle moves in a purely diffusive regime with a correlation function that decays asymptotically to zero and an active diffusivity that reaches a constant value equal to the long-time active diffusivity of the particle. As expected in the absence of a magnetic field (α =0 ), the crossover time is equal to the characteristic time scale for rotational diffusion, τrot. In the presence of a magnetic field (α >0 ), the correlation function, the active diffusivity, and the crossover time decrease with increasing α . The magnetic field regulates the regimes of propulsion of the particle. Here, the field reduces the period of time at which the active particle undergoes a directional motion. Consequently, the active particle rapidly reaches a diffusive regime at τcross≪τrot . In the limit of weak fields (α ≪1 ), the crossover time decreases quadratically with α , while in the limit of strong fields (α ≫1 ) it decays asymptotically as α-1. The results are in excellent agreement with those obtained by Brownian dynamics simulations.
Boundary Information Inflow Enhances Correlation in Flocking
NASA Astrophysics Data System (ADS)
Cavagna, Andrea; Giardina, Irene; Ginelli, Francesco
2013-04-01
The most conspicuous trait of collective animal behavior is the emergence of highly ordered structures. Less obvious to the eye, but perhaps more profound a signature of self-organization, is the presence of long-range spatial correlations. Experimental data on starling flocks in 3D show that the exponent ruling the decay of the velocity correlation function, C(r)˜1/rγ, is extremely small, γ≪1. This result can neither be explained by equilibrium field theory nor by off-equilibrium theories and simulations of active systems. Here, by means of numerical simulations and theoretical calculations, we show that a dynamical field applied to the boundary of a set of Heisenberg spins on a 3D lattice gives rise to a vanishing exponent γ, as in starling flocks. The effect of the dynamical field is to create an information inflow from border to bulk that triggers long-range spin-wave modes, thus giving rise to an anomalously long-ranged correlation. The biological origin of this phenomenon can be either exogenous—information produced by environmental perturbations is transferred from boundary to bulk of the flock—or endogenous—the flock keeps itself in a constant state of dynamical excitation that is beneficial to correlation and collective response.
NASA Astrophysics Data System (ADS)
Gabardi, Silvia; Caravati, Sebastiano; Los, Jan H.; Kühne, Thomas D.; Bernasconi, Marco
2016-05-01
We have investigated the structural, vibrational, and electronic properties of the amorphous phase of InSb and In3SbTe2 compounds of interest for applications in phase change non-volatile memories. Models of the amorphous phase have been generated by quenching from the melt by molecular dynamics simulations based on density functional theory. In particular, we have studied the dependence of the structural properties on the choice of the exchange-correlation functional. It turns out that the use of the Becke-Lee-Yang-Parr functional provides models with a much larger fraction of In atoms in a tetrahedral bonding geometry with respect to previous results obtained with the most commonly used Perdew-Becke-Ernzerhof functional. This outcome is at odd with the properties of Ge2Sb2Te5 phase change compound for which the two exchange-correlation functionals yield very similar results on the structure of the amorphous phase.
Gabardi, Silvia; Caravati, Sebastiano; Los, Jan H; Kühne, Thomas D; Bernasconi, Marco
2016-05-28
We have investigated the structural, vibrational, and electronic properties of the amorphous phase of InSb and In3SbTe2 compounds of interest for applications in phase change non-volatile memories. Models of the amorphous phase have been generated by quenching from the melt by molecular dynamics simulations based on density functional theory. In particular, we have studied the dependence of the structural properties on the choice of the exchange-correlation functional. It turns out that the use of the Becke-Lee-Yang-Parr functional provides models with a much larger fraction of In atoms in a tetrahedral bonding geometry with respect to previous results obtained with the most commonly used Perdew-Becke-Ernzerhof functional. This outcome is at odd with the properties of Ge2Sb2Te5 phase change compound for which the two exchange-correlation functionals yield very similar results on the structure of the amorphous phase.
Minati, Ludovico; Chiesa, Pietro; Tabarelli, Davide; D'Incerti, Ludovico
2015-01-01
In this paper, the topographical relationship between functional connectivity (intended as inter-regional synchronization), spectral and non-linear dynamical properties across cortical areas of the healthy human brain is considered. Based upon functional MRI acquisitions of spontaneous activity during wakeful idleness, node degree maps are determined by thresholding the temporal correlation coefficient among all voxel pairs. In addition, for individual voxel time-series, the relative amplitude of low-frequency fluctuations and the correlation dimension (D2), determined with respect to Fourier amplitude and value distribution matched surrogate data, are measured. Across cortical areas, high node degree is associated with a shift towards lower frequency activity and, compared to surrogate data, clearer saturation to a lower correlation dimension, suggesting presence of non-linear structure. An attempt to recapitulate this relationship in a network of single-transistor oscillators is made, based on a diffusive ring (n = 90) with added long-distance links defining four extended hub regions. Similarly to the brain data, it is found that oscillators in the hub regions generate signals with larger low-frequency cycle amplitude fluctuations and clearer saturation to a lower correlation dimension compared to surrogates. The effect emerges more markedly close to criticality. The homology observed between the two systems despite profound differences in scale, coupling mechanism and dynamics appears noteworthy. These experimental results motivate further investigation into the heterogeneity of cortical non-linear dynamics in relation to connectivity and underline the ability for small networks of single-transistor oscillators to recreate collective phenomena arising in much more complex biological systems, potentially representing a future platform for modelling disease-related changes. PMID:25833429
DOE Office of Scientific and Technical Information (OSTI.GOV)
Minati, Ludovico, E-mail: lminati@ieee.org, E-mail: ludovico.minati@unitn.it, E-mail: lminati@istituto-besta.it; Center for Mind/Brain Sciences, University of Trento, Trento; Chiesa, Pietro
In this paper, the topographical relationship between functional connectivity (intended as inter-regional synchronization), spectral and non-linear dynamical properties across cortical areas of the healthy human brain is considered. Based upon functional MRI acquisitions of spontaneous activity during wakeful idleness, node degree maps are determined by thresholding the temporal correlation coefficient among all voxel pairs. In addition, for individual voxel time-series, the relative amplitude of low-frequency fluctuations and the correlation dimension (D{sub 2}), determined with respect to Fourier amplitude and value distribution matched surrogate data, are measured. Across cortical areas, high node degree is associated with a shift towards lower frequencymore » activity and, compared to surrogate data, clearer saturation to a lower correlation dimension, suggesting presence of non-linear structure. An attempt to recapitulate this relationship in a network of single-transistor oscillators is made, based on a diffusive ring (n = 90) with added long-distance links defining four extended hub regions. Similarly to the brain data, it is found that oscillators in the hub regions generate signals with larger low-frequency cycle amplitude fluctuations and clearer saturation to a lower correlation dimension compared to surrogates. The effect emerges more markedly close to criticality. The homology observed between the two systems despite profound differences in scale, coupling mechanism and dynamics appears noteworthy. These experimental results motivate further investigation into the heterogeneity of cortical non-linear dynamics in relation to connectivity and underline the ability for small networks of single-transistor oscillators to recreate collective phenomena arising in much more complex biological systems, potentially representing a future platform for modelling disease-related changes.« less
Pairing-induced speedup of nuclear spontaneous fission
NASA Astrophysics Data System (ADS)
Sadhukhan, Jhilam; Dobaczewski, J.; Nazarewicz, W.; Sheikh, J. A.; Baran, A.
2014-12-01
Background: Collective inertia is strongly influenced at the level crossing at which the quantum system changes its microscopic configuration diabatically. Pairing correlations tend to make the large-amplitude nuclear collective motion more adiabatic by reducing the effect of these configuration changes. Competition between pairing and level crossing is thus expected to have a profound impact on spontaneous fission lifetimes. Purpose: To elucidate the role of nucleonic pairing on spontaneous fission, we study the dynamic fission trajectories of 264Fm and 240Pu using the state-of-the-art self-consistent framework. Methods: We employ the superfluid nuclear density functional theory with the Skyrme energy density functional SkM* and a density-dependent pairing interaction. Along with shape variables, proton and neutron pairing correlations are taken as collective coordinates. The collective inertia tensor is calculated within the nonperturbative cranking approximation. The fission paths are obtained by using the least action principle in a four-dimensional collective space of shape and pairing coordinates. Results: Pairing correlations are enhanced along the minimum-action fission path. For the symmetric fission of 264Fm, where the effect of triaxiality on the fission barrier is large, the geometry of the fission pathway in the space of the shape degrees of freedom is weakly impacted by pairing. This is not the case for 240Pu, where pairing fluctuations restore the axial symmetry of the dynamic fission trajectory. Conclusions: The minimum-action fission path is strongly impacted by nucleonic pairing. In some cases, the dynamical coupling between shape and pairing degrees of freedom can lead to a dramatic departure from the static picture. Consequently, in the dynamical description of nuclear fission, particle-particle correlations should be considered on the same footing as those associated with shape degrees of freedom.
Pairing-induced speedup of nuclear spontaneous fission
Sadhukhan, Jhilam; Dobaczewski, J.; Nazarewicz, W.; ...
2014-12-22
Collective inertia is strongly influenced at the level crossing at which the quantum system changes its microscopic configuration diabatically. Pairing correlations tend to make the large-amplitude nuclear collective motion more adiabatic by reducing the effect of these configuration changes. Competition between pairing and level crossing is thus expected to have a profound impact on spontaneous fission lifetimes. To elucidate the role of nucleonic pairing on spontaneous fission, we study the dynamic fission trajectories of 264Fm and 240Pu using the state-of-the-art self-consistent framework. We employ the superfluid nuclear density functional theory with the Skyrme energy density functional SkM* and a density-dependentmore » pairing interaction. Along with shape variables, proton and neutron pairing correlations are taken as collective coordinates. The collective inertia tensor is calculated within the nonperturbative cranking approximation. The fission paths are obtained by using the least action principle in a four-dimensional collective space of shape and pairing coordinates. Pairing correlations are enhanced along the minimum-action fission path. For the symmetric fission of 264Fm, where the effect of triaxiality on the fission barrier is large, the geometry of the fission pathway in the space of the shape degrees of freedom is weakly impacted by pairing. This is not the case for 240Pu, where pairing fluctuations restore the axial symmetry of the dynamic fission trajectory. The minimum-action fission path is strongly impacted by nucleonic pairing. In some cases, the dynamical coupling between shape and pairing degrees of freedom can lead to a dramatic departure from the static picture. As a result, in the dynamical description of nuclear fission, particle-particle correlations should be considered on the same footing as those associated with shape degrees of freedom.« less
A DYNAMIC DENSITY FUNCTIONAL THEORY APPROACH TO DIFFUSION IN WHITE DWARFS AND NEUTRON STAR ENVELOPES
DOE Office of Scientific and Technical Information (OSTI.GOV)
Diaw, A.; Murillo, M. S.
2016-09-20
We develop a multicomponent hydrodynamic model based on moments of the Born–Bogolyubov–Green–Kirkwood–Yvon hierarchy equations for physical conditions relevant to astrophysical plasmas. These equations incorporate strong correlations through a density functional theory closure, while transport enters through a relaxation approximation. This approach enables the introduction of Coulomb coupling correction terms into the standard Burgers equations. The diffusive currents for these strongly coupled plasmas is self-consistently derived. The settling of impurities and its impact on cooling can be greatly affected by strong Coulomb coupling, which we show can be quantified using the direct correlation function.
Winkler, Pamina M; Regmi, Raju; Flauraud, Valentin; Brugger, Jürgen; Rigneault, Hervé; Wenger, Jérôme; García-Parajo, María F
2018-01-04
The plasma membrane of living cells is compartmentalized at multiple spatial scales ranging from the nano- to the mesoscale. This nonrandom organization is crucial for a large number of cellular functions. At the nanoscale, cell membranes organize into dynamic nanoassemblies enriched by cholesterol, sphingolipids, and certain types of proteins. Investigating these nanoassemblies known as lipid rafts is of paramount interest in fundamental cell biology. However, this goal requires simultaneous nanometer spatial precision and microsecond temporal resolution, which is beyond the reach of common microscopes. Optical antennas based on metallic nanostructures efficiently enhance and confine light into nanometer dimensions, breaching the diffraction limit of light. In this Perspective, we discuss recent progress combining optical antennas with fluorescence correlation spectroscopy (FCS) to monitor microsecond dynamics at nanoscale spatial dimensions. These new developments offer numerous opportunities to investigate lipid and protein dynamics in both mimetic and native biological membranes.
Martini, K; Gygax, C M; Benden, C; Morgan, A R; Parker, G J M; Frauenfelder, T
2018-04-13
To demonstrate, in patients with cystic fibrosis (CF), the correlation between three-dimensional dynamic oxygen-enhanced magnetic resonance imaging (OE-MRI) measurements and computed tomography Brody score (CF-CT) and lung function testing (LFT). Twenty-one patients (median age, 25 years; female, n = 8) with a range of CF lung disease and five healthy volunteers (median age, 31 years; female, n = 2) underwent OE-MRI performed on a 1.5-T MRI scanner. Coronal volumes were acquired while patients alternately breathed room air and 100% oxygen. Pre-oxygen T 1 was measured. Dynamic series of T 1 -weighted volumes were then obtained while breathing oxygen. T 1 -parameter maps were generated and the following OE-MRI parameters were measured: oxygen uptake (ΔPO 2max ), wash-in time and wash-out time. High-resolution CT and LFT were performed. The relationship between CF-CT, LFT and OE-MRI parameters were evaluated using Pearson correlation for the whole lung and regionally. Mean CF-CT was 24.1±17.1. Mean ΔPO 2max and mean wash-in as well as skewness of wash-out showed significant correlation with CF-CT (ΔPO 2max : r = -0.741, p < 0.001; mean wash-in: r = 0.501, p = 0.017; skewness of wash-out: r = 0.597, p = 0.001). There was significant correlation for the whole lung and regionally between LFT parameters and OE-MR (ΔPO 2max : r = 0.718, p < 0.001; wash-in: r = -0.576, p = 0.003; wash-out skewness: r = -0.552, p = 0.004). Functional lung imaging using OE-MRI has the capability to assess the severity of CF lung disease and shows a significant correlation with LFT and CF-CT. • Oxygen-enhanced MRI might play a future role in evaluation and follow-up of cystic fibrosis. • Heterogeneity of parameter maps reflects localised functional impairment in cystic fibrosis. • Avoidance of cumulative radiation burden in CF is feasible using OE-MRI.
Levashov, V A; Stepanov, M G
2016-01-01
Considerations of local atomic-level stresses associated with each atom represent a particular approach to address structures of disordered materials at the atomic level. We studied structural correlations in a two-dimensional model liquid using molecular dynamics simulations in the following way. We diagonalized the atomic-level stress tensor of every atom and investigated correlations between the eigenvalues and orientations of the eigenvectors of different atoms as a function of distance between them. It is demonstrated that the suggested approach can be used to characterize structural correlations in disordered materials. In particular, we found that changes in the stress correlation functions on decrease of temperature are the most pronounced for the pairs of atoms with separation distance that corresponds to the first minimum in the pair density function. We also show that the angular dependencies of the stress correlation functions previously reported by Wu et al. [Phys. Rev. E 91, 032301 (2015)10.1103/PhysRevE.91.032301] do not represent the anisotropic Eshelby's stress fields, as it is suggested, but originate in the rotational properties of the stress tensors.
Reconstruction of the dynamics of the climatic system from time-series data
Nicolis, C.; Nicolis, G.
1986-01-01
The oxygen isotope record of the last million years, as provided by a deep sea core sediment, is analyzed by a method recently developed in the theory of dynamical systems. The analysis suggests that climatic variability is the manifestation of a chaotic dynamics described by an attractor of fractal dimensionality. A quantitative measure of the limited predictability of the climatic system is provided by the evaluation of the time-correlation function and the largest positive Lyapounov exponent of the system. PMID:16593650
Molecular dynamics on diffusive time scales from the phase-field-crystal equation.
Chan, Pak Yuen; Goldenfeld, Nigel; Dantzig, Jon
2009-03-01
We extend the phase-field-crystal model to accommodate exact atomic configurations and vacancies by requiring the order parameter to be non-negative. The resulting theory dictates the number of atoms and describes the motion of each of them. By solving the dynamical equation of the model, which is a partial differential equation, we are essentially performing molecular dynamics simulations on diffusive time scales. To illustrate this approach, we calculate the two-point correlation function of a fluid.
Microscopic and histochemical manifestations of hyaline cartilage dynamics.
Malinin, G I; Malinin, T I
1999-01-01
Structure and function of hyaline cartilages has been the focus of many correlative studies for over a hundred years. Much of what is known regarding dynamics and function of cartilage constituents has been derived or inferred from biochemical and electron microscopic investigations. Here we show that in conjunction with ultrastructural, and high-magnification transmission light and polarization microscopy, the well-developed histochemical methods are indispensable for the analysis of cartilage dynamics. Microscopically demonstrable aspects of cartilage dynamics include, but are not limited to, formation of the intracellular liquid crystals, phase transitions of the extracellular matrix and tubular connections between chondrocytes. The role of the interchondrocytic liquid crystals is considered in terms of the tensegrity hypothesis and non-apoptotic cell death. Phase transitions of the extracellular matrix are discussed in terms of self-alignment of chondrons, matrix guidance pathways and cartilage growth in the absence of mitosis. The possible role of nonenzymatic glycation reactions in cartilage dynamics is also reviewed.
Dynamic neutron scattering from conformational dynamics. I. Theory and Markov models
NASA Astrophysics Data System (ADS)
Lindner, Benjamin; Yi, Zheng; Prinz, Jan-Hendrik; Smith, Jeremy C.; Noé, Frank
2013-11-01
The dynamics of complex molecules can be directly probed by inelastic neutron scattering experiments. However, many of the underlying dynamical processes may exist on similar timescales, which makes it difficult to assign processes seen experimentally to specific structural rearrangements. Here, we show how Markov models can be used to connect structural changes observed in molecular dynamics simulation directly to the relaxation processes probed by scattering experiments. For this, a conformational dynamics theory of dynamical neutron and X-ray scattering is developed, following our previous approach for computing dynamical fingerprints of time-correlation functions [F. Noé, S. Doose, I. Daidone, M. Löllmann, J. Chodera, M. Sauer, and J. Smith, Proc. Natl. Acad. Sci. U.S.A. 108, 4822 (2011)]. Markov modeling is used to approximate the relaxation processes and timescales of the molecule via the eigenvectors and eigenvalues of a transition matrix between conformational substates. This procedure allows the establishment of a complete set of exponential decay functions and a full decomposition into the individual contributions, i.e., the contribution of every atom and dynamical process to each experimental relaxation process.
NASA Astrophysics Data System (ADS)
Vogelsberg, Cortnie Sue
Amphidynamic crystals are an extremely promising platform for the development of artificial molecular machines and stimuli-responsive materials. In analogy to skeletal muscle, their function will rely upon the collective operation of many densely packed molecular machines (i.e. actin-bound myosin) that are self-assembled in a highly organized anisotropic medium. By choosing lattice-forming elements and moving "parts" with specific functionalities, individual molecular machines may be synthesized and self-assembled in order to carry out desirable functions. In recent years, efforts in the design of amphidynamic materials based on molecular gyroscopes and compasses have shown that a certain amount of free volume is essential to facilitate internal rotation and reorientation within a crystal. In order to further establish structure/function relationships to advance the development of increasingly complex molecular machinery, molecular rotors and a molecular "spinning" top were synthesized and incorporated into a variety of solid-state architectures with different degrees of periodicity, dimensionality, and free volume. Specifically, lamellar molecular crystals, hierarchically ordered periodic mesoporous organosilicas, and metal-organic frameworks were targeted for the development of solid-state molecular machines. Using an array of solid-state nuclear magnetic resonance spectroscopy techniques, the dynamic properties of these novel molecular machine assemblies were determined and correlated with their corresponding structural features. It was found that architecture type has a profound influence on functional dynamics. The study of layered molecular crystals, composed of either molecular rotors or "spinning" tops, probed functional dynamics within dense, highly organized environments. From their study, it was discovered that: 1) crystallographically distinct sites may be utilized to differentiate machine function, 2) halogen bonding interactions are sufficiently strong to direct an assembly of molecular machines, 3) the relative flexibility of the crystal environment proximate to a dynamic component may have a significant effect on its function, and, 4) molecular machines, which possess both solid-state photochemical reactivity and dynamics may show complex reaction kinetics if the correlation time of the dynamic process and the lifetime of the excited state occur on the same time scale and the dynamic moiety inherently participates as a reaction intermediate. The study of periodic mesoporous organosilica with hierarchical order probed molecular dynamics within 2D layers of molecular rotors, organized in only one dimension and with ca. 50% exposed to the mesopore free volume. From their study, it was discovered that: 1) molecular rotors, which comprise the layers of the mesopore walls, form a 2D rotational glass, 2) rotator dynamics within the 2D rotational glass undergo a transition to a 2D rotational fluid, and, 3) a 2D rotational glass transition may be exploited to develop hyper-sensitive thermally activated molecular machines. The study of a metal-organic framework assembled from molecular rotors probed dynamics in a periodic three-dimensional free-volume environment, without the presence of close contacts. From the study of this solid-state material, it was determined that: 1) the intrinsic electronic barrier is one of the few factors, which may affect functional dynamics in a true free-volume environment, and, 2) molecular machines with dynamic barriers <
NASA Astrophysics Data System (ADS)
Obada, A.-S. F.; Ahmed, M. M. A.; Farouk, Ahmed M.
2018-04-01
In this paper, we propose a new transition scheme (Double Λ) for the interaction between a five-level atom and an electromagnetic field and study its dynamics in the presence of a cross Kerr-like medium in the exact-resonance case. The wave function is derived when the atom is initially prepared in its upper most state, and the field is initially prepared in the coherent state. We studied the atomic population inversion, the coherence degree by studying the second-order correlation function, Cauchy-Schwartz inequality (CSI) and the relation with P-function. Finally, we investigate the effect of Kerr-like medium on the evolution of Husimi Q-function of the considered system.
Removing the barrier to the calculation of activation energies
Mesele, Oluwaseun O.; Thompson, Ward H.
2016-10-06
Approaches for directly calculating the activation energy for a chemical reaction from a simulation at a single temperature are explored with applications to both classical and quantum systems. The activation energy is obtained from a time correlation function that can be evaluated from the same molecular dynamics trajectories or quantum dynamics used to evaluate the rate constant itself and thus requires essentially no extra computational work.
Infraslow Electroencephalographic and Dynamic Resting State Network Activity.
Grooms, Joshua K; Thompson, Garth J; Pan, Wen-Ju; Billings, Jacob; Schumacher, Eric H; Epstein, Charles M; Keilholz, Shella D
2017-06-01
A number of studies have linked the blood oxygenation level dependent (BOLD) signal to electroencephalographic (EEG) signals in traditional frequency bands (δ, θ, α, β, and γ), but the relationship between BOLD and its direct frequency correlates in the infraslow band (<1 Hz) has been little studied. Previously, work in rodents showed that infraslow local field potentials play a role in functional connectivity, particularly in the dynamic organization of large-scale networks. To examine the relationship between infraslow activity and network dynamics in humans, direct current (DC) EEG and resting state magnetic resonance imaging data were acquired simultaneously. The DC EEG signals were correlated with the BOLD signal in patterns that resembled resting state networks. Subsequent dynamic analysis showed that the correlation between DC EEG and the BOLD signal varied substantially over time, even within individual subjects. The variation in DC EEG appears to reflect the time-varying contribution of different resting state networks. Furthermore, some of the patterns of DC EEG and BOLD correlation are consistent with previous work demonstrating quasiperiodic spatiotemporal patterns of large-scale network activity in resting state. These findings demonstrate that infraslow electrical activity is linked to BOLD fluctuations in humans and that it may provide a basis for large-scale organization comparable to that observed in animal studies.
Mori, Mirko; Kateb, Fatiha; Bodenhausen, Geoffrey; Piccioli, Mario; Abergel, Daniel
2010-03-17
Multiple quantum relaxation in proteins reveals unexpected relationships between correlated or anti-correlated conformational backbone dynamics in alpha-helices or beta-sheets. The contributions of conformational exchange to the relaxation rates of C'N coherences (i.e., double- and zero-quantum coherences involving backbone carbonyl (13)C' and neighboring amide (15)N nuclei) depend on the kinetics of slow exchange processes, as well as on the populations of the conformations and chemical shift differences of (13)C' and (15)N nuclei. The relaxation rates of C'N coherences, which reflect concerted fluctuations due to slow chemical shift modulations (CSMs), were determined by direct (13)C detection in diamagnetic and paramagnetic proteins. In well-folded proteins such as lanthanide-substituted calbindin (CaLnCb), copper,zinc superoxide dismutase (Cu,Zn SOD), and matrix metalloproteinase (MMP12), slow conformational exchange occurs along the entire backbone. Our observations demonstrate that relaxation rates of C'N coherences arising from slow backbone dynamics have positive signs (characteristic of correlated fluctuations) in beta-sheets and negative signs (characteristic of anti-correlated fluctuations) in alpha-helices. This extends the prospects of structure-dynamics relationships to slow time scales that are relevant for protein function and enzymatic activity.
Infraslow Electroencephalographic and Dynamic Resting State Network Activity
Grooms, Joshua K.; Thompson, Garth J.; Pan, Wen-Ju; Billings, Jacob; Schumacher, Eric H.; Epstein, Charles M.
2017-01-01
Abstract A number of studies have linked the blood oxygenation level dependent (BOLD) signal to electroencephalographic (EEG) signals in traditional frequency bands (δ, θ, α, β, and γ), but the relationship between BOLD and its direct frequency correlates in the infraslow band (<1 Hz) has been little studied. Previously, work in rodents showed that infraslow local field potentials play a role in functional connectivity, particularly in the dynamic organization of large-scale networks. To examine the relationship between infraslow activity and network dynamics in humans, direct current (DC) EEG and resting state magnetic resonance imaging data were acquired simultaneously. The DC EEG signals were correlated with the BOLD signal in patterns that resembled resting state networks. Subsequent dynamic analysis showed that the correlation between DC EEG and the BOLD signal varied substantially over time, even within individual subjects. The variation in DC EEG appears to reflect the time-varying contribution of different resting state networks. Furthermore, some of the patterns of DC EEG and BOLD correlation are consistent with previous work demonstrating quasiperiodic spatiotemporal patterns of large-scale network activity in resting state. These findings demonstrate that infraslow electrical activity is linked to BOLD fluctuations in humans and that it may provide a basis for large-scale organization comparable to that observed in animal studies. PMID:28462586
Oscillations during observations: Dynamic oscillatory networks serving visuospatial attention.
Wiesman, Alex I; Heinrichs-Graham, Elizabeth; Proskovec, Amy L; McDermott, Timothy J; Wilson, Tony W
2017-10-01
The dynamic allocation of neural resources to discrete features within a visual scene enables us to react quickly and accurately to salient environmental circumstances. A network of bilateral cortical regions is known to subserve such visuospatial attention functions; however the oscillatory and functional connectivity dynamics of information coding within this network are not fully understood. Particularly, the coding of information within prototypical attention-network hubs and the subsecond functional connections formed between these hubs have not been adequately characterized. Herein, we use the precise temporal resolution of magnetoencephalography (MEG) to define spectrally specific functional nodes and connections that underlie the deployment of attention in visual space. Twenty-three healthy young adults completed a visuospatial discrimination task designed to elicit multispectral activity in visual cortex during MEG, and the resulting data were preprocessed and reconstructed in the time-frequency domain. Oscillatory responses were projected to the cortical surface using a beamformer, and time series were extracted from peak voxels to examine their temporal evolution. Dynamic functional connectivity was then computed between nodes within each frequency band of interest. We find that visual attention network nodes are defined functionally by oscillatory frequency, that the allocation of attention to the visual space dynamically modulates functional connectivity between these regions on a millisecond timescale, and that these modulations significantly correlate with performance on a spatial discrimination task. We conclude that functional hubs underlying visuospatial attention are segregated not only anatomically but also by oscillatory frequency, and importantly that these oscillatory signatures promote dynamic communication between these hubs. Hum Brain Mapp 38:5128-5140, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Cross-Correlation Asymmetries and Causal Relationships between Stock and Market Risk
Borysov, Stanislav S.; Balatsky, Alexander V.
2014-01-01
We study historical correlations and lead-lag relationships between individual stock risk (volatility of daily stock returns) and market risk (volatility of daily returns of a market-representative portfolio) in the US stock market. We consider the cross-correlation functions averaged over all stocks, using 71 stock prices from the Standard & Poor's 500 index for 1994–2013. We focus on the behavior of the cross-correlations at the times of financial crises with significant jumps of market volatility. The observed historical dynamics showed that the dependence between the risks was almost linear during the US stock market downturn of 2002 and after the US housing bubble in 2007, remaining at that level until 2013. Moreover, the averaged cross-correlation function often had an asymmetric shape with respect to zero lag in the periods of high correlation. We develop the analysis by the application of the linear response formalism to study underlying causal relations. The calculated response functions suggest the presence of characteristic regimes near financial crashes, when the volatility of an individual stock follows the market volatility and vice versa. PMID:25162697
Cross-correlation asymmetries and causal relationships between stock and market risk.
Borysov, Stanislav S; Balatsky, Alexander V
2014-01-01
We study historical correlations and lead-lag relationships between individual stock risk (volatility of daily stock returns) and market risk (volatility of daily returns of a market-representative portfolio) in the US stock market. We consider the cross-correlation functions averaged over all stocks, using 71 stock prices from the Standard & Poor's 500 index for 1994-2013. We focus on the behavior of the cross-correlations at the times of financial crises with significant jumps of market volatility. The observed historical dynamics showed that the dependence between the risks was almost linear during the US stock market downturn of 2002 and after the US housing bubble in 2007, remaining at that level until 2013. Moreover, the averaged cross-correlation function often had an asymmetric shape with respect to zero lag in the periods of high correlation. We develop the analysis by the application of the linear response formalism to study underlying causal relations. The calculated response functions suggest the presence of characteristic regimes near financial crashes, when the volatility of an individual stock follows the market volatility and vice versa.
Detection of seizures from small samples using nonlinear dynamic system theory.
Yaylali, I; Koçak, H; Jayakar, P
1996-07-01
The electroencephalogram (EEG), like many other biological phenomena, is quite likely governed by nonlinear dynamics. Certain characteristics of the underlying dynamics have recently been quantified by computing the correlation dimensions (D2) of EEG time series data. In this paper, D2 of the unbiased autocovariance function of the scalp EEG data was used to detect electrographic seizure activity. Digital EEG data were acquired at a sampling rate of 200 Hz per channel and organized in continuous frames (duration 2.56 s, 512 data points). To increase the reliability of D2 computations with short duration data, raw EEG data were initially simplified using unbiased autocovariance analysis to highlight the periodic activity that is present during seizures. The D2 computation was then performed from the unbiased autocovariance function of each channel using the Grassberger-Procaccia method with Theiler's box-assisted correlation algorithm. Even with short duration data, this preprocessing proved to be computationally robust and displayed no significant sensitivity to implementation details such as the choices of embedding dimension and box size. The system successfully identified various types of seizures in clinical studies.
NASA Astrophysics Data System (ADS)
McDermid, Richard M.; Cappellari, Michele; Alatalo, Katherine; Bayet, Estelle; Blitz, Leo; Bois, Maxime; Bournaud, Frédéric; Bureau, Martin; Crocker, Alison F.; Davies, Roger L.; Davis, Timothy A.; de Zeeuw, P. T.; Duc, Pierre-Alain; Emsellem, Eric; Khochfar, Sadegh; Krajnović, Davor; Kuntschner, Harald; Morganti, Raffaella; Naab, Thorsten; Oosterloo, Tom; Sarzi, Marc; Scott, Nicholas; Serra, Paolo; Weijmans, Anne-Marie; Young, Lisa M.
2014-09-01
We report on empirical trends between the dynamically determined stellar initial mass function (IMF) and stellar population properties for a complete, volume-limited sample of 260 early-type galaxies from the ATLAS3D project. We study trends between our dynamically derived IMF normalization αdyn ≡ (M/L)stars/(M/L)Salp and absorption line strengths, and interpret these via single stellar population-equivalent ages, abundance ratios (measured as [α/Fe]), and total metallicity, [Z/H]. We find that old and alpha-enhanced galaxies tend to have on average heavier (Salpeter-like) mass normalization of the IMF, but stellar population does not appear to be a good predictor of the IMF, with a large range of αdyn at a given population parameter. As a result, we find weak αdyn-[α/Fe] and αdyn -Age correlations and no significant αdyn -[Z/H] correlation. The observed trends appear significantly weaker than those reported in studies that measure the IMF normalization via the low-mass star demographics inferred through stellar spectral analysis.
Electron correlation and the self-interaction error of density functional theory
NASA Astrophysics Data System (ADS)
Polo, Victor; Kraka, Elfi; Cremer, Dieter
The self-interaction error (SIE) of commonly used DFT functionals has been systematically investigated by comparing the electron density distribution ρ( r ) generated by self-interaction corrected DFT (SIC-DFT) with a series of reference densities obtained by DFT or wavefunction theory (WFT) methods that cover typical electron correlation effects. Although the SIE of GGA functionals is considerably smaller than that of LDA functionals, it has significant consequences for the coverage of electron correlation effects at the DFT level of theory. The exchange SIE mimics long range (non-dynamic) pair correlation effects, and is responsible for the fact that the electron density of DFT exchange-only calculations resembles often that of MP4, MP2 or even CCSD(T) calculations. Changes in the electron density caused by SICDFT exchange are comparable with those that are associated with HF exchange. Correlation functionals contract the density towards the bond and the valence region, thus taking negative charge out of the van der Waals region where these effects are exaggerated by the influence of the SIE of the correlation functional. Hence, SIC-DFT leads in total to a relatively strong redistribution of negative charge from van der Waals, non-bonding, and valence regions of heavy atoms to the bond regions. These changes, although much stronger, resemble those obtained when comparing the densities of hybrid functionals such as B3LYP with the corresponding GGA functional BLYP. Hence, the balanced mixing of local and non-local exchange and correlation effects as it is achieved by hybrid functionals mimics SIC-DFT and can be considered as an economic way to include some SIC into standard DFT. However, the investigation shows also that the SIC-DFT description of molecules is unreliable because the standard functionals used were optimized for DFT including the SIE.
Universal Spatial Correlation Functions for Describing and Reconstructing Soil Microstructure
Skvortsova, Elena B.; Mallants, Dirk
2015-01-01
Structural features of porous materials such as soil define the majority of its physical properties, including water infiltration and redistribution, multi-phase flow (e.g. simultaneous water/air flow, or gas exchange between biologically active soil root zone and atmosphere) and solute transport. To characterize soil microstructure, conventional soil science uses such metrics as pore size and pore-size distributions and thin section-derived morphological indicators. However, these descriptors provide only limited amount of information about the complex arrangement of soil structure and have limited capability to reconstruct structural features or predict physical properties. We introduce three different spatial correlation functions as a comprehensive tool to characterize soil microstructure: 1) two-point probability functions, 2) linear functions, and 3) two-point cluster functions. This novel approach was tested on thin-sections (2.21×2.21 cm2) representing eight soils with different pore space configurations. The two-point probability and linear correlation functions were subsequently used as a part of simulated annealing optimization procedures to reconstruct soil structure. Comparison of original and reconstructed images was based on morphological characteristics, cluster correlation functions, total number of pores and pore-size distribution. Results showed excellent agreement for soils with isolated pores, but relatively poor correspondence for soils exhibiting dual-porosity features (i.e. superposition of pores and micro-cracks). Insufficient information content in the correlation function sets used for reconstruction may have contributed to the observed discrepancies. Improved reconstructions may be obtained by adding cluster and other correlation functions into reconstruction sets. Correlation functions and the associated stochastic reconstruction algorithms introduced here are universally applicable in soil science, such as for soil classification, pore-scale modelling of soil properties, soil degradation monitoring, and description of spatial dynamics of soil microbial activity. PMID:26010779
Universal spatial correlation functions for describing and reconstructing soil microstructure.
Karsanina, Marina V; Gerke, Kirill M; Skvortsova, Elena B; Mallants, Dirk
2015-01-01
Structural features of porous materials such as soil define the majority of its physical properties, including water infiltration and redistribution, multi-phase flow (e.g. simultaneous water/air flow, or gas exchange between biologically active soil root zone and atmosphere) and solute transport. To characterize soil microstructure, conventional soil science uses such metrics as pore size and pore-size distributions and thin section-derived morphological indicators. However, these descriptors provide only limited amount of information about the complex arrangement of soil structure and have limited capability to reconstruct structural features or predict physical properties. We introduce three different spatial correlation functions as a comprehensive tool to characterize soil microstructure: 1) two-point probability functions, 2) linear functions, and 3) two-point cluster functions. This novel approach was tested on thin-sections (2.21×2.21 cm2) representing eight soils with different pore space configurations. The two-point probability and linear correlation functions were subsequently used as a part of simulated annealing optimization procedures to reconstruct soil structure. Comparison of original and reconstructed images was based on morphological characteristics, cluster correlation functions, total number of pores and pore-size distribution. Results showed excellent agreement for soils with isolated pores, but relatively poor correspondence for soils exhibiting dual-porosity features (i.e. superposition of pores and micro-cracks). Insufficient information content in the correlation function sets used for reconstruction may have contributed to the observed discrepancies. Improved reconstructions may be obtained by adding cluster and other correlation functions into reconstruction sets. Correlation functions and the associated stochastic reconstruction algorithms introduced here are universally applicable in soil science, such as for soil classification, pore-scale modelling of soil properties, soil degradation monitoring, and description of spatial dynamics of soil microbial activity.
Exploration of the Energy Landscape of Acetylcholinesterase by Molecular Dynamics Simulation.
NASA Astrophysics Data System (ADS)
McCammon, J. Andrew
2002-03-01
Proteins have rough energy landscapes. Often more states than just the ground state are occupied and have biological functions. It is essential to study these conformational substates and the dynamical transitions among them. Acetylcholinesterase (AChE) is an important enzyme that has biological functions including the termination of synaptic transmission signals. X-ray structures show that it has an active site that is accessible only via a long and narrow channel from its surface. Therefore the fact that acetylcholine and larger ligands can reach the active site is believed to reflect the protein's structural fluctuation. We carried out long molecular dynamics simulations to investigate the dynamics of AChE and its relation to biological function, and compared our results with experiments. The results reveal several "doors" that open intermittantly between the active site and the surface. Instead of having simple exponential decay correlation functions, the time series of these channels reveal complex, fractal gating between conformations. We also compared the AChE dynamics data with those from an AchE-fasciculin complex. (Fasciculin is a small protein that is a natural inhibitor of AChE.) The results show remarkable effects of the protein-protein interaction, including allosteric and dynamical inhibition by fasciculin besides direct steric blocking. More information and images can be found at http://mccammon.ucsd.edu
TU-G-BRA-02: Can We Extract Lung Function Directly From 4D-CT Without Deformable Image Registration?
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kipritidis, J; Woodruff, H; Counter, W
Purpose: Dynamic CT ventilation imaging (CT-VI) visualizes air volume changes in the lung by evaluating breathing-induced lung motion using deformable image registration (DIR). Dynamic CT-VI could enable functionally adaptive lung cancer radiation therapy, but its sensitivity to DIR parameters poses challenges for validation. We hypothesize that a direct metric using CT parameters derived from Hounsfield units (HU) alone can provide similar ventilation images without DIR. We compare the accuracy of Direct and Dynamic CT-VIs versus positron emission tomography (PET) images of inhaled {sup 68}Ga-labelled nanoparticles (‘Galligas’). Methods: 25 patients with lung cancer underwent Galligas 4D-PET/CT scans prior to radiation therapy.more » For each patient we produced three CT- VIs. (i) Our novel method, Direct CT-VI, models blood-gas exchange as the product of air and tissue density at each lung voxel based on time-averaged 4D-CT HU values. Dynamic CT-VIs were produced by evaluating: (ii) regional HU changes, and (iii) regional volume changes between the exhale and inhale 4D-CT phase images using a validated B-spline DIR method. We assessed the accuracy of each CT-VI by computing the voxel-wise Spearman correlation with free-breathing Galligas PET, and also performed a visual analysis. Results: Surprisingly, Direct CT-VIs exhibited better global correlation with Galligas PET than either of the dynamic CT-VIs. The (mean ± SD) correlations were (0.55 ± 0.16), (0.41 ± 0.22) and (0.29 ± 0.27) for Direct, Dynamic HU-based and Dynamic volume-based CT-VIs respectively. Visual comparison of Direct CT-VI to PET demonstrated similarity for emphysema defects and ventral-to-dorsal gradients, but inability to identify decreased ventilation distal to tumor-obstruction. Conclusion: Our data supports the hypothesis that Direct CT-VIs are as accurate as Dynamic CT-VIs in terms of global correlation with Galligas PET. Visual analysis, however, demonstrated that different CT-VI algorithms might have varying accuracy depending on the underlying cause of ventilation abnormality. This research was supported by a National Health and Medical Research Council (NHMRC) Australia Fellowship, an Cancer Institute New South Wales Early Career Fellowship 13-ECF-1/15 and NHMRC scholarship APP1038399. No commercial funding was received for this work.« less
Dynamic modeling of GMA fillet welding using cross-correlation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hellinga, M.; Huissoon, J.; Kerr, H.
1996-12-31
The feasibility of employing the cross-correlation system identification technique as a dynamic modeling method for the GMAW process was examined. This approach has the advantages of modeling speed, the ability to operate in low signal to noise environments, the ease of digital implementation, and the lack of model order assumption, making it ideal in a welding application. The width of the weld pool was the parameter investigated as a function of torch travel speed. Both on-line and off-line width measurements were used to identify the impulse response. Experimental results are presented and comparisons made with both step and ramp response.
ERIC Educational Resources Information Center
Ghisletta, Paolo; Lindenberger, Ulman
2005-01-01
Cross-sectional and longitudinal analyses of age-heterogeneous samples have revealed correlational links between and within intellectual, sensory, and sensorimotor domains. Due to basic limitations of cross-sectional designs and a reluctance to disentangle antecedent-consequent relations in longitudinal designs, the functional significance and…
Evol and ProDy for bridging protein sequence evolution and structural dynamics
Mao, Wenzhi; Liu, Ying; Chennubhotla, Chakra; Lezon, Timothy R.; Bahar, Ivet
2014-01-01
Correlations between sequence evolution and structural dynamics are of utmost importance in understanding the molecular mechanisms of function and their evolution. We have integrated Evol, a new package for fast and efficient comparative analysis of evolutionary patterns and conformational dynamics, into ProDy, a computational toolbox designed for inferring protein dynamics from experimental and theoretical data. Using information-theoretic approaches, Evol coanalyzes conservation and coevolution profiles extracted from multiple sequence alignments of protein families with their inferred dynamics. Availability and implementation: ProDy and Evol are open-source and freely available under MIT License from http://prody.csb.pitt.edu/. Contact: bahar@pitt.edu PMID:24849577
Momentum conserving Brownian dynamics propagator for complex soft matter fluids
DOE Office of Scientific and Technical Information (OSTI.GOV)
Padding, J. T.; Briels, W. J.
2014-12-28
We present a Galilean invariant, momentum conserving first order Brownian dynamics scheme for coarse-grained simulations of highly frictional soft matter systems. Friction forces are taken to be with respect to moving background material. The motion of the background material is described by locally averaged velocities in the neighborhood of the dissolved coarse coordinates. The velocity variables are updated by a momentum conserving scheme. The properties of the stochastic updates are derived through the Chapman-Kolmogorov and Fokker-Planck equations for the evolution of the probability distribution of coarse-grained position and velocity variables, by requiring the equilibrium distribution to be a stationary solution.more » We test our new scheme on concentrated star polymer solutions and find that the transverse current and velocity time auto-correlation functions behave as expected from hydrodynamics. In particular, the velocity auto-correlation functions display a long time tail in complete agreement with hydrodynamics.« less
NASA Astrophysics Data System (ADS)
Martins, Cyril; Lenz, Benjamin; Perfetti, Luca; Brouet, Veronique; Bertran, François; Biermann, Silke
2018-03-01
We address the role of nonlocal Coulomb correlations and short-range magnetic fluctuations in the high-temperature phase of Sr2IrO4 within state-of-the-art spectroscopic and first-principles theoretical methods. Introducing an "oriented-cluster dynamical mean-field scheme", we compute momentum-resolved spectral functions, which we find to be in excellent agreement with angle-resolved photoemission spectra. We show that while short-range antiferromagnetic fluctuations are crucial to accounting for the electronic properties of Sr2IrO4 even in the high-temperature paramagnetic phase, long-range magnetic order is not a necessary ingredient of the insulating state. Upon doping, an exotic metallic state is generated, exhibiting cuprate-like pseudo-gap spectral properties, for which we propose a surprisingly simple theoretical mechanism.
Dynamic cross correlation studies of wave particle interactions in ULF phenomena
NASA Technical Reports Server (NTRS)
Mcpherron, R. L.
1979-01-01
Magnetic field observations made by satellites in the earth's magnetic field reveal a wide variety of ULF waves. These waves interact with the ambient particle populations in complex ways, causing modulation of the observed particle fluxes. This modulation is found to be a function of species, pitch angle, energy and time. The characteristics of this modulation provide information concerning the wave mode and interaction process. One important characteristic of wave-particle interactions is the phase of the particle flux modulation relative to the magnetic field variations. To display this phase as a function of time a dynamic cross spectrum program has been developed. The program produces contour maps in the frequency time plane of the cross correlation coefficient between any particle flux time series and the magnetic field vector. This program has been utilized in several studies of ULF wave-particle interactions at synchronous orbit.
Dynamic Socialized Gaussian Process Models for Human Behavior Prediction in a Health Social Network
Shen, Yelong; Phan, NhatHai; Xiao, Xiao; Jin, Ruoming; Sun, Junfeng; Piniewski, Brigitte; Kil, David; Dou, Dejing
2016-01-01
Modeling and predicting human behaviors, such as the level and intensity of physical activity, is a key to preventing the cascade of obesity and helping spread healthy behaviors in a social network. In our conference paper, we have developed a social influence model, named Socialized Gaussian Process (SGP), for socialized human behavior modeling. Instead of explicitly modeling social influence as individuals' behaviors influenced by their friends' previous behaviors, SGP models the dynamic social correlation as the result of social influence. The SGP model naturally incorporates personal behavior factor and social correlation factor (i.e., the homophily principle: Friends tend to perform similar behaviors) into a unified model. And it models the social influence factor (i.e., an individual's behavior can be affected by his/her friends) implicitly in dynamic social correlation schemes. The detailed experimental evaluation has shown the SGP model achieves better prediction accuracy compared with most of baseline methods. However, a Socialized Random Forest model may perform better at the beginning compared with the SGP model. One of the main reasons is the dynamic social correlation function is purely based on the users' sequential behaviors without considering other physical activity-related features. To address this issue, we further propose a novel “multi-feature SGP model” (mfSGP) which improves the SGP model by using multiple physical activity-related features in the dynamic social correlation learning. Extensive experimental results illustrate that the mfSGP model clearly outperforms all other models in terms of prediction accuracy and running time. PMID:27746515
Intrinsic Multi-Scale Dynamic Behaviors of Complex Financial Systems
Ouyang, Fang-Yan; Zheng, Bo; Jiang, Xiong-Fei
2015-01-01
The empirical mode decomposition is applied to analyze the intrinsic multi-scale dynamic behaviors of complex financial systems. In this approach, the time series of the price returns of each stock is decomposed into a small number of intrinsic mode functions, which represent the price motion from high frequency to low frequency. These intrinsic mode functions are then grouped into three modes, i.e., the fast mode, medium mode and slow mode. The probability distribution of returns and auto-correlation of volatilities for the fast and medium modes exhibit similar behaviors as those of the full time series, i.e., these characteristics are rather robust in multi time scale. However, the cross-correlation between individual stocks and the return-volatility correlation are time scale dependent. The structure of business sectors is mainly governed by the fast mode when returns are sampled at a couple of days, while by the medium mode when returns are sampled at dozens of days. More importantly, the leverage and anti-leverage effects are dominated by the medium mode. PMID:26427063
Dynamic restructuring drives catalytic activity on nanoporous gold–silver alloy catalysts
Zugic, Branko; Wang, Lucun; Heine, Christian; ...
2016-12-19
Bimetallic, nanostructured materials hold promise for improving catalyst activity and selectivity, yet little is known about the dynamic compositional and structural changes that these systems undergo during pretreatment that leads to efficient catalyst function. Here we use ozone-activated silver–gold alloys in the form of nanoporous gold as a case study to demonstrate the dynamic behaviour of bimetallic systems during activation to produce a functioning catalyst. We show that it is these dynamic changes that give rise to the observed catalytic activity. Advanced in situ electron microscopy and X-ray photoelectron spectroscopy are used to demonstrate that major restructuring and compositional changesmore » occur along the path to catalytic function for selective alcohol oxidation. Transient kinetic measurements correlate the restructuring to three types of oxygen on the surface. The direct influence of changes in surface silver concentration and restructuring at the nanoscale on oxidation activity is demonstrated. Finally, our results demonstrate that characterization of these dynamic changes is necessary to unlock the full potential of bimetallic catalytic materials.« less
Dynamic restructuring drives catalytic activity on nanoporous gold–silver alloy catalysts
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zugic, Branko; Wang, Lucun; Heine, Christian
Bimetallic, nanostructured materials hold promise for improving catalyst activity and selectivity, yet little is known about the dynamic compositional and structural changes that these systems undergo during pretreatment that leads to efficient catalyst function. Here we use ozone-activated silver–gold alloys in the form of nanoporous gold as a case study to demonstrate the dynamic behaviour of bimetallic systems during activation to produce a functioning catalyst. We show that it is these dynamic changes that give rise to the observed catalytic activity. Advanced in situ electron microscopy and X-ray photoelectron spectroscopy are used to demonstrate that major restructuring and compositional changesmore » occur along the path to catalytic function for selective alcohol oxidation. Transient kinetic measurements correlate the restructuring to three types of oxygen on the surface. The direct influence of changes in surface silver concentration and restructuring at the nanoscale on oxidation activity is demonstrated. Finally, our results demonstrate that characterization of these dynamic changes is necessary to unlock the full potential of bimetallic catalytic materials.« less
Property relationships of the physical infrastructure and the traffic flow networks
NASA Astrophysics Data System (ADS)
Zhou, Ta; Zou, Sheng-Rong; He, Da-Ren
2010-03-01
We studied both empirically and analytically the correlation between the degrees or the clustering coefficients, respectively, of the networks in the physical infrastructure and the traffic flow layers in three Chinese transportation systems. The systems are bus transportation systems in Beijing and Hangzhou, and the railway system in the mainland. It is found that the correlation between the degrees obey a linear function; while the correlation between the clustering coefficients obey a power law. A possible dynamic explanation on the rules is presented.
Ion Correlation Effects in Salt-Doped Block Copolymers
NASA Astrophysics Data System (ADS)
Brown, Jonathan R.; Seo, Youngmi; Hall, Lisa M.
2018-03-01
We apply classical density functional theory to study how salt changes the microphase morphology of diblock copolymers. Polymers are freely jointed and one monomer type favorably interacts with ions, to account for the selective solvation that arises from different dielectric constants of the microphases. By including correlations from liquid state theory of an unbound reference fluid, the theory can treat chain behavior, microphase separation, ion correlations, and preferential solvation, at the same coarse-grained level. We show good agreement with molecular dynamics simulations.
Zhang, Feng; Sun, Yang; Ye, Zhuo; ...
2015-05-06
In this study, we have performed molecular dynamics simulations on a typical Al-based alloy Al 90Sm 10. The short-range and medium-range correlations of the system are reliably produced by ab initio calculations, whereas the long-range correlations are obtained with the assistance of a semi-empirical potential well-fitted to ab initio data. Our calculations show that a prepeak in the structure factor of this system emerges well above the melting temperature, and the intensity of the prepeak increases with increasing undercooling of the liquid. These results are in agreement with x-ray diffraction experiments. The interplay between the short-range order of the systemmore » originating from the large affinity between Al and Sm atoms, and the intrinsic repulsion between Sm atoms gives rise to a stronger correlation in the second peak than the first peak in the Sm–Sm partial pair correlation function (PPCF), which in turn produces the prepeak in the structure factor.« less
A generative spike train model with time-structured higher order correlations.
Trousdale, James; Hu, Yu; Shea-Brown, Eric; Josić, Krešimir
2013-01-01
Emerging technologies are revealing the spiking activity in ever larger neural ensembles. Frequently, this spiking is far from independent, with correlations in the spike times of different cells. Understanding how such correlations impact the dynamics and function of neural ensembles remains an important open problem. Here we describe a new, generative model for correlated spike trains that can exhibit many of the features observed in data. Extending prior work in mathematical finance, this generalized thinning and shift (GTaS) model creates marginally Poisson spike trains with diverse temporal correlation structures. We give several examples which highlight the model's flexibility and utility. For instance, we use it to examine how a neural network responds to highly structured patterns of inputs. We then show that the GTaS model is analytically tractable, and derive cumulant densities of all orders in terms of model parameters. The GTaS framework can therefore be an important tool in the experimental and theoretical exploration of neural dynamics.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Andrews, Ross N.; Narayanan, Suresh; Zhang, Fan
X-ray photon correlation spectroscopy (XPCS), an extension of dynamic light scattering (DLS) in the X-ray regime, detects temporal intensity fluctuations of coherent speckles and provides scattering-vector-dependent sample dynamics at length scales smaller than DLS. The penetrating power of X-rays enables XPCS to probe the dynamics in a broad array of materials, including polymers, glasses and metal alloys, where attempts to describe the dynamics with a simple exponential fit usually fail. In these cases, the prevailing XPCS data analysis approach employs stretched or compressed exponential decay functions (Kohlrausch functions), which implicitly assume homogeneous dynamics. This paper proposes an alternative analysis schememore » based upon inverse Laplace or Gaussian transformation for elucidating heterogeneous distributions of dynamic time scales in XPCS, an approach analogous to the CONTIN algorithm widely accepted in the analysis of DLS from polydisperse and multimodal systems. In conclusion, using XPCS data measured from colloidal gels, it is demonstrated that the inverse transform approach reveals hidden multimodal dynamics in materials, unleashing the full potential of XPCS.« less
Andrews, Ross N.; Narayanan, Suresh; Zhang, Fan; ...
2018-02-01
X-ray photon correlation spectroscopy (XPCS), an extension of dynamic light scattering (DLS) in the X-ray regime, detects temporal intensity fluctuations of coherent speckles and provides scattering-vector-dependent sample dynamics at length scales smaller than DLS. The penetrating power of X-rays enables XPCS to probe the dynamics in a broad array of materials, including polymers, glasses and metal alloys, where attempts to describe the dynamics with a simple exponential fit usually fail. In these cases, the prevailing XPCS data analysis approach employs stretched or compressed exponential decay functions (Kohlrausch functions), which implicitly assume homogeneous dynamics. This paper proposes an alternative analysis schememore » based upon inverse Laplace or Gaussian transformation for elucidating heterogeneous distributions of dynamic time scales in XPCS, an approach analogous to the CONTIN algorithm widely accepted in the analysis of DLS from polydisperse and multimodal systems. In conclusion, using XPCS data measured from colloidal gels, it is demonstrated that the inverse transform approach reveals hidden multimodal dynamics in materials, unleashing the full potential of XPCS.« less
Weysser, F; Puertas, A M; Fuchs, M; Voigtmann, Th
2010-07-01
We analyze the slow glassy structural relaxation as measured through collective and tagged-particle density correlation functions obtained from Brownian dynamics simulations for a polydisperse system of quasi-hard spheres in the framework of the mode-coupling theory (MCT) of the glass transition. Asymptotic analyses show good agreement for the collective dynamics when polydispersity effects are taken into account in a multicomponent calculation, but qualitative disagreement at small q when the system is treated as effectively monodisperse. The origin of the different small-q behavior is attributed to the interplay between interdiffusion processes and structural relaxation. Numerical solutions of the MCT equations are obtained taking properly binned partial static structure factors from the simulations as input. Accounting for a shift in the critical density, the collective density correlation functions are well described by the theory at all densities investigated in the simulations, with quantitative agreement best around the maxima of the static structure factor and worst around its minima. A parameter-free comparison of the tagged-particle dynamics however reveals large quantitative errors for small wave numbers that are connected to the well-known decoupling of self-diffusion from structural relaxation and to dynamical heterogeneities. While deviations from MCT behavior are clearly seen in the tagged-particle quantities for densities close to and on the liquid side of the MCT glass transition, no such deviations are seen in the collective dynamics.
Zhang, Yongtao; Cui, Yan; Wang, Fei; Cai, Yangjian
2015-05-04
We have investigated the correlation singularities, coherence vortices of two-point correlation function in a partially coherent vector beam with initially radial polarization, i.e., partially coherent radially polarized (PCRP) beam. It is found that these singularities generally occur during free space propagation. Analytical formulae for characterizing the dynamics of the correlation singularities on propagation are derived. The influence of the spatial coherence length of the beam on the evolution properties of the correlation singularities and the conditions for creation and annihilation of the correlation singularities during propagation have been studied in detail based on the derived formulae. Some interesting results are illustrated. These correlation singularities have implication for interference experiments with a PCRP beam.
Eriksrud, Ola; Federolf, Peter; Anderson, Patrick; Cabri, Jan
2018-01-01
Tests of dynamic postural control eliciting full-body three-dimensional joint movements in a systematic manner are scarce. The well-established star excursion balance test (SEBT) elicits primarily three-dimensional lower extremity joint movements with minimal trunk and no upper extremity joint movements. In response to these shortcomings we created the hand reach star excursion balance test (HSEBT) based on the SEBT reach directions. The aims of the current study were to 1) compare HSEBT and SEBT measurements, 2) compare joint movements elicited by the HSEBT to both SEBT joint movements and normative range of motion values published in the literature. Ten SEBT and HSEBT reaches for each foot were obtained while capturing full-body kinematics in twenty recreationally active healthy male subjects. HSEBT and SEBT areas and composite scores (sum of reaches) for total, anterior and posterior subsections and individual reaches were correlated. Total reach score comparisons showed fair to moderate correlations (r = .393 to .606), while anterior and posterior subsections comparisons had fair to good correlations (r = .269 to .823). Individual reach comparisons had no to good correlations (r = -.182 to .822) where lateral and posterior reaches demonstrated the lowest correlations (r = -.182 to .510). The HSEBT elicited more and significantly greater joint movements than the SEBT, except for hip external rotation, knee extension and plantarflexion. Comparisons to normative range of motion values showed that 3 of 18 for the SEBT and 8 of 22 joint movements for the HSEBT were within normative values. The findings suggest that the HSEBT can be used for the assessment of dynamic postural control and is particularly suitable for examining full-body functional mobility.
Changes in dynamic resting state network connectivity following aphasia therapy.
Duncan, E Susan; Small, Steven L
2017-10-24
Resting state magnetic resonance imaging (rsfMRI) permits observation of intrinsic neural networks produced by task-independent correlations in low frequency brain activity. Various resting state networks have been described, with each thought to reflect common engagement in some shared function. There has been limited investigation of the plasticity in these network relationships after stroke or induced by therapy. Twelve individuals with language disorders after stroke (aphasia) were imaged at multiple time points before (baseline) and after an imitation-based aphasia therapy. Language assessment using a narrative production task was performed at the same time points. Group independent component analysis (ICA) was performed on the rsfMRI data to identify resting state networks. A sliding window approach was then applied to assess the dynamic nature of the correlations among these networks. Network correlations during each 30-second window were used to cluster the data into ten states for each window at each time point for each subject. Correlation was performed between changes in time spent in each state and therapeutic gains on the narrative task. The amount of time spent in a single one of the (ten overall) dynamic states was positively associated with behavioral improvement on the narrative task at the 6-week post-therapy maintenance interval, when compared with either baseline or assessment immediately following therapy. This particular state was characterized by minimal correlation among the task-independent resting state networks. Increased functional independence and segregation of resting state networks underlies improvement on a narrative production task following imitation-based aphasia treatment. This has important clinical implications for the targeting of noninvasive brain stimulation in post-stroke remediation.
Tuckerman, Mark E; Chandra, Amalendu; Marx, Dominik
2010-09-28
Extraction of relaxation times, lifetimes, and rates associated with the transport of topological charge defects in hydrogen-bonded networks from molecular dynamics simulations is a challenge because proton transfer reactions continually change the identity of the defect core. In this paper, we present a statistical mechanical theory that allows these quantities to be computed in an unbiased manner. The theory employs a set of suitably defined indicator or population functions for locating a defect structure and their associated correlation functions. These functions are then used to develop a chemical master equation framework from which the rates and lifetimes can be determined. Furthermore, we develop an integral equation formalism for connecting various types of population correlation functions and derive an iterative solution to the equation, which is given a graphical interpretation. The chemical master equation framework is applied to the problems of both hydronium and hydroxide transport in bulk water. For each case it is shown that the theory establishes direct links between the defect's dominant solvation structures, the kinetics of charge transfer, and the mechanism of structural diffusion. A detailed analysis is presented for aqueous hydroxide, examining both reorientational time scales and relaxation of the rotational anisotropy, which is correlated with recent experimental results for these quantities. Finally, for OH(-)(aq) it is demonstrated that the "dynamical hypercoordination mechanism" is consistent with available experimental data while other mechanistic proposals are shown to fail. As a means of going beyond the linear rate theory valid from short up to intermediate time scales, a fractional kinetic model is introduced in the Appendix in order to describe the nonexponential long-time behavior of time-correlation functions. Within the mathematical framework of fractional calculus the power law decay ∼t(-σ), where σ is a parameter of the model and depends on the dimensionality of the system, is obtained from Mittag-Leffler functions due to their long-time asymptotics, whereas (stretched) exponential behavior is found for short times.
Habasaki, J; Casalini, R; Ngai, K L
2010-03-25
Experimentally, superpositioning of dynamic properties such as viscosity, relaxation times, or diffusion coefficients under different conditions of temperature T, pressure P, and volume V by the scaling variable TV(gamma) (where gamma is a material constant) has been reported as a general feature of many kinds of glass-forming materials. In the present work, molecular dynamics (MD) simulations have been performed to study the scaling of dynamics near the glass-transition regime of ionic liquids. Scaling in the simulated 1-ethyl-3-methylimidazolium nitrate (EMIM-NO(3)) system has been tested over wide ranges of temperatures and pressures. TV(gamma) scaling of the dynamics is well described by master curves with gamma = 4.0 +/- 0.2 and 3.8 +/- 0.2 for cation and anion, respectively. Structures and Coulombic terms of the corresponding states are found to be quite similar. The temperature and pressure dependence of the pair correlation function show similar trends and therefore can be superpositioned onto the master curve. Although the behaviors with gamma = 4 might be expected from the relation, gamma = n/3, for the dynamics with the soft-core-type potential U = epsilon(sigma/r)(n), with n = 12, pair potentials used in the MD simulation have a more complex form, and not all the repulsive terms can play their roles in the heterogeneous structures determined by ion-ion interactions. Scaling is related to the common part of effective potentials related to the pair correlation functions, including the many-body effect in real space.
Deco, Gustavo; Mantini, Dante; Romani, Gian Luca; Hagmann, Patric; Corbetta, Maurizio
2013-01-01
Brain fluctuations at rest are not random but are structured in spatial patterns of correlated activity across different brain areas. The question of how resting-state functional connectivity (FC) emerges from the brain's anatomical connections has motivated several experimental and computational studies to understand structure–function relationships. However, the mechanistic origin of resting state is obscured by large-scale models' complexity, and a close structure–function relation is still an open problem. Thus, a realistic but simple enough description of relevant brain dynamics is needed. Here, we derived a dynamic mean field model that consistently summarizes the realistic dynamics of a detailed spiking and conductance-based synaptic large-scale network, in which connectivity is constrained by diffusion imaging data from human subjects. The dynamic mean field approximates the ensemble dynamics, whose temporal evolution is dominated by the longest time scale of the system. With this reduction, we demonstrated that FC emerges as structured linear fluctuations around a stable low firing activity state close to destabilization. Moreover, the model can be further and crucially simplified into a set of motion equations for statistical moments, providing a direct analytical link between anatomical structure, neural network dynamics, and FC. Our study suggests that FC arises from noise propagation and dynamical slowing down of fluctuations in an anatomically constrained dynamical system. Altogether, the reduction from spiking models to statistical moments presented here provides a new framework to explicitly understand the building up of FC through neuronal dynamics underpinned by anatomical connections and to drive hypotheses in task-evoked studies and for clinical applications. PMID:23825427
Deco, Gustavo; Ponce-Alvarez, Adrián; Mantini, Dante; Romani, Gian Luca; Hagmann, Patric; Corbetta, Maurizio
2013-07-03
Brain fluctuations at rest are not random but are structured in spatial patterns of correlated activity across different brain areas. The question of how resting-state functional connectivity (FC) emerges from the brain's anatomical connections has motivated several experimental and computational studies to understand structure-function relationships. However, the mechanistic origin of resting state is obscured by large-scale models' complexity, and a close structure-function relation is still an open problem. Thus, a realistic but simple enough description of relevant brain dynamics is needed. Here, we derived a dynamic mean field model that consistently summarizes the realistic dynamics of a detailed spiking and conductance-based synaptic large-scale network, in which connectivity is constrained by diffusion imaging data from human subjects. The dynamic mean field approximates the ensemble dynamics, whose temporal evolution is dominated by the longest time scale of the system. With this reduction, we demonstrated that FC emerges as structured linear fluctuations around a stable low firing activity state close to destabilization. Moreover, the model can be further and crucially simplified into a set of motion equations for statistical moments, providing a direct analytical link between anatomical structure, neural network dynamics, and FC. Our study suggests that FC arises from noise propagation and dynamical slowing down of fluctuations in an anatomically constrained dynamical system. Altogether, the reduction from spiking models to statistical moments presented here provides a new framework to explicitly understand the building up of FC through neuronal dynamics underpinned by anatomical connections and to drive hypotheses in task-evoked studies and for clinical applications.
Efimova, Y N; Lichikaki, A V; Lishmanov, B Y
2017-07-01
To study the effect of radiofrequency ablation of renal arteries on regional cerebral blood flow and cognitive function in patients with resistant arterial hypertension (AH). Transcatheter renal denervation (TRD) was performed in 17 patients with resistant AH. Examination before and after TRD included SPECT with mTc-HMPAO, 24-hours blood pressure (BP) monitoring, and comprehensive neuropsychological testing. Fifteen patients without angiographic signs of carotid atherosclerosis, coronary artery disease and AH, neurological and psychiatric disorders were investigated as control group. Compared with control group patients with AH had decreases of regional cerebral blood flow (rCBF) in right (by 13.5%, p=0.00002) and left (by 15.5%, p=0.0006) inferior frontal lobes, in right temporal brain region (by 11.5%, p=0.008); in right and left occipital lobes (by 8.2%, p=0.04). In 6 months after TRD we observed significant improvement of cognitive function, parameters of 24-hour BP monitoring, and rCBF. We also noted definite close interdependence between changes of rCBF, indices of 24-hours BP monitoring, and dynamics of cognitive function. Improvement of long-term verbal memory correlated with increases of rCBF in left superior frontal and right occipital regions while dynamics of mentation and attention correlated positively with augmentation of rCBF in right posterior parietal region. Changes of perfusion in inferior parts of left frontal lobe and in right occipital region correlated with dynamics of index of diurnal diastolic hypertension time (R2=0.64, p=0.001, and R2=0.60, p=0.03, respectively). Our results suggest, that in patients with resistant AH positive effect of TRD on levels of 24-hour mean BP as well as on indices of BP load leads to in augmentation of rCBF and improvement of cognitive function.
Dynamic Resting-State Functional Connectivity in Major Depression.
Kaiser, Roselinde H; Whitfield-Gabrieli, Susan; Dillon, Daniel G; Goer, Franziska; Beltzer, Miranda; Minkel, Jared; Smoski, Moria; Dichter, Gabriel; Pizzagalli, Diego A
2016-06-01
Major depressive disorder (MDD) is characterized by abnormal resting-state functional connectivity (RSFC), especially in medial prefrontal cortical (MPFC) regions of the default network. However, prior research in MDD has not examined dynamic changes in functional connectivity as networks form, interact, and dissolve over time. We compared unmedicated individuals with MDD (n=100) to control participants (n=109) on dynamic RSFC (operationalized as SD in RSFC over a series of sliding windows) of an MPFC seed region during a resting-state functional magnetic resonance imaging scan. Among participants with MDD, we also investigated the relationship between symptom severity and RSFC. Secondary analyses probed the association between dynamic RSFC and rumination. Results showed that individuals with MDD were characterized by decreased dynamic (less variable) RSFC between MPFC and regions of parahippocampal gyrus within the default network, a pattern related to sustained positive connectivity between these regions across sliding windows. In contrast, the MDD group exhibited increased dynamic (more variable) RSFC between MPFC and regions of insula, and higher severity of depression was related to increased dynamic RSFC between MPFC and dorsolateral prefrontal cortex. These patterns of highly variable RSFC were related to greater frequency of strong positive and negative correlations in activity across sliding windows. Secondary analyses indicated that increased dynamic RSFC between MPFC and insula was related to higher levels of recent rumination. These findings provide initial evidence that depression, and ruminative thinking in depression, are related to abnormal patterns of fluctuating communication among brain systems involved in regulating attention and self-referential thinking.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dodge, D. A.; Harris, D. B.
Correlation detectors are of considerable interest to the seismic monitoring communities because they offer reduced detection thresholds and combine detection, location and identification functions into a single operation. They appear to be ideal for applications requiring screening of frequent repeating events. However, questions remain about how broadly empirical correlation methods are applicable. We describe the effectiveness of banks of correlation detectors in a system that combines traditional power detectors with correlation detectors in terms of efficiency, which we define to be the fraction of events detected by the correlators. This paper elaborates and extends the concept of a dynamic correlationmore » detection framework – a system which autonomously creates correlation detectors from event waveforms detected by power detectors; and reports observed performance on a network of arrays in terms of efficiency. We performed a large scale test of dynamic correlation processors on an 11 terabyte global dataset using 25 arrays in the single frequency band 1-3 Hz. The system found over 3.2 million unique signals and produced 459,747 screened detections. A very satisfying result is that, on average, efficiency grows with time and, after nearly 16 years of operation, exceeds 47% for events observed over all distance ranges and approaches 70% for near regional and 90% for local events. This observation suggests that future pipeline architectures should make extensive use of correlation detectors, principally for decluttering observations of local and near-regional events. Our results also suggest that future operations based on correlation detection will require commodity large-scale computing infrastructure, since the numbers of correlators in an autonomous system can grow into the hundreds of thousands.« less
Dodge, D. A.; Harris, D. B.
2016-03-15
Correlation detectors are of considerable interest to the seismic monitoring communities because they offer reduced detection thresholds and combine detection, location and identification functions into a single operation. They appear to be ideal for applications requiring screening of frequent repeating events. However, questions remain about how broadly empirical correlation methods are applicable. We describe the effectiveness of banks of correlation detectors in a system that combines traditional power detectors with correlation detectors in terms of efficiency, which we define to be the fraction of events detected by the correlators. This paper elaborates and extends the concept of a dynamic correlationmore » detection framework – a system which autonomously creates correlation detectors from event waveforms detected by power detectors; and reports observed performance on a network of arrays in terms of efficiency. We performed a large scale test of dynamic correlation processors on an 11 terabyte global dataset using 25 arrays in the single frequency band 1-3 Hz. The system found over 3.2 million unique signals and produced 459,747 screened detections. A very satisfying result is that, on average, efficiency grows with time and, after nearly 16 years of operation, exceeds 47% for events observed over all distance ranges and approaches 70% for near regional and 90% for local events. This observation suggests that future pipeline architectures should make extensive use of correlation detectors, principally for decluttering observations of local and near-regional events. Our results also suggest that future operations based on correlation detection will require commodity large-scale computing infrastructure, since the numbers of correlators in an autonomous system can grow into the hundreds of thousands.« less
NASA Astrophysics Data System (ADS)
Hoheisel, C.; Vogelsang, R.; Schoen, M.
1987-12-01
Accurate data for the bulk viscosity ηv have been obtained by molecular dynamics calculations. Many thermodynamic states of the Lennard-Jones fluid were considered. The Green-Kubo integrand of ηv is analyzed in terms of partial correlation functions constituting the total one. These partial functions behave rather differently from those found for the shear viscosity or the thermal conductivity. Generally the total autocorrelation function of ηv shows a steeper initial decay and a more pronounced long time form than those of the shear viscosity or the thermal conductivity. For states near transition to solid phases, like the pseudotriple point of argon, the Green-Kubo integrand of ηv has a significantly longer ranged time behavior than that of the shear viscosity. Hence, for the latter states, a systematic error is expected for ηv using equilibrium molecular dynamics for its computation.
NASA Astrophysics Data System (ADS)
Cohen, Guy; Gull, Emanuel; Reichman, David R.; Millis, Andrew J.
2014-04-01
The nonequilibrium spectral properties of the Anderson impurity model with a chemical potential bias are investigated within a numerically exact real-time quantum Monte Carlo formalism. The two-time correlation function is computed in a form suitable for nonequilibrium dynamical mean field calculations. Additionally, the evolution of the model's spectral properties are simulated in an alternative representation, defined by a hypothetical but experimentally realizable weakly coupled auxiliary lead. The voltage splitting of the Kondo peak is confirmed and the dynamics of its formation after a coupling or gate quench are studied. This representation is shown to contain additional information about the dot's population dynamics. Further, we show that the voltage-dependent differential conductance gives a reasonable qualitative estimate of the equilibrium spectral function, but significant qualitative differences are found including incorrect trends and spurious temperature dependent effects.
k-space image correlation to probe the intracellular dynamics of gold nanoparticles
NASA Astrophysics Data System (ADS)
Bouzin, M.; Sironi, L.; Chirico, G.; D'Alfonso, L.; Inverso, D.; Pallavicini, P.; Collini, M.
2016-04-01
The collective action of dynein, kinesin and myosin molecular motors is responsible for the intracellular active transport of cargoes, vesicles and organelles along the semi-flexible oriented filaments of the cytoskeleton. The overall mobility of the cargoes upon binding and unbinding to motor proteins can be modeled as an intermittency between Brownian diffusion in the cell cytoplasm and active ballistic excursions along actin filaments or microtubules. Such an intermittent intracellular active transport, exhibited by star-shaped gold nanoparticles (GNSs, Gold Nanostars) upon internalization in HeLa cancer cells, is investigated here by combining live-cell time-lapse confocal reflectance microscopy and the spatio-temporal correlation, in the reciprocal Fourier space, of the acquired image sequences. At first, the analytical theoretical framework for the investigation of a two-state intermittent dynamics is presented for Fourier-space Image Correlation Spectroscopy (kICS). Then simulated kICS correlation functions are employed to evaluate the influence of, and sensitivity to, all the kinetic and dynamic parameters the model involves (the transition rates between the diffusive and the active transport states, the diffusion coefficient and drift velocity of the imaged particles). The optimal procedure for the analysis of the experimental data is outlined and finally exploited to derive whole-cell maps for the parameters underlying the GNSs super-diffusive dynamics. Applied here to the GNSs subcellular trafficking, the proposed kICS analysis can be adopted for the characterization of the intracellular (super-) diffusive dynamics of any fluorescent or scattering biological macromolecule.
Dong, Hui; Lewis, Nicholas H. C.; Oliver, Thomas A. A.; ...
2015-05-07
Changes in the electronic structure of pigments in protein environments and of polar molecules in solution inevitably induce a re-adaption of molecular nuclear structure. Both changes of electronic and vibrational energies can be probed with visible or infrared lasers, such as two-dimensional electronic spectroscopy or vibrational spectroscopy. The extent to which the two changes are correlated remains elusive. The recent demonstration of two-dimensional electronic-vibrational (2DEV) spectroscopy potentially enables a direct measurement of this correlation experimentally. However, it has hitherto been unclear how to characterize the correlation from the spectra. In this report, we present a theoretical formalism to demonstrate themore » slope of the nodal line between the excited state absorption and ground state bleach peaks in the spectra as a characterization of the correlation between electronic and vibrational transition energies. In conclusion, we also show the dynamics of the nodal line slope is correlated to the vibrational spectral dynamics. Additionally, we demonstrate the fundamental 2DEV spectral line-shape of a monomer with newly developed response functions« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dong, Hui; Lewis, Nicholas H. C.; Oliver, Thomas A. A.
2015-05-07
Changes in the electronic structure of pigments in protein environments and of polar molecules in solution inevitably induce a re-adaption of molecular nuclear structure. Both changes of electronic and vibrational energies can be probed with visible or infrared lasers, such as two-dimensional electronic spectroscopy or vibrational spectroscopy. The extent to which the two changes are correlated remains elusive. The recent demonstration of two-dimensional electronic-vibrational (2DEV) spectroscopy potentially enables a direct measurement of this correlation experimentally. However, it has hitherto been unclear how to characterize the correlation from the spectra. In this paper, we present a theoretical formalism to demonstrate themore » slope of the nodal line between the excited state absorption and ground state bleach peaks in the spectra as a characterization of the correlation between electronic and vibrational transition energies. We also show the dynamics of the nodal line slope is correlated to the vibrational spectral dynamics. Additionally, we demonstrate the fundamental 2DEV spectral line-shape of a monomer with newly developed response functions.« less
Charge and Spin Dynamics of the Hubbard Chains
NASA Technical Reports Server (NTRS)
Park, Youngho; Liang, Shoudan
1999-01-01
We calculate the local correlation functions of charge and spin for the one-chain and two-chain Hubbard model using density matrix renormalization group method and the recursion technique. Keeping only finite number of states we get good accuracy for the low energy excitations. We study the charge and spin gaps, bandwidths and weights of the spectra for various values of the on-site Coulomb interaction U and the electron filling. In the low energy part, the local correlation functions are different for the charge and spin. The bandwidths are proportional to t for the charge and J for the spin respectively.
Classical Wigner method with an effective quantum force: application to reaction rates.
Poulsen, Jens Aage; Li, Huaqing; Nyman, Gunnar
2009-07-14
We construct an effective "quantum force" to be used in the classical molecular dynamics part of the classical Wigner method when determining correlation functions. The quantum force is obtained by estimating the most important short time separation of the Feynman paths that enter into the expression for the correlation function. The evaluation of the force is then as easy as classical potential energy evaluations. The ideas are tested on three reaction rate problems. The resulting transmission coefficients are in much better agreement with accurate results than transmission coefficients from the ordinary classical Wigner method.
NASA Astrophysics Data System (ADS)
Jia, Zheng-Lin; Mei, Dong-Cheng
2010-05-01
We investigate the effects of the noise parameters and immunization strength β on the dynamical properties of a tumor growth system with both immunization and colored cross-correlated noises. The analytical expressions for the associated relaxation time TC and the normalized correlation function C(s) are derived by means of the projection operator method. The results indicate that: (i) TC as a function of the multiplicative noise intensity α shows resonance-like behavior, i.e. the curves of TC versus α exhibit a single-peak structure and its peak position changes with increasing correlation strength between noises λ, the autocorrelation time of multiplicative noise τ1, the autocorrelation time of additive noise τ2 and the cross-correlation time τ3. This behavior can be understood in terms of the noise-enhanced stability effect and the influence of the memory effects on it. (ii) The increasing λ, τ1, τ2 and the additive noise intensity D slow down the fluctuation decay of the tumor population, whereas the increasing τ3 and β speed it up. (iii) C(s) increases as λ, τ1, τ2 and β increase, while it decreases with τ3 increasing. Our study shows that the effects of some noise parameters on tumor growth can be modified due to the presence of the immunization effect.
Information properties of morphologically complex words modulate brain activity during word reading
Hultén, Annika; Lehtonen, Minna; Lagus, Krista; Salmelin, Riitta
2018-01-01
Abstract Neuroimaging studies of the reading process point to functionally distinct stages in word recognition. Yet, current understanding of the operations linked to those various stages is mainly descriptive in nature. Approaches developed in the field of computational linguistics may offer a more quantitative approach for understanding brain dynamics. Our aim was to evaluate whether a statistical model of morphology, with well‐defined computational principles, can capture the neural dynamics of reading, using the concept of surprisal from information theory as the common measure. The Morfessor model, created for unsupervised discovery of morphemes, is based on the minimum description length principle and attempts to find optimal units of representation for complex words. In a word recognition task, we correlated brain responses to word surprisal values derived from Morfessor and from other psycholinguistic variables that have been linked with various levels of linguistic abstraction. The magnetoencephalography data analysis focused on spatially, temporally and functionally distinct components of cortical activation observed in reading tasks. The early occipital and occipito‐temporal responses were correlated with parameters relating to visual complexity and orthographic properties, whereas the later bilateral superior temporal activation was correlated with whole‐word based and morphological models. The results show that the word processing costs estimated by the statistical Morfessor model are relevant for brain dynamics of reading during late processing stages. PMID:29524274
Generating Dynamic Persistence in the Time Domain
NASA Astrophysics Data System (ADS)
Guerrero, A.; Smith, L. A.; Smith, L. A.; Kaplan, D. T.
2001-12-01
Many dynamical systems present long-range correlations. Physically, these systems vary from biological to economical, including geological or urban systems. Important geophysical candidates for this type of behaviour include weather (or climate) and earthquake sequences. Persistence is characterised by slowly decaying correlation function; that, in theory, never dies out. The Persistence exponent reflects the degree of memory in the system and much effort has been expended creating and analysing methods that successfully estimate this parameter and model data that exhibits persistence. The most widely used methods for generating long correlated time series are not dynamical systems in the time domain, but instead are derived from a given spectral density. Little attention has been drawn to modelling persistence in the time domain. The time domain approach has the advantage that an observation at certain time can be calculated using previous observations which is particularly suitable when investigating the predictability of a long memory process. We will describe two of these methods in the time domain. One is a traditional approach using fractional ARIMA (autoregressive and moving average) models; the second uses a novel approach to extending a given series using random Fourier basis functions. The statistical quality of the two methods is compared, and they are contrasted with weather data which shows, reportedly, persistence. The suitability of this approach both for estimating predictability and for making predictions is discussed.
The stochastic resonance for the incidence function model of metapopulation
NASA Astrophysics Data System (ADS)
Li, Jiang-Cheng; Dong, Zhi-Wei; Zhou, Ruo-Wei; Li, Yun-Xian; Qian, Zhen-Wei
2017-06-01
A stochastic model with endogenous and exogenous periodicities is proposed in this paper on the basis of metapopulation dynamics to model the crop yield losses due to pests and diseases. The rationale is that crop yield losses occur because the physiology of the growing crop is negatively affected by pests and diseases in a dynamic way over time as crop both grows and develops. Metapopulation dynamics can thus be used to model the resultant crop yield losses. The stochastic metapopulation process is described by using the Simplified Incidence Function model (IFM). Compared to the original IFMs, endogenous and exogenous periodicities are considered in the proposed model to handle the cyclical patterns observed in pest infestations, diseases epidemics, and exogenous affecting factors such as temperature and rainfalls. Agricultural loss data in China are used to fit the proposed model. Experimental results demonstrate that: (1) Model with endogenous and exogenous periodicities is a better fit; (2) When the internal system fluctuations and external environmental fluctuations are negatively correlated, EIL or the cost of loss is monotonically increasing; when the internal system fluctuations and external environmental fluctuations are positively correlated, an outbreak of pests and diseases might occur; (3) If the internal system fluctuations and external environmental fluctuations are positively correlated, an optimal patch size can be identified which will greatly weaken the effects of external environmental influence and hence inhibit pest infestations and disease epidemics.
Information properties of morphologically complex words modulate brain activity during word reading.
Hakala, Tero; Hultén, Annika; Lehtonen, Minna; Lagus, Krista; Salmelin, Riitta
2018-06-01
Neuroimaging studies of the reading process point to functionally distinct stages in word recognition. Yet, current understanding of the operations linked to those various stages is mainly descriptive in nature. Approaches developed in the field of computational linguistics may offer a more quantitative approach for understanding brain dynamics. Our aim was to evaluate whether a statistical model of morphology, with well-defined computational principles, can capture the neural dynamics of reading, using the concept of surprisal from information theory as the common measure. The Morfessor model, created for unsupervised discovery of morphemes, is based on the minimum description length principle and attempts to find optimal units of representation for complex words. In a word recognition task, we correlated brain responses to word surprisal values derived from Morfessor and from other psycholinguistic variables that have been linked with various levels of linguistic abstraction. The magnetoencephalography data analysis focused on spatially, temporally and functionally distinct components of cortical activation observed in reading tasks. The early occipital and occipito-temporal responses were correlated with parameters relating to visual complexity and orthographic properties, whereas the later bilateral superior temporal activation was correlated with whole-word based and morphological models. The results show that the word processing costs estimated by the statistical Morfessor model are relevant for brain dynamics of reading during late processing stages. © 2018 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.
Brain dynamics during natural viewing conditions--a new guide for mapping connectivity in vivo.
Bartels, Andreas; Zeki, Semir
2005-01-15
We describe here a new way of obtaining maps of connectivity in the human brain based on interregional correlations of blood oxygen level-dependent (BOLD) signal during natural viewing conditions. We propose that anatomical connections are reflected in BOLD signal correlations during natural brain dynamics. This may provide a powerful approach to chart connectivity, more so than that based on the 'resting state' of the human brain, and it may complement diffusion tensor imaging. Our approach relies on natural brain dynamics and is therefore experimentally unbiased and independent of hypothesis-driven, specialized stimuli. It has the advantage that natural viewing leads to considerably stronger cortical activity than rest, thus facilitating detection of weaker connections. To validate our technique, we used functional magnetic resonance imaging (fMRI) to record BOLD signal while volunteers freely viewed a movie that was interrupted by resting periods. We used independent component analysis (ICA) to segregate cortical areas before characterizing the dynamics of their BOLD signal during free viewing and rest. Natural viewing and rest each revealed highly specific correlation maps, which reflected known anatomical connections. Examples are homologous regions in visual and auditory cortices in the two hemispheres and the language network consisting of Wernicke's area, Broca's area, and a premotor region. Correlations between regions known to be directly connected were always substantially higher than between nonconnected regions. Furthermore, compared to rest, natural viewing specifically increased correlations between anatomically connected regions while it decreased correlations between nonconnected regions. Our findings therefore demonstrate that natural viewing conditions lead to particularly specific interregional correlations and thus provide a powerful environment to reveal anatomical connectivity in vivo.
Sourty, Marion; Thoraval, Laurent; Roquet, Daniel; Armspach, Jean-Paul; Foucher, Jack; Blanc, Frédéric
2016-01-01
Exploring time-varying connectivity networks in neurodegenerative disorders is a recent field of research in functional MRI. Dementia with Lewy bodies (DLB) represents 20% of the neurodegenerative forms of dementia. Fluctuations of cognition and vigilance are the key symptoms of DLB. To date, no dynamic functional connectivity (DFC) investigations of this disorder have been performed. In this paper, we refer to the concept of connectivity state as a piecewise stationary configuration of functional connectivity between brain networks. From this concept, we propose a new method for group-level as well as for subject-level studies to compare and characterize connectivity state changes between a set of resting-state networks (RSNs). Dynamic Bayesian networks, statistical and graph theory-based models, enable one to learn dependencies between interacting state-based processes. Product hidden Markov models (PHMM), an instance of dynamic Bayesian networks, are introduced here to capture both statistical and temporal aspects of DFC of a set of RSNs. This analysis was based on sliding-window cross-correlations between seven RSNs extracted from a group independent component analysis performed on 20 healthy elderly subjects and 16 patients with DLB. Statistical models of DFC differed in patients compared to healthy subjects for the occipito-parieto-frontal network, the medial occipital network and the right fronto-parietal network. In addition, pairwise comparisons of DFC of RSNs revealed a decrease of dependency between these two visual networks (occipito-parieto-frontal and medial occipital networks) and the right fronto-parietal control network. The analysis of DFC state changes thus pointed out networks related to the cognitive functions that are known to be impaired in DLB: visual processing as well as attentional and executive functions. Besides this context, product HMM applied to RSNs cross-correlations offers a promising new approach to investigate structural and temporal aspects of brain DFC.
Watching proteins function with picosecond X-ray crystallography and molecular dynamics simulations.
NASA Astrophysics Data System (ADS)
Anfinrud, Philip
2006-03-01
Time-resolved electron density maps of myoglobin, a ligand-binding heme protein, have been stitched together into movies that unveil with < 2-å spatial resolution and 150-ps time-resolution the correlated protein motions that accompany and/or mediate ligand migration within the hydrophobic interior of a protein. A joint analysis of all-atom molecular dynamics (MD) calculations and picosecond time-resolved X-ray structures provides single-molecule insights into mechanisms of protein function. Ensemble-averaged MD simulations of the L29F mutant of myoglobin following ligand dissociation reproduce the direction, amplitude, and timescales of crystallographically-determined structural changes. This close agreement with experiments at comparable resolution in space and time validates the individual MD trajectories, which identify and structurally characterize a conformational switch that directs dissociated ligands to one of two nearby protein cavities. This unique combination of simulation and experiment unveils functional protein motions and illustrates at an atomic level relationships among protein structure, dynamics, and function. In collaboration with Friedrich Schotte and Gerhard Hummer, NIH.
Dynamic reorganization of human resting-state networks during visuospatial attention.
Spadone, Sara; Della Penna, Stefania; Sestieri, Carlo; Betti, Viviana; Tosoni, Annalisa; Perrucci, Mauro Gianni; Romani, Gian Luca; Corbetta, Maurizio
2015-06-30
Fundamental problems in neuroscience today are understanding how patterns of ongoing spontaneous activity are modified by task performance and whether/how these intrinsic patterns influence task-evoked activation and behavior. We examined these questions by comparing instantaneous functional connectivity (IFC) and directed functional connectivity (DFC) changes in two networks that are strongly correlated and segregated at rest: the visual (VIS) network and the dorsal attention network (DAN). We measured how IFC and DFC during a visuospatial attention task, which requires dynamic selective rerouting of visual information across hemispheres, changed with respect to rest. During the attention task, the two networks remained relatively segregated, and their general pattern of within-network correlation was maintained. However, attention induced a decrease of correlation in the VIS network and an increase of the DAN→VIS IFC and DFC, especially in a top-down direction. In contrast, within the DAN, IFC was not modified by attention, whereas DFC was enhanced. Importantly, IFC modulations were behaviorally relevant. We conclude that a stable backbone of within-network functional connectivity topography remains in place when transitioning between resting wakefulness and attention selection. However, relative decrease of correlation of ongoing "idling" activity in visual cortex and synchronization between frontoparietal and visual cortex were behaviorally relevant, indicating that modulations of resting activity patterns are important for task performance. Higher order resting connectivity in the DAN was relatively unaffected during attention, potentially indicating a role for simultaneous ongoing activity as a "prior" for attention selection.
Neipert, Christine; Space, Brian
2006-12-14
Sum vibrational frequency spectroscopy, a second order optical process, is interface specific in the dipole approximation. At charged interfaces, there exists a static field, and as a direct consequence, the experimentally detected signal is a combination of enhanced second and static field induced third order contributions. There is significant evidence in the literature of the importance/relative magnitude of this third order contribution, but no previous molecularly detailed approach existed to separately calculate the second and third order contributions. Thus, for the first time, a molecularly detailed time correlation function theory is derived here that allows for the second and third order contributions to sum frequency vibrational spectra to be individually determined. Further, a practical, molecular dynamics based, implementation procedure for the derived correlation functions that describe the third order phenomenon is also presented. This approach includes a novel generalization of point atomic polarizability models to calculate the hyperpolarizability of a molecular system. The full system hyperpolarizability appears in the time correlation functions responsible for third order contributions in the presence of a static field.
NASA Astrophysics Data System (ADS)
Guo, X.; Li, Y.; Suo, T.; Liu, H.; Zhang, C.
2017-11-01
This paper proposes a method for de-blurring of images captured in the dynamic deformation of materials. De-blurring is achieved based on the dynamic-based approach, which is used to estimate the Point Spread Function (PSF) during the camera exposure window. The deconvolution process involving iterative matrix calculations of pixels, is then performed on the GPU to decrease the time cost. Compared to the Gauss method and the Lucy-Richardson method, it has the best result of the image restoration. The proposed method has been evaluated by using the Hopkinson bar loading system. In comparison to the blurry image, the proposed method has successfully restored the image. It is also demonstrated from image processing applications that the de-blurring method can improve the accuracy and the stability of the digital imaging correlation measurement.
FAST TRACK COMMUNICATION A DFT + DMFT approach for nanosystems
NASA Astrophysics Data System (ADS)
Turkowski, Volodymyr; Kabir, Alamgir; Nayyar, Neha; Rahman, Talat S.
2010-11-01
We propose a combined density-functional-theory-dynamical-mean-field-theory (DFT + DMFT) approach for reliable inclusion of electron-electron correlation effects in nanosystems. Compared with the widely used DFT + U approach, this method has several advantages, the most important of which is that it takes into account dynamical correlation effects. The formalism is illustrated through different calculations of the magnetic properties of a set of small iron clusters (number of atoms 2 <= N <= 5). It is shown that the inclusion of dynamical effects leads to a reduction in the cluster magnetization (as compared to results from DFT + U) and that, even for such small clusters, the magnetization values agree well with experimental estimations. These results justify confidence in the ability of the method to accurately describe the magnetic properties of clusters of interest to nanoscience.
Dynamics of bid-ask spread return and volatility of the Chinese stock market
NASA Astrophysics Data System (ADS)
Qiu, Tian; Chen, Guang; Zhong, Li-Xin; Wu, Xiao-Run
2012-04-01
The bid-ask spread is taken as an important measure of the financial market liquidity. In this article, we study the dynamics of the spread return and the spread volatility of four liquid stocks in the Chinese stock market, including the memory effect and the multifractal nature. By investigating the autocorrelation function and the Detrended Fluctuation Analysis (DFA), we find that the spread return is the lack of long-range memory, while the spread volatility is long-range time correlated. Besides, the spread volatilities of different stocks present long-range cross-correlations. Moreover, by applying the Multifractal Detrended Fluctuation Analysis (MF-DFA), the spread return is observed to possess a strong multifractality, which is similar to the dynamics of a variety of financial quantities. Different from the spread return, the spread volatility exhibits a weak multifractal nature.
Assortative mixing in functional brain networks during epileptic seizures
NASA Astrophysics Data System (ADS)
Bialonski, Stephan; Lehnertz, Klaus
2013-09-01
We investigate assortativity of functional brain networks before, during, and after one-hundred epileptic seizures with different anatomical onset locations. We construct binary functional networks from multi-channel electroencephalographic data recorded from 60 epilepsy patients; and from time-resolved estimates of the assortativity coefficient, we conclude that positive degree-degree correlations are inherent to seizure dynamics. While seizures evolve, an increasing assortativity indicates a segregation of the underlying functional network into groups of brain regions that are only sparsely interconnected, if at all. Interestingly, assortativity decreases already prior to seizure end. Together with previous observations of characteristic temporal evolutions of global statistical properties and synchronizability of epileptic brain networks, our findings may help to gain deeper insights into the complicated dynamics underlying generation, propagation, and termination of seizures.
NASA Astrophysics Data System (ADS)
Kitao, Akio; Hirata, Fumio; Gō, Nobuhiro
1991-12-01
The effects of solvent on the conformation and dynamics of protein is studied by computer simulation. The dynamics is studied by focusing mainly on collective motions of the protein molecule. Three types of simulation, normal mode analysis, molecular dynamics in vacuum, and molecular dynamics in water are applied to melittin, the major component of bee venom. To define collective motions principal, component analysis as well as normal mode analysis has been carried out. The principal components with large fluctuation amplitudes have a very good correspondence with the low-frequency normal modes. Trajectories of the molecular dynamics simulation are projected onto the principal axes. From the projected motions time correlation functions are calculated. The results indicate that the very-low-frequency modes, whose frequencies are less than ≈ 50 cm -1, are overdamping in water with relaxation times roushly twice as long as the period of the oscillatory motion. Effective Langevin mode analysis is carried out by using the friction coefficient matrix determined from the velocity correlation function calculated from the molecular dynamics trajectory in water. This analysis reproduces the results of the simulation in water reasonably well. The presence of the solvent water is found also to affect the shape of the potential energy surface in such a way that it produces many local minima with low-energy barriers in between, the envelope of which is given by the surface in vacuum. Inter-minimum transitions endow the conformational dynamics of proteins in water another diffusive character, which already exists in the intra-minimum collective motions.
Correlations and Functional Connections in a Population of Grid Cells
Roudi, Yasser
2015-01-01
We study the statistics of spike trains of simultaneously recorded grid cells in freely behaving rats. We evaluate pairwise correlations between these cells and, using a maximum entropy kinetic pairwise model (kinetic Ising model), study their functional connectivity. Even when we account for the covariations in firing rates due to overlapping fields, both the pairwise correlations and functional connections decay as a function of the shortest distance between the vertices of the spatial firing pattern of pairs of grid cells, i.e. their phase difference. They take positive values between cells with nearby phases and approach zero or negative values for larger phase differences. We find similar results also when, in addition to correlations due to overlapping fields, we account for correlations due to theta oscillations and head directional inputs. The inferred connections between neurons in the same module and those from different modules can be both negative and positive, with a mean close to zero, but with the strongest inferred connections found between cells of the same module. Taken together, our results suggest that grid cells in the same module do indeed form a local network of interconnected neurons with a functional connectivity that supports a role for attractor dynamics in the generation of grid pattern. PMID:25714908
Sato, Wataru; Toichi, Motomi; Uono, Shota; Kochiyama, Takanori
2012-08-13
Impairment of social interaction via facial expressions represents a core clinical feature of autism spectrum disorders (ASD). However, the neural correlates of this dysfunction remain unidentified. Because this dysfunction is manifested in real-life situations, we hypothesized that the observation of dynamic, compared with static, facial expressions would reveal abnormal brain functioning in individuals with ASD.We presented dynamic and static facial expressions of fear and happiness to individuals with high-functioning ASD and to age- and sex-matched typically developing controls and recorded their brain activities using functional magnetic resonance imaging (fMRI). Regional analysis revealed reduced activation of several brain regions in the ASD group compared with controls in response to dynamic versus static facial expressions, including the middle temporal gyrus (MTG), fusiform gyrus, amygdala, medial prefrontal cortex, and inferior frontal gyrus (IFG). Dynamic causal modeling analyses revealed that bi-directional effective connectivity involving the primary visual cortex-MTG-IFG circuit was enhanced in response to dynamic as compared with static facial expressions in the control group. Group comparisons revealed that all these modulatory effects were weaker in the ASD group than in the control group. These results suggest that weak activity and connectivity of the social brain network underlie the impairment in social interaction involving dynamic facial expressions in individuals with ASD.
Lead-lag relationships between stock and market risk within linear response theory
NASA Astrophysics Data System (ADS)
Borysov, Stanislav; Balatsky, Alexander
2015-03-01
We study historical correlations and lead-lag relationships between individual stock risks (standard deviation of daily stock returns) and market risk (standard deviation of daily returns of a market-representative portfolio) in the US stock market. We consider the cross-correlation functions averaged over stocks, using historical stock prices from the Standard & Poor's 500 index for 1994-2013. The observed historical dynamics suggests that the dependence between the risks was almost linear during the US stock market downturn of 2002 and after the US housing bubble in 2007, remaining at that level until 2013. Moreover, the averaged cross-correlation function often had an asymmetric shape with respect to zero lag in the periods of high correlation. We develop the analysis by the application of the linear response formalism to study underlying causal relations. The calculated response functions suggest the presence of characteristic regimes near financial crashes, when individual stock risks affect market risk and vice versa. This work was supported by VR 621-2012-2983.
Reversible and non-reversible changes in nanostructured Si in humid atmosphere
NASA Astrophysics Data System (ADS)
Zhigalov, V.; Pyatilova, O.; Timoshenkov, S.; Gavrilov, S.
2014-12-01
Atmosphere water influence in the nanostructured silicon (NSS) was investigated by IR-spectroscopy and electron work function measurement. Long-term non-reversible dynamics of IR-spectra was found as a result of 100% humidity influence on the nanostructured silicon. It was indicated that air humidity affects on the work function. Dynamics of the electron work function consists of reversible and non-reversible components. Reversible component appears as strong anti-correlation between work function and humidity. Work function change of NSS is about 0.4 eV while the humidity changes between 0% and 100%. Reversible component can be explained by physical sorption of water molecules on the surface. Non-reversible component manifests as long-term decreasing trend of work function in humid atmosphere. Transition curve during abruptly humidity changes alters its shape. Non-reversible component can be explained by chemisorption of water.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kitagawa, Takuya; Pielawa, Susanne; Demler, Eugene
2010-06-25
We theoretically analyze Ramsey interference experiments in one-dimensional quasicondensates and obtain explicit expressions for the time evolution of full distribution functions of fringe contrast. We show that distribution functions contain unique signatures of the many-body mechanism of decoherence. We argue that Ramsey interference experiments provide a powerful tool for analyzing strongly correlated nature of 1D interacting systems.
Fluctuation correlation models for receptor immobilization
NASA Astrophysics Data System (ADS)
Fourcade, B.
2017-12-01
Nanoscale dynamics with cycles of receptor diffusion and immobilization by cell-external-or-internal factors is a key process in living cell adhesion phenomena at the origin of a plethora of signal transduction pathways. Motivated by modern correlation microscopy approaches, the receptor correlation functions in physical models based on diffusion-influenced reaction is studied. Using analytical and stochastic modeling, this paper focuses on the hybrid regime where diffusion and reaction are not truly separable. The time receptor autocorrelation functions are shown to be indexed by different time scales and their asymptotic expansions are given. Stochastic simulations show that this analysis can be extended to situations with a small number of molecules. It is also demonstrated that this analysis applies when receptor immobilization is coupled to environmental noise.
Dynamics of paramagnetic agents by off-resonance rotating frame technique
NASA Astrophysics Data System (ADS)
Zhang, Huiming; Xie, Yang
2006-12-01
Off-resonance rotating frame technique offers a novel tool to explore the dynamics of paramagnetic agents at high magnetic fields ( B0 > 3 T). Based on the effect of paramagnetic relaxation enhancement in the off-resonance rotating frame, a new method is described here for determining the dynamics of paramagnetic ion chelates from the residual z-magnetizations of water protons. In this method, the dynamics of the chelates are identified by the difference magnetization profiles, which are the subtraction of the residual z-magnetization as a function of frequency offset obtained at two sets of RF amplitude ω1 and pulse duration τ. The choices of ω1 and τ are guided by a 2-D magnetization map that is created numerically by plotting the residual z-magnetization as a function of effective field angle θ and off-resonance pulse duration τ. From the region of magnetization map that is the most sensitive to the alteration of the paramagnetic relaxation enhancement efficiency R1 ρ/ R1, the ratio of the off-resonance rotating frame relaxation rate constant R1 ρ verse the laboratory frame relaxation rate constant R1, three types of difference magnetization profiles can be generated. The magnetization map and the difference magnetization profiles are correlated with the rotational correlation time τR of Gd-DTPA through numerical simulations, and further validated by the experimental data for a series of macromolecule conjugated Gd-DTPA in aqueous solutions. Effects of hydration water number q, diffusion coefficient D, magnetic field strength B0 and multiple rotational correlation times are explored with the simulations of the magnetization map. This method not only provides a simple and reliable approach to determine the dynamics of paramagnetic labeling of molecular/cellular events at high magnetic fields, but also a new strategy for spectral editing in NMR/MRI based on the dynamics of paramagnetic labeling in vivo.
Structural features that predict real-value fluctuations of globular proteins
Jamroz, Michal; Kolinski, Andrzej; Kihara, Daisuke
2012-01-01
It is crucial to consider dynamics for understanding the biological function of proteins. We used a large number of molecular dynamics trajectories of non-homologous proteins as references and examined static structural features of proteins that are most relevant to fluctuations. We examined correlation of individual structural features with fluctuations and further investigated effective combinations of features for predicting the real-value of residue fluctuations using the support vector regression. It was found that some structural features have higher correlation than crystallographic B-factors with fluctuations observed in molecular dynamics trajectories. Moreover, support vector regression that uses combinations of static structural features showed accurate prediction of fluctuations with an average Pearson’s correlation coefficient of 0.669 and a root mean square error of 1.04 Å. This correlation coefficient is higher than the one observed for the prediction by the Gaussian network model. An advantage of the developed method over the Gaussian network models is that the former predicts the real-value of fluctuation. The results help improve our understanding of relationships between protein structure and fluctuation. Furthermore, the developed method provides a convienient practial way to predict fluctuations of proteins using easily computed static structural features of proteins. PMID:22328193
Dynamic testing in schizophrenia: does training change the construct validity of a test?
Wiedl, Karl H; Schöttke, Henning; Green, Michael F; Nuechterlein, Keith H
2004-01-01
Dynamic testing typically involves specific interventions for a test to assess the extent to which test performance can be modified, beyond level of baseline (static) performance. This study used a dynamic version of the Wisconsin Card Sorting Test (WCST) that is based on cognitive remediation techniques within a test-training-test procedure. From results of previous studies with schizophrenia patients, we concluded that the dynamic and static versions of the WCST should have different construct validity. This hypothesis was tested by examining the patterns of correlations with measures of executive functioning, secondary verbal memory, and verbal intelligence. Results demonstrated a specific construct validity of WCST dynamic (i.e., posttest) scores as an index of problem solving (Tower of Hanoi) and secondary verbal memory and learning (Auditory Verbal Learning Test), whereas the impact of general verbal capacity and selective attention (Verbal IQ, Stroop Test) was reduced. It is concluded that the construct validity of the test changes with dynamic administration and that this difference helps to explain why the dynamic version of the WCST predicts functional outcome better than the static version.
Local structure in anisotropic systems determined by molecular dynamics simulation
NASA Astrophysics Data System (ADS)
Komolkin, Andrei V.; Maliniak, Arnold
In the present communication we describe the investigation of local structure using a new visualization technique. The approach is based on two-dimensional pair correlation functions derived from a molecular dynamics computer simulation. We have used this method to analyse a trajectory produced in a simulation of a nematic liquid crystal of 4-n-pentyl-4'-cyanobiphenyl (5CB) (Komolkin et al., 1994, J. chem. Phys., 101, 4103). The molecule is assumed to have cylindrical symmetry, and the liquid crystalline phase is treated as uniaxial. The pair correlation functions or cylindrical distribution functions (CDFs) are calculated in the molecular (m) and laboratory (l) frames, gm2(z1 2, d1 2) and g12(Z1 2, D1 2). Anisotropic molecular organization in the liquid crystal is reflected in laboratory frame CDFs. The molecular excluded volume is determined and the effect of the fast motion in the alkyl chain is observed. The intramolecular distributions are included in the CDFs and indicate the size of the motional amplitude in the chain. Absence of long range order was confirmed, a feature typical for a nematic liquid crystal.
Collision-induced light scattering in a thin xenon layer between graphite slabs - MD study.
Dawid, A; Górny, K; Wojcieszyk, D; Dendzik, Z; Gburski, Z
2014-08-14
The collision-induced light scattering many-body correlation functions and their spectra in thin xenon layer located between two parallel graphite slabs have been investigated by molecular dynamics computer simulations. The results have been obtained at three different distances (densities) between graphite slabs. Our simulations show the increased intensity of the interaction-induced light scattering spectra at low frequencies for xenon atoms in confined space, in comparison to the bulk xenon sample. Moreover, we show substantial dependence of the interaction-induced light scattering correlation functions of xenon on the distances between graphite slabs. The dynamics of xenon atoms in a confined space was also investigated by calculating the mean square displacement functions and related diffusion coefficients. The structural property of confined xenon layer was studied by calculating the density profile, perpendicular to the graphite slabs. Building of a fluid phase of xenon in the innermost part of the slot was observed. The nonlinear dependence of xenon diffusion coefficient on the separation distance between graphite slabs has been found. Copyright © 2014. Published by Elsevier B.V.
Characterizing water-metal interfaces and machine learning potential energy surfaces
NASA Astrophysics Data System (ADS)
Ryczko, Kevin
In this thesis, we first discuss the fundamentals of ab initio electronic structure theory and density functional theory (DFT). We also discuss statistics related to computing thermodynamic averages of molecular dynamics (MD). We then use this theory to analyze and compare the structural, dynamical, and electronic properties of liquid water next to prototypical metals including platinum, graphite, and graphene. Our results are built on Born-Oppenheimer molecular dynamics (BOMD) generated using density functional theory (DFT) which explicitly include van der Waals (vdW) interactions within a first principles approach. All calculations reported use large simulation cells, allowing for an accurate treatment of the water-electrode interfaces. We have included vdW interactions through the use of the optB86b-vdW exchange correlation functional. Comparisons with the Perdew-Burke-Ernzerhof (PBE) exchange correlation functional are also shown. We find an initial peak, due to chemisorption, in the density profile of the liquid water-Pt interface not seen in the liquid water-graphite interface, liquid watergraphene interface, nor interfaces studied previously. To further investigate this chemisorption peak, we also report differences in the electronic structure of single water molecules on both Pt and graphite surfaces. We find that a covalent bond forms between the single water molecule and the platinum surface, but not between the single water molecule and the graphite surface. We also discuss the effects that defects and dopants in the graphite and graphene surfaces have on the structure and dynamics of liquid water. Lastly, we introduce artificial neural networks (ANNs), and demonstrate how they can be used to machine learn electronic structure calculations. As a proof of principle, we show the success of an ANN potential energy surfaces for a dimer molecule with a Lennard-Jones potential.
Low-Dimensional Materials for Optoelectronic and Bioelectronic Applications
NASA Astrophysics Data System (ADS)
Hong, Tu
In this thesis, we first discuss the fundamentals of ab initio electronic structure theory and density functional theory (DFT). We also discuss statistics related to computing thermodynamic averages of molecular dynamics (MD). We then use this theory to analyze and compare the structural, dynamical, and electronic properties of liquid water next to prototypical metals including platinum, graphite, and graphene. Our results are built on Born-Oppenheimer molecular dynamics (BOMD) generated using density functional theory (DFT) which explicitly include van der Waals (vdW) interactions within a first principles approach. All calculations reported use large simulation cells, allowing for an accurate treatment of the water-electrode interfaces. We have included vdW interactions through the use of the optB86b-vdW exchange correlation functional. Comparisons with the Perdew-Burke-Ernzerhof (PBE) exchange correlation functional are also shown. We find an initial peak, due to chemisorption, in the density profile of the liquid water-Pt interface not seen in the liquid water-graphite interface, liquid watergraphene interface, nor interfaces studied previously. To further investigate this chemisorption peak, we also report differences in the electronic structure of single water molecules on both Pt and graphite surfaces. We find that a covalent bond forms between the single water molecule and the platinum surface, but not between the single water molecule and the graphite surface. We also discuss the effects that defects and dopants in the graphite and graphene surfaces have on the structure and dynamics of liquid water. Lastly, we introduce artificial neural networks (ANNs), and demonstrate how they can be used to machine learn electronic structure calculations. As a proof of principle, we show the success of an ANN potential energy surfaces for a dimer molecule with a Lennard-Jones potential.
Using network technology for studying the ionosphere
NASA Astrophysics Data System (ADS)
Yasyukevich, Yury; Zhivetiev, Ilya
2015-09-01
One of the key problems of ionosphere physics is the coupling between different ionospheric regions. We apply networks technology for studying the coupling of changing ionospheric dynamics in different regions. We used data from global ionosphere maps (GIM) of total electron content (TEC) produced by CODE for 2005-2010. Distribution of cross-correlation function maxima of TEC variations is not simple. This distribution allows us to reveal two levels of ionosphere coupling: "strong" (r>0.9) and "weak" (r>0.72). The ionosphere of the Arctic region upper 50° magnetic latitude is characterized by a "strong" coupling. In the Southern hemisphere, a similar region is bigger. "Weak" coupling is typical for the whole Southern hemisphere. In North America there is an area where TEC dynamics is "strongly" correlated inside and is not correlated with other ionospheric regions.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gabardi, Silvia; Caravati, Sebastiano; Bernasconi, Marco, E-mail: marco.bernasconi@mater.unimib.it
2016-05-28
We have investigated the structural, vibrational, and electronic properties of the amorphous phase of InSb and In{sub 3}SbTe{sub 2} compounds of interest for applications in phase change non-volatile memories. Models of the amorphous phase have been generated by quenching from the melt by molecular dynamics simulations based on density functional theory. In particular, we have studied the dependence of the structural properties on the choice of the exchange-correlation functional. It turns out that the use of the Becke-Lee-Yang-Parr functional provides models with a much larger fraction of In atoms in a tetrahedral bonding geometry with respect to previous results obtainedmore » with the most commonly used Perdew-Becke-Ernzerhof functional. This outcome is at odd with the properties of Ge{sub 2}Sb{sub 2}Te{sub 5} phase change compound for which the two exchange-correlation functionals yield very similar results on the structure of the amorphous phase.« less
NASA Astrophysics Data System (ADS)
Pereverzev, Andrey; Sewell, Tommy
2018-03-01
Lattice heat-current time correlation functions for insulators and semiconductors obtained using molecular dynamics (MD) simulations exhibit features of both pure exponential decay and oscillatory-exponential decay. For some materials the oscillatory terms contribute significantly to the lattice heat conductivity calculated from the correlation functions. However, the origin of the oscillatory terms is not well understood, and their contribution to the heat conductivity is accounted for by fitting them to empirical functions. Here, a translationally invariant expression for the heat current in terms of creation and annihilation operators is derived. By using this full phonon-picture definition of the heat current and applying the relaxation-time approximation we explain, at least in part, the origin of the oscillatory terms in the lattice heat-current correlation function. We discuss the relationship between the crystal Hamiltonian and the magnitude of the oscillatory terms. A solvable one-dimensional model is used to illustrate the potential importance of terms that are omitted in the commonly used phonon-picture expression for the heat current. While the derivations are fully quantum mechanical, classical-limit expressions are provided that enable direct contact with classical quantities obtainable from MD.
Linear and quadratic static response functions and structure functions in Yukawa liquids.
Magyar, Péter; Donkó, Zoltán; Kalman, Gabor J; Golden, Kenneth I
2014-08-01
We compute linear and quadratic static density response functions of three-dimensional Yukawa liquids by applying an external perturbation potential in molecular dynamics simulations. The response functions are also obtained from the equilibrium fluctuations (static structure factors) in the system via the fluctuation-dissipation theorems. The good agreement of the quadratic response functions, obtained in the two different ways, confirms the quadratic fluctuation-dissipation theorem. We also find that the three-point structure function may be factorizable into two-point structure functions, leading to a cluster representation of the equilibrium triplet correlation function.
Thompson, Garth John; Pan, Wen-Ju; Magnuson, Matthew Evan; Jaeger, Dieter; Keilholz, Shella Dawn
2014-01-01
Functional connectivity measurements from resting state blood-oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) are proving a powerful tool to probe both normal brain function and neuropsychiatric disorders. However, the neural mechanisms that coordinate these large networks are poorly understood, particularly in the context of the growing interest in network dynamics. Recent work in anesthetized rats has shown that the spontaneous BOLD fluctuations are tightly linked to infraslow local field potentials (LFPs) that are seldom recorded but comparable in frequency to the slow BOLD fluctuations. These findings support the hypothesis that long-range coordination involves low frequency neural oscillations and establishes infraslow LFPs as an excellent candidate for probing the neural underpinnings of the BOLD spatiotemporal patterns observed in both rats and humans. To further examine the link between large-scale network dynamics and infraslow LFPs, simultaneous fMRI and microelectrode recording were performed in anesthetized rats. Using an optimized filter to isolate shared components of the signals, we found that time-lagged correlation between infraslow LFPs and BOLD is comparable in spatial extent and timing to a quasi-periodic pattern (QPP) found from BOLD alone, suggesting that fMRI-measured QPPs and the infraslow LFPs share a common mechanism. As fMRI allows spatial resolution and whole brain coverage not available with electroencephalography, QPPs can be used to better understand the role of infraslow oscillations in normal brain function and neurological or psychiatric disorders. © 2013.
Thompson, Garth John; Pan, Wen-Ju; Magnuson, Matthew Evan; Jaeger, Dieter; Keilholz, Shella Dawn
2013-01-01
Functional connectivity measurements from resting state blood-oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) are proving a powerful tool to probe both normal brain function and neuropsychiatric disorders. However, the neural mechanisms that coordinate these large networks are poorly understood, particularly in the context of the growing interest in network dynamics. Recent work in anesthetized rats has shown that the spontaneous BOLD fluctuations are tightly linked to infraslow local field potentials (LFPs) that are seldom recorded but comparable in frequency to the slow BOLD fluctuations. These findings support the hypothesis that long-range coordination involves low frequency neural oscillations and establishes infraslow LFPs as an excellent candidate for probing the neural underpinnings of the BOLD spatiotemporal patterns observed in both rats and humans. To further examine the link between large-scale network dynamics and infraslow LFPs, simultaneous fMRI and microelectrode recording were performed in anesthetized rats. Using an optimized filter to isolate shared components of the signals, we found that time-lagged correlation between infraslow LFPs and BOLD is comparable in spatial extent and timing to a quasi-periodic pattern (QPP) found from BOLD alone, suggesting that fMRI-measured QPPs and the infraslow LFPs share a common mechanism. As fMRI allows spatial resolution and whole brain coverage not available with electroencephalography, QPPs can be used to better understand the role of infraslow oscillations in normal brain function and neurological or psychiatric disorders. PMID:24071524
A diagnostic for determining the quality of single-reference electron correlation methods
NASA Technical Reports Server (NTRS)
Lee, Timothy J.; Taylor, Peter R.
1989-01-01
It was recently proposed that the Euclidian norm of the t sub 1 vector of the coupled cluster wave function (normalized by the number of electrons included in the correlation procedure) could be used to determine whether a single-reference-based electron correlation procedure is appropriate. This diagnostic, T sub 1, is defined for use with self consistent field molecular orbitals and is invariant to the same orbital rotations as the coupled cluster energy. T sub 1 is investigated for several different chemical systems which exhibit a range of multireference behavior, and is shown to be an excellent measure of the importance of nondynamical electron correlation and is far superior to C sub 0 from a singles and doubles configuration interaction wave function. It is further suggested that when the aim is to recover a large fraction of the dynamical electron correlation energy, a large T sub 1 (i.e., greater than 0.02) probably indicates the need for a multireference electron correlation procedure.
A Gaussian theory for fluctuations in simple liquids.
Krüger, Matthias; Dean, David S
2017-04-07
Assuming an effective quadratic Hamiltonian, we derive an approximate, linear stochastic equation of motion for the density-fluctuations in liquids, composed of overdamped Brownian particles. From this approach, time dependent two point correlation functions (such as the intermediate scattering function) are derived. We show that this correlation function is exact at short times, for any interaction and, in particular, for arbitrary external potentials so that it applies to confined systems. Furthermore, we discuss the relation of this approach to previous ones, such as dynamical density functional theory as well as the formally exact treatment. This approach, inspired by the well known Landau-Ginzburg Hamiltonians, and the corresponding "Model B" equation of motion, may be seen as its microscopic version, containing information about the details on the particle level.
NASA Astrophysics Data System (ADS)
Weck, Philippe F.; Kim, Eunja; Greathouse, Jeffery A.; Gordon, Margaret E.; Bryan, Charles R.
2018-04-01
Elastic and thermodynamic properties of negative thermal expansion (NTE) α -ZrW2O8 have been calculated using PBEsol and PBE exchange-correlation functionals within the framework of density functional perturbation theory (DFPT). Measured elastic constants are reproduced within ∼ 2 % with PBEsol and ∼ 6 % with PBE. The thermal evolution of the Grüneisen parameter computed within the quasi-harmonic approximation exhibits negative values below the Debye temperature, consistent with observation. The standard molar heat capacity is predicted to be CP0 = 192.2 and 193.8 J mol-1K-1 with PBEsol and PBE, respectively. These results suggest superior accuracy of DFPT/PBEsol for studying the lattice dynamics, elasticity and thermodynamics of NTE materials.
A Gaussian theory for fluctuations in simple liquids
NASA Astrophysics Data System (ADS)
Krüger, Matthias; Dean, David S.
2017-04-01
Assuming an effective quadratic Hamiltonian, we derive an approximate, linear stochastic equation of motion for the density-fluctuations in liquids, composed of overdamped Brownian particles. From this approach, time dependent two point correlation functions (such as the intermediate scattering function) are derived. We show that this correlation function is exact at short times, for any interaction and, in particular, for arbitrary external potentials so that it applies to confined systems. Furthermore, we discuss the relation of this approach to previous ones, such as dynamical density functional theory as well as the formally exact treatment. This approach, inspired by the well known Landau-Ginzburg Hamiltonians, and the corresponding "Model B" equation of motion, may be seen as its microscopic version, containing information about the details on the particle level.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Liu, Qing; Shi, Chaowei; Yu, Lu
Internal backbone dynamic motions are essential for different protein functions and occur on a wide range of time scales, from femtoseconds to seconds. Molecular dynamic (MD) simulations and nuclear magnetic resonance (NMR) spin relaxation measurements are valuable tools to gain access to fast (nanosecond) internal motions. However, there exist few reports on correlation analysis between MD and NMR relaxation data. Here, backbone relaxation measurements of {sup 15}N-labeled SH3 (Src homology 3) domain proteins in aqueous buffer were used to generate general order parameters (S{sup 2}) using a model-free approach. Simultaneously, 80 ns MD simulations of SH3 domain proteins in amore » defined hydrated box at neutral pH were conducted and the general order parameters (S{sup 2}) were derived from the MD trajectory. Correlation analysis using the Gromos force field indicated that S{sup 2} values from NMR relaxation measurements and MD simulations were significantly different. MD simulations were performed on models with different charge states for three histidine residues, and with different water models, which were SPC (simple point charge) water model and SPC/E (extended simple point charge) water model. S{sup 2} parameters from MD simulations with charges for all three histidines and with the SPC/E water model correlated well with S{sup 2} calculated from the experimental NMR relaxation measurements, in a site-specific manner. - Highlights: • Correlation analysis between NMR relaxation measurements and MD simulations. • General order parameter (S{sup 2}) as common reference between the two methods. • Different protein dynamics with different Histidine charge states in neutral pH. • Different protein dynamics with different water models.« less
Halo correlations in nonlinear cosmic density fields
NASA Astrophysics Data System (ADS)
Bernardeau, F.; Schaeffer, R.
1999-09-01
The question we address in this paper is the determination of the correlation properties of the dark matter halos appearing in cosmic density fields once they underwent a strongly nonlinear evolution induced by gravitational dynamics. A series of previous works have given indications that kind of non-Gaussian features are induced by nonlinear evolution in term of the high-order correlation functions. Assuming such patterns for the matter field, i.e. that the high-order correlation functions behave as products of two-body correlation functions, we derive the correlation properties of the halos, that are assumed to represent the correlation properties of galaxies or clusters. The hierarchical pattern originally induced by gravity is shown to be conserved for the halos. The strength of their correlations at any order varies, however, but is found to depend only on their internal properties, namely on the parameter x~ m/r(3-gamma ) where m is the mass of the halo, r its size and gamma is the power law index of the two-body correlation function. This internal parameter is seen to be close to the depth of the internal potential well of virialized objects. We were able to derive the explicit form of the generating function of the moments of the halo counts probability distribution function. In particular we show explicitly that, generically, S_P(x)-> P(P-2) in the rare halo limit. Various illustrations of our general results are presented. As a function of the properties of the underlying matter field, we construct the count probabilities for halos and in particular discuss the halo void probability. We evaluate the dependence of the halo mass function on the environment: within clusters, hierarchical clustering implies the higher masses are favored. These properties solely arise from what is a natural bias (ie, naturally induced by gravity) between the observed objects and the unseen matter field, and how it manifests itself depending on which selection effects are imposed.
Individual Differences in Dynamic Functional Brain Connectivity across the Human Lifespan.
Davison, Elizabeth N; Turner, Benjamin O; Schlesinger, Kimberly J; Miller, Michael B; Grafton, Scott T; Bassett, Danielle S; Carlson, Jean M
2016-11-01
Individual differences in brain functional networks may be related to complex personal identifiers, including health, age, and ability. Dynamic network theory has been used to identify properties of dynamic brain function from fMRI data, but the majority of analyses and findings remain at the level of the group. Here, we apply hypergraph analysis, a method from dynamic network theory, to quantify individual differences in brain functional dynamics. Using a summary metric derived from the hypergraph formalism-hypergraph cardinality-we investigate individual variations in two separate, complementary data sets. The first data set ("multi-task") consists of 77 individuals engaging in four consecutive cognitive tasks. We observe that hypergraph cardinality exhibits variation across individuals while remaining consistent within individuals between tasks; moreover, the analysis of one of the memory tasks revealed a marginally significant correspondence between hypergraph cardinality and age. This finding motivated a similar analysis of the second data set ("age-memory"), in which 95 individuals, aged 18-75, performed a memory task with a similar structure to the multi-task memory task. With the increased age range in the age-memory data set, the correlation between hypergraph cardinality and age correspondence becomes significant. We discuss these results in the context of the well-known finding linking age with network structure, and suggest that hypergraph analysis should serve as a useful tool in furthering our understanding of the dynamic network structure of the brain.
Li, Ailin; Tian, Ziqi; Yan, Tianying; Jiang, De-en; Dai, Sheng
2014-12-26
The structure and dynamics of a task-specific ionic liquid (TSIL), trihexyl(tetradecyl)phosphonium imidazolate, before and after absorbing CO(2) were studied with a molecular dynamics (MD) simulation. This particular ionic liquid is one of several newly discovered azole-based TSILs for equimolar CO(2) capture. Unlike other TSILs whose viscosity increases drastically upon reaction with CO(2), its viscosity decreases after CO(2) absorption. This unique behavior was confirmed in our MD simulation. We find that after CO(2) absorption the translational dynamics of the whole system is accelerated, accompanied by an accelerated rotational dynamics of the cations. Radial distribution function and spatial distribution function analyses show that the anions become asymmetric after reaction with CO(2), and this causes the imbalance of the interaction between the positive and negative regions of the ions. The interaction between the phosphorus atom of the cation and oxygen atoms of the carboxyl group on the anion is enhanced, while that between the phosphorus atom and the naked nitrogen atom of the anion is weakened. The ion-pair correlation functions further support that the weakened interaction leads to faster dissociation of cation-anion pairs, thereby causing an accelerated dynamics. Hence, the asymmetry of anions influences the dynamics of the system and affects the viscosity. This insight may help design better TSILs with decreased viscosity for CO(2) capture.
Neural field theory of perceptual echo and implications for estimating brain connectivity
NASA Astrophysics Data System (ADS)
Robinson, P. A.; Pagès, J. C.; Gabay, N. C.; Babaie, T.; Mukta, K. N.
2018-04-01
Neural field theory is used to predict and analyze the phenomenon of perceptual echo in which random input stimuli at one location are correlated with electroencephalographic responses at other locations. It is shown that this echo correlation (EC) yields an estimate of the transfer function from the stimulated point to other locations. Modal analysis then explains the observed spatiotemporal structure of visually driven EC and the dominance of the alpha frequency; two eigenmodes of similar amplitude dominate the response, leading to temporal beating and a line of low correlation that runs from the crown of the head toward the ears. These effects result from mode splitting and symmetry breaking caused by interhemispheric coupling and cortical folding. It is shown how eigenmodes obtained from functional magnetic resonance imaging experiments can be combined with temporal dynamics from EC or other evoked responses to estimate the spatiotemporal transfer function between any two points and hence their effective connectivity.
Network Dynamics Underlying Speed-Accuracy Trade-Offs in Response to Errors
Agam, Yigal; Carey, Caitlin; Barton, Jason J. S.; Dyckman, Kara A.; Lee, Adrian K. C.; Vangel, Mark; Manoach, Dara S.
2013-01-01
The ability to dynamically and rapidly adjust task performance based on its outcome is fundamental to adaptive, flexible behavior. Over trials of a task, responses speed up until an error is committed and after the error responses slow down. These dynamic adjustments serve to optimize performance and are well-described by the speed-accuracy trade-off (SATO) function. We hypothesized that SATOs based on outcomes reflect reciprocal changes in the allocation of attention between the internal milieu and the task-at-hand, as indexed by reciprocal changes in activity between the default and dorsal attention brain networks. We tested this hypothesis using functional MRI to examine the pattern of network activation over a series of trials surrounding and including an error. We further hypothesized that these reciprocal changes in network activity are coordinated by the posterior cingulate cortex (PCC) and would rely on the structural integrity of its white matter connections. Using diffusion tensor imaging, we examined whether fractional anisotropy of the posterior cingulum bundle correlated with the magnitude of reciprocal changes in network activation around errors. As expected, reaction time (RT) in trials surrounding errors was consistent with predictions from the SATO function. Activation in the default network was: (i) inversely correlated with RT, (ii) greater on trials before than after an error and (iii) maximal at the error. In contrast, activation in the right intraparietal sulcus of the dorsal attention network was (i) positively correlated with RT and showed the opposite pattern: (ii) less activation before than after an error and (iii) the least activation on the error. Greater integrity of the posterior cingulum bundle was associated with greater reciprocity in network activation around errors. These findings suggest that dynamic changes in attention to the internal versus external milieu in response to errors underlie SATOs in RT and are mediated by the PCC. PMID:24069223
NASA Astrophysics Data System (ADS)
Campos, João Guilherme Ferreira; Costa, Ariadne de Andrade; Copelli, Mauro; Kinouchi, Osame
2017-04-01
In a recent work, mean-field analysis and computer simulations were employed to analyze critical self-organization in networks of excitable cellular automata where randomly chosen synapses in the network were depressed after each spike (the so-called annealed dynamics). Calculations agree with simulations of the annealed version, showing that the nominal branching ratio σ converges to unity in the thermodynamic limit, as expected of a self-organized critical system. However, the question remains whether the same results apply to the biological case where only the synapses of firing neurons are depressed (the so-called quenched dynamics). We show that simulations of the quenched model yield significant deviations from σ =1 due to spatial correlations. However, the model is shown to be critical, as the largest eigenvalue of the synaptic matrix approaches unity in the thermodynamic limit, that is, λc=1 . We also study the finite size effects near the critical state as a function of the parameters of the synaptic dynamics.
NASA Astrophysics Data System (ADS)
Samuel, Boni; Retheesh, R.; Zaheer Ansari, Md; Nampoori, V. P. N.; Radhakrishnan, P.; Mujeeb, A.
2017-10-01
Quality evaluation of fruits and vegetables is of great concern as there is a shortage of unadulterated items on the market. Even unadulterated fruits and vegetables, especially those with soft tissue, cannot be stored for longer times due to physical and chemical changes. Moreover, damage can occur during harvest and in the post-harvest period, while preserving or transporting the fruits and vegetables. This work describes the use of a laser dynamic speckle imaging technique as a powerful optoelectronic tool for the quality evaluation of certain seasonal fruits and vegetables in an Indian market. A simple optical configuration was designed for developing the dynamic speckle imagining system to record dynamic specklegrams of the specimens under different conditions. These images were analysed using a cross-correlation function and the temporal history of specklegrams. The technique can be effectively adapted to the industrial environment and would be beneficial for all stakeholders in the field.
NASA Astrophysics Data System (ADS)
Mei, Dongcheng; Xie, Chongwei; Zhang, Li
2003-11-01
We study the effects of correlations between additive and multiplicative noise on relaxation time in a bistable system driven by cross-correlated noise. Using the projection-operator method, we derived an analytic expression for the relaxation time Tc of the system, which is the function of additive (α) and multiplicative (D) noise intensities, correlation intensity λ of noise, and correlation time τ of noise. After introducing a noise intensity ratio and a dimensionless parameter R=D/α, and then performing numerical computations, we find the following: (i) For the case of R<1, the relaxation time Tc increases as R increases. (ii) For the cases of R⩾1, there is a one-peak structure on the Tc-R plot and the effects of cross-correlated noise on the relaxation time are very notable. (iii) For the case of R<1, Tc almost does not change with both λ and τ, and for the cases of R⩾1, Tc decreases as λ increases, however Tc increases as τ increases. λ and τ play opposite roles in Tc, i.e., λ enhances the fluctuation decay of dynamical variable and τ slows down the fluctuation decay of dynamical variable.
NASA Astrophysics Data System (ADS)
Mathias, Gerald; Egwolf, Bernhard; Nonella, Marco; Tavan, Paul
2003-06-01
We present a combination of the structure adapted multipole method with a reaction field (RF) correction for the efficient evaluation of electrostatic interactions in molecular dynamics simulations under periodic boundary conditions. The algorithm switches from an explicit electrostatics evaluation to a continuum description at the maximal distance that is consistent with the minimum image convention, and, thus, avoids the use of a periodic electrostatic potential. A physically motivated switching function enables charge clusters interacting with a given charge to smoothly move into the solvent continuum by passing through the spherical dielectric boundary surrounding this charge. This transition is complete as soon as the cluster has reached the so-called truncation radius Rc. The algorithm is used to examine the dependence of thermodynamic properties and correlation functions on Rc in the three point transferable intermolecular potential water model. Our test simulations on pure liquid water used either the RF correction or a straight cutoff and values of Rc ranging from 14 Å to 40 Å. In the RF setting, the thermodynamic properties and the correlation functions show convergence for Rc increasing towards 40 Å. In the straight cutoff case no such convergence is found. Here, in particular, the dipole-dipole correlation functions become completely artificial. The RF description of the long-range electrostatics is verified by comparison with the results of a particle-mesh Ewald simulation at identical conditions.
Stellar dynamics around a massive black hole - II. Resonant relaxation
NASA Astrophysics Data System (ADS)
Sridhar, S.; Touma, Jihad R.
2016-06-01
We present a first-principles theory of resonant relaxation (RR) of a low-mass stellar system orbiting a more massive black hole (MBH). We first extend the kinetic theory of Gilbert to include the Keplerian field of a black hole of mass M•. Specializing to a Keplerian stellar system of mass M ≪ M•, we use the orbit-averaging method of Sridhar & Touma to derive a kinetic equation for RR. This describes the collisional evolution of a system of N ≫ 1 Gaussian rings in a reduced 5-dim space, under the combined actions of self-gravity, 1 post-Newtonian (PN) and 1.5 PN relativistic effects of the MBH and an arbitrary external potential. In general geometries, RR is driven by both apsidal and nodal resonances, so the distinction between scalar RR and vector RR disappears. The system passes through a sequence of quasi-steady secular collisionless equilibria, driven by irreversible two-ring correlations that accrue through gravitational interactions, both direct and collective. This correlation function is related to a `wake function', which is the linear response of the system to the perturbation of a chosen ring. The wake function is easier to appreciate, and satisfies a simpler equation, than the correlation function. We discuss general implications for the interplay of secular dynamics and non-equilibrium statistical mechanics in the evolution of Keplerian stellar systems towards secular thermodynamic equilibria, and set the stage for applications to the RR of axisymmetric discs in Paper III.
On an aggregation in birth-and-death stochastic dynamics
NASA Astrophysics Data System (ADS)
Finkelshtein, Dmitri; Kondratiev, Yuri; Kutoviy, Oleksandr; Zhizhina, Elena
2014-06-01
We consider birth-and-death stochastic dynamics of particle systems with attractive interaction. The heuristic generator of the dynamics has a constant birth rate and density-dependent decreasing death rate. The corresponding statistical dynamics is constructed. Using the Vlasov-type scaling we derive the limiting mesoscopic evolution and prove that this evolution propagates chaos. We study a nonlinear non-local kinetic equation for the first correlation function (density of population). The existence of uniformly bounded solutions as well as solutions growing inside of a bounded domain and expanding in the space are shown. These solutions describe two regimes in the mesoscopic system: regulation and aggregation.
Thermalization dynamics of two correlated bosonic quantum wires after a split
NASA Astrophysics Data System (ADS)
Huber, Sebastian; Buchhold, Michael; Schmiedmayer, Jörg; Diehl, Sebastian
2018-04-01
Cherently splitting a one-dimensional Bose gas provides an attractive, experimentally established platform to investigate many-body quantum dynamics. At short enough times, the dynamics is dominated by the dephasing of single quasiparticles, and well described by the relaxation towards a generalized Gibbs ensemble corresponding to the free Luttinger theory. At later times on the other hand, the approach to a thermal Gibbs ensemble is expected for a generic, interacting quantum system. Here, we go one step beyond the quadratic Luttinger theory and include the leading phonon-phonon interactions. By applying kinetic theory and nonequilibrium Dyson-Schwinger equations, we analyze the full relaxation dynamics beyond dephasing and determine the asymptotic thermalization process in the two-wire system for a symmetric splitting protocol. The major observables are the different phonon occupation functions and the experimentally accessible coherence factor, as well as the phase correlations between the two wires. We demonstrate that, depending on the splitting protocol, the presence of phonon collisions can have significant influence on the asymptotic evolution of these observables, which makes the corresponding thermalization dynamics experimentally accessible.
Dynamic scaling in natural swarms
NASA Astrophysics Data System (ADS)
Cavagna, Andrea; Conti, Daniele; Creato, Chiara; Del Castello, Lorenzo; Giardina, Irene; Grigera, Tomas S.; Melillo, Stefania; Parisi, Leonardo; Viale, Massimiliano
2017-09-01
Collective behaviour in biological systems presents theoretical challenges beyond the borders of classical statistical physics. The lack of concepts such as scaling and renormalization is particularly problematic, as it forces us to negotiate details whose relevance is often hard to assess. In an attempt to improve this situation, we present here experimental evidence of the emergence of dynamic scaling laws in natural swarms of midges. We find that spatio-temporal correlation functions in different swarms can be rescaled by using a single characteristic time, which grows with the correlation length with a dynamical critical exponent z ~ 1, a value not found in any other standard statistical model. To check whether out-of-equilibrium effects may be responsible for this anomalous exponent, we run simulations of the simplest model of self-propelled particles and find z ~ 2, suggesting that natural swarms belong to a novel dynamic universality class. This conclusion is strengthened by experimental evidence of the presence of non-dissipative modes in the relaxation, indicating that previously overlooked inertial effects are needed to describe swarm dynamics. The absence of a purely dissipative regime suggests that natural swarms undergo a near-critical censorship of hydrodynamics.
Dynamic Singularity Spectrum Distribution of Sea Clutter
NASA Astrophysics Data System (ADS)
Xiong, Gang; Yu, Wenxian; Zhang, Shuning
2015-12-01
The fractal and multifractal theory have provided new approaches for radar signal processing and target-detecting under the background of ocean. However, the related research mainly focuses on fractal dimension or multifractal spectrum (MFS) of sea clutter. In this paper, a new dynamic singularity analysis method of sea clutter using MFS distribution is developed, based on moving detrending analysis (DMA-MFSD). Theoretically, we introduce the time information by using cyclic auto-correlation of sea clutter. For transient correlation series, the instantaneous singularity spectrum based on multifractal detrending moving analysis (MF-DMA) algorithm is calculated, and the dynamic singularity spectrum distribution of sea clutter is acquired. In addition, we analyze the time-varying singularity exponent ranges and maximum position function in DMA-MFSD of sea clutter. For the real sea clutter data, we analyze the dynamic singularity spectrum distribution of real sea clutter in level III sea state, and conclude that the radar sea clutter has the non-stationary and time-varying scale characteristic and represents the time-varying singularity spectrum distribution based on the proposed DMA-MFSD method. The DMA-MFSD will also provide reference for nonlinear dynamics and multifractal signal processing.
Mode localization in the cooperative dynamics of protein recognition
NASA Astrophysics Data System (ADS)
Copperman, J.; Guenza, M. G.
2016-07-01
The biological function of proteins is encoded in their structure and expressed through the mediation of their dynamics. This paper presents a study on the correlation between local fluctuations, binding, and biological function for two sample proteins, starting from the Langevin Equation for Protein Dynamics (LE4PD). The LE4PD is a microscopic and residue-specific coarse-grained approach to protein dynamics, which starts from the static structural ensemble of a protein and predicts the dynamics analytically. It has been shown to be accurate in its prediction of NMR relaxation experiments and Debye-Waller factors. The LE4PD is solved in a set of diffusive modes which span a vast range of time scales of the protein dynamics, and provides a detailed picture of the mode-dependent localization of the fluctuation as a function of the primary structure of the protein. To investigate the dynamics of protein complexes, the theory is implemented here to treat the coarse-grained dynamics of interacting macromolecules. As an example, calculations of the dynamics of monomeric and dimerized HIV protease and the free Insulin Growth Factor II Receptor (IGF2R) domain 11 and its IGF2R:IGF2 complex are presented. Either simulation-derived or experimentally measured NMR conformers are used as input structural ensembles to the theory. The picture that emerges suggests a dynamical heterogeneous protein where biologically active regions provide energetically comparable conformational states that are trapped by a reacting partner in agreement with the conformation-selection mechanism of binding.
Dynamical Crossovers in Prethermal Critical States.
Chiocchetta, Alessio; Gambassi, Andrea; Diehl, Sebastian; Marino, Jamir
2017-03-31
We study the prethermal dynamics of an interacting quantum field theory with an N-component order parameter and O(N) symmetry, suddenly quenched in the vicinity of a dynamical critical point. Depending on the initial conditions, the evolution of the order parameter, and of the response and correlation functions, can exhibit a temporal crossover between universal dynamical scaling regimes governed, respectively, by a quantum and a classical prethermal fixed point, as well as a crossover from a Gaussian to a non-Gaussian prethermal dynamical scaling. Together with a recent experiment, this suggests that quenches may be used in order to explore the rich variety of dynamical critical points occurring in the nonequilibrium dynamics of a quantum many-body system. We illustrate this fact by using a combination of renormalization group techniques and a nonperturbative large-N limit.
NASA Astrophysics Data System (ADS)
Adjei-Acheamfour, Mischa; Storek, Michael; Böhmer, Roland
2017-05-01
Previous deuteron nuclear magnetic resonance studies revealed conflicting evidence regarding the possible motional heterogeneity of the water dynamics on the hydrate lattice of an ice-like crystal. Using oxygen-17 nuclei as a sensitive quadrupolar probe, the reorientational two-time correlation function displays a clear nonexponentiality. To check whether this dispersive behavior is a consequence of dynamic heterogeneity or rather of an intrinsic nonexponentiality, a multidimensional, four-time magnetic resonance experiment was devised that is generally applicable to strongly quadrupolarly perturbed half-integer nuclei such as oxygen-17. Measurements of an appropriate four-time function demonstrate that it is possible to select a subensemble of slow water molecules. Its mean time scale is compared to theoretical predictions and evidence for significant motional heterogeneity is found.
Supramolecular Systems Behavior at the Air-Water Interface. Molecular Dynamic Simulation Study.
NASA Astrophysics Data System (ADS)
Sandoval, C.; Saavedra, M.; Gargallo, L.; Radić, D.
2008-08-01
Atomistic molecular dynamics simulation (MDS) was development to investigate the structural and dynamic properties of a monolayer of supramolecular systems. The simulations were performed at room temperature, on inclusion complexes (ICs) of α-cyclodextrin (CD) with poly(ethylene-oxide)(PEO), poly(ɛ-caprolactone)(PEC) and poly(tetrahydrofuran)(PTHF). The simulations were carried out for a surface area of 30Å. The trajectories of the MDS show that the system more stable was IC-PEC, being the less stable IC-PEO. The disordered monolayer for the systems was proved by the orientation correlation function and the radial distribution function between the polar groups of ICs and the water molecules. We found that the system IC-PEC was more stable that the systems IC-PTHF and IC-PEO.
iCI: Iterative CI toward full CI.
Liu, Wenjian; Hoffmann, Mark R
2016-03-08
It is shown both theoretically and numerically that the minimal multireference configuration interaction (CI) approach [Liu, W.; Hoffmann, M. R. Theor. Chem. Acc. 2014, 133, 1481] converges quickly and monotonically from above to full CI by updating the primary, external, and secondary states that describe the respective static, dynamic, and again static components of correlation iteratively, even when starting with a rather poor description of a strongly correlated system. In short, the iterative CI (iCI) is a very effective means toward highly correlated wave functions and, ultimately, full CI.
Phase dependence of the unnormalized second-order photon correlation function
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ciornea, V.; Bardetski, P.; Macovei, M. A., E-mail: macovei@phys.asm.md
2016-10-15
We investigate the resonant quantum dynamics of a multi-qubit ensemble in a microcavity. Both the quantum-dot subsystem and the microcavity mode are pumped coherently. We find that the microcavity photon statistics depends on the phase difference of the driving lasers, which is not the case for the photon intensity at resonant driving. This way, one can manipulate the two-photon correlations. In particular, higher degrees of photon correlations and, eventually, stronger intensities are obtained. Furthermore, the microcavity photon statistics exhibits steady-state oscillatory behaviors as well as asymmetries.
NASA Astrophysics Data System (ADS)
Encarnación, Medina-Carmona; Palomino-Morales, Rogelio J.; Fuchs, Julian E.; Esperanza, Padín-Gonzalez; Noel, Mesa-Torres; Salido, Eduardo; Timson, David J.; Pey, Angel L.
2016-02-01
Protein dynamics is essential to understand protein function and stability, even though is rarely investigated as the origin of loss-of-function due to genetic variations. Here, we use biochemical, biophysical, cell and computational biology tools to study two loss-of-function and cancer-associated polymorphisms (p.R139W and p.P187S) in human NAD(P)H quinone oxidoreductase 1 (NQO1), a FAD-dependent enzyme which activates cancer pro-drugs and stabilizes several oncosuppressors. We show that p.P187S strongly destabilizes the NQO1 dimer in vitro and increases the flexibility of the C-terminal domain, while a combination of FAD and the inhibitor dicoumarol overcome these alterations. Additionally, changes in global stability due to polymorphisms and ligand binding are linked to the dynamics of the dimer interface, whereas the low activity and affinity for FAD in p.P187S is caused by increased fluctuations at the FAD binding site. Importantly, NQO1 steady-state protein levels in cell cultures correlate primarily with the dynamics of the C-terminal domain, supporting a directional preference in NQO1 proteasomal degradation and the use of ligands binding to this domain to stabilize p.P187S in vivo. In conclusion, protein dynamics are fundamental to understanding loss-of-function in p.P187S, and to develop new pharmacological therapies to rescue this function.
Liu, Jian; Miller, William H
2007-06-21
It is shown how quantum mechanical time correlation functions [defined, e.g., in Eq. (1.1)] can be expressed, without approximation, in the same form as the linearized approximation of the semiclassical initial value representation (LSC-IVR), or classical Wigner model, for the correlation function [cf. Eq. (2.1)], i.e., as a phase space average (over initial conditions for trajectories) of the Wigner functions corresponding to the two operators. The difference is that the trajectories involved in the LSC-IVR evolve classically, i.e., according to the classical equations of motion, while in the exact theory they evolve according to generalized equations of motion that are derived here. Approximations to the exact equations of motion are then introduced to achieve practical methods that are applicable to complex (i.e., large) molecular systems. Four such methods are proposed in the paper--the full Wigner dynamics (full WD) and the second order WD based on "Wigner trajectories" [H. W. Lee and M. D. Scully, J. Chem. Phys. 77, 4604 (1982)] and the full Donoso-Martens dynamics (full DMD) and the second order DMD based on "Donoso-Martens trajectories" [A. Donoso and C. C. Martens, Phys. Rev. Lett. 8722, 223202 (2001)]--all of which can be viewed as generalizations of the original LSC-IVR method. Numerical tests of the four versions of this new approach are made for two anharmonic model problems, and for each the momentum autocorrelation function (i.e., operators linear in coordinate or momentum operators) and the force autocorrelation function (nonlinear operators) have been calculated. These four new approximate treatments are indeed seen to be significant improvements to the original LSC-IVR approximation.
Spectral simplicity of apparent complexity. I. The nondiagonalizable metadynamics of prediction
NASA Astrophysics Data System (ADS)
Riechers, Paul M.; Crutchfield, James P.
2018-03-01
Virtually all questions that one can ask about the behavioral and structural complexity of a stochastic process reduce to a linear algebraic framing of a time evolution governed by an appropriate hidden-Markov process generator. Each type of question—correlation, predictability, predictive cost, observer synchronization, and the like—induces a distinct generator class. Answers are then functions of the class-appropriate transition dynamic. Unfortunately, these dynamics are generically nonnormal, nondiagonalizable, singular, and so on. Tractably analyzing these dynamics relies on adapting the recently introduced meromorphic functional calculus, which specifies the spectral decomposition of functions of nondiagonalizable linear operators, even when the function poles and zeros coincide with the operator's spectrum. Along the way, we establish special properties of the spectral projection operators that demonstrate how they capture the organization of subprocesses within a complex system. Circumventing the spurious infinities of alternative calculi, this leads in the sequel, Part II [P. M. Riechers and J. P. Crutchfield, Chaos 28, 033116 (2018)], to the first closed-form expressions for complexity measures, couched either in terms of the Drazin inverse (negative-one power of a singular operator) or the eigenvalues and projection operators of the appropriate transition dynamic.
An optimal strategy for functional mapping of dynamic trait loci.
Jin, Tianbo; Li, Jiahan; Guo, Ying; Zhou, Xiaojing; Yang, Runqing; Wu, Rongling
2010-02-01
As an emerging powerful approach for mapping quantitative trait loci (QTLs) responsible for dynamic traits, functional mapping models the time-dependent mean vector with biologically meaningful equations and are likely to generate biologically relevant and interpretable results. Given the autocorrelation nature of a dynamic trait, functional mapping needs the implementation of the models for the structure of the covariance matrix. In this article, we have provided a comprehensive set of approaches for modelling the covariance structure and incorporated each of these approaches into the framework of functional mapping. The Bayesian information criterion (BIC) values are used as a model selection criterion to choose the optimal combination of the submodels for the mean vector and covariance structure. In an example for leaf age growth from a rice molecular genetic project, the best submodel combination was found between the Gaussian model for the correlation structure, power equation of order 1 for the variance and the power curve for the mean vector. Under this combination, several significant QTLs for leaf age growth trajectories were detected on different chromosomes. Our model can be well used to study the genetic architecture of dynamic traits of agricultural values.
Rashid, Barnaly; Damaraju, Eswar; Pearlson, Godfrey D; Calhoun, Vince D
2014-01-01
Schizophrenia (SZ) and bipolar disorder (BP) share significant overlap in clinical symptoms, brain characteristics, and risk genes, and both are associated with dysconnectivity among large-scale brain networks. Resting state functional magnetic resonance imaging (rsfMRI) data facilitates studying macroscopic connectivity among distant brain regions. Standard approaches to identifying such connectivity include seed-based correlation and data-driven clustering methods such as independent component analysis (ICA) but typically focus on average connectivity. In this study, we utilize ICA on rsfMRI data to obtain intrinsic connectivity networks (ICNs) in cohorts of healthy controls (HCs) and age matched SZ and BP patients. Subsequently, we investigated difference in functional network connectivity, defined as pairwise correlations among the timecourses of ICNs, between HCs and patients. We quantified differences in both static (average) and dynamic (windowed) connectivity during the entire scan duration. Disease-specific differences were identified in connectivity within different dynamic states. Notably, results suggest that patients make fewer transitions to some states (states 1, 2, and 4) compared to HCs, with most such differences confined to a single state. SZ patients showed more differences from healthy subjects than did bipolars, including both hyper and hypo connectivity in one common connectivity state (dynamic state 3). Also group differences between SZ and bipolar patients were identified in patterns (states) of connectivity involving the frontal (dynamic state 1) and frontal-parietal regions (dynamic state 3). Our results provide new information about these illnesses and strongly suggest that state-based analyses are critical to avoid averaging together important factors that can help distinguish these clinical groups.
Yang, Anxiong; Stingl, Michael; Berry, David A.; Lohscheller, Jörg; Voigt, Daniel; Eysholdt, Ulrich; Döllinger, Michael
2011-01-01
With the use of an endoscopic, high-speed camera, vocal fold dynamics may be observed clinically during phonation. However, observation and subjective judgment alone may be insufficient for clinical diagnosis and documentation of improved vocal function, especially when the laryngeal disease lacks any clear morphological presentation. In this study, biomechanical parameters of the vocal folds are computed by adjusting the corresponding parameters of a three-dimensional model until the dynamics of both systems are similar. First, a mathematical optimization method is presented. Next, model parameters (such as pressure, tension and masses) are adjusted to reproduce vocal fold dynamics, and the deduced parameters are physiologically interpreted. Various combinations of global and local optimization techniques are attempted. Evaluation of the optimization procedure is performed using 50 synthetically generated data sets. The results show sufficient reliability, including 0.07 normalized error, 96% correlation, and 91% accuracy. The technique is also demonstrated on data from human hemilarynx experiments, in which a low normalized error (0.16) and high correlation (84%) values were achieved. In the future, this technique may be applied to clinical high-speed images, yielding objective measures with which to document improved vocal function of patients with voice disorders. PMID:21877808
Circadian rhythms and fractal fluctuations in forearm motion
NASA Astrophysics Data System (ADS)
Hu, Kun; Hilton, Michael F.
2005-03-01
Recent studies have shown that the circadian pacemaker --- an internal body clock located in the brain which is normally synchronized with the sleep/wake behavioral cycles --- influences key physiologic functions such as the body temperature, hormone secretion and heart rate. Surprisingly, no previous studies have investigated whether the circadian pacemaker impacts human motor activity --- a fundamental physiologic function. We investigate high-frequency actigraph recordings of forearm motion from a group of young and healthy subjects during a forced desynchrony protocol which allows to decouple the sleep/wake cycles from the endogenous circadian cycle while controlling scheduled behaviors. We investigate both static properties (mean value, standard deviation), dynamical characteristics (long-range correlations), and nonlinear features (magnitude and Fourier-phase correlations) in the fluctuations of forearm acceleration across different circadian phases. We demonstrate that while the static properties exhibit significant circadian rhythms with a broad peak in the afternoon, the dynamical and nonlinear characteristics remain invariant with circadian phase. This finding suggests an intrinsic multi-scale dynamic regulation of forearm motion the mechanism of which is not influenced by the circadian pacemaker, thus suggesting that increased cardiac risk in the early morning hours is not related to circadian-mediated influences on motor activity.
Service climate as a mediator of organizational empowerment in customer-service employees.
Mendoza-Sierra, Maria Isabel; Orgambídez-Ramos, Alejandro; Carrasco-González, Ana María; León-Jariego, José Carlos
2014-01-01
The aim of this study is to examine the mediating role of the service climate between organizational empowerment (i.e., dynamic structural framework, control of workplace decisions, fluidity in information sharing) and service quality (functional and relational). 428 contact employees from 46 hotels participated in the survey. Correlations demonstrated that dynamic structural framework, control decisions, and fluidity in information sharing are related to both functional and relational service quality. Regression analyses and Sobel tests revealed that service climate totally mediated the relationship between all three dimensions of organizational empowerment and relational service quality. Implications for practice and future research are discussed.
Different dynamic resting state fMRI patterns are linked to different frequencies of neural activity
Thompson, Garth John; Pan, Wen-Ju
2015-01-01
Resting state functional magnetic resonance imaging (rsfMRI) results have indicated that network mapping can contribute to understanding behavior and disease, but it has been difficult to translate the maps created with rsfMRI to neuroelectrical states in the brain. Recently, dynamic analyses have revealed multiple patterns in the rsfMRI signal that are strongly associated with particular bands of neural activity. To further investigate these findings, simultaneously recorded invasive electrophysiology and rsfMRI from rats were used to examine two types of electrical activity (directly measured low-frequency/infraslow activity and band-limited power of higher frequencies) and two types of dynamic rsfMRI (quasi-periodic patterns or QPP, and sliding window correlation or SWC). The relationship between neural activity and dynamic rsfMRI was tested under three anesthetic states in rats: dexmedetomidine and high and low doses of isoflurane. Under dexmedetomidine, the lightest anesthetic, infraslow electrophysiology correlated with QPP but not SWC, whereas band-limited power in higher frequencies correlated with SWC but not QPP. Results were similar under isoflurane; however, the QPP was also correlated to band-limited power, possibly due to the burst-suppression state induced by the anesthetic agent. The results provide additional support for the hypothesis that the two types of dynamic rsfMRI are linked to different frequencies of neural activity, but isoflurane anesthesia may make this relationship more complicated. Understanding which neural frequency bands appear as particular dynamic patterns in rsfMRI may ultimately help isolate components of the rsfMRI signal that are of interest to disorders such as schizophrenia and attention deficit disorder. PMID:26041826
Surveillance system and method having an adaptive sequential probability fault detection test
NASA Technical Reports Server (NTRS)
Herzog, James P. (Inventor); Bickford, Randall L. (Inventor)
2005-01-01
System and method providing surveillance of an asset such as a process and/or apparatus by providing training and surveillance procedures that numerically fit a probability density function to an observed residual error signal distribution that is correlative to normal asset operation and then utilizes the fitted probability density function in a dynamic statistical hypothesis test for providing improved asset surveillance.
Surveillance system and method having an adaptive sequential probability fault detection test
NASA Technical Reports Server (NTRS)
Bickford, Randall L. (Inventor); Herzog, James P. (Inventor)
2006-01-01
System and method providing surveillance of an asset such as a process and/or apparatus by providing training and surveillance procedures that numerically fit a probability density function to an observed residual error signal distribution that is correlative to normal asset operation and then utilizes the fitted probability density function in a dynamic statistical hypothesis test for providing improved asset surveillance.
Surveillance System and Method having an Adaptive Sequential Probability Fault Detection Test
NASA Technical Reports Server (NTRS)
Bickford, Randall L. (Inventor); Herzog, James P. (Inventor)
2008-01-01
System and method providing surveillance of an asset such as a process and/or apparatus by providing training and surveillance procedures that numerically fit a probability density function to an observed residual error signal distribution that is correlative to normal asset operation and then utilizes the fitted probability density function in a dynamic statistical hypothesis test for providing improved asset surveillance.
Molecular dynamics and vibrational relaxations in liquid nitromethane.
NASA Astrophysics Data System (ADS)
Grazia Giorgini, Maria; Mariani, Leonardo; Morresi, Assunta; Paliani, Giulio; Cataliotti, Rosario Sergio
The vibrational relaxation processes of totally symmetric v1 (CH stretching and v5 (NO2 bending) motions of liquid nitromethane have been studied as a function of temperature and concentration in CD3NO2 and CCl4 solutions. The experimental vibrational correlation functions of these two modes have shown that relaxation is collision assisted and suitable for modelling with the stochastic Kubo-Rothschild theory.
Yu, Qingbao; Erhardt, Erik B.; Sui, Jing; Du, Yuhui; He, Hao; Hjelm, Devon; Cetin, Mustafa S.; Rachakonda, Srinivas; Miller, Robyn L.; Pearlson, Godfrey; Calhoun, Vince D.
2014-01-01
Graph theory-based analysis has been widely employed in brain imaging studies, and altered topological properties of brain connectivity have emerged as important features of mental diseases such as schizophrenia. However, most previous studies have focused on graph metrics of stationary brain graphs, ignoring that brain connectivity exhibits fluctuations over time. Here we develop a new framework for accessing dynamic graph properties of time-varying functional brain connectivity in resting state fMRI data and apply it to healthy controls (HCs) and patients with schizophrenia (SZs). Specifically, nodes of brain graphs are defined by intrinsic connectivity networks (ICNs) identified by group independent component analysis (ICA). Dynamic graph metrics of the time-varying brain connectivity estimated by the correlation of sliding time-windowed ICA time courses of ICNs are calculated. First- and second-level connectivity states are detected based on the correlation of nodal connectivity strength between time-varying brain graphs. Our results indicate that SZs show decreased variance in the dynamic graph metrics. Consistent with prior stationary functional brain connectivity works, graph measures of identified first-level connectivity states show lower values in SZs. In addition, more first-level connectivity states are disassociated with the second-level connectivity state which resembles the stationary connectivity pattern computed by the entire scan. Collectively, the findings provide new evidence about altered dynamic brain graphs in schizophrenia which may underscore the abnormal brain performance in this mental illness. PMID:25514514
Fast blood flow monitoring in deep tissues with real-time software correlators
Wang, Detian; Parthasarathy, Ashwin B.; Baker, Wesley B.; Gannon, Kimberly; Kavuri, Venki; Ko, Tiffany; Schenkel, Steven; Li, Zhe; Li, Zeren; Mullen, Michael T.; Detre, John A.; Yodh, Arjun G.
2016-01-01
We introduce, validate and demonstrate a new software correlator for high-speed measurement of blood flow in deep tissues based on diffuse correlation spectroscopy (DCS). The software correlator scheme employs standard PC-based data acquisition boards to measure temporal intensity autocorrelation functions continuously at 50 – 100 Hz, the fastest blood flow measurements reported with DCS to date. The data streams, obtained in vivo for typical source-detector separations of 2.5 cm, easily resolve pulsatile heart-beat fluctuations in blood flow which were previously considered to be noise. We employ the device to separate tissue blood flow from tissue absorption/scattering dynamics and thereby show that the origin of the pulsatile DCS signal is primarily flow, and we monitor cerebral autoregulation dynamics in healthy volunteers more accurately than with traditional instrumentation as a result of increased data acquisition rates. Finally, we characterize measurement signal-to-noise ratio and identify count rate and averaging parameters needed for optimal performance. PMID:27231588
DOE Office of Scientific and Technical Information (OSTI.GOV)
Genova, Alessandro, E-mail: alessandro.genova@rutgers.edu; Pavanello, Michele, E-mail: m.pavanello@rutgers.edu; Ceresoli, Davide, E-mail: davide.ceresoli@cnr.it
2016-06-21
In this work we achieve three milestones: (1) we present a subsystem DFT method capable of running ab-initio molecular dynamics simulations accurately and efficiently. (2) In order to rid the simulations of inter-molecular self-interaction error, we exploit the ability of semilocal frozen density embedding formulation of subsystem DFT to represent the total electron density as a sum of localized subsystem electron densities that are constrained to integrate to a preset, constant number of electrons; the success of the method relies on the fact that employed semilocal nonadditive kinetic energy functionals effectively cancel out errors in semilocal exchange–correlation potentials that aremore » linked to static correlation effects and self-interaction. (3) We demonstrate this concept by simulating liquid water and solvated OH{sup •} radical. While the bulk of our simulations have been performed on a periodic box containing 64 independent water molecules for 52 ps, we also simulated a box containing 256 water molecules for 22 ps. The results show that, provided one employs an accurate nonadditive kinetic energy functional, the dynamics of liquid water and OH{sup •} radical are in semiquantitative agreement with experimental results or higher-level electronic structure calculations. Our assessments are based upon comparisons of radial and angular distribution functions as well as the diffusion coefficient of the liquid.« less
Genova, Alessandro; Ceresoli, Davide; Pavanello, Michele
2016-06-21
In this work we achieve three milestones: (1) we present a subsystem DFT method capable of running ab-initio molecular dynamics simulations accurately and efficiently. (2) In order to rid the simulations of inter-molecular self-interaction error, we exploit the ability of semilocal frozen density embedding formulation of subsystem DFT to represent the total electron density as a sum of localized subsystem electron densities that are constrained to integrate to a preset, constant number of electrons; the success of the method relies on the fact that employed semilocal nonadditive kinetic energy functionals effectively cancel out errors in semilocal exchange-correlation potentials that are linked to static correlation effects and self-interaction. (3) We demonstrate this concept by simulating liquid water and solvated OH(•) radical. While the bulk of our simulations have been performed on a periodic box containing 64 independent water molecules for 52 ps, we also simulated a box containing 256 water molecules for 22 ps. The results show that, provided one employs an accurate nonadditive kinetic energy functional, the dynamics of liquid water and OH(•) radical are in semiquantitative agreement with experimental results or higher-level electronic structure calculations. Our assessments are based upon comparisons of radial and angular distribution functions as well as the diffusion coefficient of the liquid.
Baltoumas, Fotis A; Theodoropoulou, Margarita C; Hamodrakas, Stavros J
2016-06-01
A significant amount of experimental evidence suggests that G-protein coupled receptors (GPCRs) do not act exclusively as monomers but also form biologically relevant dimers and oligomers. However, the structural determinants, stoichiometry and functional importance of GPCR oligomerization remain topics of intense speculation. In this study we attempted to evaluate the nature and dynamics of GPCR oligomeric interactions. A representative set of GPCR homodimers were studied through Coarse-Grained Molecular Dynamics simulations, combined with interface analysis and concepts from network theory for the construction and analysis of dynamic structural networks. Our results highlight important structural determinants that seem to govern receptor dimer interactions. A conserved dynamic behavior was observed among different GPCRs, including receptors belonging in different GPCR classes. Specific GPCR regions were highlighted as the core of the interfaces. Finally, correlations of motion were observed between parts of the dimer interface and GPCR segments participating in ligand binding and receptor activation, suggesting the existence of mechanisms through which dimer formation may affect GPCR function. The results of this study can be used to drive experiments aimed at exploring GPCR oligomerization, as well as in the study of transmembrane protein-protein interactions in general.