A Particle Population Control Method for Dynamic Monte Carlo
NASA Astrophysics Data System (ADS)
Sweezy, Jeremy; Nolen, Steve; Adams, Terry; Zukaitis, Anthony
2014-06-01
A general particle population control method has been derived from splitting and Russian Roulette for dynamic Monte Carlo particle transport. A well-known particle population control method, known as the particle population comb, has been shown to be a special case of this general method. This general method has been incorporated in Los Alamos National Laboratory's Monte Carlo Application Toolkit (MCATK) and examples of it's use are shown for both super-critical and sub-critical systems.
Monte Carlo techniques for real-time quantum dynamics
Dowling, Mark R. . E-mail: dowling@physics.uq.edu.au; Davis, Matthew J.; Drummond, Peter D.; Corney, Joel F.
2007-01-10
The stochastic-gauge representation is a method of mapping the equation of motion for the quantum mechanical density operator onto a set of equivalent stochastic differential equations. One of the stochastic variables is termed the 'weight', and its magnitude is related to the importance of the stochastic trajectory. We investigate the use of Monte Carlo algorithms to improve the sampling of the weighted trajectories and thus reduce sampling error in a simulation of quantum dynamics. The method can be applied to calculations in real time, as well as imaginary time for which Monte Carlo algorithms are more-commonly used. The Monte-Carlo algorithms are applicable when the weight is guaranteed to be real, and we demonstrate how to ensure this is the case. Examples are given for the anharmonic oscillator, where large improvements over stochastic sampling are observed.
Pattern Recognition for a Flight Dynamics Monte Carlo Simulation
NASA Technical Reports Server (NTRS)
Restrepo, Carolina; Hurtado, John E.
2011-01-01
The design, analysis, and verification and validation of a spacecraft relies heavily on Monte Carlo simulations. Modern computational techniques are able to generate large amounts of Monte Carlo data but flight dynamics engineers lack the time and resources to analyze it all. The growing amounts of data combined with the diminished available time of engineers motivates the need to automate the analysis process. Pattern recognition algorithms are an innovative way of analyzing flight dynamics data efficiently. They can search large data sets for specific patterns and highlight critical variables so analysts can focus their analysis efforts. This work combines a few tractable pattern recognition algorithms with basic flight dynamics concepts to build a practical analysis tool for Monte Carlo simulations. Current results show that this tool can quickly and automatically identify individual design parameters, and most importantly, specific combinations of parameters that should be avoided in order to prevent specific system failures. The current version uses a kernel density estimation algorithm and a sequential feature selection algorithm combined with a k-nearest neighbor classifier to find and rank important design parameters. This provides an increased level of confidence in the analysis and saves a significant amount of time.
Bias in Dynamic Monte Carlo Alpha Calculations
Sweezy, Jeremy Ed; Nolen, Steven Douglas; Adams, Terry R.; Trahan, Travis John
2015-02-06
A 1/N bias in the estimate of the neutron time-constant (commonly denoted as α) has been seen in dynamic neutronic calculations performed with MCATK. In this paper we show that the bias is most likely caused by taking the logarithm of a stochastic quantity. We also investigate the known bias due to the particle population control method used in MCATK. We conclude that this bias due to the particle population control method is negligible compared to other sources of bias.
Modeling and Computer Simulation: Molecular Dynamics and Kinetic Monte Carlo
Wirth, B.D.; Caturla, M.J.; Diaz de la Rubia, T.
2000-10-10
Recent years have witnessed tremendous advances in the realistic multiscale simulation of complex physical phenomena, such as irradiation and aging effects of materials, made possible by the enormous progress achieved in computational physics for calculating reliable, yet tractable interatomic potentials and the vast improvements in computational power and parallel computing. As a result, computational materials science is emerging as an important complement to theory and experiment to provide fundamental materials science insight. This article describes the atomistic modeling techniques of molecular dynamics (MD) and kinetic Monte Carlo (KMC), and an example of their application to radiation damage production and accumulation in metals. It is important to note at the outset that the primary objective of atomistic computer simulation should be obtaining physical insight into atomic-level processes. Classical molecular dynamics is a powerful method for obtaining insight about the dynamics of physical processes that occur on relatively short time scales. Current computational capability allows treatment of atomic systems containing as many as 10{sup 9} atoms for times on the order of 100 ns (10{sup -7}s). The main limitation of classical MD simulation is the relatively short times accessible. Kinetic Monte Carlo provides the ability to reach macroscopic times by modeling diffusional processes and time-scales rather than individual atomic vibrations. Coupling MD and KMC has developed into a powerful, multiscale tool for the simulation of radiation damage in metals.
Dynamical Monte Carlo methods for plasma-surface reactions
NASA Astrophysics Data System (ADS)
Guerra, Vasco; Marinov, Daniil
2016-08-01
Different dynamical Monte Carlo algorithms to investigate molecule formation on surfaces are developed, evaluated and compared with the deterministic approach based on reaction-rate equations. These include a null event algorithm, the n-fold way/BKL algorithm and an ‘hybrid’ variant of the latter. NO2 formation by NO oxidation on Pyrex and O recombination on silica with the formation of O2 are taken as case studies. The influence of the grid size on the CPU calculation time and the accuracy of the results is analysed. The role of Langmuir–Hinsehlwood recombination involving two physisorbed atoms and the effect of back diffusion and its inclusion in a deterministic formulation are investigated and discussed. It is shown that dynamical Monte Carlo schemes are flexible, simple to implement, describe easily elementary processes that are not straightforward to include in deterministic simulations, can run very efficiently if appropriately chosen and give highly reliable results. Moreover, the present approach provides a relatively simple procedure to describe fully coupled surface and gas phase chemistries.
Non-adiabatic molecular dynamics by accelerated semiclassical Monte Carlo
White, Alexander J.; Gorshkov, Vyacheslav N.; Tretiak, Sergei; Mozyrsky, Dmitry
2015-07-07
Non-adiabatic dynamics, where systems non-radiatively transition between electronic states, plays a crucial role in many photo-physical processes, such as fluorescence, phosphorescence, and photoisomerization. Methods for the simulation of non-adiabatic dynamics are typically either numerically impractical, highly complex, or based on approximations which can result in failure for even simple systems. Recently, the Semiclassical Monte Carlo (SCMC) approach was developed in an attempt to combine the accuracy of rigorous semiclassical methods with the efficiency and simplicity of widely used surface hopping methods. However, while SCMC was found to be more efficient than other semiclassical methods, it is not yet as efficient as is needed to be used for large molecular systems. Here, we have developed two new methods: the accelerated-SCMC and the accelerated-SCMC with re-Gaussianization, which reduce the cost of the SCMC algorithm up to two orders of magnitude for certain systems. In many cases shown here, the new procedures are nearly as efficient as the commonly used surface hopping schemes, with little to no loss of accuracy. This implies that these modified SCMC algorithms will be of practical numerical solutions for simulating non-adiabatic dynamics in realistic molecular systems.
Non-adiabatic molecular dynamics by accelerated semiclassical Monte Carlo
White, Alexander J.; Gorshkov, Vyacheslav N.; Tretiak, Sergei; Mozyrsky, Dmitry
2015-07-07
Non-adiabatic dynamics, where systems non-radiatively transition between electronic states, plays a crucial role in many photo-physical processes, such as fluorescence, phosphorescence, and photoisomerization. Methods for the simulation of non-adiabatic dynamics are typically either numerically impractical, highly complex, or based on approximations which can result in failure for even simple systems. Recently, the Semiclassical Monte Carlo (SCMC) approach was developed in an attempt to combine the accuracy of rigorous semiclassical methods with the efficiency and simplicity of widely used surface hopping methods. However, while SCMC was found to be more efficient than other semiclassical methods, it is not yet as efficient as is needed to be used for large molecular systems. Here, we have developed two new methods: the accelerated-SCMC and the accelerated-SCMC with re-Gaussianization, which reduce the cost of the SCMC algorithm up to two orders of magnitude for certain systems. In most cases shown here, the new procedures are nearly as efficient as the commonly used surface hopping schemes, with little to no loss of accuracy. This implies that these modified SCMC algorithms will be of practical numerical solutions for simulating non-adiabatic dynamics in realistic molecular systems.
Non-adiabatic molecular dynamics by accelerated semiclassical Monte Carlo
White, Alexander J.; Gorshkov, Vyacheslav N.; Tretiak, Sergei; Mozyrsky, Dmitry
2015-07-07
Non-adiabatic dynamics, where systems non-radiatively transition between electronic states, plays a crucial role in many photo-physical processes, such as fluorescence, phosphorescence, and photoisomerization. Methods for the simulation of non-adiabatic dynamics are typically either numerically impractical, highly complex, or based on approximations which can result in failure for even simple systems. Recently, the Semiclassical Monte Carlo (SCMC) approach was developed in an attempt to combine the accuracy of rigorous semiclassical methods with the efficiency and simplicity of widely used surface hopping methods. However, while SCMC was found to be more efficient than other semiclassical methods, it is not yet as efficientmore » as is needed to be used for large molecular systems. Here, we have developed two new methods: the accelerated-SCMC and the accelerated-SCMC with re-Gaussianization, which reduce the cost of the SCMC algorithm up to two orders of magnitude for certain systems. In many cases shown here, the new procedures are nearly as efficient as the commonly used surface hopping schemes, with little to no loss of accuracy. This implies that these modified SCMC algorithms will be of practical numerical solutions for simulating non-adiabatic dynamics in realistic molecular systems.« less
Energy Science and Technology Software Center (ESTSC)
2010-10-20
The "Monte Carlo Benchmark" (MCB) is intended to model the computatiional performance of Monte Carlo algorithms on parallel architectures. It models the solution of a simple heuristic transport equation using a Monte Carlo technique. The MCB employs typical features of Monte Carlo algorithms such as particle creation, particle tracking, tallying particle information, and particle destruction. Particles are also traded among processors using MPI calls.
Monte Carlo Simulation of Exciton Dynamics in Supramolecular Semiconductor Architectures
NASA Astrophysics Data System (ADS)
Silva, Carlos; Beljonne, David; Herz, Laura; Hoeben, Freek
2005-03-01
Supramolecular chemistry is useful to construct molecular architectures with functional semiconductor properties. To explore the consequences of this approach in molecular electronics, we have carried out ultrafast measurements of exciton dynamics in supramolecular assemblies of an oligo-p-phenyl-ene-vinyl-ene derivative functionalized to form chiral stacks in dodecane solution in a thermotropically reversible manner. We apply a model of incoherent exciton hopping within a Monte Carlo scheme to extract microscopic physical quantities. The simulation first builds the chiral stacks with a Gaussian disorder of site energies and then simulates exciton hopping on the structure and exciton-exciton annihilation to reproduce ensemble-averaged experimental data. The exciton transfer rates are calculated beyond the point-dipole approximation using the so-called line-dipole approach in combination with the Förster expression. The model of incoherent hopping successfully reproduces the data and we extract a high diffusion coefficient illustrating the polymeric properties of such supramolecular assemblies. The scope and limitations of the line-dipole approximation as well as the resonance energy transfer concept in this system are discussed.
Dynamic Monte Carlo simulation for highly efficient polymer blend photovoltaics.
Meng, Lingyi; Shang, Yuan; Li, Qikai; Li, Yongfang; Zhan, Xiaowei; Shuai, Zhigang; Kimber, Robin G E; Walker, Alison B
2010-01-14
We developed a model system for blend polymers with electron-donating and -accepting compounds. It is found that the optimal energy conversion efficiency can be achieved when the feature size is around 10 nm. The first reaction method is used to describe the key processes (e.g., the generation, the diffusion, the dissociation at the interface for the excitons, the drift, the injection from the electrodes, and the collection by the electrodes for the charge carries) in the organic solar cell by the dynamic Monte Carlo simulation. Our simulations indicate that a 5% power conversion efficiency (PCE) is reachable with an optimum combination of charge mobility and morphology. The parameters used in this model study correspond to a blend of novel polymers (bis(thienylenevinylene)-substituted polythiophene and poly(perylene diimide-alt-dithienothiophene)), which features a broad absorption and a high mobility. The I-V curves are well-reproduced by our simulations, and the PCE for the polymer blend can reach up to 2.2%, which is higher than the experimental value (>1%), one of the best available experimental results up to now for the all-polymer solar cells. In addition, the dependency of PCE on the charge mobility and the material structure are also investigated. PMID:20000370
Monte Carlo-based simulation of dynamic jaws tomotherapy
Sterpin, E.; Chen, Y.; Chen, Q.; Lu, W.; Mackie, T. R.; Vynckier, S.
2011-09-15
Purpose: Original TomoTherapy systems may involve a trade-off between conformity and treatment speed, the user being limited to three slice widths (1.0, 2.5, and 5.0 cm). This could be overcome by allowing the jaws to define arbitrary fields, including very small slice widths (<1 cm), which are challenging for a beam model. The aim of this work was to incorporate the dynamic jaws feature into a Monte Carlo (MC) model called TomoPen, based on the MC code PENELOPE, previously validated for the original TomoTherapy system. Methods: To keep the general structure of TomoPen and its efficiency, the simulation strategy introduces several techniques: (1) weight modifiers to account for any jaw settings using only the 5 cm phase-space file; (2) a simplified MC based model called FastStatic to compute the modifiers faster than pure MC; (3) actual simulation of dynamic jaws. Weight modifiers computed with both FastStatic and pure MC were compared. Dynamic jaws simulations were compared with the convolution/superposition (C/S) of TomoTherapy in the ''cheese'' phantom for a plan with two targets longitudinally separated by a gap of 3 cm. Optimization was performed in two modes: asymmetric jaws-constant couch speed (''running start stop,'' RSS) and symmetric jaws-variable couch speed (''symmetric running start stop,'' SRSS). Measurements with EDR2 films were also performed for RSS for the formal validation of TomoPen with dynamic jaws. Results: Weight modifiers computed with FastStatic were equivalent to pure MC within statistical uncertainties (0.5% for three standard deviations). Excellent agreement was achieved between TomoPen and C/S for both asymmetric jaw opening/constant couch speed and symmetric jaw opening/variable couch speed, with deviations well within 2%/2 mm. For RSS procedure, agreement between C/S and measurements was within 2%/2 mm for 95% of the points and 3%/3 mm for 98% of the points, where dose is greater than 30% of the prescription dose (gamma analysis
Energy Science and Technology Software Center (ESTSC)
2006-05-09
The Monte Carlo example programs VARHATOM and DMCATOM are two small, simple FORTRAN programs that illustrate the use of the Monte Carlo Mathematical technique for calculating the ground state energy of the hydrogen atom.
Monte Carlo and quasi-Monte Carlo methods
NASA Astrophysics Data System (ADS)
Caflisch, Russel E.
Monte Carlo is one of the most versatile and widely used numerical methods. Its convergence rate, O(N-1/2), is independent of dimension, which shows Monte Carlo to be very robust but also slow. This article presents an introduction to Monte Carlo methods for integration problems, including convergence theory, sampling methods and variance reduction techniques. Accelerated convergence for Monte Carlo quadrature is attained using quasi-random (also called low-discrepancy) sequences, which are a deterministic alternative to random or pseudo-random sequences. The points in a quasi-random sequence are correlated to provide greater uniformity. The resulting quadrature method, called quasi-Monte Carlo, has a convergence rate of approximately O((logN)kN-1). For quasi-Monte Carlo, both theoretical error estimates and practical limitations are presented. Although the emphasis in this article is on integration, Monte Carlo simulation of rarefied gas dynamics is also discussed. In the limit of small mean free path (that is, the fluid dynamic limit), Monte Carlo loses its effectiveness because the collisional distance is much less than the fluid dynamic length scale. Computational examples are presented throughout the text to illustrate the theory. A number of open problems are described.
Brown, F.B.; Sutton, T.M.
1996-02-01
This report is composed of the lecture notes from the first half of a 32-hour graduate-level course on Monte Carlo methods offered at KAPL. These notes, prepared by two of the principle developers of KAPL`s RACER Monte Carlo code, cover the fundamental theory, concepts, and practices for Monte Carlo analysis. In particular, a thorough grounding in the basic fundamentals of Monte Carlo methods is presented, including random number generation, random sampling, the Monte Carlo approach to solving transport problems, computational geometry, collision physics, tallies, and eigenvalue calculations. Furthermore, modern computational algorithms for vector and parallel approaches to Monte Carlo calculations are covered in detail, including fundamental parallel and vector concepts, the event-based algorithm, master/slave schemes, parallel scaling laws, and portability issues.
NASA Astrophysics Data System (ADS)
Guan, Fada
Monte Carlo method has been successfully applied in simulating the particles transport problems. Most of the Monte Carlo simulation tools are static and they can only be used to perform the static simulations for the problems with fixed physics and geometry settings. Proton therapy is a dynamic treatment technique in the clinical application. In this research, we developed a method to perform the dynamic Monte Carlo simulation of proton therapy using Geant4 simulation toolkit. A passive-scattering treatment nozzle equipped with a rotating range modulation wheel was modeled in this research. One important application of the Monte Carlo simulation is to predict the spatial dose distribution in the target geometry. For simplification, a mathematical model of a human body is usually used as the target, but only the average dose over the whole organ or tissue can be obtained rather than the accurate spatial dose distribution. In this research, we developed a method using MATLAB to convert the medical images of a patient from CT scanning into the patient voxel geometry. Hence, if the patient voxel geometry is used as the target in the Monte Carlo simulation, the accurate spatial dose distribution in the target can be obtained. A data analysis tool---root was used to score the simulation results during a Geant4 simulation and to analyze the data and plot results after simulation. Finally, we successfully obtained the accurate spatial dose distribution in part of a human body after treating a patient with prostate cancer using proton therapy.
The Specific Bias in Dynamic Monte Carlo Simulations of Nuclear Reactor
NASA Astrophysics Data System (ADS)
Yamamoto, Toshihisa; Endo, Hiroshi; Ishizu, Tomoko; Tatewaki, Isao
2014-06-01
During the development of Monte-Carlo-based dynamic code system, we have encountered two major Monte-Carlo-specific problems. One is the break down due to "false super-criticality" which is caused by an accidentally large eigenvalue due to statistical error in spite of the fact that the reactor is actually not. The other problem, which is the main topic in this paper, is that the statistical error in power level using the reactivity calculated with Monte Carlo code is not symmetric about its mean but always positively biased. This signifies that the bias is accumulated as the calculation proceeds and consequently results in over-estimation of the final power level. It should be noted that the bias will not eliminated by refining time step as long as the variance is not zero. A preliminary investigation on this matter using the one-group-precursor point kinetic equations was made and it was concluded that the bias in power level is approximately proportional to the product of variance in Monte Carlo calculation and elapsed time. This conclusion was verified with some numerical experiments. This outcome is important in quantifying the required precision of the Monte-Carlo-based reactivity calculations.
Epitaxial growth simulation employing a combined molecular dynamics and Monte Carlo approach
Grein, C.H.; Benedek, R.; Rubia, T. de la
1995-07-01
The epitaxial growth of Ge on Si(OO1) is simulated by employing a hybrid approach based on molecular dynamics to describe the initial kinetic behavior of deposited adatoms and Monte Carlo displacements to account for subsequent equilibration. This method is well suited to describe initial nucleation and growth. Stillinger-Weber potentials are employed to describe interatomic interactions.
Molecular dynamics, monte carlo simulations, and langevin dynamics: a computational review.
Paquet, Eric; Viktor, Herna L
2015-01-01
Macromolecular structures, such as neuraminidases, hemagglutinins, and monoclonal antibodies, are not rigid entities. Rather, they are characterised by their flexibility, which is the result of the interaction and collective motion of their constituent atoms. This conformational diversity has a significant impact on their physicochemical and biological properties. Among these are their structural stability, the transport of ions through the M2 channel, drug resistance, macromolecular docking, binding energy, and rational epitope design. To assess these properties and to calculate the associated thermodynamical observables, the conformational space must be efficiently sampled and the dynamic of the constituent atoms must be simulated. This paper presents algorithms and techniques that address the abovementioned issues. To this end, a computational review of molecular dynamics, Monte Carlo simulations, Langevin dynamics, and free energy calculation is presented. The exposition is made from first principles to promote a better understanding of the potentialities, limitations, applications, and interrelations of these computational methods. PMID:25785262
Molecular Dynamics, Monte Carlo Simulations, and Langevin Dynamics: A Computational Review
Paquet, Eric; Viktor, Herna L.
2015-01-01
Macromolecular structures, such as neuraminidases, hemagglutinins, and monoclonal antibodies, are not rigid entities. Rather, they are characterised by their flexibility, which is the result of the interaction and collective motion of their constituent atoms. This conformational diversity has a significant impact on their physicochemical and biological properties. Among these are their structural stability, the transport of ions through the M2 channel, drug resistance, macromolecular docking, binding energy, and rational epitope design. To assess these properties and to calculate the associated thermodynamical observables, the conformational space must be efficiently sampled and the dynamic of the constituent atoms must be simulated. This paper presents algorithms and techniques that address the abovementioned issues. To this end, a computational review of molecular dynamics, Monte Carlo simulations, Langevin dynamics, and free energy calculation is presented. The exposition is made from first principles to promote a better understanding of the potentialities, limitations, applications, and interrelations of these computational methods. PMID:25785262
Cramer, S.N.
1984-01-01
The MORSE code is a large general-use multigroup Monte Carlo code system. Although no claims can be made regarding its superiority in either theoretical details or Monte Carlo techniques, MORSE has been, since its inception at ORNL in the late 1960s, the most widely used Monte Carlo radiation transport code. The principal reason for this popularity is that MORSE is relatively easy to use, independent of any installation or distribution center, and it can be easily customized to fit almost any specific need. Features of the MORSE code are described.
Monte Carlo variance reduction
NASA Technical Reports Server (NTRS)
Byrn, N. R.
1980-01-01
Computer program incorporates technique that reduces variance of forward Monte Carlo method for given amount of computer time in determining radiation environment in complex organic and inorganic systems exposed to significant amounts of radiation.
NASA Astrophysics Data System (ADS)
Tringe, J. W.; Ileri, N.; Levie, H. W.; Stroeve, P.; Ustach, V.; Faller, R.; Renaud, P.
2015-08-01
We use Molecular Dynamics and Monte Carlo simulations to examine molecular transport phenomena in nanochannels, explaining four orders of magnitude difference in wheat germ agglutinin (WGA) protein diffusion rates observed by fluorescence correlation spectroscopy (FCS) and by direct imaging of fluorescently-labeled proteins. We first use the ESPResSo Molecular Dynamics code to estimate the surface transport distance for neutral and charged proteins. We then employ a Monte Carlo model to calculate the paths of protein molecules on surfaces and in the bulk liquid transport medium. Our results show that the transport characteristics depend strongly on the degree of molecular surface coverage. Atomic force microscope characterization of surfaces exposed to WGA proteins for 1000 s show large protein aggregates consistent with the predicted coverage. These calculations and experiments provide useful insight into the details of molecular motion in confined geometries.
Monte Carlo Simulation of Laser-Ablated Particle Splitting Dynamic in a Low Pressure Inert Gas
NASA Astrophysics Data System (ADS)
Ding, Xuecheng; Zhang, Zicai; Liang, Weihua; Chu, Lizhi; Deng, Zechao; Wang, Yinglong
2016-06-01
A Monte Carlo simulation method with an instantaneous density dependent mean-free-path of the ablated particles and the Ar gas is developed for investigating the transport dynamics of the laser-ablated particles in a low pressure inert gas. The ablated-particle density and velocity distributions are analyzed. The force distributions acting on the ablated particles are investigated. The influence of the substrate on the ablated-particle velocity distribution and the force distribution acting on the ablated particles are discussed. The Monte Carlo simulation results approximately agree with the experimental data at the pressure of 8 Pa to 17 Pa. This is helpful to investigate the gas phase nucleation and growth mechanism of nanoparticles. supported by the Natural Science Foundation of Hebei Province, China (No. A2015201166) and the Natural Science Foundation of Hebei University, China (No. 2013-252)
Monte Carlo Study of Real Time Dynamics on the Lattice.
Alexandru, Andrei; Başar, Gökçe; Bedaque, Paulo F; Vartak, Sohan; Warrington, Neill C
2016-08-19
Monte Carlo studies involving real time dynamics are severely restricted by the sign problem that emerges from a highly oscillatory phase of the path integral. In this Letter, we present a new method to compute real time quantities on the lattice using the Schwinger-Keldysh formalism via Monte Carlo simulations. The key idea is to deform the path integration domain to a complex manifold where the phase oscillations are mild and the sign problem is manageable. We use the previously introduced "contraction algorithm" to create a Markov chain on this alternative manifold. We substantiate our approach by analyzing the quantum mechanical anharmonic oscillator. Our results are in agreement with the exact ones obtained by diagonalization of the Hamiltonian. The method we introduce is generic and, in principle, applicable to quantum field theory albeit very slow. We discuss some possible improvements that should speed up the algorithm. PMID:27588844
Raga: Monte Carlo simulations of gravitational dynamics of non-spherical stellar systems
NASA Astrophysics Data System (ADS)
Vasiliev, Eugene
2014-11-01
Raga (Relaxation in Any Geometry) is a Monte Carlo simulation method for gravitational dynamics of non-spherical stellar systems. It is based on the SMILE software (ascl:1308.001) for orbit analysis. It can simulate stellar systems with a much smaller number of particles N than the number of stars in the actual system, represent an arbitrary non-spherical potential with a basis-set or spline spherical-harmonic expansion with the coefficients of expansion computed from particle trajectories, and compute particle trajectories independently and in parallel using a high-accuracy adaptive-timestep integrator. Raga can also model two-body relaxation by local (position-dependent) velocity diffusion coefficients (as in Spitzer's Monte Carlo formulation) and adjust the magnitude of relaxation to the actual number of stars in the target system, and model the effect of a central massive black hole.
Time-quantified Monte Carlo algorithm for interacting spin array micromagnetic dynamics
NASA Astrophysics Data System (ADS)
Cheng, X. Z.; Jalil, M. B. A.; Lee, Hwee Kuan
2006-06-01
In this paper, we reexamine the validity of using time-quantified Monte Carlo (TQMC) method [Phys. Rev. Lett. 84, 163 (2000); 96, 067208 (2006)] in simulating the stochastic dynamics of interacting magnetic nanoparticles. The Fokker-Planck coefficients corresponding to both TQMC and the Langevin dynamical equation (Landau-Lifshitz-Gilbert, LLG) are derived and compared in the presence of interparticle interactions. The time quantification factor is obtained and justified. Numerical verification is shown by using TQMC and Langevin methods in analyzing spin-wave dispersion in a linear array of magnetic nanoparticles.
Verhaegen, F; Liu, H H
2001-02-01
In radiation therapy, new treatment modalities employing dynamic collimation and intensity modulation increase the complexity of dose calculation because a new dimension, time, has to be incorporated into the traditional three-dimensional problem. In this work, we investigated two classes of sampling technique to incorporate dynamic collimator motion in Monte Carlo simulation. The methods were initially evaluated for modelling enhanced dynamic wedges (EDWs) from Varian accelerators (Varian Medical Systems, Palo Alto, USA). In the position-probability-sampling or PPS method, a cumulative probability distribution function (CPDF) was computed for the collimator position, which could then be sampled during simulations. In the static-component-simulation or SCS method, a dynamic field is approximated by multiple static fields in a step-shoot fashion. The weights of the particles or the number of particles simulated for each component field are computed from the probability distribution function (PDF) of the collimator position. The CPDF and PDF were computed from the segmented treatment tables (STTs) for the EDWs. An output correction factor had to be applied in this calculation to account for the backscattered radiation affecting monitor chamber readings. Comparison of the phase-space data from the PPS method (with the step-shoot motion) with those from the SCS method showed excellent agreement. The accuracy of the PPS method was further verified from the agreement between the measured and calculated dose distributions. Compared to the SCS method, the PPS method is more automated and efficient from an operational point of view. The principle of the PPS method can be extended to simulate other dynamic motions, and in particular, intensity-modulated beams using multileaf collimators. PMID:11229715
Event-driven Monte Carlo: Exact dynamics at all time scales for discrete-variable models
NASA Astrophysics Data System (ADS)
Mendoza-Coto, Alejandro; Díaz-Méndez, Rogelio; Pupillo, Guido
2016-06-01
We present an algorithm for the simulation of the exact real-time dynamics of classical many-body systems with discrete energy levels. In the same spirit of kinetic Monte Carlo methods, a stochastic solution of the master equation is found, with no need to define any other phase-space construction. However, unlike existing methods, the present algorithm does not assume any particular statistical distribution to perform moves or to advance the time, and thus is a unique tool for the numerical exploration of fast and ultra-fast dynamical regimes. By decomposing the problem in a set of two-level subsystems, we find a natural variable step size, that is well defined from the normalization condition of the transition probabilities between the levels. We successfully test the algorithm with known exact solutions for non-equilibrium dynamics and equilibrium thermodynamical properties of Ising-spin models in one and two dimensions, and compare to standard implementations of kinetic Monte Carlo methods. The present algorithm is directly applicable to the study of the real-time dynamics of a large class of classical Markovian chains, and particularly to short-time situations where the exact evolution is relevant.
Development of a dynamic simulation mode in Serpent 2 Monte Carlo code
Leppaenen, J.
2013-07-01
This paper presents a dynamic neutron transport mode, currently being implemented in the Serpent 2 Monte Carlo code for the purpose of simulating short reactivity transients with temperature feedback. The transport routine is introduced and validated by comparison to MCNP5 calculations. The method is also tested in combination with an internal temperature feedback module, which forms the inner part of a multi-physics coupling scheme in Serpent 2. The demo case for the coupled calculation is a reactivity-initiated accident (RIA) in PWR fuel. (authors)
New approach to dynamical Monte Carlo methods: application to an epidemic model
NASA Astrophysics Data System (ADS)
Aiello, O. E.; da Silva, M. A. A.
2003-09-01
In this work we introduce a new approach to dynamical Monte Carlo methods to simulate Markovian processes. We apply this approach to formulate and study an epidemic generalized SIRS model. The results are in excellent agreement with the forth order Runge-Kutta Method in a region of deterministic solution. We also show that purely local interactions reproduce a poissonian-like process at mesoscopic level. The simulations for this case are checked self-consistently using a stochastic version of the Euler Method.
A new Monte Carlo method for dynamical evolution of non-spherical stellar systems
NASA Astrophysics Data System (ADS)
Vasiliev, Eugene
2015-01-01
We have developed a novel Monte Carlo method for simulating the dynamical evolution of stellar systems in arbitrary geometry. The orbits of stars are followed in a smooth potential represented by a basis-set expansion and perturbed after each timestep using local velocity diffusion coefficients from the standard two-body relaxation theory. The potential and diffusion coefficients are updated after an interval of time that is a small fraction of the relaxation time, but may be longer than the dynamical time. Thus, our approach is a bridge between the Spitzer's formulation of the Monte Carlo method and the temporally smoothed self-consistent field method. The primary advantages are the ability to follow the secular evolution of shape of the stellar system, and the possibility of scaling the amount of two-body relaxation to the necessary value, unrelated to the actual number of particles in the simulation. Possible future applications of this approach in galaxy dynamics include the problem of consumption of stars by a massive black hole in a non-spherical galactic nucleus, evolution of binary supermassive black holes, and the influence of chaos on the shape of galaxies, while for globular clusters it may be used for studying the influence of rotation.
NASA Astrophysics Data System (ADS)
Dytman, Steven
2011-10-01
Every neutrino experiment requires a Monte Carlo event generator for various purposes. Historically, each series of experiments developed their own code which tuned to their needs. Modern experiments would benefit from a universal code (e.g. PYTHIA) which would allow more direct comparison between experiments. GENIE attempts to be that code. This paper compares most commonly used codes and provides some details of GENIE.
Dynamic measurements and uncertainty estimation of clinical thermometers using Monte Carlo method
NASA Astrophysics Data System (ADS)
Ogorevc, Jaka; Bojkovski, Jovan; Pušnik, Igor; Drnovšek, Janko
2016-09-01
Clinical thermometers in intensive care units are used for the continuous measurement of body temperature. This study describes a procedure for dynamic measurement uncertainty evaluation in order to examine the requirements for clinical thermometer dynamic properties in standards and recommendations. In this study thermistors were used as temperature sensors, transient temperature measurements were performed in water and air and the measurement data were processed for the investigation of thermometer dynamic properties. The thermometers were mathematically modelled. A Monte Carlo method was implemented for dynamic measurement uncertainty evaluation. The measurement uncertainty was analysed for static and dynamic conditions. Results showed that dynamic uncertainty is much larger than steady-state uncertainty. The results of dynamic uncertainty analysis were applied on an example of clinical measurements and were compared to current requirements in ISO standard for clinical thermometers. It can be concluded that there was no need for dynamic evaluation of clinical thermometers for continuous measurement, while dynamic measurement uncertainty was within the demands of target uncertainty. Whereas in the case of intermittent predictive thermometers, the thermometer dynamic properties had a significant impact on the measurement result. Estimation of dynamic uncertainty is crucial for the assurance of traceable and comparable measurements.
A Monte Carlo study of the dynamics of G-protein activation.
Mahama, P A; Linderman, J J
1994-01-01
To link quantitatively the cell surface binding of ligand to receptor with the production of cellular responses, it may be necessary to explore early events in signal transduction such as G-protein activation. Two different model frameworks relating receptor/ligand binding to G-protein activation are examined. In the first framework, a simple ordinary differential equation model is used to describe receptor/ligand binding and G-protein activation. In the second framework, the events leading to G-protein activation are simulated using a dynamic Monte Carlo model. In both models, reactions between ligand-bound receptors and G-proteins are assumed to be diffusion-limited. The Monte Carlo model predicts two regimes of G-protein activation, depending upon whether the lifetime of a receptor/ligand complex is long or short compared with the time needed for diffusional encounters of complexes and G-proteins. When the lifetime of a complex is relatively short compared with the diffusion time, the movement of ligand among free receptors by binding and unbinding ("switching") significantly enhances G-protein activation. Receptor antagonists dramatically reduce G-protein activation and, thus, signal transduction in this case, and significant clustering of active G-proteins near receptor/ligand complexes results. The simple ordinary differential equation model poorly predicts G-protein activation for this situation. In the alternative case, when diffusion is relatively fast, ligand movement among receptors is less important and the simple ordinary differential equation model and Monte Carlo model results are similar. In this case, there is little clustering of active G-proteins near receptor/ligand complexes. Results also indicate that as the GTPase activity of the alpha-subunit decreases, the steady-state level of alpha-GTP increases, although temporal sensitivity is compromised. PMID:7811949
Monte Carlo simulations of dynamic phase transitions in ferromagnetic thin-films
NASA Astrophysics Data System (ADS)
Aktaş, B. O.; Vatansever, E.; Polat, H.
2016-04-01
By means of detailed Monte Carlo (MC) simulations, we have presented dynamic phase transition (DPT) properties of ferromagnetic thin-films. Thermal variations of surface, bulk and total dynamical order parameters (DOP) for a film and total order parameter for the films with different thicknesses have been examined. Opposite regimes of reduced exchange interaction (surface to bulk ratio values in R
A Variable Coefficient Method for Accurate Monte Carlo Simulation of Dynamic Asset Price
NASA Astrophysics Data System (ADS)
Li, Yiming; Hung, Chih-Young; Yu, Shao-Ming; Chiang, Su-Yun; Chiang, Yi-Hui; Cheng, Hui-Wen
2007-07-01
In this work, we propose an adaptive Monte Carlo (MC) simulation technique to compute the sample paths for the dynamical asset price. In contrast to conventional MC simulation with constant drift and volatility (μ,σ), our MC simulation is performed with variable coefficient methods for (μ,σ) in the solution scheme, where the explored dynamic asset pricing model starts from the formulation of geometric Brownian motion. With the method of simultaneously updated (μ,σ), more than 5,000 runs of MC simulation are performed to fulfills basic accuracy of the large-scale computation and suppresses statistical variance. Daily changes of stock market index in Taiwan and Japan are investigated and analyzed.
Quantum dynamics at finite temperature: Time-dependent quantum Monte Carlo study
NASA Astrophysics Data System (ADS)
Christov, Ivan P.
2016-08-01
In this work we investigate the ground state and the dissipative quantum dynamics of interacting charged particles in an external potential at finite temperature. The recently devised time-dependent quantum Monte Carlo (TDQMC) method allows a self-consistent treatment of the system of particles together with bath oscillators first for imaginary-time propagation of Schrödinger type of equations where both the system and the bath converge to their finite temperature ground state, and next for real time calculation where the dissipative dynamics is demonstrated. In that context the application of TDQMC appears as promising alternative to the path-integral related techniques where the real time propagation can be a challenge.
NASA Astrophysics Data System (ADS)
Anagnostopoulos, K.; Azuma, T.; Nishimura, J.
The IKKT or IIB matrix model has been postulated to be a non perturbative definition of superstring theory. It has the attractive feature that spacetime is dynamically generated, which makes possible the scenario of dynamical compactification of extra dimensions, which in the Euclidean model manifests by spontaneously breaking the SO(10) rotational invariance (SSB). In this work we study using Monte Carlo simulations the 6 dimensional version of the Euclidean IIB matrix model. Simulations are found to be plagued by a strong complex action problem and the factorization method is used for effective sampling and computing expectation values of the extent of spacetime in various dimensions. Our results are consistent with calculations using the Gaussian Expansion method which predict SSB to SO(3) symmetric vacua, a finite universal extent of the compactified dimensions and finite spacetime volume.
Dynamic load balancing for petascale quantum Monte Carlo applications: The Alias method
NASA Astrophysics Data System (ADS)
Sudheer, C. D.; Krishnan, S.; Srinivasan, A.; Kent, P. R. C.
2013-02-01
Diffusion Monte Carlo is a highly accurate Quantum Monte Carlo method for electronic structure calculations of materials, but it requires frequent load balancing or population redistribution steps to maintain efficiency on parallel machines. This step can be a significant factor affecting performance, and will become more important as the number of processing elements increases. We propose a new dynamic load balancing algorithm, the Alias Method, and evaluate it theoretically and empirically. An important feature of the new algorithm is that the load can be perfectly balanced with each process receiving at most one message. It is also optimal in the maximum size of messages received by any process. We also optimize its implementation to reduce network contention, a process facilitated by the low messaging requirement of the algorithm: a simple renumbering of the MPI ranks based on proximity and a space filling curve significantly improves the MPI Allgather performance. Empirical results on the petaflop Cray XT Jaguar supercomputer at ORNL show up to 30% improvement in performance on 120,000 cores. The load balancing algorithm may be straightforwardly implemented in existing codes. The algorithm may also be employed by any method with many near identical computational tasks that require load balancing.
Dynamic load balancing for petascale quantum Monte Carlo applications: The Alias method
Sudheer, C. D.; Krishnan, S.; Srinivasan, A.; Kent, P. R. C.
2013-02-01
Diffusion Monte Carlo is the most accurate widely used Quantum Monte Carlo method for the electronic structure of materials, but it requires frequent load balancing or population redistribution steps to maintain efficiency and avoid accumulation of systematic errors on parallel machines. The load balancing step can be a significant factor affecting performance, and will become more important as the number of processing elements increases. We propose a new dynamic load balancing algorithm, the Alias Method, and evaluate it theoretically and empirically. An important feature of the new algorithm is that the load can be perfectly balanced with each process receiving at most one message. It is also optimal in the maximum size of messages received by any process. We also optimize its implementation to reduce network contention, a process facilitated by the low messaging requirement of the algorithm. Empirical results on the petaflop Cray XT Jaguar supercomputer at ORNL showing up to 30% improvement in performance on 120,000 cores. The load balancing algorithm may be straightforwardly implemented in existing codes. The algorithm may also be employed by any method with many near identical computational tasks that requires load balancing.
Eged, Katalin; Kis, Zoltán; Voigt, Gabriele
2006-01-01
After an accidental release of radionuclides to the inhabited environment the external gamma irradiation from deposited radioactivity contributes significantly to the radiation exposure of the population for extended periods. For evaluating this exposure pathway, three main model requirements are needed: (i) to calculate the air kerma value per photon emitted per unit source area, based on Monte Carlo (MC) simulations; (ii) to describe the distribution and dynamics of radionuclides on the diverse urban surfaces; and (iii) to combine all these elements in a relevant urban model to calculate the resulting doses according to the actual scenario. This paper provides an overview about the different approaches to calculate photon transport in urban areas and about several dose calculation codes published. Two types of Monte Carlo simulations are presented using the global and the local approaches of photon transport. Moreover, two different philosophies of the dose calculation, the "location factor method" and a combination of relative contamination of surfaces with air kerma values are described. The main features of six codes (ECOSYS, EDEM2M, EXPURT, PARATI, TEMAS, URGENT) are highlighted together with a short model-model features intercomparison. PMID:16095771
Polynomial-time-scaling quantum dynamics with time-dependent quantum Monte Carlo.
Christov, Ivan P
2009-05-21
Here we study the dynamics of many-body quantum systems using the time-dependent quantum Monte Carlo method where the evolution is described by ensembles of particles and guide waves. The exponential time scaling inherent to the quantum many-body problem is reduced to polynomial-time computation by solving concurrently a set of coupled Schrodinger equations for the guide waves in physical space and a set of first-order equations for the Monte Carlo walkers. We use effective potentials to account for the local and nonlocal quantum correlations in time-varying fields, where for fermionic states an exchange "hole" is introduced explicitly through screened Coulomb potentials. The walker distributions for the ground states of para- and ortho-helium reproduce well the statistical properties, such as the electron-pair density function, of the real atoms. Our predictions for the dipole response and the ionization of an atom exposed to strong ultrashort optical pulse are in good agreement with the exact results. PMID:19391581
Chin, P.W. . E-mail: mary.chin@physics.org
2005-10-15
This project developed a solution for verifying external photon beam radiotherapy. The solution is based on a calibration chain for deriving portal dose maps from acquired portal images, and a calculation framework for predicting portal dose maps. Quantitative comparison between acquired and predicted portal dose maps accomplishes both geometric (patient positioning with respect to the beam) and dosimetric (two-dimensional fluence distribution of the beam) verifications. A disagreement would indicate that beam delivery had not been according to plan. The solution addresses the clinical need for verifying radiotherapy both pretreatment (without the patient in the beam) and on treatment (with the patient in the beam). Medical linear accelerators mounted with electronic portal imaging devices (EPIDs) were used to acquire portal images. Two types of EPIDs were investigated: the amorphous silicon (a-Si) and the scanning liquid ion chamber (SLIC). The EGSnrc family of Monte Carlo codes were used to predict portal dose maps by computer simulation of radiation transport in the beam-phantom-EPID configuration. Monte Carlo simulations have been implemented on several levels of high throughput computing (HTC), including the grid, to reduce computation time. The solution has been tested across the entire clinical range of gantry angle, beam size (5 cmx5 cm to 20 cmx20 cm), and beam-patient and patient-EPID separations (4 to 38 cm). In these tests of known beam-phantom-EPID configurations, agreement between acquired and predicted portal dose profiles was consistently within 2% of the central axis value. This Monte Carlo portal dosimetry solution therefore achieved combined versatility, accuracy, and speed not readily achievable by other techniques.
Compressible generalized hybrid Monte Carlo
NASA Astrophysics Data System (ADS)
Fang, Youhan; Sanz-Serna, J. M.; Skeel, Robert D.
2014-05-01
One of the most demanding calculations is to generate random samples from a specified probability distribution (usually with an unknown normalizing prefactor) in a high-dimensional configuration space. One often has to resort to using a Markov chain Monte Carlo method, which converges only in the limit to the prescribed distribution. Such methods typically inch through configuration space step by step, with acceptance of a step based on a Metropolis(-Hastings) criterion. An acceptance rate of 100% is possible in principle by embedding configuration space in a higher dimensional phase space and using ordinary differential equations. In practice, numerical integrators must be used, lowering the acceptance rate. This is the essence of hybrid Monte Carlo methods. Presented is a general framework for constructing such methods under relaxed conditions: the only geometric property needed is (weakened) reversibility; volume preservation is not needed. The possibilities are illustrated by deriving a couple of explicit hybrid Monte Carlo methods, one based on barrier-lowering variable-metric dynamics and another based on isokinetic dynamics.
Dynamical evolution of the Oort cloud. I. A Monte Carlo simulation. II. A theoretical approach
Remy, F.; Mignard, F.
1985-07-01
A Monte Carlo model is used to trace the dynamical evolution of the Oort cloud of comets to its ultimate end. After a review of previous simulations, the necessity of considering perturbations of the aphelion distance because of passing stars, the density of passing stars, and the three-body problem of sun-star-comet is discussed. For convenience, the solar gravitation is assumed to be zero as a star passes. It is also assumed that the initial cometary distribution had a perihelion near the orbits of Uranus-Neptune. Six orbital elements are calculated to obtain orbital distributions for the population in the Oort cloud. The cloud is estimated to contain 10 trillion comets, which would satisfy the present apparition rate of new comets. 34 references.
Ab initio molecular dynamics simulation of liquid water by quantum Monte Carlo
Zen, Andrea; Luo, Ye Mazzola, Guglielmo Sorella, Sandro; Guidoni, Leonardo
2015-04-14
Although liquid water is ubiquitous in chemical reactions at roots of life and climate on the earth, the prediction of its properties by high-level ab initio molecular dynamics simulations still represents a formidable task for quantum chemistry. In this article, we present a room temperature simulation of liquid water based on the potential energy surface obtained by a many-body wave function through quantum Monte Carlo (QMC) methods. The simulated properties are in good agreement with recent neutron scattering and X-ray experiments, particularly concerning the position of the oxygen-oxygen peak in the radial distribution function, at variance of previous density functional theory attempts. Given the excellent performances of QMC on large scale supercomputers, this work opens new perspectives for predictive and reliable ab initio simulations of complex chemical systems.
Schierz, Philipp; Zierenberg, Johannes; Janke, Wolfhard
2015-10-01
Molecular Dynamics (MD) and Monte Carlo (MC) simulations are the most popular simulation techniques for many-particle systems. Although they are often applied to similar systems, it is unclear to which extent one has to expect quantitative agreement of the two simulation techniques. In this work, we present a quantitative comparison of MD and MC simulations in the microcanonical ensemble. For three test examples, we study first- and second-order phase transitions with a focus on liquid-gas like transitions. We present MD analysis techniques to compensate for conservation law effects due to linear and angular momentum conservation. Additionally, we apply the weighted histogram analysis method to microcanonical histograms reweighted from MD simulations. By this means, we are able to estimate the density of states from many microcanonical simulations at various total energies. This further allows us to compute estimates of canonical expectation values. PMID:26450299
NASA Astrophysics Data System (ADS)
Dhiman, Isha; Gupta, Arvind Kumar
2016-03-01
This work is devoted to the development of a novel theoretical approach, named hybrid approach, to handle a localized bottleneck in a symmetrically coupled two-channel totally asymmetric simple exclusion process with Langmuir kinetics. The hybrid approach is combined with singular perturbation technique to get steady-state phase diagrams and density profiles. We have thoroughly examined the role played by the strength of bottleneck, binding constant and lane-changing rate in the system dynamics. The appearances of bottleneck-induced shock, a bottleneck phase and Meissner phase are explained. Further, the critical values of bottleneck rate are identified, which signify the changes in the topology of phase diagram. It is also found that an increase in lane-changing rate as well as unequal attachment, detachment rates weaken the bottleneck effect. Our theoretical arguments are in good agreement with extensively performed Monte Carlo simulations.
Monte Carlo simulations to study the effect of static and dynamic properties of polymer melts
NASA Astrophysics Data System (ADS)
Khanal, Kiran; Luettmer-Strathmann, Jutta
2009-03-01
Static and dynamic properties of polymers are affected by the stiffness of the chains. In this work, we investigate structural and thermodynamic properties of a lattice model for semiflexible polymer chains. The model is an extension of Shaffer's bond-fluctuation model and includes attractive interactions between monomers and an adjustable bending penalty that determines the Kuhn segment length. This allows us to model melts of flexible and semiflexible chains. For this work, we performed Monte Carlo simulations for polymer melts with a range of bending parameters and densities. Results for chain dimensions show that the Kuhn segment length increases monotonously with the bending penalty and has a linear dependence for a range of bending parameters. Results for self diffusion constants show that the translational mobility is strongly reduced by increasing chain stiffness. We also investigate the effect of chain stiffness on thermodynamic properties of the melts.
Monte Carlo Simulations of PAC-Spectra as a General Approach to Dynamic Interactions
NASA Astrophysics Data System (ADS)
Danielsen, Eva; Jørgensen, Lars Elkjær; Sestoft, Peter
Time Dependent Perturbed Angular Correlations of γ-rays (PAC) can be used to study hyperfine interactions of a dynamic nature. However, the exact effect of the dynamic interaction on the PAC-spectrum is sometimes difficult to derive analytically. A new approach based on Monte Carlo simulations is therefore suggested, here implemented as a Fortran 90 program for simulating PAC spectra of dynamic electric field gradients of any origin. The program is designed for the most common experimental condition where the intermediate level has spin 5/2, but the approach can equally well be used for other spin states. Codes for 4 different situations have been developed: (1) Rotational diffusion by jumps; used as a test case. (2) Jumps between two states with different electric field gradients, different lifetimes and different orientations of the electric field gradient principal axes. (3) Relaxation of one state to another. (4) Molecules adhering to a surface with random rotational jumps around the axis perpendicular to the surface. To illustrate how this approach can be used to improve data-interpretation, previously published data on 111mCd-plastocyanin and 111Ag-plastocyanin are re-considered. The strength of this novel approach is its simplicity and generality so that other dynamic processes can easily be included by only adding new program units describing the random process behind the dynamics. The program is hereby made publicly available.
Semiclassical Monte Carlo: A first principles approach to non-adiabatic molecular dynamics
White, Alexander J.; Gorshkov, Vyacheslav N.; Wang, Ruixi; Tretiak, Sergei; Mozyrsky, Dmitry
2014-11-14
Modeling the dynamics of photophysical and (photo)chemical reactions in extended molecular systems is a new frontier for quantum chemistry. Many dynamical phenomena, such as intersystem crossing, non-radiative relaxation, and charge and energy transfer, require a non-adiabatic description which incorporate transitions between electronic states. Additionally, these dynamics are often highly sensitive to quantum coherences and interference effects. Several methods exist to simulate non-adiabatic dynamics; however, they are typically either too expensive to be applied to large molecular systems (10's-100's of atoms), or they are based on ad hoc schemes which may include severe approximations due to inconsistencies in classical and quantum mechanics. We present, in detail, an algorithm based on Monte Carlo sampling of the semiclassical time-dependent wavefunction that involves running simple surface hopping dynamics, followed by a post-processing step which adds little cost. The method requires only a few quantities from quantum chemistry calculations, can systematically be improved, and provides excellent agreement with exact quantum mechanical results. Here we show excellent agreement with exact solutions for scattering results of standard test problems. Additionally, we find that convergence of the wavefunction is controlled by complex valued phase factors, the size of the non-adiabatic coupling region, and the choice of sampling function. These results help in determining the range of applicability of the method, and provide a starting point for further improvement.
Semiclassical Monte Carlo: A first principles approach to non-adiabatic molecular dynamics
NASA Astrophysics Data System (ADS)
White, Alexander J.; Gorshkov, Vyacheslav N.; Wang, Ruixi; Tretiak, Sergei; Mozyrsky, Dmitry
2014-11-01
Modeling the dynamics of photophysical and (photo)chemical reactions in extended molecular systems is a new frontier for quantum chemistry. Many dynamical phenomena, such as intersystem crossing, non-radiative relaxation, and charge and energy transfer, require a non-adiabatic description which incorporate transitions between electronic states. Additionally, these dynamics are often highly sensitive to quantum coherences and interference effects. Several methods exist to simulate non-adiabatic dynamics; however, they are typically either too expensive to be applied to large molecular systems (10's-100's of atoms), or they are based on ad hoc schemes which may include severe approximations due to inconsistencies in classical and quantum mechanics. We present, in detail, an algorithm based on Monte Carlo sampling of the semiclassical time-dependent wavefunction that involves running simple surface hopping dynamics, followed by a post-processing step which adds little cost. The method requires only a few quantities from quantum chemistry calculations, can systematically be improved, and provides excellent agreement with exact quantum mechanical results. Here we show excellent agreement with exact solutions for scattering results of standard test problems. Additionally, we find that convergence of the wavefunction is controlled by complex valued phase factors, the size of the non-adiabatic coupling region, and the choice of sampling function. These results help in determining the range of applicability of the method, and provide a starting point for further improvement.
Extending canonical Monte Carlo methods
NASA Astrophysics Data System (ADS)
Velazquez, L.; Curilef, S.
2010-02-01
In this paper, we discuss the implications of a recently obtained equilibrium fluctuation-dissipation relation for the extension of the available Monte Carlo methods on the basis of the consideration of the Gibbs canonical ensemble to account for the existence of an anomalous regime with negative heat capacities C < 0. The resulting framework appears to be a suitable generalization of the methodology associated with the so-called dynamical ensemble, which is applied to the extension of two well-known Monte Carlo methods: the Metropolis importance sampling and the Swendsen-Wang cluster algorithm. These Monte Carlo algorithms are employed to study the anomalous thermodynamic behavior of the Potts models with many spin states q defined on a d-dimensional hypercubic lattice with periodic boundary conditions, which successfully reduce the exponential divergence of the decorrelation time τ with increase of the system size N to a weak power-law divergence \\tau \\propto N^{\\alpha } with α≈0.2 for the particular case of the 2D ten-state Potts model.
Marcus, Ryan C.
2012-07-25
MCMini is a proof of concept that demonstrates the possibility for Monte Carlo neutron transport using OpenCL with a focus on performance. This implementation, written in C, shows that tracing particles and calculating reactions on a 3D mesh can be done in a highly scalable fashion. These results demonstrate a potential path forward for MCNP or other Monte Carlo codes.
Chatterjee, Abhijit; Voter, Arthur
2009-01-01
We develop a variation of the temperature accelerated dynamics (TAD) method, called the p-TAD method, that efficiently generates an on-the-fly kinetic Monte Carlo (KMC) process catalog with control over the accuracy of the catalog. It is assumed that transition state theory is valid. The p-TAD method guarantees that processes relevant at the timescales of interest to the simulation are present in the catalog with a chosen confidence. A confidence measure associated with the process catalog is derived. The dynamics is then studied using the process catalog with the KMC method. Effective accuracy of a p-TAD calculation is derived when a KMC catalog is reused for conditions different from those the catalog was originally generated for. Different KMC catalog generation strategies that exploit the features of the p-TAD method and ensure higher accuracy and/or computational efficiency are presented. The accuracy and the computational requirements of the p-TAD method are assessed. Comparisons to the original TAD method are made. As an example, we study dynamics in sub-monolayer Ag/Cu(110) at the time scale of seconds using the p-TAD method. It is demonstrated that the p-TAD method overcomes several challenges plaguing the conventional KMC method.
Solution of deterministic-stochastic epidemic models by dynamical Monte Carlo method
NASA Astrophysics Data System (ADS)
Aièllo, O. E.; Haas, V. J.; daSilva, M. A. A.; Caliri, A.
2000-07-01
This work is concerned with dynamical Monte Carlo (MC) method and its application to models originally formulated in a continuous-deterministic approach. Specifically, a susceptible-infected-removed-susceptible (SIRS) model is used in order to analyze aspects of the dynamical MC algorithm and achieve its applications in epidemic contexts. We first examine two known approaches to the dynamical interpretation of the MC method and follow with the application of one of them in the SIRS model. The working method chosen is based on the Poisson process where hierarchy of events, properly calculated waiting time between events, and independence of the events simulated, are the basic requirements. To verify the consistence of the method, some preliminary MC results are compared against exact steady-state solutions and other general numerical results (provided by Runge-Kutta method): good agreement is found. Finally, a space-dependent extension of the SIRS model is introduced and treated by MC. The results are interpreted under and in accordance with aspects of the herd-immunity concept.
NASA Astrophysics Data System (ADS)
Huang, B. Y.; Lu, Z. X.; Zhang, Y.; Xie, Y. L.; Zeng, M.; Yan, Z. B.; Liu, J.-M.
2016-05-01
The polarization-electric field hysteresis loops and the dynamics of polarization switching in a two-dimensional antiferroelectric (AFE) lattice submitted to a time-oscillating electric field E(t) of frequency f and amplitude E0, is investigated using Monte Carlo simulation based on the Landau-Devonshire phenomenological theory on antiferroelectrics. It is revealed that the AFE double-loop hysteresis area A, i.e., the energy loss in one cycle of polarization switching, exhibits the single-peak frequency dispersion A(f), suggesting the unique characteristic time for polarization switching, which is independent of E0 as long as E0 is larger than the quasi-static coercive field for the antiferroelectric-ferroelectric transitions. However, the dependence of recoverable stored energy W on amplitude E0 seems to be complicated depending on temperature T and frequency f. A dynamic scaling behavior of the energy loss dispersion A(f) over a wide range of E0 is obtained, confirming the unique characteristic time for polarization switching of an AFE lattice. The present simulation may shed light on the dynamics of energy storage and release in AFE thin films.
Chen, Yunjie; Kale, Seyit; Weare, Jonathan; Dinner, Aaron R; Roux, Benoît
2016-04-12
A multiple time-step integrator based on a dual Hamiltonian and a hybrid method combining molecular dynamics (MD) and Monte Carlo (MC) is proposed to sample systems in the canonical ensemble. The Dual Hamiltonian Multiple Time-Step (DHMTS) algorithm is based on two similar Hamiltonians: a computationally expensive one that serves as a reference and a computationally inexpensive one to which the workload is shifted. The central assumption is that the difference between the two Hamiltonians is slowly varying. Earlier work has shown that such dual Hamiltonian multiple time-step schemes effectively precondition nonlinear differential equations for dynamics by reformulating them into a recursive root finding problem that can be solved by propagating a correction term through an internal loop, analogous to RESPA. Of special interest in the present context, a hybrid MD-MC version of the DHMTS algorithm is introduced to enforce detailed balance via a Metropolis acceptance criterion and ensure consistency with the Boltzmann distribution. The Metropolis criterion suppresses the discretization errors normally associated with the propagation according to the computationally inexpensive Hamiltonian, treating the discretization error as an external work. Illustrative tests are carried out to demonstrate the effectiveness of the method. PMID:26918826
NASA Astrophysics Data System (ADS)
Vitali, Ettore; Shi, Hao; Qin, Mingpu; Zhang, Shiwei
The possibility of calculating dynamical correlation functions from first principles provides a unique opportunity to explore the manifold of the excited states of a quantum many-body system. Such calculations allow us to predict interesting physical properties like spectral functions, excitation spectra and charge and spin gaps, which are more difficult to access from usual equilibrium calculations. We address the ab-initio calculation of dynamical Green functions and two-body correlation functions in the Auxiliary-field Quantum Monte Carlo method, using the two-dimensional Hubbard model as an example. When the sign problem is not present, an unbiased estimation of imaginary time correlation functions is obtained. We discuss in detail the complexity and the stability of the calculations. Moreover, we propose a new approach which is expected to be very useful when dealing with dilute systems, e.g. for cold gases, allowing calculations with a very favorable complexity in the system size. Supported by NSF, DOE SciDAC, and Simons Foundation.
Static and dynamic properties of tethered chains at adsorbing surfaces: A Monte Carlo study
NASA Astrophysics Data System (ADS)
Descas, Radu; Sommer, Jens-Uwe; Blumen, Alexander
2004-05-01
We present extensive Monte Carlo simulations of tethered chains of length N on adsorbing surfaces, considering the dilute case in good solvents, and analyze our results using scaling arguments. We focus on the mean number M of chain contacts with the adsorbing wall, on the chain's extension (the radius of gyration) perpendicular and parallel to the adsorbing surface, on the probability distribution of the free end and on the density profile for all monomers. At the critical adsorption strength ɛc one has Mc˜Nφ, and we find (using the above results) as best candidate φ to equal 0.59. However, slight changes in the estimation of ɛc lead to large deviations in the resulting φ; this might be a possible reason for the difference in the φ values reported in the literature. We also investigate the dynamical scaling behavior at ɛc, by focusing on the end-to-end correlation function and on the correlation function of monomers adsorbed at the wall. We find that at ɛc the dynamic scaling exponent a (which describes the relaxation time of the chain as a function of N) is the same as that of free chains. Furthermore, we find that for tethered chains the modes perpendicular to the surface relax quicker than those parallel to it, which may be seen as a splitting in the relaxation spectrum.
Weare, Jonathan; Dinner, Aaron R.; Roux, Benoît
2016-01-01
A multiple time-step integrator based on a dual Hamiltonian and a hybrid method combining molecular dynamics (MD) and Monte Carlo (MC) is proposed to sample systems in the canonical ensemble. The Dual Hamiltonian Multiple Time-Step (DHMTS) algorithm is based on two similar Hamiltonians: a computationally expensive one that serves as a reference and a computationally inexpensive one to which the workload is shifted. The central assumption is that the difference between the two Hamiltonians is slowly varying. Earlier work has shown that such dual Hamiltonian multiple time-step schemes effectively precondition nonlinear differential equations for dynamics by reformulating them into a recursive root finding problem that can be solved by propagating a correction term through an internal loop, analogous to RESPA. Of special interest in the present context, a hybrid MD-MC version of the DHMTS algorithm is introduced to enforce detailed balance via a Metropolis acceptance criterion and ensure consistency with the Boltzmann distribution. The Metropolis criterion suppresses the discretization errors normally associated with the propagation according to the computationally inexpensive Hamiltonian, treating the discretization error as an external work. Illustrative tests are carried out to demonstrate the effectiveness of the method. PMID:26918826
An Event-Driven Hybrid Molecular Dynamics and Direct Simulation Monte Carlo Algorithm
Donev, A; Garcia, A L; Alder, B J
2007-07-30
A novel algorithm is developed for the simulation of polymer chains suspended in a solvent. The polymers are represented as chains of hard spheres tethered by square wells and interact with the solvent particles with hard core potentials. The algorithm uses event-driven molecular dynamics (MD) for the simulation of the polymer chain and the interactions between the chain beads and the surrounding solvent particles. The interactions between the solvent particles themselves are not treated deterministically as in event-driven algorithms, rather, the momentum and energy exchange in the solvent is determined stochastically using the Direct Simulation Monte Carlo (DSMC) method. The coupling between the solvent and the solute is consistently represented at the particle level, however, unlike full MD simulations of both the solvent and the solute, the spatial structure of the solvent is ignored. The algorithm is described in detail and applied to the study of the dynamics of a polymer chain tethered to a hard wall subjected to uniform shear. The algorithm closely reproduces full MD simulations with two orders of magnitude greater efficiency. Results do not confirm the existence of periodic (cycling) motion of the polymer chain.
NASA Astrophysics Data System (ADS)
Vogel, Thomas; Perez, Danny; Junghans, Christoph
2014-03-01
We show direct formal relationships between the Wang-Landau iteration [PRL 86, 2050 (2001)], metadynamics [PNAS 99, 12562 (2002)] and statistical temperature molecular dynamics [PRL 97, 050601 (2006)], the major Monte Carlo and molecular dynamics work horses for sampling from a generalized, multicanonical ensemble. We aim at helping to consolidate the developments in the different areas by indicating how methodological advancements can be transferred in a straightforward way, avoiding the parallel, largely independent, developments tracks observed in the past.
COOL: A code for Dynamic Monte Carlo Simulation of molecular dynamics
NASA Astrophysics Data System (ADS)
Barletta, Paolo
2012-02-01
Cool is a program to simulate evaporative and sympathetic cooling for a mixture of two gases co-trapped in an harmonic potential. The collisions involved are assumed to be exclusively elastic, and losses are due to evaporation from the trap. Each particle is followed individually in its trajectory, consequently properties such as spatial densities or energy distributions can be readily evaluated. The code can be used sequentially, by employing one output as input for another run. The code can be easily generalised to describe more complicated processes, such as the inclusion of inelastic collisions, or the possible presence of more than two species in the trap. New version program summaryProgram title: COOL Catalogue identifier: AEHJ_v2_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEHJ_v2_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 1 097 733 No. of bytes in distributed program, including test data, etc.: 18 425 722 Distribution format: tar.gz Programming language: C++ Computer: Desktop Operating system: Linux RAM: 500 Mbytes Classification: 16.7, 23 Catalogue identifier of previous version: AEHJ_v1_0 Journal reference of previous version: Comput. Phys. Comm. 182 (2011) 388 Does the new version supersede the previous version?: Yes Nature of problem: Simulation of the sympathetic process occurring for two molecular gases co-trapped in a deep optical trap. Solution method: The Direct Simulation Monte Carlo method exploits the decoupling, over a short time period, of the inter-particle interaction from the trapping potential. The particle dynamics is thus exclusively driven by the external optical field. The rare inter-particle collisions are considered with an acceptance/rejection mechanism, that is, by comparing a random number to the collisional probability
Parallelizing Monte Carlo with PMC
Rathkopf, J.A.; Jones, T.R.; Nessett, D.M.; Stanberry, L.C.
1994-11-01
PMC (Parallel Monte Carlo) is a system of generic interface routines that allows easy porting of Monte Carlo packages of large-scale physics simulation codes to Massively Parallel Processor (MPP) computers. By loading various versions of PMC, simulation code developers can configure their codes to run in several modes: serial, Monte Carlo runs on the same processor as the rest of the code; parallel, Monte Carlo runs in parallel across many processors of the MPP with the rest of the code running on other MPP processor(s); distributed, Monte Carlo runs in parallel across many processors of the MPP with the rest of the code running on a different machine. This multi-mode approach allows maintenance of a single simulation code source regardless of the target machine. PMC handles passing of messages between nodes on the MPP, passing of messages between a different machine and the MPP, distributing work between nodes, and providing independent, reproducible sequences of random numbers. Several production codes have been parallelized under the PMC system. Excellent parallel efficiency in both the distributed and parallel modes results if sufficient workload is available per processor. Experiences with a Monte Carlo photonics demonstration code and a Monte Carlo neutronics package are described.
Wormhole Hamiltonian Monte Carlo
Lan, Shiwei; Streets, Jeffrey; Shahbaba, Babak
2015-01-01
In machine learning and statistics, probabilistic inference involving multimodal distributions is quite difficult. This is especially true in high dimensional problems, where most existing algorithms cannot easily move from one mode to another. To address this issue, we propose a novel Bayesian inference approach based on Markov Chain Monte Carlo. Our method can effectively sample from multimodal distributions, especially when the dimension is high and the modes are isolated. To this end, it exploits and modifies the Riemannian geometric properties of the target distribution to create wormholes connecting modes in order to facilitate moving between them. Further, our proposed method uses the regeneration technique in order to adapt the algorithm by identifying new modes and updating the network of wormholes without affecting the stationary distribution. To find new modes, as opposed to redis-covering those previously identified, we employ a novel mode searching algorithm that explores a residual energy function obtained by subtracting an approximate Gaussian mixture density (based on previously discovered modes) from the target density function. PMID:25861551
A dynamic Monte Carlo study of anomalous current voltage behaviour in organic solar cells
Feron, K. Fell, C. J.; Zhou, X.; Belcher, W. J.; Dastoor, P. C.
2014-12-07
We present a dynamic Monte Carlo (DMC) study of s-shaped current-voltage (I-V) behaviour in organic solar cells. This anomalous behaviour causes a substantial decrease in fill factor and thus power conversion efficiency. We show that this s-shaped behaviour is induced by charge traps that are located at the electrode interface rather than in the bulk of the active layer, and that the anomaly becomes more pronounced with increasing trap depth or density. Furthermore, the s-shape anomaly is correlated with interface recombination, but not bulk recombination, thus highlighting the importance of controlling the electrode interface. While thermal annealing is known to remove the s-shape anomaly, the reason has been not clear, since these treatments induce multiple simultaneous changes to the organic solar cell structure. The DMC modelling indicates that it is the removal of aluminium clusters at the electrode, which act as charge traps, that removes the anomalous I-V behaviour. Finally, this work shows that the s-shape becomes less pronounced with increasing electron-hole recombination rate; suggesting that efficient organic photovoltaic material systems are more susceptible to these electrode interface effects.
Kinetic Monte Carlo and cellular particle dynamics simulations of multicellular systems
NASA Astrophysics Data System (ADS)
Flenner, Elijah; Janosi, Lorant; Barz, Bogdan; Neagu, Adrian; Forgacs, Gabor; Kosztin, Ioan
2012-03-01
Computer modeling of multicellular systems has been a valuable tool for interpreting and guiding in vitro experiments relevant to embryonic morphogenesis, tumor growth, angiogenesis and, lately, structure formation following the printing of cell aggregates as bioink particles. Here we formulate two computer simulation methods: (1) a kinetic Monte Carlo (KMC) and (2) a cellular particle dynamics (CPD) method, which are capable of describing and predicting the shape evolution in time of three-dimensional multicellular systems during their biomechanical relaxation. Our work is motivated by the need of developing quantitative methods for optimizing postprinting structure formation in bioprinting-assisted tissue engineering. The KMC and CPD model parameters are determined and calibrated by using an original computational-theoretical-experimental framework applied to the fusion of two spherical cell aggregates. The two methods are used to predict the (1) formation of a toroidal structure through fusion of spherical aggregates and (2) cell sorting within an aggregate formed by two types of cells with different adhesivities.
Rheological properties of polymer melts in confined shear flow from dynamic Monte Carlo simulations.
NASA Astrophysics Data System (ADS)
Dorgan, John
2007-03-01
The viscoelastic properties of dense polymer melts in shear flow are examined using dynamic Monte Carlo simulation for plate spacings less than 10 times the molecular radius of gyration. The coarse graining methodology employed consists of the cooperative motion algorithm of Pakula and a derived biasing technique based on previous studies of Binder and Baushnagel. For relatively large plate spacings and slow flows, a uniform linear velocity profile is obtainable. Use of the Kramers form for entropic springs allows the calculation of stress in the simulation providing a means for exploring rheological properties including viscosity and normal stress differences. Results are in excellent agreement with well-established experimental facts; a shear thinning viscosity is obtained, the first normal stress difference increases with shear rate, and the first normal stress coefficient decreases with shear rate. Evidence of entanglements are present for longer chain lengths. For fast flows, the linear velocity profile is lost and shear banding is observed. A non-monotonic stress with shear rate is found in conjunction with the shear banding and mechanistically this is attributable to a cohesive failure with an excess of chain ends being found at the slip plane. Results for variable plate spacings shed some insight into novel confinement effects that are being exploited in emerging areas of nanotechnology.
A Kushner-Stratonovich Monte Carlo filter applied to nonlinear dynamical system identification
NASA Astrophysics Data System (ADS)
Sarkar, S.; Chowdhury, S. R.; Venugopal, M.; Vasu, R. M.; Roy, D.
2014-03-01
A Monte Carlo filter, based on the idea of averaging over characteristics and fashioned after a particle-based time-discretized approximation to the Kushner-Stratonovich (KS) nonlinear filtering equation, is proposed. A key aspect of the new filter is the gain-like additive update, designed to approximate the innovation integral in the KS equation and implemented through an annealing-type iterative procedure, which is aimed at rendering the innovation (observation-prediction mismatch) for a given time-step to a zero-mean Brownian increment corresponding to the measurement noise. This may be contrasted with the weight-based multiplicative updates in most particle filters that are known to precipitate the numerical problem of weight collapse within a finite-ensemble setting. A study to estimate the a-priori error bounds in the proposed scheme is undertaken. The numerical evidence, presently gathered from the assessed performance of the proposed and a few other competing filters on a class of nonlinear dynamic system identification and target tracking problems, is suggestive of the remarkably improved convergence and accuracy of the new filter.
Liu, Susan M; Haynes, Charles A
2005-02-15
Two-dimensional dynamic Monte Carlo simulations are applied to the protein-like HP chain model to investigate the influence of lateral confinement of the adsorbed chain on adsorption thermodynamics and the ensemble of accessible chain conformations. The structure of the model makes it possible to enumerate all possible chain conformations and thereby define with precision the relation between adsorption thermodynamics and changes in accessible chain conformations resulting from the adsorption process. Lateral confinement of the adsorbed chain is shown to dramatically reduce the number of accessible energy states and unique chain conformations such that, under certain conditions, adsorption is predicted to actually stabilize the chain against denaturation. Lateral confinement preferentially eliminates expanded conformations of the adsorbed chain, shifting the equilibrium from the unfolded state toward the native state. As a result, the conformational entropy of the adsorbed chain is predicted to be lower than that of the chain free in solution. The protein-like HP chain responds to an increase in the hydrophobicity of the sorbent surface by strongly favoring those conformations that minimize the overall internal energy of the system. As a result, adsorption severely destabilizes the native-state conformation. The ability of our simulation results to provide insights into underlying mechanisms for nonspecific protein adsorption is illustrated through qualitative comparison with activity data for hen egg-white lysozyme adsorbed on silica at different surface concentrations. PMID:15589532
NASA Astrophysics Data System (ADS)
Bousige, Colin; BoÅ£an, Alexandru; Ulm, Franz-Josef; Pellenq, Roland J.-M.; Coasne, Benoît
2015-03-01
We report an efficient atom-scale reconstruction method that consists of combining the Hybrid Reverse Monte Carlo algorithm (HRMC) with Molecular Dynamics (MD) in the framework of a simulated annealing technique. In the spirit of the experimentally constrained molecular relaxation technique [Biswas et al., Phys. Rev. B 69, 195207 (2004)], this modified procedure offers a refined strategy in the field of reconstruction techniques, with special interest for heterogeneous and disordered solids such as amorphous porous materials. While the HRMC method generates physical structures, thanks to the use of energy penalties, the combination with MD makes the method at least one order of magnitude faster than HRMC simulations to obtain structures of similar quality. Furthermore, in order to ensure the transferability of this technique, we provide rational arguments to select the various input parameters such as the relative weight ω of the energy penalty with respect to the structure optimization. By applying the method to disordered porous carbons, we show that adsorption properties provide data to test the global texture of the reconstructed sample but are only weakly sensitive to the presence of defects. In contrast, the vibrational properties such as the phonon density of states are found to be very sensitive to the local structure of the sample.
Bousige, Colin; Boţan, Alexandru; Coasne, Benoît; Ulm, Franz-Josef; Pellenq, Roland J.-M.
2015-03-21
We report an efficient atom-scale reconstruction method that consists of combining the Hybrid Reverse Monte Carlo algorithm (HRMC) with Molecular Dynamics (MD) in the framework of a simulated annealing technique. In the spirit of the experimentally constrained molecular relaxation technique [Biswas et al., Phys. Rev. B 69, 195207 (2004)], this modified procedure offers a refined strategy in the field of reconstruction techniques, with special interest for heterogeneous and disordered solids such as amorphous porous materials. While the HRMC method generates physical structures, thanks to the use of energy penalties, the combination with MD makes the method at least one order of magnitude faster than HRMC simulations to obtain structures of similar quality. Furthermore, in order to ensure the transferability of this technique, we provide rational arguments to select the various input parameters such as the relative weight ω of the energy penalty with respect to the structure optimization. By applying the method to disordered porous carbons, we show that adsorption properties provide data to test the global texture of the reconstructed sample but are only weakly sensitive to the presence of defects. In contrast, the vibrational properties such as the phonon density of states are found to be very sensitive to the local structure of the sample.
Molecular dynamics and Monte Carlo hybrid simulation for fuzzy tungsten nanostructure formation
NASA Astrophysics Data System (ADS)
Ito, A. M.; Takayama, A.; Oda, Y.; Tamura, T.; Kobayashi, R.; Hattori, T.; Ogata, S.; Ohno, N.; Kajita, S.; Yajima, M.; Noiri, Y.; Yoshimoto, Y.; Saito, S.; Takamura, S.; Murashima, T.; Miyamoto, M.; Nakamura, H.
2015-07-01
For the purposes of long-term use of tungsten divertor walls, the formation process of the fuzzy tungsten nanostructure induced by exposure to the helium plasma was studied. In the present paper, the fuzzy nanostructure's formation has been successfully reproduced by the new hybrid simulation method in which the deformation of the tungsten material due to pressure of the helium bubbles was simulated by the molecular dynamics and the diffusion of the helium atoms was simulated by the random walk based on the Monte Carlo method. By the simulation results, the surface height of the fuzzy nanostructure increased only when helium retention was under the steady state. It was proven that the growth of the fuzzy nanostructure was brought about by bursting of the helium bubbles. Moreover, we suggest the following key formation mechanisms of the fuzzy nanostructure: (1) lifting in which the surface lifted up by the helium bubble changes into a convexity, (2) bursting by which the region of the helium bubble changes into a concavity, and (3) the difference of the probability of helium retention by which the helium bubbles tend to appear under the concavity. Consequently, the convex-concave surface structure was enhanced and grew to create the fuzzy nanostructure.
Davis, Mitchell A; Dunn, Andrew K
2015-06-29
Few methods exist that can accurately handle dynamic light scattering in the regime between single and highly multiple scattering. We demonstrate dynamic light scattering Monte Carlo (DLS-MC), a numerical method by which the electric field autocorrelation function may be calculated for arbitrary geometries if the optical properties and particle motion are known or assumed. DLS-MC requires no assumptions regarding the number of scattering events, the final form of the autocorrelation function, or the degree of correlation between scattering events. Furthermore, the method is capable of rapidly determining the effect of particle motion changes on the autocorrelation function in heterogeneous samples. We experimentally validated the method and demonstrated that the simulations match both the expected form and the experimental results. We also demonstrate the perturbation capabilities of the method by calculating the autocorrelation function of flow in a representation of mouse microvasculature and determining the sensitivity to flow changes as a function of depth. PMID:26191723
Isotropic Monte Carlo Grain Growth
Energy Science and Technology Software Center (ESTSC)
2013-04-25
IMCGG performs Monte Carlo simulations of normal grain growth in metals on a hexagonal grid in two dimensions with periodic boundary conditions. This may be performed with either an isotropic or a misorientation - and incliantion-dependent grain boundary energy.
Monte Carlo calculation of dynamical properties of the two-dimensional Hubbard model
NASA Technical Reports Server (NTRS)
White, S. R.; Scalapino, D. J.; Sugar, R. L.; Bickers, N. E.
1989-01-01
A new method is introduced for analytically continuing imaginary-time data from quantum Monte Carlo calculations to the real-frequency axis. The method is based on a least-squares-fitting procedure with constraints of positivity and smoothness on the real-frequency quantities. Results are shown for the single-particle spectral-weight function and density of states for the half-filled, two-dimensional Hubbard model.
NASA Technical Reports Server (NTRS)
Lim, J. T.; Gold, H. J.; Wilkerson, G. G.; Raper, C. D. Jr; Raper CD, J. r. (Principal Investigator)
1989-01-01
We describe the application of a strategy for conducting a sensitivity analysis for a complex dynamic model. The procedure involves preliminary screening of parameter sensitivities by numerical estimation of linear sensitivity coefficients, followed by generation of a response surface based on Monte Carlo simulation. Application is to a physiological model of the vegetative growth of soybean plants. The analysis provides insights as to the relative importance of certain physiological processes in controlling plant growth. Advantages and disadvantages of the strategy are discussed.
Sampling Enrichment toward Target Structures Using Hybrid Molecular Dynamics-Monte Carlo Simulations
Yang, Kecheng; Różycki, Bartosz; Cui, Fengchao; Shi, Ce; Chen, Wenduo; Li, Yunqi
2016-01-01
Sampling enrichment toward a target state, an analogue of the improvement of sampling efficiency (SE), is critical in both the refinement of protein structures and the generation of near-native structure ensembles for the exploration of structure-function relationships. We developed a hybrid molecular dynamics (MD)-Monte Carlo (MC) approach to enrich the sampling toward the target structures. In this approach, the higher SE is achieved by perturbing the conventional MD simulations with a MC structure-acceptance judgment, which is based on the coincidence degree of small angle x-ray scattering (SAXS) intensity profiles between the simulation structures and the target structure. We found that the hybrid simulations could significantly improve SE by making the top-ranked models much closer to the target structures both in the secondary and tertiary structures. Specifically, for the 20 mono-residue peptides, when the initial structures had the root-mean-squared deviation (RMSD) from the target structure smaller than 7 Å, the hybrid MD-MC simulations afforded, on average, 0.83 Å and 1.73 Å in RMSD closer to the target than the parallel MD simulations at 310K and 370K, respectively. Meanwhile, the average SE values are also increased by 13.2% and 15.7%. The enrichment of sampling becomes more significant when the target states are gradually detectable in the MD-MC simulations in comparison with the parallel MD simulations, and provide >200% improvement in SE. We also performed a test of the hybrid MD-MC approach in the real protein system, the results showed that the SE for 3 out of 5 real proteins are improved. Overall, this work presents an efficient way of utilizing solution SAXS to improve protein structure prediction and refinement, as well as the generation of near native structures for function annotation. PMID:27227775
NASA Astrophysics Data System (ADS)
Crifo, J.-F.; Loukianov, G. A.; Rodionov, A. V.; Zakharov, V. V.
2005-07-01
This paper describes the first computations of dust distributions in the vicinity of an active cometary nucleus, using a multidimensional Direct Simulation Monte Carlo Method (DSMC). The physical model is simplistic: spherical grains of a broad range of sizes are liberated by H 2O sublimation from a selection of nonrotating sunlit spherical nuclei, and submitted to the nucleus gravity, the gas drag, and the solar radiation pressure. The results are compared to those obtained by the previously described Dust Multi-Fluid Method (DMF) and demonstrate an excellent agreement in the regions where the DMF is usable. Most importantly, the DSMC allows the discovery of hitherto unsuspected dust coma properties in those cases which cannot be treated by the DMF. This leads to a thorough reconsideration of the properties of the near-nucleus dust dynamics. In particular, the results show that (1) none of the three forces considered here can be neglected a priori, in particular not the radiation pressure; (2) hitherto unsuspected new families of grain trajectories exist, for instance trajectories leading from the nightside surface to the dayside coma; (3) a wealth of balistic-like trajectories leading from one point of the surface to another point exist; on the dayside, such trajectories lead to the formation of "mini-volcanoes." The present model and results are discussed carefully. It is shown that (1) the neglected forces (inertia associated with a nucleus rotation, solar tidal force) are, in general, not negligible everywhere, and (2) when allowing for these additional forces, a time-dependent model will, in general, have to be used. The future steps of development of the model are outlined.
SU-E-T-238: Monte Carlo Estimation of Cerenkov Dose for Photo-Dynamic Radiotherapy
Chibani, O; Price, R; Ma, C; Eldib, A; Mora, G
2014-06-01
Purpose: Estimation of Cerenkov dose from high-energy megavoltage photon and electron beams in tissue and its impact on the radiosensitization using Protoporphyrine IX (PpIX) for tumor targeting enhancement in radiotherapy. Methods: The GEPTS Monte Carlo code is used to generate dose distributions from 18MV Varian photon beam and generic high-energy (45-MV) photon and (45-MeV) electron beams in a voxel-based tissueequivalent phantom. In addition to calculating the ionization dose, the code scores Cerenkov energy released in the wavelength range 375–425 nm corresponding to the pick of the PpIX absorption spectrum (Fig. 1) using the Frank-Tamm formula. Results: The simulations shows that the produced Cerenkov dose suitable for activating PpIX is 4000 to 5500 times lower than the overall radiation dose for all considered beams (18MV, 45 MV and 45 MeV). These results were contradictory to the recent experimental studies by Axelsson et al. (Med. Phys. 38 (2011) p 4127), where Cerenkov dose was reported to be only two orders of magnitude lower than the radiation dose. Note that our simulation results can be corroborated by a simple model where the Frank and Tamm formula is applied for electrons with 2 MeV/cm stopping power generating Cerenkov photons in the 375–425 nm range and assuming these photons have less than 1mm penetration in tissue. Conclusion: The Cerenkov dose generated by high-energy photon and electron beams may produce minimal clinical effect in comparison with the photon fluence (or dose) commonly used for photo-dynamic therapy. At the present time, it is unclear whether Cerenkov radiation is a significant contributor to the recently observed tumor regression for patients receiving radiotherapy and PpIX versus patients receiving radiotherapy only. The ongoing study will include animal experimentation and investigation of dose rate effects on PpIX response.
Constant-pH Hybrid Nonequilibrium Molecular Dynamics-Monte Carlo Simulation Method.
Chen, Yunjie; Roux, Benoît
2015-08-11
A computational method is developed to carry out explicit solvent simulations of complex molecular systems under conditions of constant pH. In constant-pH simulations, preidentified ionizable sites are allowed to spontaneously protonate and deprotonate as a function of time in response to the environment and the imposed pH. The method, based on a hybrid scheme originally proposed by H. A. Stern (J. Chem. Phys. 2007, 126, 164112), consists of carrying out short nonequilibrium molecular dynamics (neMD) switching trajectories to generate physically plausible configurations with changed protonation states that are subsequently accepted or rejected according to a Metropolis Monte Carlo (MC) criterion. To ensure microscopic detailed balance arising from such nonequilibrium switches, the atomic momenta are altered according to the symmetric two-ends momentum reversal prescription. To achieve higher efficiency, the original neMD-MC scheme is separated into two steps, reducing the need for generating a large number of unproductive and costly nonequilibrium trajectories. In the first step, the protonation state of a site is randomly attributed via a Metropolis MC process on the basis of an intrinsic pKa; an attempted nonequilibrium switch is generated only if this change in protonation state is accepted. This hybrid two-step inherent pKa neMD-MC simulation method is tested with single amino acids in solution (Asp, Glu, and His) and then applied to turkey ovomucoid third domain and hen egg-white lysozyme. Because of the simple linear increase in the computational cost relative to the number of titratable sites, the present method is naturally able to treat extremely large systems. PMID:26300709
Direct Simulation Monte Carlo for astrophysical flows - II. Ram-pressure dynamics
NASA Astrophysics Data System (ADS)
Weinberg, Martin D.
2014-03-01
We use the Direct Simulation Monte Carlo method combined with an N-body code to study the dynamics of the interaction between a gas-rich spiral galaxy and intracluster or intragroup medium, often known as the ram pressure scenario. The advantage of this gas kinetic approach over traditional hydrodynamics is explicit treatment of the interface between the hot and cold, dense and rarefied media typical of astrophysical flows and the explicit conservation of energy and momentum and the interface. This approach yields some new physical insight. Owing to the shock and backward wave that forms at the point intracluster medium (ICM)-interstellar medium (ISM) contact, ICM gas is compressed, heated and slowed. The shock morphology is Mach disc like. In the outer galaxy, the hot turbulent post-shock gas flows around the galaxy disc while heating and ablating the initially cool disc gas. The outer gas and angular momentum are lost to the flow. In the inner galaxy, the hot gas pressurizes the neutral ISM gas causing a strong two-phase instability. As a result, the momentum of the wind is no longer impulsively communicated to the cold gas as assumed in the Gunn-Gott formula, but oozes through the porous disc, transferring its linear momentum to the disc en masse. The escaping gas mixture has a net positive angular momentum and forms a slowly rotating sheath. The shear flow caused by the post-shock ICM flowing through the porous multiphase ISM creates a strong Kelvin-Helmholtz instability in the disc that results in Cartwheel-like ring and spoke morphology.
Morokoff, W.J.; Caflisch, R.E.
1995-12-01
The standard Monte Carlo approach to evaluating multidimensional integrals using (pseudo)-random integration nodes is frequently used when quadrature methods are too difficult or expensive to implement. As an alternative to the random methods, it has been suggested that lower error and improved convergence may be obtained by replacing the pseudo-random sequences with more uniformly distributed sequences known as quasi-random. In this paper quasi-random (Halton, Sobol`, and Faure) and pseudo-random sequences are compared in computational experiments designed to determine the effects on convergence of certain properties of the integrand, including variance, variation, smoothness, and dimension. The results show that variation, which plays an important role in the theoretical upper bound given by the Koksma-Hlawka inequality, does not affect convergence, while variance, the determining factor in random Monte Carlo, is shown to provide a rough upper bound, but does not accurately predict performance. In general, quasi-Monte Carlo methods are superior to random Monte Carlo, but the advantage may be slight, particularly in high dimensions or for integrands that are not smooth. For discontinuous integrands, we derive a bound which shows that the exponent for algebraic decay of the integration error from quasi-Monte Carlo is only slightly larger than {1/2} in high dimensions. 21 refs., 6 figs., 5 tabs.
NASA Astrophysics Data System (ADS)
Morokoff, William J.; Caflisch, Russel E.
1995-12-01
The standard Monte Carlo approach to evaluating multidimensional integrals using (pseudo)-random integration nodes is frequently used when quadrature methods are too difficult or expensive to implement. As an alternative to the random methods, it has been suggested that lower error and improved convergence may be obtained by replacing the pseudo-random sequences with more uniformly distributed sequences known as quasi-random. In this paper quasi-random (Halton, Sobol', and Faure) and pseudo-random sequences are compared in computational experiments designed to determine the effects on convergence of certain properties of the integrand, including variance, variation, smoothness, and dimension. The results show that variation, which plays an important role in the theoretical upper bound given by the Koksma-Hlawka inequality, does not affect convergence, while variance, the determining factor in random Monte Carlo, is shown to provide a rough upper bound, but does not accurately predict performance. In general, quasi-Monte Carlo methods are superior to random Monte Carlo, but the advantage may be slight, particularly in high dimensions or for integrands that are not smooth. For discontinuous integrands, we derive a bound which shows that the exponent for algebraic decay of the integration error from quasi-Monte Carlo is only slightly larger than {1}/{2} in high dimensions.
Monte Carlo investigation of critical dynamics in the three-dimensional Ising model
NASA Astrophysics Data System (ADS)
Wansleben, S.; Landau, D. P.
1991-03-01
We report the results of a Monte Carlo investigation of the (equilibrium) time-displaced correlation functions for the magnetization and energy of a simple cubic Ising model as a function of time, temperature, and lattice size. The simulations were carried out on a CDC CYBER 205 supercomputer employing a high-speed, vectorized multispin coding program and using a total of 5×1012 Monte Carlo spin-flip trials. We used L×L×L lattices with periodic boundary conditions and L as large as 96. The short-time and long-time behaviors of the correlation functions are analyzed by fits to a sum of exponential decays, and the critical exponent z for the largest relaxation time is extracted using a finite-size-scaling analysis. Our estimate z=2.04+/-0.03 resolves an intriguing contradiction in the literature; it satisfies the theoretical lower bound and is in agreement with the prediction obtained by ɛ expansion. We also consider various small systematic errors that typically occur in the analysis of relaxation functions and show how they can lead to spurious results if sufficient care is not exercised.
Correlated electron dynamics with time-dependent quantum Monte Carlo: three-dimensional helium.
Christov, Ivan P
2011-07-28
Here the recently proposed time-dependent quantum Monte Carlo method is applied to three dimensional para- and ortho-helium atoms subjected to an external electromagnetic field with amplitude sufficient to cause significant ionization. By solving concurrently sets of up to 20,000 coupled 3D time-dependent Schrödinger equations for the guide waves and corresponding sets of first order equations of motion for the Monte Carlo walkers we obtain ground state energies in close agreement with the exact values. The combined use of spherical coordinates and B-splines along the radial coordinate proves to be especially accurate and efficient for such calculations. Our results for the dipole response and the ionization of an atom with un-correlated electrons are in good agreement with the predictions of the conventional time-dependent Hartree-Fock method while the calculations with correlated electrons show enhanced ionization that is due to the electron-electron repulsion. PMID:21806103
Proton Upset Monte Carlo Simulation
NASA Technical Reports Server (NTRS)
O'Neill, Patrick M.; Kouba, Coy K.; Foster, Charles C.
2009-01-01
The Proton Upset Monte Carlo Simulation (PROPSET) program calculates the frequency of on-orbit upsets in computer chips (for given orbits such as Low Earth Orbit, Lunar Orbit, and the like) from proton bombardment based on the results of heavy ion testing alone. The software simulates the bombardment of modern microelectronic components (computer chips) with high-energy (.200 MeV) protons. The nuclear interaction of the proton with the silicon of the chip is modeled and nuclear fragments from this interaction are tracked using Monte Carlo techniques to produce statistically accurate predictions.
MCMAC: Monte Carlo Merger Analysis Code
NASA Astrophysics Data System (ADS)
Dawson, William A.
2014-07-01
Monte Carlo Merger Analysis Code (MCMAC) aids in the study of merging clusters. It takes observed priors on each subcluster's mass, radial velocity, and projected separation, draws randomly from those priors, and uses them in a analytic model to get posterior PDF's for merger dynamic properties of interest (e.g. collision velocity, time since collision).
Multilevel sequential Monte Carlo samplers
Beskos, Alexandros; Jasra, Ajay; Law, Kody; Tempone, Raul; Zhou, Yan
2016-08-24
Here, we study the approximation of expectations w.r.t. probability distributions associated to the solution of partial differential equations (PDEs); this scenario appears routinely in Bayesian inverse problems. In practice, one often has to solve the associated PDE numerically, using, for instance finite element methods and leading to a discretisation bias, with the step-size level hL. In addition, the expectation cannot be computed analytically and one often resorts to Monte Carlo methods. In the context of this problem, it is known that the introduction of the multilevel Monte Carlo (MLMC) method can reduce the amount of computational effort to estimate expectations, for a given level of error. This is achieved via a telescoping identity associated to a Monte Carlo approximation of a sequence of probability distributions with discretisation levelsmore » $${\\infty}$$ >h0>h1 ...>hL. In many practical problems of interest, one cannot achieve an i.i.d. sampling of the associated sequence of probability distributions. A sequential Monte Carlo (SMC) version of the MLMC method is introduced to deal with this problem. In conclusion, it is shown that under appropriate assumptions, the attractive property of a reduction of the amount of computational effort to estimate expectations, for a given level of error, can be maintained within the SMC context.« less
Synchronous Parallel Kinetic Monte Carlo
Mart?nez, E; Marian, J; Kalos, M H
2006-12-14
A novel parallel kinetic Monte Carlo (kMC) algorithm formulated on the basis of perfect time synchronicity is presented. The algorithm provides an exact generalization of any standard serial kMC model and is trivially implemented in parallel architectures. We demonstrate the mathematical validity and parallel performance of the method by solving several well-understood problems in diffusion.
Monte Carlo calculations of nuclei
Pieper, S.C.
1997-10-01
Nuclear many-body calculations have the complication of strong spin- and isospin-dependent potentials. In these lectures the author discusses the variational and Green`s function Monte Carlo techniques that have been developed to address this complication, and presents a few results.
Mapping the Monte Carlo scheme to Langevin dynamics: a Fokker-Planck approach.
Cheng, X Z; Jalil, M B A; Lee, Hwee Kuan; Okabe, Yutaka
2006-02-17
We propose a general method of using the Fokker-Planck equation (FPE) to link the Monte Carlo (MC) and the Langevin micromagnetic schemes. We derive the drift and diffusion FPE terms corresponding to the MC method and show that it is analytically equivalent to the stochastic Landau-Lifshitz-Gilbert (LLG) equation of Langevin-based micromagnetics. Subsequent results such as the time-quantification factor for the Metropolis MC method can be rigorously derived from this mapping equivalence. The validity of the mapping is shown by the close numerical convergence between the MC method and the LLG equation for the case of a single magnetic particle as well as interacting arrays of particles. We also find that our Metropolis MC method is accurate for a large range of damping factors alpha, unlike previous time-quantified MC methods which break down at low alpha, where precessional motion dominates. PMID:16606044
Mapping the Monte Carlo Scheme to Langevin Dynamics: A Fokker-Planck Approach
NASA Astrophysics Data System (ADS)
Cheng, X. Z.; Jalil, M. B.; Lee, Hwee Kuan; Okabe, Yutaka
2006-02-01
We propose a general method of using the Fokker-Planck equation (FPE) to link the Monte Carlo (MC) and the Langevin micromagnetic schemes. We derive the drift and diffusion FPE terms corresponding to the MC method and show that it is analytically equivalent to the stochastic Landau-Lifshitz-Gilbert (LLG) equation of Langevin-based micromagnetics. Subsequent results such as the time-quantification factor for the Metropolis MC method can be rigorously derived from this mapping equivalence. The validity of the mapping is shown by the close numerical convergence between the MC method and the LLG equation for the case of a single magnetic particle as well as interacting arrays of particles. We also find that our Metropolis MC method is accurate for a large range of damping factors α, unlike previous time-quantified MC methods which break down at low α, where precessional motion dominates.
NASA Technical Reports Server (NTRS)
Haviland, J. K.
1974-01-01
The results are reported of two unrelated studies. The first was an investigation of the formulation of the equations for non-uniform unsteady flows, by perturbation of an irrotational flow to obtain the linear Green's equation. The resulting integral equation was found to contain a kernel which could be expressed as the solution of the adjoint flow equation, a linear equation for small perturbations, but with non-constant coefficients determined by the steady flow conditions. It is believed that the non-uniform flow effects may prove important in transonic flutter, and that in such cases, the use of doublet type solutions of the wave equation would then prove to be erroneous. The second task covered an initial investigation into the use of the Monte Carlo method for solution of acoustical field problems. Computed results are given for a rectangular room problem, and for a problem involving a circular duct with a source located at the closed end.
GPU accelerated Monte Carlo simulation of Brownian motors dynamics with CUDA
NASA Astrophysics Data System (ADS)
Spiechowicz, J.; Kostur, M.; Machura, L.
2015-06-01
This work presents an updated and extended guide on methods of a proper acceleration of the Monte Carlo integration of stochastic differential equations with the commonly available NVIDIA Graphics Processing Units using the CUDA programming environment. We outline the general aspects of the scientific computing on graphics cards and demonstrate them with two models of a well known phenomenon of the noise induced transport of Brownian motors in periodic structures. As a source of fluctuations in the considered systems we selected the three most commonly occurring noises: the Gaussian white noise, the white Poissonian noise and the dichotomous process also known as a random telegraph signal. The detailed discussion on various aspects of the applied numerical schemes is also presented. The measured speedup can be of the astonishing order of about 3000 when compared to a typical CPU. This number significantly expands the range of problems solvable by use of stochastic simulations, allowing even an interactive research in some cases.
Cozmuta, Ioana; Blanco, Mario; Goddard, William A
2007-03-29
It is important for many industrial processes to design new materials with improved selective permeability properties. Besides diffusion, the molecule's solubility contributes largely to the overall permeation process. This study presents a method to calculate solubility coefficients of gases such as O2, H2O (vapor), N2, and CO2 in polymeric matrices from simulation methods (Molecular Dynamics and Monte Carlo) using first principle predictions. The generation and equilibration (annealing) of five polymer models (polypropylene, polyvinyl alcohol, polyvinyl dichloride, polyvinyl chloride-trifluoroethylene, and polyethylene terephtalate) are extensively described. For each polymer, the average density and Hansen solubilities over a set of ten samples compare well with experimental data. For polyethylene terephtalate, the average properties between a small (n = 10) and a large (n = 100) set are compared. Boltzmann averages and probability density distributions of binding and strain energies indicate that the smaller set is biased in sampling configurations with higher energies. However, the sample with the lowest cohesive energy density from the smaller set is representative of the average of the larger set. Density-wise, low molecular weight polymers tend to have on average lower densities. Infinite molecular weight samples do however provide a very good representation of the experimental density. Solubility constants calculated with two ensembles (grand canonical and Henry's constant) are equivalent within 20%. For each polymer sample, the solubility constant is then calculated using the faster (10x) Henry's constant ensemble (HCE) from 150 ps of NPT dynamics of the polymer matrix. The influence of various factors (bad contact fraction, number of iterations) on the accuracy of Henry's constant is discussed. To validate the calculations against experimental results, the solubilities of nitrogen and carbon dioxide in polypropylene are examined over a range of
NASA Astrophysics Data System (ADS)
Chen, Yin-Chu; Ferracane, Jack L.; Prahl, Scott A.
2005-03-01
Photo-cured dental composites are widely used in dental practices to restore teeth due to the esthetic appearance of the composites and the ability to cure in situ. However, their complex optical characteristics make it difficult to understand the light transport within the composites and to predict the depth of cure. Our previous work showed that the absorption and scattering coefficients of the composite changed after the composite was cured. The static Monte Carlo simulation showed that the penetration of radiant exposures differed significantly for cured and uncured optical properties. This means that a dynamic model is required for accurate prediction of radiant exposure in the composites. The purpose of this study was to develop and verify a dynamic Monte Carlo (DMC) model simulating light propagation in dental composites that have dynamic optical properties while photons are absorbed. The composite was divided into many small cubes, each of which had its own scattering and absorption coefficients. As light passed through the composite, the light was scattered and absorbed. The amount of light absorbed in each cube was calculated using Beer's Law and was used to determine the next optical properties in that cube. Finally, the predicted total reflectance and transmittance as well as the optical property during curing were verified numerically and experimentally. Our results showed that the model predicted values agreed with the theoretical values within 1% difference. The DMC model results are comparable with experimental results within 5% differences.
Luo, Ye Sorella, Sandro; Zen, Andrea
2014-11-21
We present a systematic study of a recently developed ab initio simulation scheme based on molecular dynamics and quantum Monte Carlo. In this approach, a damped Langevin molecular dynamics is employed by using a statistical evaluation of the forces acting on each atom by means of quantum Monte Carlo. This allows the use of an highly correlated wave function parametrized by several variational parameters and describing quite accurately the Born-Oppenheimer energy surface, as long as these parameters are determined at the minimum energy condition. However, in a statistical method both the minimization method and the evaluation of the atomic forces are affected by the statistical noise. In this work, we study systematically the accuracy and reliability of this scheme by targeting the vibrational frequencies of simple molecules such as the water monomer, hydrogen sulfide, sulfur dioxide, ammonia, and phosphine. We show that all sources of systematic errors can be controlled and reliable frequencies can be obtained with a reasonable computational effort. This work provides convincing evidence that this molecular dynamics scheme can be safely applied also to realistic systems containing several atoms.
Monte Carlo Simulation for Perusal and Practice.
ERIC Educational Resources Information Center
Brooks, Gordon P.; Barcikowski, Robert S.; Robey, Randall R.
The meaningful investigation of many problems in statistics can be solved through Monte Carlo methods. Monte Carlo studies can help solve problems that are mathematically intractable through the analysis of random samples from populations whose characteristics are known to the researcher. Using Monte Carlo simulation, the values of a statistic are…
Rota, R; Casulleras, J; Mazzanti, F; Boronat, J
2015-03-21
We present a method based on the path integral Monte Carlo formalism for the calculation of ground-state time correlation functions in quantum systems. The key point of the method is the consideration of time as a complex variable whose phase δ acts as an adjustable parameter. By using high-order approximations for the quantum propagator, it is possible to obtain Monte Carlo data all the way from purely imaginary time to δ values near the limit of real time. As a consequence, it is possible to infer accurately the spectral functions using simple inversion algorithms. We test this approach in the calculation of the dynamic structure function S(q, ω) of two one-dimensional model systems, harmonic and quartic oscillators, for which S(q, ω) can be exactly calculated. We notice a clear improvement in the calculation of the dynamic response with respect to the common approach based on the inverse Laplace transform of the imaginary-time correlation function. PMID:25796238
Zimmerman, G.B.
1997-06-24
Monte Carlo methods appropriate to simulate the transport of x-rays, neutrons, ion and electrons in Inertial Confinement Fusion targets are described and analyzed. The Implicit Monte Carlo method of x-ray transport handles symmetry within indirect drive ICF hohlraums well, but can be improved 50X in efficiency by angular biasing the x-rays towards the fuel capsule. Accurate simulation of thermonuclear burns nd burn diagnostics involves detailed particle source spectra, charged particle ranges, inflight reaction kinematics, corrections for bulk and thermal Doppler effects and variance reduction to obtain adequate statistics for rare events. It is found that the effects of angular Coulomb scattering must be included in models of charged particle transport through heterogeneous materials.
Shell model Monte Carlo methods
Koonin, S.E.; Dean, D.J.
1996-10-01
We review quantum Monte Carlo methods for dealing with large shell model problems. These methods reduce the imaginary-time many-body evolution operator to a coherent superposition of one-body evolutions in fluctuating one-body fields; resultant path integral is evaluated stochastically. We first discuss the motivation, formalism, and implementation of such Shell Model Monte Carlo methods. There then follows a sampler of results and insights obtained from a number of applications. These include the ground state and thermal properties of pf-shell nuclei, thermal behavior of {gamma}-soft nuclei, and calculation of double beta-decay matrix elements. Finally, prospects for further progress in such calculations are discussed. 87 refs.
Womersley, J. . Dept. of Physics)
1992-10-01
The D0 detector at the Fermilab Tevatron began its first data taking run in May 1992. For analysis of the expected 25 pb[sup [minus]1] data sample, roughly half a million simulated events will be needed. The GEANT-based Monte Carlo program used to generate these events is described, together with comparisons to test beam data. Some novel techniques used to speed up execution and simplify geometrical input are described.
Two-dimensional dynamical drainage-flow model with Monte Carlo transport and diffusion calculations
Garrett, A.J.; Smith, F.G. III
1982-09-01
A simplified drainage flow model was developed from the equations of motion and the mass continuity equation in a terrain-following coordinate system. The equations were reduced to a two-dimensional system by vertically integrating over the drainage layer. A numerical solution for the drainage layer depth and wind field was obtained using a fourth order finite difference scheme. A Monte Carlo simulation was used to calculate the transport and diffusion of tracer gases. Model simulations of drainage flow have been compared to observations from the 1980 Geysers area experiments. The Geysers area is mountainous, with steep slopes, some of which are steeper than 10/sup 0/. The model predictions of wind direction are good, but with speeds are not predicted as accurately. Simulation of perfluorocarbon tracer concentrations were in good agreement with observed values. Maximum tracer concentration was predicted to within a factor of five. While predicted plume arrival was somewhat early, the model closely predicted the duration of the passage for plume concentrations greater than 0.5 ppt. The two-dimensional model was found to work equally well in simulating drainage flows over the Savannah River Plant (SRP) and surrounding terrain with slopes of around 1/sup 0/. The model correctly predicted that drainage winds at SRP are usually shallower than 60 m, which is the height at which meteorological towers measure the winds in the SRP production areas. The modest computational requirements of the model make it suitable for use in screening potential industrial sites.
Kamibayashi, Yuki; Miura, Shinichi
2016-08-21
In the present study, variational path integral molecular dynamics and associated hybrid Monte Carlo (HMC) methods have been developed on the basis of a fourth order approximation of a density operator. To reveal various parameter dependence of physical quantities, we analytically solve one dimensional harmonic oscillators by the variational path integral; as a byproduct, we obtain the analytical expression of the discretized density matrix using the fourth order approximation for the oscillators. Then, we apply our methods to realistic systems like a water molecule and a para-hydrogen cluster. In the HMC, we adopt two level description to avoid the time consuming Hessian evaluation. For the systems examined in this paper, the HMC method is found to be about three times more efficient than the molecular dynamics method if appropriate HMC parameters are adopted; the advantage of the HMC method is suggested to be more evident for systems described by many body interaction. PMID:27544094
NASA Astrophysics Data System (ADS)
Meng, Lingyi; Wang, Dong; Li, Qikai; Yi, Yuanping; Brédas, Jean-Luc; Shuai, Zhigang
2011-03-01
We describe a new dynamic Monte Carlo model to simulate the operation of a polymer-blend solar cell; this model provides major improvements with respect to the one we developed earlier [J. Phys. Chem. B 114, 36 (2010)] by incorporating the Poisson equation and a charge thermoactivation mechanism. The advantage of the present approach is its capacity to deal with a nonuniform electrostatic potential that dynamically depends on the charge distribution. In this way, the unbalance in electron and hole mobilities and the space-charge induced potential distribution can be treated explicitly. Simulations reproduce well the experimental I-V curve in the dark and the open-circuit voltage under illumination of a polymer-blend solar cell. The dependence of the photovoltaic performance on the difference in electron and hole mobilities is discussed.
NASA Astrophysics Data System (ADS)
Jehan, Musarrat
The response of a dynamic system is random. There is randomness in both the applied loads and the strength of the system. Therefore, to account for the uncertainty, the safety of the system must be quantified using its probability of survival (reliability). Monte Carlo Simulation (MCS) is a widely used method for probabilistic analysis because of its robustness. However, a challenge in reliability assessment using MCS is that the high computational cost limits the accuracy of MCS. Haftka et al. [2010] developed an improved sampling technique for reliability assessment called separable Monte Carlo (SMC) that can significantly increase the accuracy of estimation without increasing the cost of sampling. However, this method was applied to time-invariant problems involving two random variables only. This dissertation extends SMC to random vibration problems with multiple random variables. This research also develops a novel method for estimation of the standard deviation of the probability of failure of a structure under static or random vibration. The method is demonstrated on quarter car models and a wind turbine. The proposed method is validated using repeated standard MCS.
Khajeh, Masoud; Safigholi, Habib
2016-03-01
A miniature X-ray source has been optimized for electronic brachytherapy. The cooling fluid for this device is water. Unlike the radionuclide brachytherapy sources, this source is able to operate at variable voltages and currents to match the dose with the tumor depth. First, Monte Carlo (MC) optimization was performed on the tungsten target-buffer thickness layers versus energy such that the minimum X-ray attenuation occurred. Second optimization was done on the selection of the anode shape based on the Monte Carlo in water TG-43U1 anisotropy function. This optimization was carried out to get the dose anisotropy functions closer to unity at any angle from 0° to 170°. Three anode shapes including cylindrical, spherical, and conical were considered. Moreover, by Computational Fluid Dynamic (CFD) code the optimal target-buffer shape and different nozzle shapes for electronic brachytherapy were evaluated. The characterization criteria of the CFD were the minimum temperature on the anode shape, cooling water, and pressure loss from inlet to outlet. The optimal anode was conical in shape with a conical nozzle. Finally, the TG-43U1 parameters of the optimal source were compared with the literature. PMID:26966563
Khajeh, Masoud; Safigholi, Habib
2015-01-01
A miniature X-ray source has been optimized for electronic brachytherapy. The cooling fluid for this device is water. Unlike the radionuclide brachytherapy sources, this source is able to operate at variable voltages and currents to match the dose with the tumor depth. First, Monte Carlo (MC) optimization was performed on the tungsten target-buffer thickness layers versus energy such that the minimum X-ray attenuation occurred. Second optimization was done on the selection of the anode shape based on the Monte Carlo in water TG-43U1 anisotropy function. This optimization was carried out to get the dose anisotropy functions closer to unity at any angle from 0° to 170°. Three anode shapes including cylindrical, spherical, and conical were considered. Moreover, by Computational Fluid Dynamic (CFD) code the optimal target-buffer shape and different nozzle shapes for electronic brachytherapy were evaluated. The characterization criteria of the CFD were the minimum temperature on the anode shape, cooling water, and pressure loss from inlet to outlet. The optimal anode was conical in shape with a conical nozzle. Finally, the TG-43U1 parameters of the optimal source were compared with the literature. PMID:26966563
NASA Astrophysics Data System (ADS)
Oliver, Mike; Staruch, Robert; Gladwish, Adam; Craig, Jeff; Chen, Jeff; Wong, Eugene
2008-05-01
Respiratory gating is emerging as a tool to limit the effect of motion for liver and lung tumors. In order to study the impact of target motion and gated intensity modulated radiation therapy (IMRT) delivery, a computer program was developed to simulate segmental IMRT delivery to a moving phantom. Two distinct plans were delivered to a rigid-motion phantom with a film insert in place under four conditions: static, sinusoidal motion, gated sinusoidal motion with a duty cycle of 25% and gated sinusoidal motion with duty cycle of 50% under motion conditions of a typical patient (A = 1 cm, T = 4 s). The MLC controller log files and gating log files were retained to perform a retrospective Monte Carlo dose calculation of the plans. Comparison of the 2D planar dose distributions between simulation and measurement demonstrated that our technique had at least 94% of the points passing gamma criteria of 3% for dose difference and 3 mm as the distance to agreement. This note demonstrates that the use of dynamic multi-leaf collimator and respiratory monitoring system log files together with a fast Monte Carlo dose calculation algorithm is an accurate and efficient way to study the dosimetric effect of motion for gated or non-gated IMRT delivery on a rigidly-moving body.
Applications of Maxent to quantum Monte Carlo
Silver, R.N.; Sivia, D.S.; Gubernatis, J.E. ); Jarrell, M. . Dept. of Physics)
1990-01-01
We consider the application of maximum entropy methods to the analysis of data produced by computer simulations. The focus is the calculation of the dynamical properties of quantum many-body systems by Monte Carlo methods, which is termed the Analytical Continuation Problem.'' For the Anderson model of dilute magnetic impurities in metals, we obtain spectral functions and transport coefficients which obey Kondo Universality.'' 24 refs., 7 figs.
NASA Astrophysics Data System (ADS)
Tsirkunov, Yu. M.; Romanyuk, D. A.
2016-07-01
A dusty gas flow through two, moving and immovable, cascades of airfoils (blades) is studied numerically. In the mathematical model of two-phase gas-particle flow, the carrier gas is treated as a continuum and it is described by the Navier-Stokes equations (pseudo-DNS (direct numerical simulation) approach) or the Reynolds averaged Navier-Stokes (RANS) equations (unsteady RANS approach) with the Menter k-ω shear stress transport (SST) turbulence model. The governing equations in both cases are solved by computational fluid dynamics (CFD) methods. The dispersed phase is treated as a discrete set of solid particles, the behavior of which is described by the generalized kinetic Boltzmann equation. The effects of gas-particle interaction, interparticle collisions, and particle scattering in particle-blade collisions are taken into account. The direct simulation Monte Carlo (DSMC) method is used for computational simulation of the dispersed phase flow. The effects of interparticle collisions and particle scattering are discussed.
NASA Astrophysics Data System (ADS)
Konoplev, V.; Caturla, M. J.; Abril, I.; Gras-Marti, A.
1994-05-01
We investigate the atomic mixing produced in the bulk of a zero-temperature silicon target by internally-starting low-energy (100 eV) self-recoils. Molecular Dynamics (MD) and Monte Carlo (MC) simulations are applied. The many-body Tersoff potential connected smoothly with the pairlike Ziegler-Biersack potential is used in the MD simulation. The collisional model of the MC code is based on the Ziegler-Biersack potential and includes a calculation of the mean free-flight path and the random impact parameter by using the energy-dependent total cross-section for elastic collisions. For a quantitative description of the process of ion-induced atomic mixing we calculate the depth dependence of the number of displaced atoms, and the first and second moments of the relocation cross-section. We analyse the discrepancies between the two computer simulations, and suggest an adjustment of the pertinent parameters in the MC model.
NASA Astrophysics Data System (ADS)
Khanal, Kiran; Luettmer-Strathmann, Jutta
2009-04-01
Static and dynamic properties of polymers are affected by the stiffness of the chains. In this work, we investigate structural and thermodynamic properties of a lattice model for semiflexible polymer chains. The model is an extension of Shaffer's bond- fluctuation model and includes attractive interactions between monomers and an adjustable bending penalty that determines the Kuhn segment length. This allows us to model melts of flexible and semiflexible chains. For this work, we performed Monte Carlo simulations for polymer melts with a range of bending parameters and densities. Results for chain dimensions show that the Kuhn segment length increases monotonously with the bending penalty and has a linear dependence for a range of bending parameters. Results for self diffusion constants show that the translational mobility is strongly reduced by increasing chain stiffness. We also investigate equation-of-state properties of the melts.
Alcaraz, Olga; Trullàs, Joaquim; Tahara, Shuta; Kawakita, Yukinobu; Takeda, Shin'ichi
2016-09-01
The results of the structural properties of molten copper chloride are reported from high-energy X-ray diffraction measurements, reverse Monte Carlo modeling method, and molecular dynamics simulations using a polarizable ion model. The simulated X-ray structure factor reproduces all trends observed experimentally, in particular the shoulder at around 1 Å(-1) related to intermediate range ordering, as well as the partial copper-copper correlations from the reverse Monte Carlo modeling, which cannot be reproduced by using a simple rigid ion model. It is shown that the shoulder comes from intermediate range copper-copper correlations caused by the polarized chlorides. PMID:27609000
Monte Carlo surface flux tallies
Favorite, Jeffrey A
2010-11-19
Particle fluxes on surfaces are difficult to calculate with Monte Carlo codes because the score requires a division by the surface-crossing angle cosine, and grazing angles lead to inaccuracies. We revisit the standard practice of dividing by half of a cosine 'cutoff' for particles whose surface-crossing cosines are below the cutoff. The theory behind this approximation is sound, but the application of the theory to all possible situations does not account for two implicit assumptions: (1) the grazing band must be symmetric about 0, and (2) a single linear expansion for the angular flux must be applied in the entire grazing band. These assumptions are violated in common circumstances; for example, for separate in-going and out-going flux tallies on internal surfaces, and for out-going flux tallies on external surfaces. In some situations, dividing by two-thirds of the cosine cutoff is more appropriate. If users were able to control both the cosine cutoff and the substitute value, they could use these parameters to make accurate surface flux tallies. The procedure is demonstrated in a test problem in which Monte Carlo surface fluxes in cosine bins are converted to angular fluxes and compared with the results of a discrete ordinates calculation.
Multidimensional stochastic approximation Monte Carlo.
Zablotskiy, Sergey V; Ivanov, Victor A; Paul, Wolfgang
2016-06-01
Stochastic Approximation Monte Carlo (SAMC) has been established as a mathematically founded powerful flat-histogram Monte Carlo method, used to determine the density of states, g(E), of a model system. We show here how it can be generalized for the determination of multidimensional probability distributions (or equivalently densities of states) of macroscopic or mesoscopic variables defined on the space of microstates of a statistical mechanical system. This establishes this method as a systematic way for coarse graining a model system, or, in other words, for performing a renormalization group step on a model. We discuss the formulation of the Kadanoff block spin transformation and the coarse-graining procedure for polymer models in this language. We also apply it to a standard case in the literature of two-dimensional densities of states, where two competing energetic effects are present g(E_{1},E_{2}). We show when and why care has to be exercised when obtaining the microcanonical density of states g(E_{1}+E_{2}) from g(E_{1},E_{2}). PMID:27415383
Multidimensional stochastic approximation Monte Carlo
NASA Astrophysics Data System (ADS)
Zablotskiy, Sergey V.; Ivanov, Victor A.; Paul, Wolfgang
2016-06-01
Stochastic Approximation Monte Carlo (SAMC) has been established as a mathematically founded powerful flat-histogram Monte Carlo method, used to determine the density of states, g (E ) , of a model system. We show here how it can be generalized for the determination of multidimensional probability distributions (or equivalently densities of states) of macroscopic or mesoscopic variables defined on the space of microstates of a statistical mechanical system. This establishes this method as a systematic way for coarse graining a model system, or, in other words, for performing a renormalization group step on a model. We discuss the formulation of the Kadanoff block spin transformation and the coarse-graining procedure for polymer models in this language. We also apply it to a standard case in the literature of two-dimensional densities of states, where two competing energetic effects are present g (E1,E2) . We show when and why care has to be exercised when obtaining the microcanonical density of states g (E1+E2) from g (E1,E2) .
1-D EQUILIBRIUM DISCRETE DIFFUSION MONTE CARLO
T. EVANS; ET AL
2000-08-01
We present a new hybrid Monte Carlo method for 1-D equilibrium diffusion problems in which the radiation field coexists with matter in local thermodynamic equilibrium. This method, the Equilibrium Discrete Diffusion Monte Carlo (EqDDMC) method, combines Monte Carlo particles with spatially discrete diffusion solutions. We verify the EqDDMC method with computational results from three slab problems. The EqDDMC method represents an incremental step toward applying this hybrid methodology to non-equilibrium diffusion, where it could be simultaneously coupled to Monte Carlo transport.
Novel phase-space Monte-Carlo method for quench dynamics in 1D and 2D spin models
NASA Astrophysics Data System (ADS)
Pikovski, Alexander; Schachenmayer, Johannes; Rey, Ana Maria
2015-05-01
An important outstanding problem is the effcient numerical computation of quench dynamics in large spin systems. We propose a semiclassical method to study many-body spin dynamics in generic spin lattice models. The method, named DTWA, is based on a novel type of discrete Monte-Carlo sampling in phase-space. We demonstare the power of the technique by comparisons with analytical and numerically exact calculations. It is shown that DTWA captures the dynamics of one- and two-point correlations 1D systems. We also use DTWA to study the dynamics of correlations in 2D systems with many spins and different types of long-range couplings, in regimes where other numerical methods are generally unreliable. Computing spatial and time-dependent correlations, we find a sharp change in the speed of propagation of correlations at a critical range of interactions determined by the system dimension. The investigations are relevant for a broad range of systems including solids, atom-photon systems and ultracold gases of polar molecules, trapped ions, Rydberg, and magnetic atoms. This work has been financially supported by JILA-NSF-PFC-1125844, NSF-PIF-1211914, ARO, AFOSR, AFOSR-MURI.
Jones, Stuart; Lacey, Peter; Walshe, Terry
2009-04-01
Lake Toolibin, an ephemeral lake in the agricultural zone of Western Australia, is under threat from secondary salinity due to land clearance throughout the catchment. The lake is extensively covered with native vegetation and is a Ramsar listed wetland, being one of the few remaining significant migratory bird habitats in the region. Currently, inflow with salinity greater than 1000 mg/L TDS is diverted from the lake in an effort to protect sensitive lakebed vegetation. However, this conservative threshold compromises the frequency and extent of lake inundation, which is essential for bird breeding. It is speculated that relaxing the threshold to 5000 mg/L may pose negligible additional risk to the condition of lakebed vegetation. To characterise the magnitude of improvement in the provision of bird breeding habitat that might be generated by relaxing the threshold, a dynamic water and salt balance model of the lake was developed and implemented using Monte Carlo simulation. Results from best estimate model inputs indicate that relaxation of the threshold increases the likelihood of satisfying habitat requirements by a factor of 9.7. A second-order Monte Carlo analysis incorporating incertitude generated plausible bounds of [2.6, 37.5] around the best estimate for the relative likelihood of satisfying habitat requirements. Parameter-specific sensitivity analyses suggest the availability of habitat is most sensitive to pan evaporation, lower than expected inflow volume, and higher than expected inflow salt concentration. The characterisation of uncertainty associated with environmental variation and incertitude allows managers to make informed risk-weighted decisions. PMID:19114292
NASA Astrophysics Data System (ADS)
Cepeda, Jose; Luna, Byron Quan; Nadim, Farrokh
2013-04-01
An essential component of a quantitative landslide hazard assessment is establishing the extent of the endangered area. This task requires accurate prediction of the run-out behaviour of a landslide, which includes the estimation of the run-out distance, run-out width, velocities, pressures, and depth of the moving mass and the final configuration of the deposits. One approach to run-out modelling is to reproduce accurately the dynamics of the propagation processes. A number of dynamic numerical models are able to compute the movement of the flow over irregular topographic terrains (3-D) controlled by a complex interaction between mechanical properties that may vary in space and time. Given the number of unknown parameters and the fact that most of the rheological parameters cannot be measured in the laboratory or field, the parametrization of run-out models is very difficult in practice. For this reason, the application of run-out models is mostly used for back-analysis of past events and very few studies have attempted to achieve forward predictions. Consequently all models are based on simplified descriptions that attempt to reproduce the general features of the failed mass motion through the use of parameters (mostly controlling shear stresses at the base of the moving mass) which account for aspects not explicitly described or oversimplified. The uncertainties involved in the run-out process have to be approached in a stochastic manner. It is of significant importance to develop methods for quantifying and properly handling the uncertainties in dynamic run-out models, in order to allow a more comprehensive approach to quantitative risk assessment. A method was developed to compute the variation in run-out intensities by using a dynamic run-out model (MassMov2D) and a probabilistic framework based on a Monte Carlo simulation in order to analyze the effect of the uncertainty of input parameters. The probability density functions of the rheological parameters
Statics and dynamics of the ten-state mean-field Potts glass model: a Monte Carlo study
NASA Astrophysics Data System (ADS)
Brangian, Claudio; Kob, Walter; Binder, Kurt
2002-01-01
We investigate by means of Monte Carlo simulations the fully connected p-state Potts model for different system sizes in order to see how the static and dynamic properties of a finite model compare with the, exactly known, behaviour of the system in the thermodynamic limit. Using p = 10 we are able to study the equilibrium dynamics for system sizes as large as N = 2560. We find that the static quantities, such as the energy, the entropy, the spin glass susceptibility as well as the distribution of the order parameter P(q) show very strong finite-size effects. From P(q) we calculate the fourth-order cumulant g4(N,T) and the Guerra parameter G(N,T) and show that these quantities cannot be used to locate the static transition temperature for the system sizes investigated. Also the spin-autocorrelation function C(t) shows strong finite-size effects in that it does not show a plateau even for temperatures around the dynamical critical temperature TD. We show that the dependence on N and T of the α-relaxation time can be understood by means of a dynamical finite-size scaling ansatz. C(t) does not obey the time-temperature superposition principle for temperatures around TD, but does so for significantly lower T. Finally we study the relaxation dynamics of the individual spins and show that their dependence on time depends strongly on the chosen spin, i.e. that the system is dynamically very heterogeneous, which explains the non-exponentiality of C(t).
NASA Astrophysics Data System (ADS)
Taneri, Sencer
We investigate the folding dynamics of the plant-seed protein Crambin in a liquid environment, that usually happens to be water with some certain viscosity. To take into account the viscosity, necessitates a stochastic approach. This can be summarized by a 2D-Langevin equation, even though the simulation is still carried out in 3D. Solution of the Langevin equation will be the basic task in order to proceed with a Molecular Dynamics simulation, which will accompany a delicate Monte Carlo technique. The potential wells, used to engineer the energy space assuming the interaction of monomers constituting the protein-chain, are simply modeled by a combination of two parabola. This combination will approximate the real physical interactions, that is given by the well known Lennard-Jones potential. Contributions to the total potential from torsion, bending and distance dependent potentials are good to the fourth nearest neighbor. The final image is in a very good geometric agreement with the real shape of the protein chain, which can be obtained from the protein data bank. The quantitative measure of this agreement is the similarity parameter with the native structure, which is found to be 0.91 < 1 for the best sample. The folding time can be determined from Debye-relaxation process. We apply two regimes and calculate the folding time, corresponding to the elastic domain mode, which yields 5.2 ps for the same sample.
NASA Astrophysics Data System (ADS)
Ahmad, Munir; Deng, Jun; Lund, Molly W.; Chen, Zhe; Kimmett, James; Moran, Meena S.; Nath, Ravinder
2009-01-01
The goal of this work is to present a systematic Monte Carlo validation study on the clinical implementation of the enhanced dynamic wedges (EDWs) into the Pinnacle3 (Philips Medical Systems, Fitchburg, WI) treatment planning system (TPS) and QA procedures for patient plan verification treated with EDWs. Modeling of EDW beams in the Pinnacle3 TPS, which employs a collapsed-cone convolution superposition (CCCS) dose model, was based on a combination of measured open-beam data and the 'Golden Segmented Treatment Table' (GSTT) provided by Varian for each photon beam energy. To validate EDW models, dose profiles of 6 and 10 MV photon beams from a Clinac 2100 C/D were measured in virtual water at depths from near-surface to 30 cm for a wide range of field sizes and wedge angles using the Profiler 2 (Sun Nuclear Corporation, Melbourne, FL) diode array system. The EDW output factors (EDWOFs) for square fields from 4 to 20 cm wide were measured in virtual water using a small-volume Farmer-type ionization chamber placed at a depth of 10 cm on the central axis. Furthermore, the 6 and 10 MV photon beams emerging from the treatment head of Clinac 2100 C/D were fully modeled and the central-axis depth doses, the off-axis dose profiles and the output factors in water for open and dynamically wedged fields were calculated using the Monte Carlo (MC) package EGS4. Our results have shown that (1) both the central-axis depth doses and the off-axis dose profiles of various EDWs computed with the CCCS dose model and MC simulations showed good agreement with the measurements to within 2%/2 mm; (2) measured EDWOFs used for monitor-unit calculation in Pinnacle3 TPS agreed well with the CCCS and MC predictions within 2%; (3) all the EDW fields satisfied our validation criteria of 1% relative dose difference and 2 mm distance-to-agreement (DTA) with 99-100% passing rate in routine patient treatment plan verification using MapCheck 2D diode array.
Ahmad, Munir; Deng, Jun; Lund, Molly W; Chen, Zhe; Kimmett, James; Moran, Meena S; Nath, Ravinder
2009-01-21
The goal of this work is to present a systematic Monte Carlo validation study on the clinical implementation of the enhanced dynamic wedges (EDWs) into the Pinnacle(3) (Philips Medical Systems, Fitchburg, WI) treatment planning system (TPS) and QA procedures for patient plan verification treated with EDWs. Modeling of EDW beams in the Pinnacle(3) TPS, which employs a collapsed-cone convolution superposition (CCCS) dose model, was based on a combination of measured open-beam data and the 'Golden Segmented Treatment Table' (GSTT) provided by Varian for each photon beam energy. To validate EDW models, dose profiles of 6 and 10 MV photon beams from a Clinac 2100 C/D were measured in virtual water at depths from near-surface to 30 cm for a wide range of field sizes and wedge angles using the Profiler 2 (Sun Nuclear Corporation, Melbourne, FL) diode array system. The EDW output factors (EDWOFs) for square fields from 4 to 20 cm wide were measured in virtual water using a small-volume Farmer-type ionization chamber placed at a depth of 10 cm on the central axis. Furthermore, the 6 and 10 MV photon beams emerging from the treatment head of Clinac 2100 C/D were fully modeled and the central-axis depth doses, the off-axis dose profiles and the output factors in water for open and dynamically wedged fields were calculated using the Monte Carlo (MC) package EGS4. Our results have shown that (1) both the central-axis depth doses and the off-axis dose profiles of various EDWs computed with the CCCS dose model and MC simulations showed good agreement with the measurements to within 2%/2 mm; (2) measured EDWOFs used for monitor-unit calculation in Pinnacle(3) TPS agreed well with the CCCS and MC predictions within 2%; (3) all the EDW fields satisfied our validation criteria of 1% relative dose difference and 2 mm distance-to-agreement (DTA) with 99-100% passing rate in routine patient treatment plan verification using MapCheck 2D diode array. PMID:19098353
Kinetic Monte Carlo simulations of proton conductivity
NASA Astrophysics Data System (ADS)
Masłowski, T.; Drzewiński, A.; Ulner, J.; Wojtkiewicz, J.; Zdanowska-Frączek, M.; Nordlund, K.; Kuronen, A.
2014-07-01
The kinetic Monte Carlo method is used to model the dynamic properties of proton diffusion in anhydrous proton conductors. The results have been discussed with reference to a two-step process called the Grotthuss mechanism. There is a widespread belief that this mechanism is responsible for fast proton mobility. We showed in detail that the relative frequency of reorientation and diffusion processes is crucial for the conductivity. Moreover, the current dependence on proton concentration has been analyzed. In order to test our microscopic model the proton transport in polymer electrolyte membranes based on benzimidazole C7H6N2 molecules is studied.
A Monte Carlo approach to water management
NASA Astrophysics Data System (ADS)
Koutsoyiannis, D.
2012-04-01
Common methods for making optimal decisions in water management problems are insufficient. Linear programming methods are inappropriate because hydrosystems are nonlinear with respect to their dynamics, operation constraints and objectives. Dynamic programming methods are inappropriate because water management problems cannot be divided into sequential stages. Also, these deterministic methods cannot properly deal with the uncertainty of future conditions (inflows, demands, etc.). Even stochastic extensions of these methods (e.g. linear-quadratic-Gaussian control) necessitate such drastic oversimplifications of hydrosystems that may make the obtained results irrelevant to the real world problems. However, a Monte Carlo approach is feasible and can form a general methodology applicable to any type of hydrosystem. This methodology uses stochastic simulation to generate system inputs, either unconditional or conditioned on a prediction, if available, and represents the operation of the entire system through a simulation model as faithful as possible, without demanding a specific mathematical form that would imply oversimplifications. Such representation fully respects the physical constraints, while at the same time it evaluates the system operation constraints and objectives in probabilistic terms, and derives their distribution functions and statistics through Monte Carlo simulation. As the performance criteria of a hydrosystem operation will generally be highly nonlinear and highly nonconvex functions of the control variables, a second Monte Carlo procedure, implementing stochastic optimization, is necessary to optimize system performance and evaluate the control variables of the system. The latter is facilitated if the entire representation is parsimonious, i.e. if the number of control variables is kept at a minimum by involving a suitable system parameterization. The approach is illustrated through three examples for (a) a hypothetical system of two reservoirs
Goujon, Florent; Malfreyt, Patrice; Simon, Jean-Marc; Boutin, Anne; Rousseau, Bernard; Fuchs, Alain H
2004-12-22
The Monte Carlo (MC) and molecular dynamics (MD) methodologies are now well established for computing equilibrium properties in homogeneous fluids. This is not yet the case for the direct simulation of two-phase systems, which exhibit nonuniformity of the density distribution across the interface. We have performed direct MC and MD simulations of the liquid-gas interface of n-pentane using a standard force-field model. We obtained density and pressure components profiles along the direction normal to the interface that can be very different, depending on the truncation and long range correction strategies. We discuss the influence on predicted properties of different potential truncation schemes implemented in both MC and MD simulations. We show that the MD and MC profiles can be made in agreement by using a Lennard-Jones potential truncated via a polynomial function that makes the first and second derivatives of the potential continuous at the cutoff distance. In this case however, the predicted thermodynamic properties (phase envelope, surface tension) deviate from experiments, because of the changes made in the potential. A further readjustment of the potential parameters is needed if one wants to use this method. We conclude that a straightforward use of bulk phase force fields in MD simulations may lead to some physical inconsistencies when computing interfacial properties. PMID:15606277
Dix, James A.; Hom, Erik F. Y.; Verkman, A. S.
2011-01-01
Fluorescence correlation spectroscopy (FCS) is being applied increasingly to study diffusion and interactions of fluorescently labeled macromolecules in complex biological systems. Fluctuations in detected fluorescence, δF(t), are expressed as time-correlation functions, G(τ), and photon-count histograms, P(k;ΔT). Here, we developed a generalized simulation approach to compute G(τ) and P(k;ΔT) for complex systems with arbitrary geometry, photophysics, diffusion, and macromolecular interactions. G(τ) and P(k;ΔT) were computed from δF(t) generated by a Brownian dynamics simulation of single-molecule trajectories followed by a Monte Carlo simulation of fluorophore excitation and detection statistics. Simulations were validated by comparing analytical and simulated G(τ) and P(k;ΔT) for diffusion of noninteracting fluorophores in a three-dimensional Gaussian excitation and detection volume. Inclusion of photobleaching and triplet-state relaxation produced significant changes in G(τ) and P(k;ΔT). Simulations of macromolecular interactions and complex diffusion were done, including transient fluorophore binding to an immobile matrix, cross-correlation analysis of interacting fluorophores, and anomalous sub- and superdiffusion. The computational method developed here is generally applicable for simulating FCS measurements on systems complicated by fluorophore interactions or molecular crowding, and experimental protocols for which G(τ) and P(k;ΔT) cannot be computed analytically. PMID:16471761
Dawson, William A.
2013-08-01
Merging galaxy clusters have become one of the most important probes of dark matter, providing evidence for dark matter over modified gravity and even constraints on the dark matter self-interaction cross-section. To properly constrain the dark matter cross-section it is necessary to understand the dynamics of the merger, as the inferred cross-section is a function of both the velocity of the collision and the observed time since collision. While the best understanding of merging system dynamics comes from N-body simulations, these are computationally intensive and often explore only a limited volume of the merger phase space allowed by observed parameter uncertainty. Simple analytic models exist but the assumptions of these methods invalidate their results near the collision time, plus error propagation of the highly correlated merger parameters is unfeasible. To address these weaknesses I develop a Monte Carlo method to discern the properties of dissociative mergers and propagate the uncertainty of the measured cluster parameters in an accurate and Bayesian manner. I introduce this method, verify it against an existing hydrodynamic N-body simulation, and apply it to two known dissociative mergers: 1ES 0657-558 (Bullet Cluster) and DLSCL J0916.2+2951 (Musket Ball Cluster). I find that this method surpasses existing analytic models-providing accurate (10% level) dynamic parameter and uncertainty estimates throughout the merger history. This, coupled with minimal required a priori information (subcluster mass, redshift, and projected separation) and relatively fast computation ({approx}6 CPU hours), makes this method ideal for large samples of dissociative merging clusters.
Monte Carlo Shower Counter Studies
NASA Technical Reports Server (NTRS)
Snyder, H. David
1991-01-01
Activities and accomplishments related to the Monte Carlo shower counter studies are summarized. A tape of the VMS version of the GEANT software was obtained and installed on the central computer at Gallaudet University. Due to difficulties encountered in updating this VMS version, a decision was made to switch to the UNIX version of the package. This version was installed and used to generate the set of data files currently accessed by various analysis programs. The GEANT software was used to write files of data for positron and proton showers. Showers were simulated for a detector consisting of 50 alternating layers of lead and scintillator. Each file consisted of 1000 events at each of the following energies: 0.1, 0.5, 2.0, 10, 44, and 200 GeV. Data analysis activities related to clustering, chi square, and likelihood analyses are summarized. Source code for the GEANT user subprograms and data analysis programs are provided along with example data plots.
Solano, Carlos J F; Pothula, Karunakar R; Prajapati, Jigneshkumar D; De Biase, Pablo M; Noskov, Sergei Yu; Kleinekathöfer, Ulrich
2016-05-10
All-atom molecular dynamics simulations have a long history of applications studying ion and substrate permeation across biological and artificial pores. While offering unprecedented insights into the underpinning transport processes, MD simulations are limited in time-scales and ability to simulate physiological membrane potentials or asymmetric salt solutions and require substantial computational power. While several approaches to circumvent all of these limitations were developed, Brownian dynamics simulations remain an attractive option to the field. The main limitation, however, is an apparent lack of protein flexibility important for the accurate description of permeation events. In the present contribution, we report an extension of the Brownian dynamics scheme which includes conformational dynamics. To achieve this goal, the dynamics of amino-acid residues was incorporated into the many-body potential of mean force and into the Langevin equations of motion. The developed software solution, called BROMOCEA, was applied to ion transport through OmpC as a test case. Compared to fully atomistic simulations, the results show a clear improvement in the ratio of permeating anions and cations. The present tests strongly indicate that pore flexibility can enhance permeation properties which will become even more important in future applications to substrate translocation. PMID:27088446
Improved Monte Carlo Renormalization Group Method
DOE R&D Accomplishments Database
Gupta, R.; Wilson, K. G.; Umrigar, C.
1985-01-01
An extensive program to analyze critical systems using an Improved Monte Carlo Renormalization Group Method (IMCRG) being undertaken at LANL and Cornell is described. Here we first briefly review the method and then list some of the topics being investigated.
Monte Carlo Ion Transport Analysis Code.
Energy Science and Technology Software Center (ESTSC)
2009-04-15
Version: 00 TRIPOS is a versatile Monte Carlo ion transport analysis code. It has been applied to the treatment of both surface and bulk radiation effects. The media considered is composed of multilayer polyatomic materials.
Monte Carlo Transport for Electron Thermal Transport
NASA Astrophysics Data System (ADS)
Chenhall, Jeffrey; Cao, Duc; Moses, Gregory
2015-11-01
The iSNB (implicit Schurtz Nicolai Busquet multigroup electron thermal transport method of Cao et al. is adapted into a Monte Carlo transport method in order to better model the effects of non-local behavior. The end goal is a hybrid transport-diffusion method that combines Monte Carlo Transport with a discrete diffusion Monte Carlo (DDMC). The hybrid method will combine the efficiency of a diffusion method in short mean free path regions with the accuracy of a transport method in long mean free path regions. The Monte Carlo nature of the approach allows the algorithm to be massively parallelized. Work to date on the method will be presented. This work was supported by Sandia National Laboratory - Albuquerque and the University of Rochester Laboratory for Laser Energetics.
Extra Chance Generalized Hybrid Monte Carlo
NASA Astrophysics Data System (ADS)
Campos, Cédric M.; Sanz-Serna, J. M.
2015-01-01
We study a method, Extra Chance Generalized Hybrid Monte Carlo, to avoid rejections in the Hybrid Monte Carlo method and related algorithms. In the spirit of delayed rejection, whenever a rejection would occur, extra work is done to find a fresh proposal that, hopefully, may be accepted. We present experiments that clearly indicate that the additional work per sample carried out in the extra chance approach clearly pays in terms of the quality of the samples generated.
Quantum Monte Carlo methods for nuclear physics
Carlson, Joseph A.; Gandolfi, Stefano; Pederiva, Francesco; Pieper, Steven C.; Schiavilla, Rocco; Schmidt, K. E,; Wiringa, Robert B.
2014-10-19
Quantum Monte Carlo methods have proved very valuable to study the structure and reactions of light nuclei and nucleonic matter starting from realistic nuclear interactions and currents. These ab-initio calculations reproduce many low-lying states, moments and transitions in light nuclei, and simultaneously predict many properties of light nuclei and neutron matter over a rather wide range of energy and momenta. We review the nuclear interactions and currents, and describe the continuum Quantum Monte Carlo methods used in nuclear physics. These methods are similar to those used in condensed matter and electronic structure but naturally include spin-isospin, tensor, spin-orbit, and three-body interactions. We present a variety of results including the low-lying spectra of light nuclei, nuclear form factors, and transition matrix elements. We also describe low-energy scattering techniques, studies of the electroweak response of nuclei relevant in electron and neutrino scattering, and the properties of dense nucleonic matter as found in neutron stars. A coherent picture of nuclear structure and dynamics emerges based upon rather simple but realistic interactions and currents.
THE MCNPX MONTE CARLO RADIATION TRANSPORT CODE
WATERS, LAURIE S.; MCKINNEY, GREGG W.; DURKEE, JOE W.; FENSIN, MICHAEL L.; JAMES, MICHAEL R.; JOHNS, RUSSELL C.; PELOWITZ, DENISE B.
2007-01-10
MCNPX (Monte Carlo N-Particle eXtended) is a general-purpose Monte Carlo radiation transport code with three-dimensional geometry and continuous-energy transport of 34 particles and light ions. It contains flexible source and tally options, interactive graphics, and support for both sequential and multi-processing computer platforms. MCNPX is based on MCNP4B, and has been upgraded to most MCNP5 capabilities. MCNP is a highly stable code tracking neutrons, photons and electrons, and using evaluated nuclear data libraries for low-energy interaction probabilities. MCNPX has extended this base to a comprehensive set of particles and light ions, with heavy ion transport in development. Models have been included to calculate interaction probabilities when libraries are not available. Recent additions focus on the time evolution of residual nuclei decay, allowing calculation of transmutation and delayed particle emission. MCNPX is now a code of great dynamic range, and the excellent neutronics capabilities allow new opportunities to simulate devices of interest to experimental particle physics; particularly calorimetry. This paper describes the capabilities of the current MCNPX version 2.6.C, and also discusses ongoing code development.
Quantum Monte Carlo methods for nuclear physics
Carlson, J.; Gandolfi, S.; Pederiva, F.; Pieper, Steven C.; Schiavilla, R.; Schmidt, K. E.; Wiringa, R. B.
2015-09-01
Quantum Monte Carlo methods have proved valuable to study the structure and reactions of light nuclei and nucleonic matter starting from realistic nuclear interactions and currents. These ab-initio calculations reproduce many low-lying states, moments, and transitions in light nuclei, and simultaneously predict many properties of light nuclei and neutron matter over a rather wide range of energy and momenta. The nuclear interactions and currents are reviewed along with a description of the continuum quantum Monte Carlo methods used in nuclear physics. These methods are similar to those used in condensed matter and electronic structure but naturally include spin-isospin, tensor, spin-orbit, and three-body interactions. A variety of results are presented, including the low-lying spectra of light nuclei, nuclear form factors, and transition matrix elements. Low-energy scattering techniques, studies of the electroweak response of nuclei relevant in electron and neutrino scattering, and the properties of dense nucleonic matter as found in neutron stars are also described. Furthermore, a coherent picture of nuclear structure and dynamics emerges based upon rather simple but realistic interactions and currents.
Quantum Monte Carlo methods for nuclear physics
Carlson, J.; Gandolfi, S.; Pederiva, F.; Pieper, Steven C.; Schiavilla, R.; Schmidt, K. E.; Wiringa, R. B.
2015-09-01
Quantum Monte Carlo methods have proved valuable to study the structure and reactions of light nuclei and nucleonic matter starting from realistic nuclear interactions and currents. These ab-initio calculations reproduce many low-lying states, moments, and transitions in light nuclei, and simultaneously predict many properties of light nuclei and neutron matter over a rather wide range of energy and momenta. The nuclear interactions and currents are reviewed along with a description of the continuum quantum Monte Carlo methods used in nuclear physics. These methods are similar to those used in condensed matter and electronic structure but naturally include spin-isospin, tensor, spin-orbit,more » and three-body interactions. A variety of results are presented, including the low-lying spectra of light nuclei, nuclear form factors, and transition matrix elements. Low-energy scattering techniques, studies of the electroweak response of nuclei relevant in electron and neutrino scattering, and the properties of dense nucleonic matter as found in neutron stars are also described. Furthermore, a coherent picture of nuclear structure and dynamics emerges based upon rather simple but realistic interactions and currents.« less
Quantum Monte Carlo methods for nuclear physics
Carlson, Joseph A.; Gandolfi, Stefano; Pederiva, Francesco; Pieper, Steven C.; Schiavilla, Rocco; Schmidt, K. E,; Wiringa, Robert B.
2014-10-19
Quantum Monte Carlo methods have proved very valuable to study the structure and reactions of light nuclei and nucleonic matter starting from realistic nuclear interactions and currents. These ab-initio calculations reproduce many low-lying states, moments and transitions in light nuclei, and simultaneously predict many properties of light nuclei and neutron matter over a rather wide range of energy and momenta. We review the nuclear interactions and currents, and describe the continuum Quantum Monte Carlo methods used in nuclear physics. These methods are similar to those used in condensed matter and electronic structure but naturally include spin-isospin, tensor, spin-orbit, and three-bodymore » interactions. We present a variety of results including the low-lying spectra of light nuclei, nuclear form factors, and transition matrix elements. We also describe low-energy scattering techniques, studies of the electroweak response of nuclei relevant in electron and neutrino scattering, and the properties of dense nucleonic matter as found in neutron stars. A coherent picture of nuclear structure and dynamics emerges based upon rather simple but realistic interactions and currents.« less
Quantum Monte Carlo methods for nuclear physics
Carlson, J.; Gandolfi, S.; Pederiva, F.; Pieper, Steven C.; Schiavilla, R.; Schmidt, K. E.; Wiringa, R. B.
2015-09-09
Quantum Monte Carlo methods have proved valuable to study the structure and reactions of light nuclei and nucleonic matter starting from realistic nuclear interactions and currents. These ab-initio calculations reproduce many low-lying states, moments, and transitions in light nuclei, and simultaneously predict many properties of light nuclei and neutron matter over a rather wide range of energy and momenta. The nuclear interactions and currents are reviewed along with a description of the continuum quantum Monte Carlo methods used in nuclear physics. These methods are similar to those used in condensed matter and electronic structure but naturally include spin-isospin, tensor, spin-orbit, and three-body interactions. A variety of results are presented, including the low-lying spectra of light nuclei, nuclear form factors, and transition matrix elements. Low-energy scattering techniques, studies of the electroweak response of nuclei relevant in electron and neutrino scattering, and the properties of dense nucleonic matter as found in neutron stars are also described. Furthermore, a coherent picture of nuclear structure and dynamics emerges based upon rather simple but realistic interactions and currents.
Monte Carlo methods in lattice gauge theories
Otto, S.W.
1983-01-01
The mass of the O/sup +/ glueball for SU(2) gauge theory in 4 dimensions is calculated. This computation was done on a prototype parallel processor and the implementation of gauge theories on this system is described in detail. Using an action of the purely Wilson form (tract of plaquette in the fundamental representation), results with high statistics are obtained. These results are not consistent with scaling according to the continuum renormalization group. Using actions containing higher representations of the group, a search is made for one which is closer to the continuum limit. The choice is based upon the phase structure of these extended theories and also upon the Migdal-Kadanoff approximation to the renormalizaiton group on the lattice. The mass of the O/sup +/ glueball for this improved action is obtained and the mass divided by the square root of the string tension is a constant as the lattice spacing is varied. The other topic studied is the inclusion of dynamical fermions into Monte Carlo calculations via the pseudo fermion technique. Monte Carlo results obtained with this method are compared with those from an exact algorithm based on Gauss-Seidel inversion. First applied were the methods to the Schwinger model and SU(3) theory.
NASA Astrophysics Data System (ADS)
Zhang, M. Q.
1989-09-01
A new Monte Carlo algorithm for 3D Kawasaki spin-exchange simulations and its implementation on a CDC CYBER 205 is presented. This approach is applicable to lattices with sizes between 4×4×4 and 256×L2×L3 ((L2+2)(L3+4)/4⩽65535) and periodic boundary conditions. It is adjustable to various kinetic models in which the total magnetization is conserved. Maximum speed on 10 million steps per second can be reached for 3-D Ising model with Metropolis rate.
Assaraf, Roland; Caffarel, Michel; Kollias, A C
2011-04-15
We present a method to efficiently evaluate small energy differences of two close N-body systems by employing stochastic processes having a stability versus chaos property. By using the same random noise, energy differences are computed from close trajectories without reweighting procedures. The approach is presented for quantum systems but can be applied to classical N-body systems as well. It is exemplified with diffusion Monte Carlo simulations for long chains of hydrogen atoms and molecules for which it is shown that the long-standing problem of computing energy derivatives is solved. PMID:21568537
NASA Astrophysics Data System (ADS)
Gauthier, Michel G.
with a very wide range of polymer lengths. We thus propose a new Monte Carlo method based on a one-dimensional random-walk representation of the translocation problem that can easily be used to study chain lengths as large as 10' monomers. This model works in conjunction with an exact calculation technique to compute the key results of the translocation events such as the probability to occur and the average time duration. It is used to validate previous and make new theoretical predictions about translocation dynamics as the polymer and channel lengths are varied. It is also applied to the study of chain heterogeneity effects.
Pothoczki, Szilvia Temleitner, László; Pusztai, László
2014-02-07
Synchrotron X-ray diffraction measurements have been conducted on liquid phosphorus trichloride, tribromide, and triiodide. Molecular Dynamics simulations for these molecular liquids were performed with a dual purpose: (1) to establish whether existing intermolecular potential functions can provide a picture that is consistent with diffraction data and (2) to generate reliable starting configurations for subsequent Reverse Monte Carlo modelling. Structural models (i.e., sets of coordinates of thousands of atoms) that were fully consistent with experimental diffraction information, within errors, have been prepared by means of the Reverse Monte Carlo method. Comparison with reference systems, generated by hard sphere-like Monte Carlo simulations, was also carried out to demonstrate the extent to which simple space filling effects determine the structure of the liquids (and thus, also estimating the information content of measured data). Total scattering structure factors, partial radial distribution functions and orientational correlations as a function of distances between the molecular centres have been calculated from the models. In general, more or less antiparallel arrangements of the primary molecular axes that are found to be the most favourable orientation of two neighbouring molecules. In liquid PBr{sub 3} electrostatic interactions seem to play a more important role in determining intermolecular correlations than in the other two liquids; molecular arrangements in both PCl{sub 3} and PI{sub 3} are largely driven by steric effects.
NASA Astrophysics Data System (ADS)
Pothoczki, Szilvia; Temleitner, László; Pusztai, László
2014-02-01
Synchrotron X-ray diffraction measurements have been conducted on liquid phosphorus trichloride, tribromide, and triiodide. Molecular Dynamics simulations for these molecular liquids were performed with a dual purpose: (1) to establish whether existing intermolecular potential functions can provide a picture that is consistent with diffraction data and (2) to generate reliable starting configurations for subsequent Reverse Monte Carlo modelling. Structural models (i.e., sets of coordinates of thousands of atoms) that were fully consistent with experimental diffraction information, within errors, have been prepared by means of the Reverse Monte Carlo method. Comparison with reference systems, generated by hard sphere-like Monte Carlo simulations, was also carried out to demonstrate the extent to which simple space filling effects determine the structure of the liquids (and thus, also estimating the information content of measured data). Total scattering structure factors, partial radial distribution functions and orientational correlations as a function of distances between the molecular centres have been calculated from the models. In general, more or less antiparallel arrangements of the primary molecular axes that are found to be the most favourable orientation of two neighbouring molecules. In liquid PBr3 electrostatic interactions seem to play a more important role in determining intermolecular correlations than in the other two liquids; molecular arrangements in both PCl3 and PI3 are largely driven by steric effects.
Approaching chemical accuracy with quantum Monte Carlo.
Petruzielo, F R; Toulouse, Julien; Umrigar, C J
2012-03-28
A quantum Monte Carlo study of the atomization energies for the G2 set of molecules is presented. Basis size dependence of diffusion Monte Carlo atomization energies is studied with a single determinant Slater-Jastrow trial wavefunction formed from Hartree-Fock orbitals. With the largest basis set, the mean absolute deviation from experimental atomization energies for the G2 set is 3.0 kcal/mol. Optimizing the orbitals within variational Monte Carlo improves the agreement between diffusion Monte Carlo and experiment, reducing the mean absolute deviation to 2.1 kcal/mol. Moving beyond a single determinant Slater-Jastrow trial wavefunction, diffusion Monte Carlo with a small complete active space Slater-Jastrow trial wavefunction results in near chemical accuracy. In this case, the mean absolute deviation from experimental atomization energies is 1.2 kcal/mol. It is shown from calculations on systems containing phosphorus that the accuracy can be further improved by employing a larger active space. PMID:22462844
Gliksman, N R; Skibbens, R V; Salmon, E D
1993-01-01
Microtubules (MTs) in newt mitotic spindles grow faster than MTs in the interphase cytoplasmic microtubule complex (CMTC), yet spindle MTs do not have the long lengths or lifetimes of the CMTC microtubules. Because MTs undergo dynamic instability, it is likely that changes in the durations of growth or shortening are responsible for this anomaly. We have used a Monte Carlo computer simulation to examine how changes in the number of MTs and changes in the catastrophe and rescue frequencies of dynamic instability may be responsible for the cell cycle dependent changes in MT characteristics. We used the computer simulations to model interphase-like or mitotic-like MT populations on the basis of the dynamic instability parameters available from newt lung epithelial cells in vivo. We started with parameters that produced MT populations similar to the interphase newt lung cell CMTC. In the simulation, increasing the number of MTs and either increasing the frequency of catastrophe or decreasing the frequency of rescue reproduced the changes in MT dynamics measured in vivo between interphase and mitosis. Images PMID:8298190
Quantum speedup of Monte Carlo methods
Montanaro, Ashley
2015-01-01
Monte Carlo methods use random sampling to estimate numerical quantities which are hard to compute deterministically. One important example is the use in statistical physics of rapidly mixing Markov chains to approximately compute partition functions. In this work, we describe a quantum algorithm which can accelerate Monte Carlo methods in a very general setting. The algorithm estimates the expected output value of an arbitrary randomized or quantum subroutine with bounded variance, achieving a near-quadratic speedup over the best possible classical algorithm. Combining the algorithm with the use of quantum walks gives a quantum speedup of the fastest known classical algorithms with rigorous performance bounds for computing partition functions, which use multiple-stage Markov chain Monte Carlo techniques. The quantum algorithm can also be used to estimate the total variation distance between probability distributions efficiently. PMID:26528079
Quantum Monte Carlo calculations of light nuclei
Pieper, S.C.
1998-12-01
Quantum Monte Carlo calculations using realistic two- and three-nucleon interactions are presented for nuclei with up to eight nucleons. We have computed the ground and a few excited states of all such nuclei with Greens function Monte Carlo (GFMC) and all of the experimentally known excited states using variational Monte Carlo (VMC). The GFMC calculations show that for a given Hamiltonian, the VMC calculations of excitation spectra are reliable, but the VMC ground-state energies are significantly above the exact values. We find that the Hamiltonian we are using (which was developed based on {sup 3}H,{sup 4}He, and nuclear matter calculations) underpredicts the binding energy of p-shell nuclei. However our results for excitation spectra are very good and one can see both shell-model and collective spectra resulting from fundamental many-nucleon calculations. Possible improvements in the three-nucleon potential are also be discussed. {copyright} {ital 1998 American Institute of Physics.}
Quantum Monte Carlo calculations of light nuclei
Pieper, Steven C.
1998-12-21
Quantum Monte Carlo calculations using realistic two- and three-nucleon interactions are presented for nuclei with up to eight nucleons. We have computed the ground and a few excited states of all such nuclei with Greens function Monte Carlo (GFMC) and all of the experimentally known excited states using variational Monte Carlo (VMC). The GFMC calculations show that for a given Hamiltonian, the VMC calculations of excitation spectra are reliable, but the VMC ground-state energies are significantly above the exact values. We find that the Hamiltonian we are using (which was developed based on {sup 3}H,{sup 4}He, and nuclear matter calculations) underpredicts the binding energy of p-shell nuclei. However our results for excitation spectra are very good and one can see both shell-model and collective spectra resulting from fundamental many-nucleon calculations. Possible improvements in the three-nucleon potential are also be discussed.
Quantum Monte Carlo calculations of light nuclei.
Pieper, S. C.
1998-08-25
Quantum Monte Carlo calculations using realistic two- and three-nucleon interactions are presented for nuclei with up to eight nucleons. We have computed the ground and a few excited states of all such nuclei with Greens function Monte Carlo (GFMC) and all of the experimentally known excited states using variational Monte Carlo (VMC). The GFMC calculations show that for a given Hamiltonian, the VMC calculations of excitation spectra are reliable, but the VMC ground-state energies are significantly above the exact values. We find that the Hamiltonian we are using (which was developed based on {sup 3}H, {sup 4}He, and nuclear matter calculations) underpredicts the binding energy of p-shell nuclei. However our results for excitation spectra are very good and one can see both shell-model and collective spectra resulting from fundamental many-nucleon calculations. Possible improvements in the three-nucleon potential are also be discussed.
Spatial Correlations in Monte Carlo Criticality Simulations
NASA Astrophysics Data System (ADS)
Dumonteil, E.; Malvagi, F.; Zoia, A.; Mazzolo, A.; Artusio, D.; Dieudonné, C.; De Mulatier, C.
2014-06-01
Temporal correlations arising in Monte Carlo criticality codes have focused the attention of both developers and practitioners for a long time. Those correlations affects the evaluation of tallies of loosely coupled systems, where the system's typical size is very large compared to the diffusion/absorption length scale of the neutrons. These time correlations are closely related to spatial correlations, both variables being linked by the transport equation. Therefore this paper addresses the question of diagnosing spatial correlations in Monte Carlo criticality simulations. In that aim, we will propose a spatial correlation function well suited to Monte Carlo simulations, and show its use while simulating a fuel pin-cell. The results will be discussed, modeled and interpreted using the tools of branching processes of statistical mechanics. A mechanism called "neutron clustering", affecting simulations, will be discussed in this frame.
Zen, Andrea; Coccia, Emanuele; Luo, Ye; Sorella, Sandro; Guidoni, Leonardo
2014-03-11
Diradical molecules are essential species involved in many organic and inorganic chemical reactions. The computational study of their electronic structure is often challenging, because a reliable description of the correlation, and in particular of the static one, requires multireference techniques. The Jastrow correlated antisymmetrized geminal power (JAGP) is a compact and efficient wave function ansatz, based on the valence-bond representation, which can be used within quantum Monte Carlo (QMC) approaches. The AGP part can be rewritten in terms of molecular orbitals, obtaining a multideterminant expansion with zero-seniority number. In the present work we demonstrate the capability of the JAGP ansatz to correctly describe the electronic structure of two diradical prototypes: the orthogonally twisted ethylene, C2H4, and the methylene, CH2, representing respectively a homosymmetric and heterosymmetric system. In the orthogonally twisted ethylene, we find a degeneracy of π and π* molecular orbitals, as correctly predicted by multireference procedures, and our best estimates of the twisting barrier, using respectively the variational Monte Carlo (VMC) and the lattice regularized diffusion Monte Carlo (LRDMC) methods, are 71.9(1) and 70.2(2) kcal/mol, in very good agreement with the high-level MR-CISD+Q value, 69.2 kcal/mol. In the methylene we estimate an adiabatic triplet-singlet (X̃(3)B1-ã(1)A1) energy gap of 8.32(7) and 8.64(6) kcal/mol, using respectively VMC and LRDMC, consistently with the experimental-derived finding for Te, 9.363 kcal/mol. On the other hand, we show that the simple ansatz of a Jastrow correlated single determinant (JSD) wave function is unable to provide an accurate description of the electronic structure in these diradical molecules, both at variational level (VMC torsional barrier of C2H4 of 99.3(2) kcal/mol, triplet-singlet energy gap of CH2 of 13.45(10) kcal/mol) and, more remarkably, in the fixed-nodes projection schemes (LRDMC
Interaction picture density matrix quantum Monte Carlo
Malone, Fionn D. Lee, D. K. K.; Foulkes, W. M. C.; Blunt, N. S.; Shepherd, James J.; Spencer, J. S.
2015-07-28
The recently developed density matrix quantum Monte Carlo (DMQMC) algorithm stochastically samples the N-body thermal density matrix and hence provides access to exact properties of many-particle quantum systems at arbitrary temperatures. We demonstrate that moving to the interaction picture provides substantial benefits when applying DMQMC to interacting fermions. In this first study, we focus on a system of much recent interest: the uniform electron gas in the warm dense regime. The basis set incompleteness error at finite temperature is investigated and extrapolated via a simple Monte Carlo sampling procedure. Finally, we provide benchmark calculations for a four-electron system, comparing our results to previous work where possible.
Fast quantum Monte Carlo on a GPU
NASA Astrophysics Data System (ADS)
Lutsyshyn, Y.
2015-02-01
We present a scheme for the parallelization of quantum Monte Carlo method on graphical processing units, focusing on variational Monte Carlo simulation of bosonic systems. We use asynchronous execution schemes with shared memory persistence, and obtain an excellent utilization of the accelerator. The CUDA code is provided along with a package that simulates liquid helium-4. The program was benchmarked on several models of Nvidia GPU, including Fermi GTX560 and M2090, and the Kepler architecture K20 GPU. Special optimization was developed for the Kepler cards, including placement of data structures in the register space of the Kepler GPUs. Kepler-specific optimization is discussed.
Monte Carlo dose computation for IMRT optimization*
NASA Astrophysics Data System (ADS)
Laub, W.; Alber, M.; Birkner, M.; Nüsslin, F.
2000-07-01
A method which combines the accuracy of Monte Carlo dose calculation with a finite size pencil-beam based intensity modulation optimization is presented. The pencil-beam algorithm is employed to compute the fluence element updates for a converging sequence of Monte Carlo dose distributions. The combination is shown to improve results over the pencil-beam based optimization in a lung tumour case and a head and neck case. Inhomogeneity effects like a broader penumbra and dose build-up regions can be compensated for by intensity modulation.
Monte Carlo simulation of neutron scattering instruments
Seeger, P.A.
1995-12-31
A library of Monte Carlo subroutines has been developed for the purpose of design of neutron scattering instruments. Using small-angle scattering as an example, the philosophy and structure of the library are described and the programs are used to compare instruments at continuous wave (CW) and long-pulse spallation source (LPSS) neutron facilities. The Monte Carlo results give a count-rate gain of a factor between 2 and 4 using time-of-flight analysis. This is comparable to scaling arguments based on the ratio of wavelength bandwidth to resolution width.
Monte Carlo simulation of an expanding gas
NASA Technical Reports Server (NTRS)
Boyd, Iain D.
1989-01-01
By application of simple computer graphics techniques, the statistical performance of two Monte Carlo methods used in the simulation of rarefied gas flows are assessed. Specifically, two direct simulation Monte Carlo (DSMC) methods developed by Bird and Nanbu are considered. The graphics techniques are found to be of great benefit in the reduction and interpretation of the large volume of data generated, thus enabling important conclusions to be drawn about the simulation results. Hence, it is discovered that the method of Nanbu suffers from increased statistical fluctuations, thereby prohibiting its use in the solution of practical problems.
Geodesic Monte Carlo on Embedded Manifolds.
Byrne, Simon; Girolami, Mark
2013-12-01
Markov chain Monte Carlo methods explicitly defined on the manifold of probability distributions have recently been established. These methods are constructed from diffusions across the manifold and the solution of the equations describing geodesic flows in the Hamilton-Jacobi representation. This paper takes the differential geometric basis of Markov chain Monte Carlo further by considering methods to simulate from probability distributions that themselves are defined on a manifold, with common examples being classes of distributions describing directional statistics. Proposal mechanisms are developed based on the geodesic flows over the manifolds of support for the distributions, and illustrative examples are provided for the hypersphere and Stiefel manifold of orthonormal matrices. PMID:25309024
Geodesic Monte Carlo on Embedded Manifolds
Byrne, Simon; Girolami, Mark
2013-01-01
Markov chain Monte Carlo methods explicitly defined on the manifold of probability distributions have recently been established. These methods are constructed from diffusions across the manifold and the solution of the equations describing geodesic flows in the Hamilton–Jacobi representation. This paper takes the differential geometric basis of Markov chain Monte Carlo further by considering methods to simulate from probability distributions that themselves are defined on a manifold, with common examples being classes of distributions describing directional statistics. Proposal mechanisms are developed based on the geodesic flows over the manifolds of support for the distributions, and illustrative examples are provided for the hypersphere and Stiefel manifold of orthonormal matrices. PMID:25309024
Maier, Thomas A; Alvarez, Gonzalo; Summers, Michael Stuart; Schulthess, Thomas C
2010-01-01
Using dynamic cluster quantum Monte Carlo simulations, we study the superconducting behavior of a 1=8 doped two-dimensional Hubbard model with imposed unidirectional stripelike charge-density-wave modulation. We find a significant increase of the pairing correlations and critical temperature relative to the homogeneous system when the modulation length scale is sufficiently large. With a separable form of the irreducible particle-particle vertex, we show that optimized superconductivity is obtained for a moderate modulation strength due to a delicate balance between the modulation enhanced pairing interaction, and a concomitant suppression of the bare particle-particle excitations by a modulation reduction of the quasiparticle weight.
NASA Technical Reports Server (NTRS)
Gann, R. C.; Chakravarty, S.; Chester, G. V.
1978-01-01
Monte Carlo simulation, lattice dynamics in the harmonic approximation, and solution of the hypernetted chain equation were used to study the classical two-dimensional one component plasma. The system consists of a single species of charged particles immersed in a uniform neutralizing background. The particles interact via a l/r potential, where r is the two dimensional separation. Equations of state were calculated for both the liquid and solid phases. Results of calculation of the thermodynamic functions and one and two particle correlation functions are presented.
Monte Carlo treatment planning for photon and electron beams
NASA Astrophysics Data System (ADS)
Reynaert, N.; van der Marck, S. C.; Schaart, D. R.; Van der Zee, W.; Van Vliet-Vroegindeweij, C.; Tomsej, M.; Jansen, J.; Heijmen, B.; Coghe, M.; De Wagter, C.
2007-04-01
During the last few decades, accuracy in photon and electron radiotherapy has increased substantially. This is partly due to enhanced linear accelerator technology, providing more flexibility in field definition (e.g. the usage of computer-controlled dynamic multileaf collimators), which led to intensity modulated radiotherapy (IMRT). Important improvements have also been made in the treatment planning process, more specifically in the dose calculations. Originally, dose calculations relied heavily on analytic, semi-analytic and empirical algorithms. The more accurate convolution/superposition codes use pre-calculated Monte Carlo dose "kernels" partly accounting for tissue density heterogeneities. It is generally recognized that the Monte Carlo method is able to increase accuracy even further. Since the second half of the 1990s, several Monte Carlo dose engines for radiotherapy treatment planning have been introduced. To enable the use of a Monte Carlo treatment planning (MCTP) dose engine in clinical circumstances, approximations have been introduced to limit the calculation time. In this paper, the literature on MCTP is reviewed, focussing on patient modeling, approximations in linear accelerator modeling and variance reduction techniques. An overview of published comparisons between MC dose engines and conventional dose calculations is provided for phantom studies and clinical examples, evaluating the added value of MCTP in the clinic. An overview of existing Monte Carlo dose engines and commercial MCTP systems is presented and some specific issues concerning the commissioning of a MCTP system are discussed.
NASA Astrophysics Data System (ADS)
Inoue, Jun-Ichi
2013-09-01
In terms of the stochastic process of a quantum-mechanical variant of Markov chain Monte Carlo method based on the Suzuki-Trotter decomposition, we analytically derive deterministic flows of order parameters such as magnetization in infinite-range (a mean-field like) quantum spin systems. Under the static approximation, differential equations with respect to order parameters are explicitly obtained from the Master equation that describes the microscopic-law in the corresponding classical system. We discuss several possible applications of our approach to several research topics, say, image processing and neural networks. This paper is written as a self-review of two papers1,2 for Symposium on Interface between Quantum Information and Statistical Physics at Kinki University in Osaka, Japan.
Structure and dynamics of Ebola virus matrix protein VP40 by a coarse-grained Monte Carlo simulation
NASA Astrophysics Data System (ADS)
Pandey, Ras; Farmer, Barry
Ebola virus matrix protein VP40 (consisting of 326 residues) plays a critical role in viral assembly and its functions such as regulation of viral transcription, packaging, and budding of mature virions into the plasma membrane of infected cells. How does the protein VP40 go through structural evolution during the viral life cycle remains an open question? Using a coarse-grained Monte Carlo simulation we investigate the structural evolution of VP40 as a function of temperature with the input of a knowledge-based residue-residue interaction. A number local and global physical quantities (e.g. mobility profile, contact map, radius of gyration, structure factor) are analyzed with our large-scale simulations. Our preliminary data show that the structure of the protein evolves through different state with well-defined morphologies which can be identified and quantified via a detailed analysis of structure factor.
NASA Astrophysics Data System (ADS)
M. Tsysar, K.; V. Kolesnikov, S.; M. Saletsky, A.
2015-09-01
We present an investigation of the one-dimensional ferromagnetism in Au-Co nanowires deposited on the Cu(110) surface. By using the density functional theory, the influence of the nonmagnetic copper substrate Cu(110) on the magnetic properties of the bimetallic Au-Co nanowires is studied. The results show the emergence of magnetic anisotropy in the supported Au-Co nanowires. The magnetic anisotropy energy has the same order of magnitude as the exchange interaction energy between Co atoms in the wire. Our electronic structure calculation reveals the emergence of new hybridized bands between Au and Co atoms and surface Cu atoms. The Curie temperature of the Au-Co wires is calculated by means of kinetic Monte Carlo simulation. The strong size effect of the Curie temperature is demonstrated. Project supported by the Russian Foundation of Basic Researches.
A comparison of Monte Carlo generators
NASA Astrophysics Data System (ADS)
Golan, Tomasz
2015-05-01
A comparison of GENIE, NEUT, NUANCE, and NuWro Monte Carlo neutrino event generators is presented using a set of four observables: protons multiplicity, total visible energy, most energetic proton momentum, and π+ two-dimensional energy vs cosine distribution.
A quasi-Monte Carlo Metropolis algorithm
Owen, Art B.; Tribble, Seth D.
2005-01-01
This work presents a version of the Metropolis–Hastings algorithm using quasi-Monte Carlo inputs. We prove that the method yields consistent estimates in some problems with finite state spaces and completely uniformly distributed inputs. In some numerical examples, the proposed method is much more accurate than ordinary Metropolis–Hastings sampling. PMID:15956207
Monte Carlo methods in genetic analysis
Lin, Shili
1996-12-31
Many genetic analyses require computation of probabilities and likelihoods of pedigree data. With more and more genetic marker data deriving from new DNA technologies becoming available to researchers, exact computations are often formidable with standard statistical methods and computational algorithms. The desire to utilize as much available data as possible, coupled with complexities of realistic genetic models, push traditional approaches to their limits. These methods encounter severe methodological and computational challenges, even with the aid of advanced computing technology. Monte Carlo methods are therefore increasingly being explored as practical techniques for estimating these probabilities and likelihoods. This paper reviews the basic elements of the Markov chain Monte Carlo method and the method of sequential imputation, with an emphasis upon their applicability to genetic analysis. Three areas of applications are presented to demonstrate the versatility of Markov chain Monte Carlo for different types of genetic problems. A multilocus linkage analysis example is also presented to illustrate the sequential imputation method. Finally, important statistical issues of Markov chain Monte Carlo and sequential imputation, some of which are unique to genetic data, are discussed, and current solutions are outlined. 72 refs.
Scalable Domain Decomposed Monte Carlo Particle Transport
O'Brien, Matthew Joseph
2013-12-05
In this dissertation, we present the parallel algorithms necessary to run domain decomposed Monte Carlo particle transport on large numbers of processors (millions of processors). Previous algorithms were not scalable, and the parallel overhead became more computationally costly than the numerical simulation.
A comparison of Monte Carlo generators
Golan, Tomasz
2015-05-15
A comparison of GENIE, NEUT, NUANCE, and NuWro Monte Carlo neutrino event generators is presented using a set of four observables: protons multiplicity, total visible energy, most energetic proton momentum, and π{sup +} two-dimensional energy vs cosine distribution.
Monte Carlo simulations of lattice gauge theories
Rebbi, C
1980-02-01
Monte Carlo simulations done for four-dimensional lattice gauge systems are described, where the gauge group is one of the following: U(1); SU(2); Z/sub N/, i.e., the subgroup of U(1) consisting of the elements e 2..pi..in/N with integer n and N; the eight-element group of quaternions, Q; the 24- and 48-element subgroups of SU(2), denoted by T and O, which reduce to the rotation groups of the tetrahedron and the octahedron when their centers Z/sub 2/, are factored out. All of these groups can be considered subgroups of SU(2) and a common normalization was used for the action. The following types of Monte Carlo experiments are considered: simulations of a thermal cycle, where the temperature of the system is varied slightly every few Monte Carlo iterations and the internal energy is measured; mixed-phase runs, where several Monte Carlo iterations are done at a few temperatures near a phase transition starting with a lattice which is half ordered and half disordered; measurements of averages of Wilson factors for loops of different shape. 5 figures, 1 table. (RWR)
Structural Reliability and Monte Carlo Simulation.
ERIC Educational Resources Information Center
Laumakis, P. J.; Harlow, G.
2002-01-01
Analyzes a simple boom structure and assesses its reliability using elementary engineering mechanics. Demonstrates the power and utility of Monte-Carlo simulation by showing that such a simulation can be implemented more readily with results that compare favorably to the theoretical calculations. (Author/MM)
Markov Chain Monte Carlo and Irreversibility
NASA Astrophysics Data System (ADS)
Ottobre, Michela
2016-06-01
Markov Chain Monte Carlo (MCMC) methods are statistical methods designed to sample from a given measure π by constructing a Markov chain that has π as invariant measure and that converges to π. Most MCMC algorithms make use of chains that satisfy the detailed balance condition with respect to π; such chains are therefore reversible. On the other hand, recent work [18, 21, 28, 29] has stressed several advantages of using irreversible processes for sampling. Roughly speaking, irreversible diffusions converge to equilibrium faster (and lead to smaller asymptotic variance as well). In this paper we discuss some of the recent progress in the study of nonreversible MCMC methods. In particular: i) we explain some of the difficulties that arise in the analysis of nonreversible processes and we discuss some analytical methods to approach the study of continuous-time irreversible diffusions; ii) most of the rigorous results on irreversible diffusions are available for continuous-time processes; however, for computational purposes one needs to discretize such dynamics. It is well known that the resulting discretized chain will not, in general, retain all the good properties of the process that it is obtained from. In particular, if we want to preserve the invariance of the target measure, the chain might no longer be reversible. Therefore iii) we conclude by presenting an MCMC algorithm, the SOL-HMC algorithm [23], which results from a nonreversible discretization of a nonreversible dynamics.
Monte Carlo simulation framework for TMT
NASA Astrophysics Data System (ADS)
Vogiatzis, Konstantinos; Angeli, George Z.
2008-07-01
This presentation describes a strategy for assessing the performance of the Thirty Meter Telescope (TMT). A Monte Carlo Simulation Framework has been developed to combine optical modeling with Computational Fluid Dynamics simulations (CFD), Finite Element Analysis (FEA) and controls to model the overall performance of TMT. The framework consists of a two year record of observed environmental parameters such as atmospheric seeing, site wind speed and direction, ambient temperature and local sunset and sunrise times, along with telescope azimuth and elevation with a given sampling rate. The modeled optical, dynamic and thermal seeing aberrations are available in a matrix form for distinct values within the range of influencing parameters. These parameters are either part of the framework parameter set or can be derived from them at each time-step. As time advances, the aberrations are interpolated and combined based on the current value of their parameters. Different scenarios can be generated based on operating parameters such as venting strategy, optical calibration frequency and heat source control. Performance probability distributions are obtained and provide design guidance. The sensitivity of the system to design, operating and environmental parameters can be assessed in order to maximize the % of time the system meets the performance specifications.
Multiple-time-stepping generalized hybrid Monte Carlo methods
Escribano, Bruno; Akhmatskaya, Elena; Reich, Sebastian; Azpiroz, Jon M.
2015-01-01
Performance of the generalized shadow hybrid Monte Carlo (GSHMC) method [1], which proved to be superior in sampling efficiency over its predecessors [2–4], molecular dynamics and hybrid Monte Carlo, can be further improved by combining it with multi-time-stepping (MTS) and mollification of slow forces. We demonstrate that the comparatively simple modifications of the method not only lead to better performance of GSHMC itself but also allow for beating the best performed methods, which use the similar force splitting schemes. In addition we show that the same ideas can be successfully applied to the conventional generalized hybrid Monte Carlo method (GHMC). The resulting methods, MTS-GHMC and MTS-GSHMC, provide accurate reproduction of thermodynamic and dynamical properties, exact temperature control during simulation and computational robustness and efficiency. MTS-GHMC uses a generalized momentum update to achieve weak stochastic stabilization to the molecular dynamics (MD) integrator. MTS-GSHMC adds the use of a shadow (modified) Hamiltonian to filter the MD trajectories in the HMC scheme. We introduce a new shadow Hamiltonian formulation adapted to force-splitting methods. The use of such Hamiltonians improves the acceptance rate of trajectories and has a strong impact on the sampling efficiency of the method. Both methods were implemented in the open-source MD package ProtoMol and were tested on a water and a protein systems. Results were compared to those obtained using a Langevin Molly (LM) method [5] on the same systems. The test results demonstrate the superiority of the new methods over LM in terms of stability, accuracy and sampling efficiency. This suggests that putting the MTS approach in the framework of hybrid Monte Carlo and using the natural stochasticity offered by the generalized hybrid Monte Carlo lead to improving stability of MTS and allow for achieving larger step sizes in the simulation of complex systems.
Multiple-time-stepping generalized hybrid Monte Carlo methods
NASA Astrophysics Data System (ADS)
Escribano, Bruno; Akhmatskaya, Elena; Reich, Sebastian; Azpiroz, Jon M.
2015-01-01
Performance of the generalized shadow hybrid Monte Carlo (GSHMC) method [1], which proved to be superior in sampling efficiency over its predecessors [2-4], molecular dynamics and hybrid Monte Carlo, can be further improved by combining it with multi-time-stepping (MTS) and mollification of slow forces. We demonstrate that the comparatively simple modifications of the method not only lead to better performance of GSHMC itself but also allow for beating the best performed methods, which use the similar force splitting schemes. In addition we show that the same ideas can be successfully applied to the conventional generalized hybrid Monte Carlo method (GHMC). The resulting methods, MTS-GHMC and MTS-GSHMC, provide accurate reproduction of thermodynamic and dynamical properties, exact temperature control during simulation and computational robustness and efficiency. MTS-GHMC uses a generalized momentum update to achieve weak stochastic stabilization to the molecular dynamics (MD) integrator. MTS-GSHMC adds the use of a shadow (modified) Hamiltonian to filter the MD trajectories in the HMC scheme. We introduce a new shadow Hamiltonian formulation adapted to force-splitting methods. The use of such Hamiltonians improves the acceptance rate of trajectories and has a strong impact on the sampling efficiency of the method. Both methods were implemented in the open-source MD package ProtoMol and were tested on a water and a protein systems. Results were compared to those obtained using a Langevin Molly (LM) method [5] on the same systems. The test results demonstrate the superiority of the new methods over LM in terms of stability, accuracy and sampling efficiency. This suggests that putting the MTS approach in the framework of hybrid Monte Carlo and using the natural stochasticity offered by the generalized hybrid Monte Carlo lead to improving stability of MTS and allow for achieving larger step sizes in the simulation of complex systems.
Atomistic Monte Carlo Simulation of Lipid Membranes
Wüstner, Daniel; Sklenar, Heinz
2014-01-01
Biological membranes are complex assemblies of many different molecules of which analysis demands a variety of experimental and computational approaches. In this article, we explain challenges and advantages of atomistic Monte Carlo (MC) simulation of lipid membranes. We provide an introduction into the various move sets that are implemented in current MC methods for efficient conformational sampling of lipids and other molecules. In the second part, we demonstrate for a concrete example, how an atomistic local-move set can be implemented for MC simulations of phospholipid monomers and bilayer patches. We use our recently devised chain breakage/closure (CBC) local move set in the bond-/torsion angle space with the constant-bond-length approximation (CBLA) for the phospholipid dipalmitoylphosphatidylcholine (DPPC). We demonstrate rapid conformational equilibration for a single DPPC molecule, as assessed by calculation of molecular energies and entropies. We also show transition from a crystalline-like to a fluid DPPC bilayer by the CBC local-move MC method, as indicated by the electron density profile, head group orientation, area per lipid, and whole-lipid displacements. We discuss the potential of local-move MC methods in combination with molecular dynamics simulations, for example, for studying multi-component lipid membranes containing cholesterol. PMID:24469314
Interaction picture density matrix quantum Monte Carlo.
Malone, Fionn D; Blunt, N S; Shepherd, James J; Lee, D K K; Spencer, J S; Foulkes, W M C
2015-07-28
The recently developed density matrix quantum Monte Carlo (DMQMC) algorithm stochastically samples the N-body thermal density matrix and hence provides access to exact properties of many-particle quantum systems at arbitrary temperatures. We demonstrate that moving to the interaction picture provides substantial benefits when applying DMQMC to interacting fermions. In this first study, we focus on a system of much recent interest: the uniform electron gas in the warm dense regime. The basis set incompleteness error at finite temperature is investigated and extrapolated via a simple Monte Carlo sampling procedure. Finally, we provide benchmark calculations for a four-electron system, comparing our results to previous work where possible. PMID:26233116
Quantum Monte Carlo calculations for carbon nanotubes
NASA Astrophysics Data System (ADS)
Luu, Thomas; Lähde, Timo A.
2016-04-01
We show how lattice quantum Monte Carlo can be applied to the electronic properties of carbon nanotubes in the presence of strong electron-electron correlations. We employ the path-integral formalism and use methods developed within the lattice QCD community for our numerical work. Our lattice Hamiltonian is closely related to the hexagonal Hubbard model augmented by a long-range electron-electron interaction. We apply our method to the single-quasiparticle spectrum of the (3,3) armchair nanotube configuration, and consider the effects of strong electron-electron correlations. Our approach is equally applicable to other nanotubes, as well as to other carbon nanostructures. We benchmark our Monte Carlo calculations against the two- and four-site Hubbard models, where a direct numerical solution is feasible.
Status of Monte Carlo at Los Alamos
Thompson, W.L.; Cashwell, E.D.; Godfrey, T.N.K.; Schrandt, R.G.; Deutsch, O.L.; Booth, T.E.
1980-05-01
Four papers were presented by Group X-6 on April 22, 1980, at the Oak Ridge Radiation Shielding Information Center (RSIC) Seminar-Workshop on Theory and Applications of Monte Carlo Methods. These papers are combined into one report for convenience and because they are related to each other. The first paper (by Thompson and Cashwell) is a general survey about X-6 and MCNP and is an introduction to the other three papers. It can also serve as a resume of X-6. The second paper (by Godfrey) explains some of the details of geometry specification in MCNP. The third paper (by Cashwell and Schrandt) illustrates calculating flux at a point with MCNP; in particular, the once-more-collided flux estimator is demonstrated. Finally, the fourth paper (by Thompson, Deutsch, and Booth) is a tutorial on some variance-reduction techniques. It should be required for a fledging Monte Carlo practitioner.
Quantum Monte Carlo calculations of light nuclei.
Pieper, S. C.; Physics
2008-01-01
Variational Monte Carlo and Green's function Monte Carlo are powerful tools for cal- culations of properties of light nuclei using realistic two-nucleon (NN) and three-nucleon (NNN) potentials. Recently the GFMC method has been extended to multiple states with the same quantum numbers. The combination of the Argonne v18 two-nucleon and Illinois-2 three-nucleon potentials gives a good prediction of many energies of nuclei up to 12 C. A number of other recent results are presented: comparison of binding energies with those obtained by the no-core shell model; the incompatibility of modern nuclear Hamiltonians with a bound tetra-neutron; difficulties in computing RMS radii of very weakly bound nuclei, such as 6He; center-of-mass effects on spectroscopic factors; and the possible use of an artificial external well in calculations of neutron-rich isotopes.
Status of Monte Carlo at Los Alamos
Thompson, W.L.; Cashwell, E.D.
1980-01-01
At Los Alamos the early work of Fermi, von Neumann, and Ulam has been developed and supplemented by many followers, notably Cashwell and Everett, and the main product today is the continuous-energy, general-purpose, generalized-geometry, time-dependent, coupled neutron-photon transport code called MCNP. The Los Alamos Monte Carlo research and development effort is concentrated in Group X-6. MCNP treats an arbitrary three-dimensional configuration of arbitrary materials in geometric cells bounded by first- and second-degree surfaces and some fourth-degree surfaces (elliptical tori). Monte Carlo has evolved into perhaps the main method for radiation transport calculations at Los Alamos. MCNP is used in every technical division at the Laboratory by over 130 users about 600 times a month accounting for nearly 200 hours of CDC-7600 time.
An enhanced Monte Carlo outlier detection method.
Zhang, Liangxiao; Li, Peiwu; Mao, Jin; Ma, Fei; Ding, Xiaoxia; Zhang, Qi
2015-09-30
Outlier detection is crucial in building a highly predictive model. In this study, we proposed an enhanced Monte Carlo outlier detection method by establishing cross-prediction models based on determinate normal samples and analyzing the distribution of prediction errors individually for dubious samples. One simulated and three real datasets were used to illustrate and validate the performance of our method, and the results indicated that this method outperformed Monte Carlo outlier detection in outlier diagnosis. After these outliers were removed, the value of validation by Kovats retention indices and the root mean square error of prediction decreased from 3.195 to 1.655, and the average cross-validation prediction error decreased from 2.0341 to 1.2780. This method helps establish a good model by eliminating outliers. © 2015 Wiley Periodicals, Inc. PMID:26226927
Fast Lattice Monte Carlo Simulations of Polymers
NASA Astrophysics Data System (ADS)
Wang, Qiang; Zhang, Pengfei
2014-03-01
The recently proposed fast lattice Monte Carlo (FLMC) simulations (with multiple occupancy of lattice sites (MOLS) and Kronecker δ-function interactions) give much faster/better sampling of configuration space than both off-lattice molecular simulations (with pair-potential calculations) and conventional lattice Monte Carlo simulations (with self- and mutual-avoiding walk and nearest-neighbor interactions) of polymers.[1] Quantitative coarse-graining of polymeric systems can also be performed using lattice models with MOLS.[2] Here we use several model systems, including polymer melts, solutions, blends, as well as confined and/or grafted polymers, to demonstrate the great advantages of FLMC simulations in the study of equilibrium properties of polymers.
Monte-Carlo Opening Books for Amazons
NASA Astrophysics Data System (ADS)
Kloetzer, Julien
Automatically creating opening books is a natural step towards the building of strong game-playing programs, especially when there is little available knowledge about the game. However, while recent popular Monte-Carlo Tree-Search programs showed strong results for various games, we show here that programs based on such methods cannot efficiently use opening books created using algorithms based on minimax. To overcome this issue, we propose to use an MCTS-based technique, Meta-MCTS, to create such opening books. This method, while requiring some tuning to arrive at the best opening book possible, shows promising results to create an opening book for the game of the Amazons, even if this is at the cost of removing its Monte-Carlo part.
Monte Carlo modeling of exospheric bodies - Mercury
NASA Technical Reports Server (NTRS)
Smith, G. R.; Broadfoot, A. L.; Wallace, L.; Shemansky, D. E.
1978-01-01
In order to study the interaction with the surface, a Monte Carlo program is developed to determine the distribution with altitude as well as the global distribution of density at the surface in a single operation. The analysis presented shows that the appropriate source distribution should be Maxwell-Boltzmann flux if the particles in the distribution are to be treated as components of flux. Monte Carlo calculations with a Maxwell-Boltzmann flux source are compared with Mariner 10 UV spectrometer data. Results indicate that the presently operating models are not capable of fitting the observed Mercury exosphere. It is suggested that an atmosphere calculated with a barometric source distribution is suitable for more realistic future exospheric models.
Monte Carlo Methods in the Physical Sciences
Kalos, M H
2007-06-06
I will review the role that Monte Carlo methods play in the physical sciences. They are very widely used for a number of reasons: they permit the rapid and faithful transformation of a natural or model stochastic process into a computer code. They are powerful numerical methods for treating the many-dimensional problems that derive from important physical systems. Finally, many of the methods naturally permit the use of modern parallel computers in efficient ways. In the presentation, I will emphasize four aspects of the computations: whether or not the computation derives from a natural or model stochastic process; whether the system under study is highly idealized or realistic; whether the Monte Carlo methodology is straightforward or mathematically sophisticated; and finally, the scientific role of the computation.
Inhomogeneous Monte Carlo simulations of dermoscopic spectroscopy
NASA Astrophysics Data System (ADS)
Gareau, Daniel S.; Li, Ting; Jacques, Steven; Krueger, James
2012-03-01
Clinical skin-lesion diagnosis uses dermoscopy: 10X epiluminescence microscopy. Skin appearance ranges from black to white with shades of blue, red, gray and orange. Color is an important diagnostic criteria for diseases including melanoma. Melanin and blood content and distribution impact the diffuse spectral remittance (300-1000nm). Skin layers: immersion medium, stratum corneum, spinous epidermis, basal epidermis and dermis as well as laterally asymmetric features (eg. melanocytic invasion) were modeled in an inhomogeneous Monte Carlo model.
Monte Carlo simulation of Alaska wolf survival
NASA Astrophysics Data System (ADS)
Feingold, S. J.
1996-02-01
Alaskan wolves live in a harsh climate and are hunted intensively. Penna's biological aging code, using Monte Carlo methods, has been adapted to simulate wolf survival. It was run on the case in which hunting causes the disruption of wolves' social structure. Social disruption was shown to increase the number of deaths occurring at a given level of hunting. For high levels of social disruption, the population did not survive.
Linear-scaling quantum Monte Carlo calculations.
Williamson, A J; Hood, R Q; Grossman, J C
2001-12-10
A method is presented for using truncated, maximally localized Wannier functions to introduce sparsity into the Slater determinant part of the trial wave function in quantum Monte Carlo calculations. When combined with an efficient numerical evaluation of these localized orbitals, the dominant cost in the calculation, namely, the evaluation of the Slater determinant, scales linearly with system size. This technique is applied to accurate total energy calculation of hydrogenated silicon clusters and carbon fullerenes containing 20-1000 valence electrons. PMID:11736525
A separable shadow Hamiltonian hybrid Monte Carlo method
NASA Astrophysics Data System (ADS)
Sweet, Christopher R.; Hampton, Scott S.; Skeel, Robert D.; Izaguirre, Jesús A.
2009-11-01
Hybrid Monte Carlo (HMC) is a rigorous sampling method that uses molecular dynamics (MD) as a global Monte Carlo move. The acceptance rate of HMC decays exponentially with system size. The shadow hybrid Monte Carlo (SHMC) was previously introduced to reduce this performance degradation by sampling instead from the shadow Hamiltonian defined for MD when using a symplectic integrator. SHMC's performance is limited by the need to generate momenta for the MD step from a nonseparable shadow Hamiltonian. We introduce the separable shadow Hamiltonian hybrid Monte Carlo (S2HMC) method based on a formulation of the leapfrog/Verlet integrator that corresponds to a separable shadow Hamiltonian, which allows efficient generation of momenta. S2HMC gives the acceptance rate of a fourth order integrator at the cost of a second-order integrator. Through numerical experiments we show that S2HMC consistently gives a speedup greater than two over HMC for systems with more than 4000 atoms for the same variance. By comparison, SHMC gave a maximum speedup of only 1.6 over HMC. S2HMC has the additional advantage of not requiring any user parameters beyond those of HMC. S2HMC is available in the program PROTOMOL 2.1. A Python version, adequate for didactic purposes, is also in MDL (http://mdlab.sourceforge.net/s2hmc).
jTracker and Monte Carlo Comparison
NASA Astrophysics Data System (ADS)
Selensky, Lauren; SeaQuest/E906 Collaboration
2015-10-01
SeaQuest is designed to observe the characteristics and behavior of `sea-quarks' in a proton by reconstructing them from the subatomic particles produced in a collision. The 120 GeV beam from the main injector collides with a fixed target and then passes through a series of detectors which records information about the particles produced in the collision. However, this data becomes meaningful only after it has been processed, stored, analyzed, and interpreted. Several programs are involved in this process. jTracker (sqerp) reads wire or hodoscope hits and reconstructs the tracks of potential dimuon pairs from a run, and Geant4 Monte Carlo simulates dimuon production and background noise from the beam. During track reconstruction, an event must meet the criteria set by the tracker to be considered a viable dimuon pair; this ensures that relevant data is retained. As a check, a comparison between a new version of jTracker and Monte Carlo was made in order to see how accurately jTracker could reconstruct the events created by Monte Carlo. In this presentation, the results of the inquest and their potential effects on the programming will be shown. This work is supported by U.S. DOE MENP Grant DE-FG02-03ER41243.
Numerical reproducibility for implicit Monte Carlo simulations
Cleveland, M.; Brunner, T.; Gentile, N.
2013-07-01
We describe and compare different approaches for achieving numerical reproducibility in photon Monte Carlo simulations. Reproducibility is desirable for code verification, testing, and debugging. Parallelism creates a unique problem for achieving reproducibility in Monte Carlo simulations because it changes the order in which values are summed. This is a numerical problem because double precision arithmetic is not associative. In [1], a way of eliminating this roundoff error using integer tallies was described. This approach successfully achieves reproducibility at the cost of lost accuracy by rounding double precision numbers to fewer significant digits. This integer approach, and other extended reproducibility techniques, are described and compared in this work. Increased precision alone is not enough to ensure reproducibility of photon Monte Carlo simulations. A non-arbitrary precision approaches required a varying degree of rounding to achieve reproducibility. For the problems investigated in this work double precision global accuracy was achievable by using 100 bits of precision or greater on all unordered sums which where subsequently rounded to double precision at the end of every time-step. (authors)
Monte Carlo dose mapping on deforming anatomy
NASA Astrophysics Data System (ADS)
Zhong, Hualiang; Siebers, Jeffrey V.
2009-10-01
This paper proposes a Monte Carlo-based energy and mass congruent mapping (EMCM) method to calculate the dose on deforming anatomy. Different from dose interpolation methods, EMCM separately maps each voxel's deposited energy and mass from a source image to a reference image with a displacement vector field (DVF) generated by deformable image registration (DIR). EMCM was compared with other dose mapping methods: energy-based dose interpolation (EBDI) and trilinear dose interpolation (TDI). These methods were implemented in EGSnrc/DOSXYZnrc, validated using a numerical deformable phantom and compared for clinical CT images. On the numerical phantom with an analytically invertible deformation map, EMCM mapped the dose exactly the same as its analytic solution, while EBDI and TDI had average dose errors of 2.5% and 6.0%. For a lung patient's IMRT treatment plan, EBDI and TDI differed from EMCM by 1.96% and 7.3% in the lung patient's entire dose region, respectively. As a 4D Monte Carlo dose calculation technique, EMCM is accurate and its speed is comparable to 3D Monte Carlo simulation. This method may serve as a valuable tool for accurate dose accumulation as well as for 4D dosimetry QA.
Path Integral Monte Carlo Methods for Fermions
NASA Astrophysics Data System (ADS)
Ethan, Ethan; Dubois, Jonathan; Ceperley, David
2014-03-01
In general, Quantum Monte Carlo methods suffer from a sign problem when simulating fermionic systems. This causes the efficiency of a simulation to decrease exponentially with the number of particles and inverse temperature. To circumvent this issue, a nodal constraint is often implemented, restricting the Monte Carlo procedure from sampling paths that cause the many-body density matrix to change sign. Unfortunately, this high-dimensional nodal surface is not a priori known unless the system is exactly solvable, resulting in uncontrolled errors. We will discuss two possible routes to extend the applicability of finite-temperatue path integral Monte Carlo. First we extend the regime where signful simulations are possible through a novel permutation sampling scheme. Afterwards, we discuss a method to variationally improve the nodal surface by minimizing a free energy during simulation. Applications of these methods will include both free and interacting electron gases, concluding with discussion concerning extension to inhomogeneous systems. Support from DOE DE-FG52-09NA29456, DE-AC52-07NA27344, LLNL LDRD 10- ERD-058, and the Lawrence Scholar program.
Teaching Ionic Solvation Structure with a Monte Carlo Liquid Simulation Program
ERIC Educational Resources Information Center
Serrano, Agostinho; Santos, Flavia M. T.; Greca, Ileana M.
2004-01-01
The use of molecular dynamics and Monte Carlo methods has provided efficient means to stimulate the behavior of molecular liquids and solutions. A Monte Carlo simulation program is used to compute the structure of liquid water and of water as a solvent to Na(super +), Cl(super -), and Ar on a personal computer to show that it is easily feasible to…
Monte Carlo event generators in atomic collisions: A new tool to tackle the few-body dynamics
NASA Astrophysics Data System (ADS)
Ciappina, M. F.; Kirchner, T.; Schulz, M.
2010-04-01
We present a set of routines to produce theoretical event files, for both single and double ionization of atoms by ion impact, based on a Monte Carlo event generator (MCEG) scheme. Such event files are the theoretical counterpart of the data obtained from a kinematically complete experiment; i.e. they contain the momentum components of all collision fragments for a large number of ionization events. Among the advantages of working with theoretical event files is the possibility to incorporate the conditions present in a real experiment, such as the uncertainties in the measured quantities. Additionally, by manipulating them it is possible to generate any type of cross sections, specially those that are usually too complicated to compute with conventional methods due to a lack of symmetry. Consequently, the numerical effort of such calculations is dramatically reduced. We show examples for both single and double ionization, with special emphasis on a new data analysis tool, called four-body Dalitz plots, developed very recently. Program summaryProgram title: MCEG Catalogue identifier: AEFV_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEFV_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 2695 No. of bytes in distributed program, including test data, etc.: 18 501 Distribution format: tar.gz Programming language: FORTRAN 77 with parallelization directives using scripting Computer: Single machines using Linux and Linux servers/clusters (with cores with any clock speed, cache memory and bits in a word) Operating system: Linux (any version and flavor) and FORTRAN 77 compilers Has the code been vectorised or parallelized?: Yes RAM: 64-128 kBytes (the codes are very cpu intensive) Classification: 2.6 Nature of problem: The code deals with single and double
Monte Carlo approach to tissue-cell populations
NASA Astrophysics Data System (ADS)
Drasdo, D.; Kree, R.; McCaskill, J. S.
1995-12-01
We describe a stochastic dynamics of tissue cells with special emphasis on epithelial cells and fibro- blasts and fibrocytes of the connective tissue. Pattern formation and growth characteristics of such cell populations in culture are investigated numerically by Monte Carlo simulations for quasi-two-dimensional systems of cells. A number of quantitative predictions are obtained which may be confronted with experimental results. Furthermore we introduce several biologically motivated variants of our basic model and briefly discuss the simulation of two dimensional analogs of two complex processes in tissues: the growth of a sarcoma across an epithelial boundary and the wound healing of a skin cut. As compared to other approaches, we find the Monte Carlo approach to tissue growth and structure to be particularly simple and flexible. It allows for a hierarchy of models reaching from global description of birth-death processes to very specific features of intracellular dynamics. (c) 1995 The American Physical Society
Monte Carlo methods: Application to hydrogen gas and hard spheres
NASA Astrophysics Data System (ADS)
Dewing, Mark Douglas
2001-08-01
Quantum Monte Carlo (QMC) methods are among the most accurate for computing ground state properties of quantum systems. The two major types of QMC we use are Variational Monte Carlo (VMC), which evaluates integrals arising from the variational principle, and Diffusion Monte Carlo (DMC), which stochastically projects to the ground state from a trial wave function. These methods are applied to a system of boson hard spheres to get exact, infinite system size results for the ground state at several densities. The kinds of problems that can be simulated with Monte Carlo methods are expanded through the development of new algorithms for combining a QMC simulation with a classical Monte Carlo simulation, which we call Coupled Electronic-Ionic Monte Carlo (CEIMC). The new CEIMC method is applied to a system of molecular hydrogen at temperatures ranging from 2800K to 4500K and densities from 0.25 to 0.46 g/cm3. VMC requires optimizing a parameterized wave function to find the minimum energy. We examine several techniques for optimizing VMC wave functions, focusing on the ability to optimize parameters appearing in the Slater determinant. Classical Monte Carlo simulations use an empirical interatomic potential to compute equilibrium properties of various states of matter. The CEIMC method replaces the empirical potential with a QMC calculation of the electronic energy. This is similar in spirit to the Car-Parrinello technique, which uses Density Functional Theory for the electrons and molecular dynamics for the nuclei. The challenges in constructing an efficient CEIMC simulation center mostly around the noisy results generated from the QMC computations of the electronic energy. We introduce two complementary techniques, one for tolerating the noise and the other for reducing it. The penalty method modifies the Metropolis acceptance ratio to tolerate noise without introducing a bias in the simulation of the nuclei. For reducing the noise, we introduce the two-sided energy
Monte Carlo Volcano Seismic Moment Tensors
NASA Astrophysics Data System (ADS)
Waite, G. P.; Brill, K. A.; Lanza, F.
2015-12-01
Inverse modeling of volcano seismic sources can provide insight into the geometry and dynamics of volcanic conduits. But given the logistical challenges of working on an active volcano, seismic networks are typically deficient in spatial and temporal coverage; this potentially leads to large errors in source models. In addition, uncertainties in the centroid location and moment-tensor components, including volumetric components, are difficult to constrain from the linear inversion results, which leads to a poor understanding of the model space. In this study, we employ a nonlinear inversion using a Monte Carlo scheme with the objective of defining robustly resolved elements of model space. The model space is randomized by centroid location and moment tensor eigenvectors. Point sources densely sample the summit area and moment tensors are constrained to a randomly chosen geometry within the inversion; Green's functions for the random moment tensors are all calculated from modeled single forces, making the nonlinear inversion computationally reasonable. We apply this method to very-long-period (VLP) seismic events that accompany minor eruptions at Fuego volcano, Guatemala. The library of single force Green's functions is computed with a 3D finite-difference modeling algorithm through a homogeneous velocity-density model that includes topography, for a 3D grid of nodes, spaced 40 m apart, within the summit region. The homogenous velocity and density model is justified by long wavelength of VLP data. The nonlinear inversion reveals well resolved model features and informs the interpretation through a better understanding of the possible models. This approach can also be used to evaluate possible station geometries in order to optimize networks prior to deployment.
Monte Carlo Simulations for Spinodal Decomposition
NASA Astrophysics Data System (ADS)
Sander, Evelyn; Wanner, Thomas
1999-06-01
This paper addresses the phenomenon of spinodal decomposition for the Cahn-Hilliard equation. Namely, we are interested in why most solutions to the Cahn-Hilliard equation which start near a homogeneous equilibrium u 0≡ μ in the spinodal interval exhibit phase separation with a characteristic wavelength when exiting a ball of radius R in a Hilbert space centered at u 0. There are two mathematical explanations for spinodal decomposition, due to Grant and to Maier-Paape and Wanner. In this paper, we numerically compare these two mathematical approaches. In fact, we are able to synthesize the understanding we gain from our numerics with the approach of Maier-Paape and Wanner, leading to a better understanding of the underlying mechanism for this behavior. With this new approach, we can explain spinodal decomposition for a longer time and larger radius than either of the previous two approaches. A rigorous mathematical explanation is contained in a separate paper. Our approach is to use Monte Carlo simulations to examine the dependence of R, the radius to which spinodal decomposition occurs, as a function of the parameter ɛ of the governing equation. We give a description of the dominating regions on the surface of the ball by estimating certain densities of the distributions of the exit points. We observe, and can show rigorously, that the behavior of most solutions originating near the equilibrium is determined completely by the linearization for an unexpectedly long time. We explain the mechanism for this unexpectedly linear behavior, and show that for some exceptional solutions this cannot be observed. We also describe the dynamics of these exceptional solutions.
Monte Carlo simulations for spinodal decomposition
Sander, E.; Wanner, T.
1999-06-01
This paper addresses the phenomenon of spinodal decomposition for the Cahn-Hilliard equation. Namely, the authors are interested in why most solutions to the Cahn-Hilliard equation which start near a homogeneous equilibrium u{sub 0} {equivalent_to} {mu} in the spinodal interval exhibit phase separation with a characteristic wavelength when exiting a ball of radius R in a Hilbert space centered at u{sub 0}. There are two mathematical explanations for spinodal decomposition, due to Grant and to Maier-Paape and Wanner. In this paper, the authors numerically compare these two mathematical approaches. In fact, they are able to synthesize the understanding they gain from the numerics with the approach of Maier-Paape and Wanner, leading to a better understanding of the underlying mechanism for this behavior. With this new approach, they can explain spinodal decomposition for a longer time and larger radius than either of the previous two approaches. A rigorous mathematical explanation is contained in a separate paper. The approach is to use Monte Carlo simulations to examine the dependence of R, the radius to which spinodal decomposition occurs, as a function of the parameter {var_epsilon} of the governing equation. The authors give a description of the dominating regions on the surface of the ball by estimating certain densities of the distributions of the exit points. They observe, and can show rigorously, that the behavior of most solutions originating near the equilibrium is determined completely by the linearization for an unexpectedly long time. They explain the mechanism for this unexpectedly linear behavior, and show that for some exceptional solutions this cannot be observed. They also describe the dynamics of these exceptional solutions.
Gentile, N A
2000-10-01
We present a method for accelerating time dependent Monte Carlo radiative transfer calculations by using a discretization of the diffusion equation to calculate probabilities that are used to advance particles in regions with small mean free path. The method is demonstrated on problems with on 1 and 2 dimensional orthogonal grids. It results in decreases in run time of more than an order of magnitude on these problems, while producing answers with accuracy comparable to pure IMC simulations. We call the method Implicit Monte Carlo Diffusion, which we abbreviate IMD.
Four decades of implicit Monte Carlo
Wollaber, Allan B.
2016-04-25
In 1971, Fleck and Cummings derived a system of equations to enable robust Monte Carlo simulations of time-dependent, thermal radiative transfer problems. Denoted the “Implicit Monte Carlo” (IMC) equations, their solution remains the de facto standard of high-fidelity radiative transfer simulations. Over the course of 44 years, their numerical properties have become better understood, and accuracy enhancements, novel acceleration methods, and variance reduction techniques have been suggested. In this review, we rederive the IMC equations—explicitly highlighting assumptions as they are made—and outfit the equations with a Monte Carlo interpretation. We put the IMC equations in context with other approximate formsmore » of the radiative transfer equations and present a new demonstration of their equivalence to another well-used linearization solved with deterministic transport methods for frequency-independent problems. We discuss physical and numerical limitations of the IMC equations for asymptotically small time steps, stability characteristics and the potential of maximum principle violations for large time steps, and solution behaviors in an asymptotically thick diffusive limit. We provide a new stability analysis for opacities with general monomial dependence on temperature. Here, we consider spatial accuracy limitations of the IMC equations and discussion acceleration and variance reduction techniques.« less
Fission Matrix Capability for MCNP Monte Carlo
Carney, Sean E.; Brown, Forrest B.; Kiedrowski, Brian C.; Martin, William R.
2012-09-05
In a Monte Carlo criticality calculation, before the tallying of quantities can begin, a converged fission source (the fundamental eigenvector of the fission kernel) is required. Tallies of interest may include powers, absorption rates, leakage rates, or the multiplication factor (the fundamental eigenvalue of the fission kernel, k{sub eff}). Just as in the power iteration method of linear algebra, if the dominance ratio (the ratio of the first and zeroth eigenvalues) is high, many iterations of neutron history simulations are required to isolate the fundamental mode of the problem. Optically large systems have large dominance ratios, and systems containing poor neutron communication between regions are also slow to converge. The fission matrix method, implemented into MCNP[1], addresses these problems. When Monte Carlo random walk from a source is executed, the fission kernel is stochastically applied to the source. Random numbers are used for: distances to collision, reaction types, scattering physics, fission reactions, etc. This method is used because the fission kernel is a complex, 7-dimensional operator that is not explicitly known. Deterministic methods use approximations/discretization in energy, space, and direction to the kernel. Consequently, they are faster. Monte Carlo directly simulates the physics, which necessitates the use of random sampling. Because of this statistical noise, common convergence acceleration methods used in deterministic methods do not work. In the fission matrix method, we are using the random walk information not only to build the next-iteration fission source, but also a spatially-averaged fission kernel. Just like in deterministic methods, this involves approximation and discretization. The approximation is the tallying of the spatially-discretized fission kernel with an incorrect fission source. We address this by making the spatial mesh fine enough that this error is negligible. As a consequence of discretization we get a
Status of Monte-Carlo Event Generators
Hoeche, Stefan; /SLAC
2011-08-11
Recent progress on general-purpose Monte-Carlo event generators is reviewed with emphasis on the simulation of hard QCD processes and subsequent parton cascades. Describing full final states of high-energy particle collisions in contemporary experiments is an intricate task. Hundreds of particles are typically produced, and the reactions involve both large and small momentum transfer. The high-dimensional phase space makes an exact solution of the problem impossible. Instead, one typically resorts to regarding events as factorized into different steps, ordered descending in the mass scales or invariant momentum transfers which are involved. In this picture, a hard interaction, described through fixed-order perturbation theory, is followed by multiple Bremsstrahlung emissions off initial- and final-state and, finally, by the hadronization process, which binds QCD partons into color-neutral hadrons. Each of these steps can be treated independently, which is the basic concept inherent to general-purpose event generators. Their development is nowadays often focused on an improved description of radiative corrections to hard processes through perturbative QCD. In this context, the concept of jets is introduced, which allows to relate sprays of hadronic particles in detectors to the partons in perturbation theory. In this talk, we briefly review recent progress on perturbative QCD in event generation. The main focus lies on the general-purpose Monte-Carlo programs HERWIG, PYTHIA and SHERPA, which will be the workhorses for LHC phenomenology. A detailed description of the physics models included in these generators can be found in [8]. We also discuss matrix-element generators, which provide the parton-level input for general-purpose Monte Carlo.
Monte Carlo simulation of intercalated carbon nanotubes.
Mykhailenko, Oleksiy; Matsui, Denis; Prylutskyy, Yuriy; Le Normand, Francois; Eklund, Peter; Scharff, Peter
2007-01-01
Monte Carlo simulations of the single- and double-walled carbon nanotubes (CNT) intercalated with different metals have been carried out. The interrelation between the length of a CNT, the number and type of metal atoms has also been established. This research is aimed at studying intercalated systems based on CNTs and d-metals such as Fe and Co. Factors influencing the stability of these composites have been determined theoretically by the Monte Carlo method with the Tersoff potential. The modeling of CNTs intercalated with metals by the Monte Carlo method has proved that there is a correlation between the length of a CNT and the number of endo-atoms of specific type. Thus, in the case of a metallic CNT (9,0) with length 17 bands (3.60 nm), in contrast to Co atoms, Fe atoms are extruded out of the CNT if the number of atoms in the CNT is not less than eight. Thus, this paper shows that a CNT of a certain size can be intercalated with no more than eight Fe atoms. The systems investigated are stabilized by coordination of 3d-atoms close to the CNT wall with a radius-vector of (0.18-0.20) nm. Another characteristic feature is that, within the temperature range of (400-700) K, small systems exhibit ground-state stabilization which is not characteristic of the higher ones. The behavior of Fe and Co endo-atoms between the walls of a double-walled carbon nanotube (DW CNT) is explained by a dominating van der Waals interaction between the Co atoms themselves, which is not true for the Fe atoms. PMID:17033783
Quantum Monte Carlo for vibrating molecules
Brown, W.R. |
1996-08-01
Quantum Monte Carlo (QMC) has successfully computed the total electronic energies of atoms and molecules. The main goal of this work is to use correlation function quantum Monte Carlo (CFQMC) to compute the vibrational state energies of molecules given a potential energy surface (PES). In CFQMC, an ensemble of random walkers simulate the diffusion and branching processes of the imaginary-time time dependent Schroedinger equation in order to evaluate the matrix elements. The program QMCVIB was written to perform multi-state VMC and CFQMC calculations and employed for several calculations of the H{sub 2}O and C{sub 3} vibrational states, using 7 PES`s, 3 trial wavefunction forms, two methods of non-linear basis function parameter optimization, and on both serial and parallel computers. In order to construct accurate trial wavefunctions different wavefunctions forms were required for H{sub 2}O and C{sub 3}. In order to construct accurate trial wavefunctions for C{sub 3}, the non-linear parameters were optimized with respect to the sum of the energies of several low-lying vibrational states. In order to stabilize the statistical error estimates for C{sub 3} the Monte Carlo data was collected into blocks. Accurate vibrational state energies were computed using both serial and parallel QMCVIB programs. Comparison of vibrational state energies computed from the three C{sub 3} PES`s suggested that a non-linear equilibrium geometry PES is the most accurate and that discrete potential representations may be used to conveniently determine vibrational state energies.
Miura, Tomoaki; Murai, Hisao
2015-06-01
Magnetic field effect is a powerful tool to study dynamics and kinetics of radical pairs (RPs), which are one of the most important intermediates for organic photon-energy conversion reactions. However, quantitative discussion regarding the relationship between the modulation of interelectron interactions and spin dynamics at low magnetic fields (<10 mT) is still an open question. We have studied the spin dynamics of a long-lived RP in a micelle by newly developed Monte Carlo simulation, in which fluctuations of the exchange and magnetic dipolar interactions by in-cage diffusion are directly introduced to the time-domain spin dynamics calculation. State-dependent relaxation/dephasing times of a few to a few tens of nanoseconds are obtained by simulations without hyperfine interactions (HFIs) as a function of the mutual diffusion constant (∼10(-6) cm(2)/s). Simulations with the HFIs exhibit incoherent singlet-triplet (S-T) mixings resulting from interplay between the HFIs and the fluctuating spin-spin interactions. The experimentally observed incoherent S-T mixing of ∼20 ns at 3 mT for a singlet-born RP in a sodium dodecyl sulfate micelle is reproduced by the simulation with reasonable diffusion coefficients. The computational method developed here contributes to quantitative detection of molecular motion that governs the recombination efficiency of RPs. PMID:25942039
Quantum Monte Carlo calculations for light nuclei.
Wiringa, R. B.
1998-10-23
Quantum Monte Carlo calculations of ground and low-lying excited states for nuclei with A {le} 8 are made using a realistic Hamiltonian that fits NN scattering data. Results for more than 40 different (J{pi}, T) states, plus isobaric analogs, are obtained and the known excitation spectra are reproduced reasonably well. Various density and momentum distributions and electromagnetic form factors and moments have also been computed. These are the first microscopic calculations that directly produce nuclear shell structure from realistic NN interactions.
Marcus, Ryan C.
2012-07-24
Overview of this presentation is (1) Exascale computing - different technologies, getting there; (2) high-performance proof-of-concept MCMini - features and results; and (3) OpenCL toolkit - Oatmeal (OpenCL Automatic Memory Allocation Library) - purpose and features. Despite driver issues, OpenCL seems like a good, hardware agnostic tool. MCMini demonstrates the possibility for GPGPU-based Monte Carlo methods - it shows great scaling for HPC application and algorithmic equivalence. Oatmeal provides a flexible framework to aid in the development of scientific OpenCL codes.
Monte Carlo procedure for protein design
NASA Astrophysics Data System (ADS)
Irbäck, Anders; Peterson, Carsten; Potthast, Frank; Sandelin, Erik
1998-11-01
A method for sequence optimization in protein models is presented. The approach, which has inherited its basic philosophy from recent work by Deutsch and Kurosky [Phys. Rev. Lett. 76, 323 (1996)] by maximizing conditional probabilities rather than minimizing energy functions, is based upon a different and very efficient multisequence Monte Carlo scheme. By construction, the method ensures that the designed sequences represent good folders thermodynamically. A bootstrap procedure for the sequence space search is devised making very large chains feasible. The algorithm is successfully explored on the two-dimensional HP model [K. F. Lau and K. A. Dill, Macromolecules 32, 3986 (1989)] with chain lengths N=16, 18, and 32.
Discovering correlated fermions using quantum Monte Carlo.
Wagner, Lucas K; Ceperley, David M
2016-09-01
It has become increasingly feasible to use quantum Monte Carlo (QMC) methods to study correlated fermion systems for realistic Hamiltonians. We give a summary of these techniques targeted at researchers in the field of correlated electrons, focusing on the fundamentals, capabilities, and current status of this technique. The QMC methods often offer the highest accuracy solutions available for systems in the continuum, and, since they address the many-body problem directly, the simulations can be analyzed to obtain insight into the nature of correlated quantum behavior. PMID:27518859
Monte Carlo methods to calculate impact probabilities
NASA Astrophysics Data System (ADS)
Rickman, H.; Wiśniowski, T.; Wajer, P.; Gabryszewski, R.; Valsecchi, G. B.
2014-09-01
Context. Unraveling the events that took place in the solar system during the period known as the late heavy bombardment requires the interpretation of the cratered surfaces of the Moon and terrestrial planets. This, in turn, requires good estimates of the statistical impact probabilities for different source populations of projectiles, a subject that has received relatively little attention, since the works of Öpik (1951, Proc. R. Irish Acad. Sect. A, 54, 165) and Wetherill (1967, J. Geophys. Res., 72, 2429). Aims: We aim to work around the limitations of the Öpik and Wetherill formulae, which are caused by singularities due to zero denominators under special circumstances. Using modern computers, it is possible to make good estimates of impact probabilities by means of Monte Carlo simulations, and in this work, we explore the available options. Methods: We describe three basic methods to derive the average impact probability for a projectile with a given semi-major axis, eccentricity, and inclination with respect to a target planet on an elliptic orbit. One is a numerical averaging of the Wetherill formula; the next is a Monte Carlo super-sizing method using the target's Hill sphere. The third uses extensive minimum orbit intersection distance (MOID) calculations for a Monte Carlo sampling of potentially impacting orbits, along with calculations of the relevant interval for the timing of the encounter allowing collision. Numerical experiments are carried out for an intercomparison of the methods and to scrutinize their behavior near the singularities (zero relative inclination and equal perihelion distances). Results: We find an excellent agreement between all methods in the general case, while there appear large differences in the immediate vicinity of the singularities. With respect to the MOID method, which is the only one that does not involve simplifying assumptions and approximations, the Wetherill averaging impact probability departs by diverging toward
Monte Carlo radiation transport¶llelism
Cox, L. J.; Post, S. E.
2002-01-01
This talk summarizes the main aspects of the LANL ASCI Eolus project and its major unclassified code project, MCNP. The MCNP code provide a state-of-the-art Monte Carlo radiation transport to approximately 3000 users world-wide. Almost all hardware platforms are supported because we strictly adhere to the FORTRAN-90/95 standard. For parallel processing, MCNP uses a mixture of OpenMp combined with either MPI or PVM (shared and distributed memory). This talk summarizes our experiences on various platforms using MPI with and without OpenMP. These platforms include PC-Windows, Intel-LINUX, BlueMountain, Frost, ASCI-Q and others.
Monte Carlo simulation for the transport beamline
Romano, F.; Cuttone, G.; Jia, S. B.; Varisano, A.; Attili, A.; Marchetto, F.; Russo, G.; Cirrone, G. A. P.; Schillaci, F.; Scuderi, V.; Carpinelli, M.
2013-07-26
In the framework of the ELIMED project, Monte Carlo (MC) simulations are widely used to study the physical transport of charged particles generated by laser-target interactions and to preliminarily evaluate fluence and dose distributions. An energy selection system and the experimental setup for the TARANIS laser facility in Belfast (UK) have been already simulated with the GEANT4 (GEometry ANd Tracking) MC toolkit. Preliminary results are reported here. Future developments are planned to implement a MC based 3D treatment planning in order to optimize shots number and dose delivery.
Discovering correlated fermions using quantum Monte Carlo
NASA Astrophysics Data System (ADS)
Wagner, Lucas K.; Ceperley, David M.
2016-09-01
It has become increasingly feasible to use quantum Monte Carlo (QMC) methods to study correlated fermion systems for realistic Hamiltonians. We give a summary of these techniques targeted at researchers in the field of correlated electrons, focusing on the fundamentals, capabilities, and current status of this technique. The QMC methods often offer the highest accuracy solutions available for systems in the continuum, and, since they address the many-body problem directly, the simulations can be analyzed to obtain insight into the nature of correlated quantum behavior.
Monte Carlo analysis of magnetic aftereffect phenomena
NASA Astrophysics Data System (ADS)
Andrei, Petru; Stancu, Alexandru
2006-04-01
Magnetic aftereffect phenomena are analyzed by using the Monte Carlo technique. This technique has the advantage that it can be applied to any model of hysteresis. It is shown that a log t-type dependence of the magnetization can be qualitatively predicted even in the framework of hysteresis models with local history, such as the Jiles-Atherton model. These models are computationally much more efficient than the models with global history such as the Preisach model. Numerical results related to the decay of the magnetization as of function of time, as well as to the viscosity coefficient, are presented.
Monte Carlo simulation of the enantioseparation process
NASA Astrophysics Data System (ADS)
Bustos, V. A.; Acosta, G.; Gomez, M. R.; Pereyra, V. D.
2012-09-01
By means of Monte Carlo simulation, a study of enantioseparation by capillary electrophoresis has been carried out. A simplified system consisting of two enantiomers S (R) and a selector chiral C, which reacts with the enantiomers to form complexes RC (SC), has been considered. The dependence of Δμ (enantioseparation) with the concentration of chiral selector and with temperature have been analyzed by simulation. The effect of the binding constant and the charge of the complexes are also analyzed. The results are qualitatively satisfactory, despite the simplicity of the model.
A Monte Carlo algorithm for degenerate plasmas
Turrell, A.E. Sherlock, M.; Rose, S.J.
2013-09-15
A procedure for performing Monte Carlo calculations of plasmas with an arbitrary level of degeneracy is outlined. It has possible applications in inertial confinement fusion and astrophysics. Degenerate particles are initialised according to the Fermi–Dirac distribution function, and scattering is via a Pauli blocked binary collision approximation. The algorithm is tested against degenerate electron–ion equilibration, and the degenerate resistivity transport coefficient from unmagnetised first order transport theory. The code is applied to the cold fuel shell and alpha particle equilibration problem of inertial confinement fusion.
Modulated pulse bathymetric lidar Monte Carlo simulation
NASA Astrophysics Data System (ADS)
Luo, Tao; Wang, Yabo; Wang, Rong; Du, Peng; Min, Xia
2015-10-01
A typical modulated pulse bathymetric lidar system is investigated by simulation using a modulated pulse lidar simulation system. In the simulation, the return signal is generated by Monte Carlo method with modulated pulse propagation model and processed by mathematical tools like cross-correlation and digital filter. Computer simulation results incorporating the modulation detection scheme reveal a significant suppression of the water backscattering signal and corresponding target contrast enhancement. More simulation experiments are performed with various modulation and reception variables to investigate the effect of them on the bathymetric system performance.
Monte Carlo Methodology Serves Up a Software Success
NASA Technical Reports Server (NTRS)
2003-01-01
Widely used for the modeling of gas flows through the computation of the motion and collisions of representative molecules, the Direct Simulation Monte Carlo method has become the gold standard for producing research and engineering predictions in the field of rarefied gas dynamics. Direct Simulation Monte Carlo was first introduced in the early 1960s by Dr. Graeme Bird, a professor at the University of Sydney, Australia. It has since proved to be a valuable tool to the aerospace and defense industries in providing design and operational support data, as well as flight data analysis. In 2002, NASA brought to the forefront a software product that maintains the same basic physics formulation of Dr. Bird's method, but provides effective modeling of complex, three-dimensional, real vehicle simulations and parallel processing capabilities to handle additional computational requirements, especially in areas where computational fluid dynamics (CFD) is not applicable. NASA's Direct Simulation Monte Carlo Analysis Code (DAC) software package is now considered the Agency s premier high-fidelity simulation tool for predicting vehicle aerodynamics and aerothermodynamic environments in rarified, or low-density, gas flows.
Cluster Monte Carlo methods for the FePt Hamiltonian
NASA Astrophysics Data System (ADS)
Lyberatos, A.; Parker, G. J.
2016-02-01
Cluster Monte Carlo methods for the classical spin Hamiltonian of FePt with long range exchange interactions are presented. We use a combination of the Swendsen-Wang (or Wolff) and Metropolis algorithms that satisfies the detailed balance condition and ergodicity. The algorithms are tested by calculating the temperature dependence of the magnetization, susceptibility and heat capacity of L10-FePt nanoparticles in a range including the critical region. The cluster models yield numerical results in good agreement within statistical error with the standard single-spin flipping Monte Carlo method. The variation of the spin autocorrelation time with grain size is used to deduce the dynamic exponent of the algorithms. Our cluster models do not provide a more accurate estimate of the magnetic properties at equilibrium.
Advanced interacting sequential Monte Carlo sampling for inverse scattering
NASA Astrophysics Data System (ADS)
Giraud, F.; Minvielle, P.; Del Moral, P.
2013-09-01
The following electromagnetism (EM) inverse problem is addressed. It consists in estimating the local radioelectric properties of materials recovering an object from global EM scattering measurements, at various incidences and wave frequencies. This large scale ill-posed inverse problem is explored by an intensive exploitation of an efficient 2D Maxwell solver, distributed on high performance computing machines. Applied to a large training data set, a statistical analysis reduces the problem to a simpler probabilistic metamodel, from which Bayesian inference can be performed. Considering the radioelectric properties as a hidden dynamic stochastic process that evolves according to the frequency, it is shown how advanced Markov chain Monte Carlo methods—called sequential Monte Carlo or interacting particles—can take benefit of the structure and provide local EM property estimates.
Minimising biases in full configuration interaction quantum Monte Carlo.
Vigor, W A; Spencer, J S; Bearpark, M J; Thom, A J W
2015-03-14
We show that Full Configuration Interaction Quantum Monte Carlo (FCIQMC) is a Markov chain in its present form. We construct the Markov matrix of FCIQMC for a two determinant system and hence compute the stationary distribution. These solutions are used to quantify the dependence of the population dynamics on the parameters defining the Markov chain. Despite the simplicity of a system with only two determinants, it still reveals a population control bias inherent to the FCIQMC algorithm. We investigate the effect of simulation parameters on the population control bias for the neon atom and suggest simulation setups to, in general, minimise the bias. We show a reweight ing scheme to remove the bias caused by population control commonly used in diffusion Monte Carlo [Umrigar et al., J. Chem. Phys. 99, 2865 (1993)] is effective and recommend its use as a post processing step. PMID:25770522
Quantum Monte Carlo : not just for energy levels.
Nollett, K. M.; Physics
2007-01-01
Quantum Monte Carlo and realistic interactions can provide well-motivated vertices and overlaps for DWBA analyses of reactions. Given an interaction in vaccum, there are several computational approaches to nuclear systems, as you have been hearing: No-core shell model with Lee-Suzuki or Bloch-Horowitz for Hamiltonian Coupled clusters with G-matrix interaction Density functional theory, granted an energy functional derived from the interaction Quantum Monte Carlo - Variational Monte Carlo Green's function Monte Carlo. The last two work directly with a bare interaction and bare operators and describe the wave function without expanding in basis functions, so they have rather different sets of advantages and disadvantages from the others. Variational Monte Carlo (VMC) is built on a sophisticated Ansatz for the wave function, built on shell model like structure modified by operator correlations. Green's function Monte Carlo (GFMC) uses an operator method to project the true ground state out of a reasonable guess wave function.
Discrete diffusion Monte Carlo for frequency-dependent radiative transfer
Densmore, Jeffrey D; Kelly, Thompson G; Urbatish, Todd J
2010-11-17
Discrete Diffusion Monte Carlo (DDMC) is a technique for increasing the efficiency of Implicit Monte Carlo radiative-transfer simulations. In this paper, we develop an extension of DDMC for frequency-dependent radiative transfer. We base our new DDMC method on a frequency-integrated diffusion equation for frequencies below a specified threshold. Above this threshold we employ standard Monte Carlo. With a frequency-dependent test problem, we confirm the increased efficiency of our new DDMC technique.
Scalable Domain Decomposed Monte Carlo Particle Transport
NASA Astrophysics Data System (ADS)
O'Brien, Matthew Joseph
In this dissertation, we present the parallel algorithms necessary to run domain decomposed Monte Carlo particle transport on large numbers of processors (millions of processors). Previous algorithms were not scalable, and the parallel overhead became more computationally costly than the numerical simulation. The main algorithms we consider are: • Domain decomposition of constructive solid geometry: enables extremely large calculations in which the background geometry is too large to fit in the memory of a single computational node. • Load Balancing: keeps the workload per processor as even as possible so the calculation runs efficiently. • Global Particle Find: if particles are on the wrong processor, globally resolve their locations to the correct processor based on particle coordinate and background domain. • Visualizing constructive solid geometry, sourcing particles, deciding that particle streaming communication is completed and spatial redecomposition. These algorithms are some of the most important parallel algorithms required for domain decomposed Monte Carlo particle transport. We demonstrate that our previous algorithms were not scalable, prove that our new algorithms are scalable, and run some of the algorithms up to 2 million MPI processes on the Sequoia supercomputer.
Chemical application of diffusion quantum Monte Carlo
NASA Astrophysics Data System (ADS)
Reynolds, P. J.; Lester, W. A., Jr.
1983-10-01
The diffusion quantum Monte Carlo (QMC) method gives a stochastic solution to the Schroedinger equation. As an example the singlet-triplet splitting of the energy of the methylene molecule CH2 is given. The QMC algorithm was implemented on the CYBER 205, first as a direct transcription of the algorithm running on our VAX 11/780, and second by explicitly writing vector code for all loops longer than a crossover length C. The speed of the codes relative to one another as a function of C, and relative to the VAX is discussed. Since CH2 has only eight electrons, most of the loops in this application are fairly short. The longest inner loops run over the set of atomic basis functions. The CPU time dependence obtained versus the number of basis functions is discussed and compared with that obtained from traditional quantum chemistry codes and that obtained from traditional computer architectures. Finally, preliminary work on restructuring the algorithm to compute the separate Monte Carlo realizations in parallel is discussed.
Discrete range clustering using Monte Carlo methods
NASA Technical Reports Server (NTRS)
Chatterji, G. B.; Sridhar, B.
1993-01-01
For automatic obstacle avoidance guidance during rotorcraft low altitude flight, a reliable model of the nearby environment is needed. Such a model may be constructed by applying surface fitting techniques to the dense range map obtained by active sensing using radars. However, for covertness, passive sensing techniques using electro-optic sensors are desirable. As opposed to the dense range map obtained via active sensing, passive sensing algorithms produce reliable range at sparse locations, and therefore, surface fitting techniques to fill the gaps in the range measurement are not directly applicable. Both for automatic guidance and as a display for aiding the pilot, these discrete ranges need to be grouped into sets which correspond to objects in the nearby environment. The focus of this paper is on using Monte Carlo methods for clustering range points into meaningful groups. One of the aims of the paper is to explore whether simulated annealing methods offer significant advantage over the basic Monte Carlo method for this class of problems. We compare three different approaches and present application results of these algorithms to a laboratory image sequence and a helicopter flight sequence.
Composite biasing in Monte Carlo radiative transfer
NASA Astrophysics Data System (ADS)
Baes, Maarten; Gordon, Karl D.; Lunttila, Tuomas; Bianchi, Simone; Camps, Peter; Juvela, Mika; Kuiper, Rolf
2016-05-01
Biasing or importance sampling is a powerful technique in Monte Carlo radiative transfer, and can be applied in different forms to increase the accuracy and efficiency of simulations. One of the drawbacks of the use of biasing is the potential introduction of large weight factors. We discuss a general strategy, composite biasing, to suppress the appearance of large weight factors. We use this composite biasing approach for two different problems faced by current state-of-the-art Monte Carlo radiative transfer codes: the generation of photon packages from multiple components, and the penetration of radiation through high optical depth barriers. In both cases, the implementation of the relevant algorithms is trivial and does not interfere with any other optimisation techniques. Through simple test models, we demonstrate the general applicability, accuracy and efficiency of the composite biasing approach. In particular, for the penetration of high optical depths, the gain in efficiency is spectacular for the specific problems that we consider: in simulations with composite path length stretching, high accuracy results are obtained even for simulations with modest numbers of photon packages, while simulations without biasing cannot reach convergence, even with a huge number of photon packages.
Calculating Pi Using the Monte Carlo Method
NASA Astrophysics Data System (ADS)
Williamson, Timothy
2013-11-01
During the summer of 2012, I had the opportunity to participate in a research experience for teachers at the center for sustainable energy at Notre Dame University (RET @ cSEND) working with Professor John LoSecco on the problem of using antineutrino detection to accurately determine the fuel makeup and operating power of nuclear reactors. During full power operation, a reactor may produce 1021 antineutrinos per second with approximately 100 per day being detected. While becoming familiar with the design and operation of the detectors, and how total antineutrino flux could be obtained from such a small sample, I read about a simulation program called Monte Carlo. Further investigation led me to the Monte Carlo method page of Wikipedia2 where I saw an example of approximating pi using this simulation. Other examples where this method was applied were typically done with computer simulations2 or purely mathematical.3 It is my belief that this method may be easily related to the students by performing the simple activity of sprinkling rice on an arc drawn in a square. The activity that follows was inspired by those simulations and was used by my AP Physics class last year with very good results.
Monte Carlo simulations within avalanche rescue
NASA Astrophysics Data System (ADS)
Reiweger, Ingrid; Genswein, Manuel; Schweizer, Jürg
2016-04-01
Refining concepts for avalanche rescue involves calculating suitable settings for rescue strategies such as an adequate probing depth for probe line searches or an optimal time for performing resuscitation for a recovered avalanche victim in case of additional burials. In the latter case, treatment decisions have to be made in the context of triage. However, given the low number of incidents it is rarely possible to derive quantitative criteria based on historical statistics in the context of evidence-based medicine. For these rare, but complex rescue scenarios, most of the associated concepts, theories, and processes involve a number of unknown "random" parameters which have to be estimated in order to calculate anything quantitatively. An obvious approach for incorporating a number of random variables and their distributions into a calculation is to perform a Monte Carlo (MC) simulation. We here present Monte Carlo simulations for calculating the most suitable probing depth for probe line searches depending on search area and an optimal resuscitation time in case of multiple avalanche burials. The MC approach reveals, e.g., new optimized values for the duration of resuscitation that differ from previous, mainly case-based assumptions.
Multilevel Monte Carlo simulation of Coulomb collisions
Rosin, M. S.; Ricketson, L. F.; Dimits, A. M.; Caflisch, R. E.; Cohen, B. I.
2014-05-29
We present a new, for plasma physics, highly efficient multilevel Monte Carlo numerical method for simulating Coulomb collisions. The method separates and optimally minimizes the finite-timestep and finite-sampling errors inherent in the Langevin representation of the Landau–Fokker–Planck equation. It does so by combining multiple solutions to the underlying equations with varying numbers of timesteps. For a desired level of accuracy ε , the computational cost of the method is O(ε–2) or (ε–2(lnε)2), depending on the underlying discretization, Milstein or Euler–Maruyama respectively. This is to be contrasted with a cost of O(ε–3) for direct simulation Monte Carlo or binary collision methods.more » We successfully demonstrate the method with a classic beam diffusion test case in 2D, making use of the Lévy area approximation for the correlated Milstein cross terms, and generating a computational saving of a factor of 100 for ε=10–5. Lastly, we discuss the importance of the method for problems in which collisions constitute the computational rate limiting step, and its limitations.« less
Multilevel Monte Carlo simulation of Coulomb collisions
Rosin, M. S.; Ricketson, L. F.; Dimits, A. M.; Caflisch, R. E.; Cohen, B. I.
2014-05-29
We present a new, for plasma physics, highly efficient multilevel Monte Carlo numerical method for simulating Coulomb collisions. The method separates and optimally minimizes the finite-timestep and finite-sampling errors inherent in the Langevin representation of the Landau–Fokker–Planck equation. It does so by combining multiple solutions to the underlying equations with varying numbers of timesteps. For a desired level of accuracy ε , the computational cost of the method is O(ε^{–2}) or (ε^{–2}(lnε)^{2}), depending on the underlying discretization, Milstein or Euler–Maruyama respectively. This is to be contrasted with a cost of O(ε^{–3}) for direct simulation Monte Carlo or binary collision methods. We successfully demonstrate the method with a classic beam diffusion test case in 2D, making use of the Lévy area approximation for the correlated Milstein cross terms, and generating a computational saving of a factor of 100 for ε=10^{–5}. Lastly, we discuss the importance of the method for problems in which collisions constitute the computational rate limiting step, and its limitations.
Quantum Monte Carlo for atoms and molecules
Barnett, R.N.
1989-11-01
The diffusion quantum Monte Carlo with fixed nodes (QMC) approach has been employed in studying energy-eigenstates for 1--4 electron systems. Previous work employing the diffusion QMC technique yielded energies of high quality for H{sub 2}, LiH, Li{sub 2}, and H{sub 2}O. Here, the range of calculations with this new approach has been extended to include additional first-row atoms and molecules. In addition, improvements in the previously computed fixed-node energies of LiH, Li{sub 2}, and H{sub 2}O have been obtained using more accurate trial functions. All computations were performed within, but are not limited to, the Born-Oppenheimer approximation. In our computations, the effects of variation of Monte Carlo parameters on the QMC solution of the Schroedinger equation were studied extensively. These parameters include the time step, renormalization time and nodal structure. These studies have been very useful in determining which choices of such parameters will yield accurate QMC energies most efficiently. Generally, very accurate energies (90--100% of the correlation energy is obtained) have been computed with single-determinant trail functions multiplied by simple correlation functions. Improvements in accuracy should be readily obtained using more complex trial functions.
Metallic lithium by quantum Monte Carlo
Sugiyama, G.; Zerah, G.; Alder, B.J.
1986-12-01
Lithium was chosen as the simplest known metal for the first application of quantum Monte Carlo methods in order to evaluate the accuracy of conventional one-electron band theories. Lithium has been extensively studied using such techniques. Band theory calculations have certain limitations in general and specifically in their application to lithium. Results depend on such factors as charge shape approximations (muffin tins), pseudopotentials (a special problem for lithium where the lack of rho core states requires a strong pseudopotential), and the form and parameters chosen for the exchange potential. The calculations are all one-electron methods in which the correlation effects are included in an ad hoc manner. This approximation may be particularly poor in the high compression regime, where the core states become delocalized. Furthermore, band theory provides only self-consistent results rather than strict limits on the energies. The quantum Monte Carlo method is a totally different technique using a many-body rather than a mean field approach which yields an upper bound on the energies. 18 refs., 4 figs., 1 tab.
Monte Carlo modeling of spatial coherence: free-space diffraction.
Fischer, David G; Prahl, Scott A; Duncan, Donald D
2008-10-01
We present a Monte Carlo method for propagating partially coherent fields through complex deterministic optical systems. A Gaussian copula is used to synthesize a random source with an arbitrary spatial coherence function. Physical optics and Monte Carlo predictions of the first- and second-order statistics of the field are shown for coherent and partially coherent sources for free-space propagation, imaging using a binary Fresnel zone plate, and propagation through a limiting aperture. Excellent agreement between the physical optics and Monte Carlo predictions is demonstrated in all cases. Convergence criteria are presented for judging the quality of the Monte Carlo predictions. PMID:18830335
Monte Carlo techniques for analyzing deep-penetration problems
Cramer, S.N.; Gonnord, J.; Hendricks, J.S.
1986-02-01
Current methods and difficulties in Monte Carlo deep-penetration calculations are reviewed, including statistical uncertainty and recent adjoint optimization of splitting, Russian roulette, and exponential transformation biasing. Other aspects of the random walk and estimation processes are covered, including the relatively new DXANG angular biasing technique. Specific items summarized are albedo scattering, Monte Carlo coupling techniques with discrete ordinates and other methods, adjoint solutions, and multigroup Monte Carlo. The topic of code-generated biasing parameters is presented, including the creation of adjoint importance functions from forward calculations. Finally, current and future work in the area of computer learning and artificial intelligence is discussed in connection with Monte Carlo applications.
Quantum Monte Carlo Endstation for Petascale Computing
Lubos Mitas
2011-01-26
NCSU research group has been focused on accomplising the key goals of this initiative: establishing new generation of quantum Monte Carlo (QMC) computational tools as a part of Endstation petaflop initiative for use at the DOE ORNL computational facilities and for use by computational electronic structure community at large; carrying out high accuracy quantum Monte Carlo demonstration projects in application of these tools to the forefront electronic structure problems in molecular and solid systems; expanding the impact of QMC methods and approaches; explaining and enhancing the impact of these advanced computational approaches. In particular, we have developed quantum Monte Carlo code (QWalk, www.qwalk.org) which was significantly expanded and optimized using funds from this support and at present became an actively used tool in the petascale regime by ORNL researchers and beyond. These developments have been built upon efforts undertaken by the PI's group and collaborators over the period of the last decade. The code was optimized and tested extensively on a number of parallel architectures including petaflop ORNL Jaguar machine. We have developed and redesigned a number of code modules such as evaluation of wave functions and orbitals, calculations of pfaffians and introduction of backflow coordinates together with overall organization of the code and random walker distribution over multicore architectures. We have addressed several bottlenecks such as load balancing and verified efficiency and accuracy of the calculations with the other groups of the Endstation team. The QWalk package contains about 50,000 lines of high quality object-oriented C++ and includes also interfaces to data files from other conventional electronic structure codes such as Gamess, Gaussian, Crystal and others. This grant supported PI for one month during summers, a full-time postdoc and partially three graduate students over the period of the grant duration, it has resulted in 13
Finding organic vapors - a Monte Carlo approach
NASA Astrophysics Data System (ADS)
Vuollekoski, Henri; Boy, Michael; Kerminen, Veli-Matti; Kulmala, Markku
2010-05-01
drawbacks in accuracy, the inability to find diurnal variation and the lack of size resolution. Here, we aim to shed some light onto the problem by applying an ad hoc Monte Carlo algorithm to a well established aerosol dynamical model, the University of Helsinki Multicomponent Aerosol model (UHMA). By performing a side-by-side comparison with measurement data within the algorithm, this approach has the significant advantage of decreasing the amount of manual labor. But more importantly, by basing the comparison on particle number size distribution data - a quantity that can be quite reliably measured - the accuracy of the results is good.
Chemical accuracy from quantum Monte Carlo for the benzene dimer
Azadi, Sam; Cohen, R. E.
2015-09-14
We report an accurate study of interactions between benzene molecules using variational quantum Monte Carlo (VMC) and diffusion quantum Monte Carlo (DMC) methods. We compare these results with density functional theory using different van der Waals functionals. In our quantum Monte Carlo (QMC) calculations, we use accurate correlated trial wave functions including three-body Jastrow factors and backflow transformations. We consider two benzene molecules in the parallel displaced geometry, and find that by highly optimizing the wave function and introducing more dynamical correlation into the wave function, we compute the weak chemical binding energy between aromatic rings accurately. We find optimal VMC and DMC binding energies of −2.3(4) and −2.7(3) kcal/mol, respectively. The best estimate of the coupled-cluster theory through perturbative triplets/complete basis set limit is −2.65(2) kcal/mol [Miliordos et al., J. Phys. Chem. A 118, 7568 (2014)]. Our results indicate that QMC methods give chemical accuracy for weakly bound van der Waals molecular interactions, comparable to results from the best quantum chemistry methods.