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.
Visibility assessment : Monte Carlo characterization of temporal variability.
Laulainen, N.; Shannon, J.; Trexler, E. C., Jr.
1997-12-12
Current techniques for assessing the benefits of certain anthropogenic emission reductions are largely influenced by limitations in emissions data and atmospheric modeling capability and by the highly variant nature of meteorology. These data and modeling limitations are likely to continue for the foreseeable future, during which time important strategic decisions need to be made. Statistical atmospheric quality data and apportionment techniques are used in Monte-Carlo models to offset serious shortfalls in emissions, entrainment, topography, statistical meteorology data and atmospheric modeling. This paper describes the evolution of Department of Energy (DOE) Monte-Carlo based assessment models and the development of statistical inputs. A companion paper describes techniques which are used to develop the apportionment factors used in the assessment models.
Photon beam characterization and modelling for Monte Carlo treatment planning
NASA Astrophysics Data System (ADS)
Deng, Jun; Jiang, Steve B.; Kapur, Ajay; Li, Jinsheng; Pawlicki, Todd; Ma, C.-M.
2000-02-01
Photon beams of 4, 6 and 15 MV from Varian Clinac 2100C and 2300C/D accelerators were simulated using the EGS4/BEAM code system. The accelerators were modelled as a combination of component modules (CMs) consisting of a target, primary collimator, exit window, flattening filter, monitor chamber, secondary collimator, ring collimator, photon jaws and protection window. A full phase space file was scored directly above the upper photon jaws and analysed using beam data processing software, BEAMDP, to derive the beam characteristics, such as planar fluence, angular distribution, energy spectrum and the fractional contributions of each individual CM. A multiple-source model has been further developed to reconstruct the original phase space. Separate sources were created with accurate source intensity, energy, fluence and angular distributions for the target, primary collimator and flattening filter. Good agreement (within 2%) between the Monte Carlo calculations with the source model and those with the original phase space was achieved in the dose distributions for field sizes of 4 cm × 4 cm to 40 cm × 40 cm at source surface distances (SSDs) of 80-120 cm. The dose distributions in lung and bone heterogeneous phantoms have also been found to be in good agreement (within 2%) for 4, 6 and 15 MV photon beams for various field sizes between the Monte Carlo calculations with the source model and those with the original phase space.
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.
Characterization of parallel-hole collimator using Monte Carlo Simulation
Pandey, Anil Kumar; Sharma, Sanjay Kumar; Karunanithi, Sellam; Kumar, Praveen; Bal, Chandrasekhar; Kumar, Rakesh
2015-01-01
Objective: Accuracy of in vivo activity quantification improves after the correction of penetrated and scattered photons. However, accurate assessment is not possible with physical experiment. We have used Monte Carlo Simulation to accurately assess the contribution of penetrated and scattered photons in the photopeak window. Materials and Methods: Simulations were performed with Simulation of Imaging Nuclear Detectors Monte Carlo Code. The simulations were set up in such a way that it provides geometric, penetration, and scatter components after each simulation and writes binary images to a data file. These components were analyzed graphically using Microsoft Excel (Microsoft Corporation, USA). Each binary image was imported in software (ImageJ) and logarithmic transformation was applied for visual assessment of image quality, plotting profile across the center of the images and calculating full width at half maximum (FWHM) in horizontal and vertical directions. Results: The geometric, penetration, and scatter at 140 keV for low-energy general-purpose were 93.20%, 4.13%, 2.67% respectively. Similarly, geometric, penetration, and scatter at 140 keV for low-energy high-resolution (LEHR), medium-energy general-purpose (MEGP), and high-energy general-purpose (HEGP) collimator were (94.06%, 3.39%, 2.55%), (96.42%, 1.52%, 2.06%), and (96.70%, 1.45%, 1.85%), respectively. For MEGP collimator at 245 keV photon and for HEGP collimator at 364 keV were 89.10%, 7.08%, 3.82% and 67.78%, 18.63%, 13.59%, respectively. Conclusion: Low-energy general-purpose and LEHR collimator is best to image 140 keV photon. HEGP can be used for 245 keV and 364 keV; however, correction for penetration and scatter must be applied if one is interested to quantify the in vivo activity of energy 364 keV. Due to heavy penetration and scattering, 511 keV photons should not be imaged with HEGP collimator. PMID:25829730
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.
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.
Characterizing a proton beam scanning system for Monte Carlo dose calculation in patients
NASA Astrophysics Data System (ADS)
Grassberger, C.; Lomax, Anthony; Paganetti, H.
2015-01-01
The presented work has two goals. First, to demonstrate the feasibility of accurately characterizing a proton radiation field at treatment head exit for Monte Carlo dose calculation of active scanning patient treatments. Second, to show that this characterization can be done based on measured depth dose curves and spot size alone, without consideration of the exact treatment head delivery system. This is demonstrated through calibration of a Monte Carlo code to the specific beam lines of two institutions, Massachusetts General Hospital (MGH) and Paul Scherrer Institute (PSI). Comparison of simulations modeling the full treatment head at MGH to ones employing a parameterized phase space of protons at treatment head exit reveals the adequacy of the method for patient simulations. The secondary particle production in the treatment head is typically below 0.2% of primary fluence, except for low-energy electrons (<0.6 MeV for 230 MeV protons), whose contribution to skin dose is negligible. However, there is significant difference between the two methods in the low-dose penumbra, making full treatment head simulations necessary to study out-of-field effects such as secondary cancer induction. To calibrate the Monte Carlo code to measurements in a water phantom, we use an analytical Bragg peak model to extract the range-dependent energy spread at the two institutions, as this quantity is usually not available through measurements. Comparison of the measured with the simulated depth dose curves demonstrates agreement within 0.5 mm over the entire energy range. Subsequently, we simulate three patient treatments with varying anatomical complexity (liver, head and neck and lung) to give an example how this approach can be employed to investigate site-specific discrepancies between treatment planning system and Monte Carlo simulations.
Characterizing a proton beam scanning system for Monte Carlo dose calculation in patients.
Grassberger, C; Lomax, Anthony; Paganetti, H
2015-01-21
The presented work has two goals. First, to demonstrate the feasibility of accurately characterizing a proton radiation field at treatment head exit for Monte Carlo dose calculation of active scanning patient treatments. Second, to show that this characterization can be done based on measured depth dose curves and spot size alone, without consideration of the exact treatment head delivery system. This is demonstrated through calibration of a Monte Carlo code to the specific beam lines of two institutions, Massachusetts General Hospital (MGH) and Paul Scherrer Institute (PSI). Comparison of simulations modeling the full treatment head at MGH to ones employing a parameterized phase space of protons at treatment head exit reveals the adequacy of the method for patient simulations. The secondary particle production in the treatment head is typically below 0.2% of primary fluence, except for low-energy electrons (<0.6 MeV for 230 MeV protons), whose contribution to skin dose is negligible. However, there is significant difference between the two methods in the low-dose penumbra, making full treatment head simulations necessary to study out-of-field effects such as secondary cancer induction. To calibrate the Monte Carlo code to measurements in a water phantom, we use an analytical Bragg peak model to extract the range-dependent energy spread at the two institutions, as this quantity is usually not available through measurements. Comparison of the measured with the simulated depth dose curves demonstrates agreement within 0.5 mm over the entire energy range. Subsequently, we simulate three patient treatments with varying anatomical complexity (liver, head and neck and lung) to give an example how this approach can be employed to investigate site-specific discrepancies between treatment planning system and Monte Carlo simulations. PMID:25549079
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.
SU-E-T-237: Monte Carlo Dosimetric Characterization of the Mobetron Mobile Linac
Garcia, F; Granero, D; Vijande, J; Ballester, F; Perez-Calatayud, J
2014-06-01
Purpose: The aim of this work is to characterize dosimetrically a clinical intraoperative electron beam accelerator, Mobetron (IntraOp Medical, Inc.) in clinical use in our Hospital. Once this first step is completed our purpose is to evaluate shielding requirements for such a device by preparing adequate phase space files. Methods: It is known that electron beam simulation parameters required for state-of-the-art Monte Carlo codes to obtain a good match with measured data, like the mean energy or the FWHM, may not be code-independent due to the different set of process simulated and formalisms involved. Then, to cross-check our results against any issue in the simulation we have compared experimental data (PDD and profiles for electrons in the range 4 to 12 MeV) with simulations performed independently using both Penelope2011 and Geant4 codes. To do so, the geometry and materials of the head of the accelerator have been fully characterized following information provided by the manufacturer. Results: Both simulations agree with experimental data within experimental uncertainties (±1 mm displacement), although small variations (less than 10%) in the mean energy and FWHM are required to match measured values depending on the code used. Conclusion: Independent Monte Carlo simulations were used to obtain an excellent match to measured electron dose distributions. This opens the road to use such data for evaluating shielding requirements which is the main objective of this project.
NASA Astrophysics Data System (ADS)
Grolemund, Daniel Lee
The dissertation concerns the extraction, via signal processing, of structural information from the scattering of low megahertz, low power ultrasonic waves in two specific media of great practical interest--fiber reinforced composites and soft biological tissue. In fiber reinforced composites, this work represents the first measurement of second-order statistics in porous laminates, and the first application of Monte Carlo methods to acoustical scattering in composites. A numerical model of porous composites backscatter was derived which is suitable for direct numerical implementation. The model treats the total backscattered field as the result of a two-mode scattering process. In the first mode, the void-free composite is treated as a continuously varying medium in which the density and compressibility are functions of position. The second mode is the distribution of gas voids that failed to escape the material before gel, and are dealt with as discrete Rayleigh scatterers. Convolution techniques were developed that allowed the numerical model to reproduce the long range order seen in the void-free composite. The results of the Monte Carlo derivation were coded, and simulations run with data sets that duplicate the properties of the composite samples used in the study. In the area of tissue characterization, two leading methods have been proposed to extract structural data from the raw backscattered waveforms. Both techniques were developed from an understanding of the periodicities created by semi-regularly spaced, coherent scatterers. In the second half of the dissertation, a complete analytical and numerical treatment of these two techniques was done from a first principles approach. Computer simulations were performed to determine the general behavior of the algorithms. The main focus is on the envelope correlation spectrum, or ECS. Monte Carlo methods were employed to examine the signal-to-noise ratio of the ECS in terms of the variances of the backscattered
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.
Characterization of Scatter and Penetration Using Monte Carlo Simulation in 131I Imaging
Dewaraja, Yuni K.; Ljungberg, Michael; Koral, Kenneth F.
2010-01-01
In 131I SPECT, image quality and quantification accuracy are degraded by object scatter as well as scatter and penetration in the collimator. The characterization of energy and spatial distributions of scatter and penetration performed in this study by Monte Carlo simulation will be useful for the development and evaluation of techniques that compensate for such events in 131I imaging. Methods First, to test the accuracy of the Monte Carlo model, simulated and measured data were compared for both a point source and a phantom. Next, simulations to investigate scatter and penetration were performed for four geometries: point source in air, point source in a water-filled cylinder, hot sphere in a cylinder filled with nonradioactive water, and hot sphere in a cylinder filled with radioactive water. Energy spectra were separated according to order of scatter, type of interaction, and γ-ray emission energy. A preliminary evaluation of the triple-energy window (TEW) scatter correction method was performed. Results The accuracy of the Monte Carlo model was verified by the good agreement between measured and simulated energy spectra and radial point spread functions. For a point source in air, simulations show that 73% of events in the photopeak window had either scattered in or penetrated the collimator, indicating the significance of collimator interactions. For a point source in a water-filled phantom, the separated energy spectra showed that a 20% photopeak window can be used to eliminate events that scatter more than two times in the phantom. For the hot sphere phantoms, it was shown that in the photopeak region the spectrum shape of penetration events is very similar to that of primary (no scatter and no penetration) events. For the hot sphere regions of interest, the percentage difference between true scatter counts and the TEW estimate of scatter counts was <12%. Conclusion In 131I SPECT, object scatter as well as collimator scatter and penetration are significant
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.
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.
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
NASA Astrophysics Data System (ADS)
Oumano, Michael
Proton and carbon therapy are expanding in popularity as a clinical modality of external beam radiotherapy due to their finite range in tissue. However, patient setup, tumor tracking, and range uncertainties all continue to cause problems in delivering treatment. The development of proton/carbon radiography offers the potential to rectify all three of these problems. Imaging the patient immediately before (or even during) treatment would aid in patient setup and tumor tracking. Radiographs can also provide range information, which would reduce range uncertainties. Finally, both proton and carbon beams deliver a smaller absorbed dose to patients than their photon counterparts, when used to produce images. The aim of this study was to investigate the spatial resolution of both proton (230 MeV and 330 MeV) and carbon (400MeV/nucleon) radiography via monte carlo simulations. This was done for both cases by characterizing their modulation transfers functions (MTFs) and taking the 10% points. Our results indicate that both types of radiography yield sub-millimeter resolution and that carbon yields the better spatial resolution.
Baba, Justin S; John, Dwayne O; Koju, Vijay
2015-01-01
The propagation of light in turbid media is an active area of research with relevance to numerous investigational fields, e.g., biomedical diagnostics and therapeutics. The statistical random-walk nature of photon propagation through turbid media is ideal for computational based modeling and simulation. Ready access to super computing resources provide a means for attaining brute force solutions to stochastic light-matter interactions entailing scattering by facilitating timely propagation of sufficient (>10million) photons while tracking characteristic parameters based on the incorporated physics of the problem. One such model that works well for isotropic but fails for anisotropic scatter, which is the case for many biomedical sample scattering problems, is the diffusion approximation. In this report, we address this by utilizing Berry phase (BP) evolution as a means for capturing anisotropic scattering characteristics of samples in the preceding depth where the diffusion approximation fails. We extend the polarization sensitive Monte Carlo method of Ramella-Roman, et al.,1 to include the computationally intensive tracking of photon trajectory in addition to polarization state at every scattering event. To speed-up the computations, which entail the appropriate rotations of reference frames, the code was parallelized using OpenMP. The results presented reveal that BP is strongly correlated to the photon penetration depth, thus potentiating the possibility of polarimetric depth resolved characterization of highly scattering samples, e.g., biological tissues.
Characterizing the three-orbital Hubbard model with determinant quantum Monte Carlo
Kung, Y. F.; Chen, C. -C.; Wang, Yao; Huang, E. W.; Nowadnick, E. A.; Moritz, B.; Scalettar, R. T.; Johnston, S.; Devereaux, T. P.
2016-04-29
Here, we characterize the three-orbital Hubbard model using state-of-the-art determinant quantum Monte Carlo (DQMC) simulations with parameters relevant to the cuprate high-temperature superconductors. The simulations find that doped holes preferentially reside on oxygen orbitals and that the (π,π) antiferromagnetic ordering vector dominates in the vicinity of the undoped system, as known from experiments. The orbitally-resolved spectral functions agree well with photoemission spectroscopy studies and enable identification of orbital content in the bands. A comparison of DQMC results with exact diagonalization and cluster perturbation theory studies elucidates how these different numerical techniques complement one another to produce a more complete understandingmore » of the model and the cuprates. Interestingly, our DQMC simulations predict a charge-transfer gap that is significantly smaller than the direct (optical) gap measured in experiment. Most likely, it corresponds to the indirect gap that has recently been suggested to be on the order of 0.8 eV, and demonstrates the subtlety in identifying charge gaps.« less
Characterizing the three-orbital Hubbard model with determinant quantum Monte Carlo
NASA Astrophysics Data System (ADS)
Kung, Y. F.; Chen, C.-C.; Wang, Yao; Huang, E. W.; Nowadnick, E. A.; Moritz, B.; Scalettar, R. T.; Johnston, S.; Devereaux, T. P.
2016-04-01
We characterize the three-orbital Hubbard model using state-of-the-art determinant quantum Monte Carlo (DQMC) simulations with parameters relevant to the cuprate high-temperature superconductors. The simulations find that doped holes preferentially reside on oxygen orbitals and that the (π ,π ) antiferromagnetic ordering vector dominates in the vicinity of the undoped system, as known from experiments. The orbitally-resolved spectral functions agree well with photoemission spectroscopy studies and enable identification of orbital content in the bands. A comparison of DQMC results with exact diagonalization and cluster perturbation theory studies elucidates how these different numerical techniques complement one another to produce a more complete understanding of the model and the cuprates. Interestingly, our DQMC simulations predict a charge-transfer gap that is significantly smaller than the direct (optical) gap measured in experiment. Most likely, it corresponds to the indirect gap that has recently been suggested to be on the order of 0.8 eV, and demonstrates the subtlety in identifying charge gaps.
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.
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.
NASA Astrophysics Data System (ADS)
Brunetti, Antonio; Depalmas, Anna; di Gennaro, Francesco; Serges, Alessandra; Schiavon, Nicola
2016-07-01
The chemical composition of a unique bronze artifact known as the "Cesta" ("Basket") belonging to the ancient Nuragic civilization of the Island of Sardinia, Italy has been analyzed by combining X-ray Fluorescence Spectroscopy (XRF) with Monte Carlo simulations using the XRMC code. The "Cesta" had been discovered probably in the XVIII century with the first graphic representation reported around 1761. In a later draft (dated 1764), the basket has been depicted as being carried upside-down on the shoulder of a large bronze warrior Barthélemy (1761), Pinza (1901), Winckelmann (1776) . The two pictorial representations differed only by the presence of handles in the most recent one. XRF measurements revealed that the handles of the object are composed by brass while the other parts are composed by bronze suggesting the handles as being a later addition to the original object. The artifact is covered at its surface by a fairly thick corrosion patina. In order to determine the bronze bulk composition without the need for removing the outer patina, the artifact has been modeled as a two layer object in Monte Carlo simulations.
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.
Figueroa, R G; Valente, M
2015-09-21
The main purpose of this work is to determine the feasibility and physical characteristics of a new teletherapy device of radiation therapy based on the application of a convergent x-ray beam of energies like those used in radiotherapy providing highly concentrated dose delivery to the target. We have denominated it Convergent Beam Radio Therapy (CBRT). Analytical methods are developed first in order to determine the dosimetry characteristic of an ideal convergent photon beam in a hypothetical water phantom. Then, using the PENELOPE Monte Carlo code, a similar convergent beam that is applied to the water phantom is compared with that of the analytical method. The CBRT device (Converay(®)) is designed to adapt to the head of LINACs. The converging beam photon effect is achieved thanks to the perpendicular impact of LINAC electrons on a large thin spherical cap target where Bremsstrahlung is generated (high-energy x-rays). This way, the electrons impact upon various points of the cap (CBRT condition), aimed at the focal point. With the X radiation (Bremsstrahlung) directed forward, a system of movable collimators emits many beams from the output that make a virtually definitive convergent beam. Other Monte Carlo simulations are performed using realistic conditions. The simulations are performed for a thin target in the shape of a large, thin, spherical cap, with an r radius of around 10-30 cm and a curvature radius of approximately 70 to 100 cm, and a cubed water phantom centered in the focal point of the cap. All the interaction mechanisms of the Bremsstrahlung radiation with the phantom are taken into consideration for different energies and cap thicknesses. Also, the magnitudes of the electric and/or magnetic fields, which are necessary to divert clinical-use electron beams (0.1 to 20 MeV), are determined using electromagnetism equations with relativistic corrections. This way the above-mentioned beam is manipulated and guided for its perpendicular impact
Characterization, nanoparticle self-organization, and Monte Carlo simulation of magnetoliposomes
NASA Astrophysics Data System (ADS)
Salvador, Michele Aparecida; Costa, Anderson Silva; Gaeti, Marilisa; Mendes, Livia Palmerston; Lima, Eliana Martins; Bakuzis, Andris Figueiroa; Miotto, Ronei
2016-02-01
In this work we have developed and implement a new approach for the study of magnetoliposomes using Monte Carlo simulations. Our model is based on interaction among nanoparticles considering magnetic dipolar, van der Waals, ionic-steric, and Zeeman interaction potentials. The ionic interaction between nanoparticles and the lipid bilayer is represented by an ionic repulsion electrical surface potential that depends on the nanoparticle-lipid bilayer distance and the concentration of ions in the solution. A direct comparison among transmission electron microscopy, vibrating sample magnetometer, dynamic light scattering, nanoparticle tracking analysis, and experimentally derived static magnetic birefringence and simulation data allow us to validate our implementation. Our simulations suggest that confinement plays an important role in aggregate formation.
Pozzi, Sara A; Downar, Thomas J; Padovani, Enrico; Clarke, Shaun D
2006-01-01
This work illustrates a methodology based on photon interrogation and coincidence counting for determining the characteristics of fissile material. The feasibility of the proposed methods was demonstrated using a Monte Carlo code system to simulate the full statistics of the neutron and photon field generated by the photon interrogation of fissile and non-fissile materials. Time correlation functions between detectors were simulated for photon beam-on and photon beam-off operation. In the latter case, the correlation signal is obtained via delayed neutrons from photofission, which induce further fission chains in the nuclear material. An analysis methodology was demonstrated based on features selected from the simulated correlation functions and on the use of artificial neural networks. We show that the methodology can reliably differentiate between highly enriched uranium and plutonium. Furthermore, the mass of the material can be determined with a relative error of about 12%. Keywords: MCNP, MCNP-PoliMi, Artificial neural network, Correlation measurement, Photofission
Guerra, J G; Rubiano, J G; Winter, G; Guerra, A G; Alonso, H; Arnedo, M A; Tejera, A; Gil, J M; Rodríguez, R; Martel, P; Bolivar, J P
2015-11-01
The determination in a sample of the activity concentration of a specific radionuclide by gamma spectrometry needs to know the full energy peak efficiency (FEPE) for the energy of interest. The difficulties related to the experimental calibration make it advisable to have alternative methods for FEPE determination, such as the simulation of the transport of photons in the crystal by the Monte Carlo method, which requires an accurate knowledge of the characteristics and geometry of the detector. The characterization process is mainly carried out by Canberra Industries Inc. using proprietary techniques and methodologies developed by that company. It is a costly procedure (due to shipping and to the cost of the process itself) and for some research laboratories an alternative in situ procedure can be very useful. The main goal of this paper is to find an alternative to this costly characterization process, by establishing a method for optimizing the parameters of characterizing the detector, through a computational procedure which could be reproduced at a standard research lab. This method consists in the determination of the detector geometric parameters by using Monte Carlo simulation in parallel with an optimization process, based on evolutionary algorithms, starting from a set of reference FEPEs determined experimentally or computationally. The proposed method has proven to be effective and simple to implement. It provides a set of characterization parameters which it has been successfully validated for different source-detector geometries, and also for a wide range of environmental samples and certified materials. PMID:26188622
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.
Geochemical Characterization Using Geophysical Data and Markov Chain Monte Carlo Methods
NASA Astrophysics Data System (ADS)
Chen, J.; Hubbard, S.; Rubin, Y.; Murray, C.; Roden, E.; Majer, E.
2002-12-01
if they were available from direct measurements or as variables otherwise. To estimate the geochemical parameters, we first assigned a prior model for each variable and a likelihood model for each type of data, which together define posterior probability distributions for each variable on the domain. Since the posterior probability distribution may involve hundreds of variables, we used a Markov Chain Monte Carlo (MCMC) method to explore each variable by generating and subsequently evaluating hundreds of realizations. Results from this case study showed that although geophysical attributes are not necessarily directly related to geochemical parameters, geophysical data could be very useful for providing accurate and high-resolution information about geochemical parameter distribution through their joint and indirect connections with hydrogeological properties such as lithofacies. This case study also demonstrated that MCMC methods were particularly useful for geochemical parameter estimation using geophysical data because they allow incorporation into the procedure of spatial correlation information, measurement errors, and cross correlations among different types of parameters.
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…
Noise characterization of block-iterative reconstruction algorithms: II. Monte Carlo simulations.
Soares, Edward J; Glick, Stephen J; Hoppin, John W
2005-01-01
In Soares et al. (2000), the ensemble statistical properties of the rescaled block-iterative expectation-maximization (RBI-EM) reconstruction algorithm and rescaled block-iterative simultaneous multiplicative algebraic reconstruction technique (RBI-SMART) were derived. Included in this analysis were the special cases of RBI-EM, maximum-likelihood EM (ML-EM) and ordered-subset EM (OS-EM), and the special case of RBI-SMART, SMART. Explicit expressions were found for the ensemble mean, covariance matrix, and probability density function of RBI reconstructed images, as a function of iteration number. The theoretical formulations relied on one approximation, namely that the noise in the reconstructed image was small compared to the mean image. In this paper, we evaluate the predictions of the theory by using Monte Carlo methods to calculate the sample statistical properties of each algorithm and then compare the results with the theoretical formulations. In addition, the validity of the approximation will be justified. PMID:15638190
Tzika, Faidra; Savidou, Anastasia; Stamatelatos, Ion E
2007-11-01
A semi-empirical non-destructive technique to assay radioactive waste drums is presented. The technique is based on gamma spectrometry performed using a portable NaI detector and Monte Carlo simulations using the MCNP code in order to derive the gamma ray detector efficiency for the volume source. The derivation of detector efficiency was performed assuming homogeneous distribution of the source activity within the matrix material. Moreover, the MCNP model was used to examine the effect of inhomogeneities in activity distribution, variation of matrix material density, and drum filling height on the accuracy of the technique, and to estimate the measurement bias. The technique was verified by estimating radioactivity levels in 25 drums containing ion exchange resin waste, and comparing the results of the non-destructive method against the analytical results of samples obtained from each drum. Satisfactory agreement between the two assay techniques was observed. The discussed technique represents a cost effective technology that can be used to assay low-activity, low-density waste drums provided the contribution to the gamma ray spectrum can be resolved. PMID:18049246
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.
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.
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.
Characterization of scattered radiation in kV CBCT images using Monte Carlo simulations
Jarry, Genevieve; Graham, Sean A.; Moseley, Douglas J.; Jaffray, David J.; Siewerdsen, Jeffrey H.; Verhaegen, Frank
2006-11-15
Kilovoltage (kV) cone beam computed tomography (CBCT) images suffer from a substantial scatter contribution. In this study, Monte Carlo (MC) simulations are used to evaluate the scattered radiation present in projection images. These predicted scatter distributions are also used as a scatter correction technique. Images were acquired using a kV CBCT bench top system. The EGSnrc MC code was used to model the flat panel imager, the phantoms, and the x-ray source. The x-ray source model was validated using first and second half-value layers (HVL) and profile measurements. The HVLs and the profile were found to agree within 3% and 6%, respectively. MC simulated and measured projection images for a cylindrical water phantom and for an anthropomorphic head phantom agreed within 8% and 10%. A modified version of the DOSXYZnrc MC code was used to score phase space files with identified scattered and primary particles behind the phantoms. The cone angle, the source-to-detector distance, the phantom geometry, and the energy were varied to determine their effect on the scattered radiation distribution. A scatter correction technique was developed in which the MC predicted scatter distribution is subtracted from the projections prior to reconstruction. Preliminary testing of the procedure was done with an anthropomorphic head phantom and a contrast phantom. Contrast and profile measurements were obtained for the scatter corrected and noncorrected images. An improvement of 3% for contrast between solid water and a liver insert and 11% between solid water and a Teflon insert were obtained and a significant reduction in cupping and streaking artifacts was observed.
Chen, Yu; Liu, Bob; O’Connor, J. Michael; Didier, Clay S.; Glick, Stephen J.
2009-01-01
It is commonly understood that scattered radiation in x-ray computed tomography (CT) degrades the reconstructed image. As a precursor to developing scatter compensation methods, it is important to characterize this scatter using both empirical measurements and Monte Carlo simulations. Previous studies characterizing scatter using both experimental measurements and Monte Carlo simulations have been reported in diagnostic radiology and conventional mammography. The emerging technology of cone-beam CT breast imaging (CTBI) differs significantly from conventional mammography in the breast shape and imaging geometry, aspects that are important factors impacting the measured scatter. This study used a bench-top cone-beam CTBI system with an indirect flat-panel detector. A cylindrical phantom with equivalent composition of 50% fibroglandular and 50% adipose tissues was used, and scatter distributions were measured by beam stop and aperture methods. The GEANT4-based simulation package GATE was used to model x-ray photon interactions in the phantom and detector. Scatter to primary ratio (SPR) measurements using both the beam stop and aperture methods were consistent within 5% after subtraction of nonbreast scatter contributions and agree with the low energy electromagnetic model simulation in GATE. The validated simulation model was used to characterize the SPR in different CTBI conditions. In addition, a realistic, digital breast phantom was simulated to determine the characteristics of various scatter components that cannot be separated in measurements. The simulation showed that the scatter distribution from multiple Compton and Rayleigh scatterings, as well as from the single Compton scattering, has predominantly low-frequency characteristics. The single Rayleigh scatter was observed to be the primary contribution to the spatially variant scatter component. PMID:19378746
NASA Astrophysics Data System (ADS)
Mirzaee, Sh; Farjami shayesteh, S.; Mahdavifar, S.; Hekmatara, S. Hoda.
2015-11-01
To study the influence of polymer matrix on the effective magnetic anisotropy constant and coercivity of magnetic nanoparticles, we have synthesized the Cobalt ferrite/Polyvinylpyrrolidone (PVP) nanocomposites by co-precipitation method in four different processes. In addition the Monte Carlo simulation and law of approach to the saturation magnetization have been applied to achieve the anisotropy constants. The obtained experimental and theoretical results showed a decrease in anisotropy constant relative to the bulk cobalt ferrite. We have showed that the PVP matrix can interact with metal cations and made them approximately immobilized to participate in spinel structure. Hence different anisotropy constants or coercivity were obtained for synthesized nanocomposites. In addition, PVP matrix can attach to the surface of magnetic particles and make them approximately non-interacting. The synthesized samples have been characterized by Fourier transform infrared spectroscopy (FT-IR) and X-ray diffraction (XRD). Magnetic measurements were made at room temperature using a vibrating sample magnetometer (VSM).
Leon, Stephanie M. Wagner, Louis K.; Brateman, Libby F.
2014-11-01
Purpose: Monte Carlo simulations were performed with the goal of verifying previously published physical measurements characterizing scatter as a function of apparent thickness. A secondary goal was to provide a way of determining what effect tissue glandularity might have on the scatter characteristics of breast tissue. The overall reason for characterizing mammography scatter in this research is the application of these data to an image processing-based scatter-correction program. Methods: MCNPX was used to simulate scatter from an infinitesimal pencil beam using typical mammography geometries and techniques. The spreading of the pencil beam was characterized by two parameters: mean radial extent (MRE) and scatter fraction (SF). The SF and MRE were found as functions of target, filter, tube potential, phantom thickness, and the presence or absence of a grid. The SF was determined by separating scatter and primary by the angle of incidence on the detector, then finding the ratio of the measured scatter to the total number of detected events. The accuracy of the MRE was determined by placing ring-shaped tallies around the impulse and fitting those data to the point-spread function (PSF) equation using the value for MRE derived from the physical measurements. The goodness-of-fit was determined for each data set as a means of assessing the accuracy of the physical MRE data. The effect of breast glandularity on the SF, MRE, and apparent tissue thickness was also considered for a limited number of techniques. Results: The agreement between the physical measurements and the results of the Monte Carlo simulations was assessed. With a grid, the SFs ranged from 0.065 to 0.089, with absolute differences between the measured and simulated SFs averaging 0.02. Without a grid, the range was 0.28–0.51, with absolute differences averaging −0.01. The goodness-of-fit values comparing the Monte Carlo data to the PSF from the physical measurements ranged from 0.96 to 1.00 with a
Graaf, E. R. van der Dendooven, P.; Brandenburg, S.
2014-06-15
A detector model optimization procedure based on matching Monte Carlo simulations with measurements for two experimentally calibrated sample geometries which are frequently used in radioactivity measurement laboratories results in relative agreement within 5% between simulated and measured efficiencies for a high purity germanium detector. The optimization procedure indicated that the increase in dead layer thickness is largely responsible for a detector efficiency decrease in time. The optimized detector model allows Monte Carlo efficiency calibration for all other samples of which the geometry and bulk composition is known. The presented method is a competitive and economic alternative to more elaborate detector scanning methods and results in a comparable accuracy.
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.
Pérez-Calatayud, J; Granero, D; Ballester, F; Puchades, V; Casal, E
2004-03-01
The purpose of this study is to calculate the dose rate distribution for the Amersham Cs-137 pellet source used in brachytherapy with the Selectron low-dose-rate remote afterloading system in gynaecological applications using the Monte Carlo code GEANT4. The absolute dose rate distribution for the pellet source was obtained and presented as a one-dimensional absolute dose rate table as well as in the Task Group 43 dose-calculation formalism. In this study, excellent agreement was found between the point source theoretical model using fitted polynomial values and Monte Carlo calculations of the dose rate distribution for the pellet source. A comparison study was also made between the dose rate distribution obtained from a complete Monte Carlo simulation (Cs-137 pellet sources + remote afterloading system plastic guide tube + gynaecological applicator) and that calculated by applying the superposition principle to Monte Carlo data of the individual pellet sources. The data were obtained for a portion of uterine tandem of typical train source configurations. Significant differences with a strong dependence on polar angle have been found that must be kept in mind for clinical dosimetry. PMID:15070245
Safronov, V. V.; Sozontov, E. A.; Gutman, G.
2013-05-15
A new concept of an X-ray brachytherapy setup based on the use of fluorescence from a secondary target placed at the tip of an implantable needle is proposed. Spatial dose-rate distributions for four combinations of secondary target materials and shapes are calculated by the Monte-Carlo method.
NASA Astrophysics Data System (ADS)
Sharma, Peter; Abraham, J. B. S.; Ten Eyck, G.; Childs, K. D.; Bielejec, E.; Carroll, M. S.
Detection of single ion implantation within a nanostructure is necessary for the high yield fabrication of implanted donor-based quantum computing architectures. Single ion Geiger mode avalanche (SIGMA) diodes with a laterally integrated nanostructure capable of forming a quantum dot were fabricated and characterized using photon pulses. The detection efficiency of this design was measured as a function of wavelength, lateral position, and for varying delay times between the photon pulse and the overbias detection window. Monte Carlo simulations based only on the random diffusion of photo-generated carriers and the geometrical placement of the avalanche region agrees qualitatively with device characterization. Based on these results, SIGMA detection efficiency appears to be determined solely by the diffusion of photo-generated electron-hole pairs into a buried avalanche region. Device performance is then highly dependent on the uniformity of the underlying silicon substrate and the proximity of photo-generated carriers to the silicon-silicon dioxide interface, which are the most important limiting factors for reaching the single ion detection limit with SIGMA detectors. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under Contract DE-AC04-94AL85000.
SU-D-19A-04: Parameter Characterization of Electron Beam Monte Carlo Phase Space of TrueBeam Linacs
Rodrigues, A; Yin, F; Wu, Q; Sawkey, D
2014-06-01
Purpose: For TrueBeam Monte Carlo simulations, Varian does not distribute linac head geometry and material compositions, instead providing a phase space file (PSF) for the users. The PSF has a finite number of particle histories and can have very large file size, yet still contains inherent statistical noises. The purpose of this study is to characterize the electron beam PSF with parameters. Methods: The PSF is a snapshot of all particles' information at a given plane above jaws including type, energy, position, and directions. This study utilized a preliminary TrueBeam PSF, of which validation against measurement is presented in another study. To characterize the PSF, distributions of energy, position, and direction of all particles are analyzed as piece-wise parameterized functions of radius and polar angle. Subsequently, a pseudo PSF was generated based on this characterization. Validation was assessed by directly comparing the true and pseudo PSFs, and by using both PSFs in the down-stream MC simulations (BEAMnrc/DOSXYZnrc) and comparing dose distributions for 3 applicators at 15 MeV. Statistical uncertainty of 4% was limited by the number of histories in the original PSF. Percent depth dose (PDD) and orthogonal (PRF) profiles at various depths were evaluated. Results: Preliminary results showed that this PSF parameterization was accurate, with no visible differences between original and pseudo PSFs except at the edge (6 cm off axis), which did not impact dose distributions in phantom. PDD differences were within 1 mm for R{sub 7} {sub 0}, R{sub 5} {sub 0}, R{sub 3} {sub 0}, and R{sub 1} {sub 0}, and PRF field size and penumbras were within 2 mm. Conclusion: A PSF can be successfully characterized by distributions for energy, position, and direction as parameterized functions of radius and polar angles; this facilitates generating sufficient particles at any statistical precision. Analyses for all other electron energies are under way and results will be
Torres, Javier; Buades, Manuel J; Almansa, Julio F; Guerrero, Rafael; Lallena, Antonio M
2004-02-01
Monte Carlo calculations using the codes PENELOPE and GEANT4 have been performed to characterize the dosimetric parameters of the new 20 mm long catheter-based 32P beta source manufactured by the Guidant Corporation. The dose distribution along the transverse axis and the two-dimensional dose rate table have been calculated. Also, the dose rate at the reference point, the radial dose function, and the anisotropy function were evaluated according to the adapted TG-60 formalism for cylindrical sources. PENELOPE and GEANT4 codes were first verified against previous results corresponding to the old 27 mm Guidant 32P beta source. The dose rate at the reference point for the unsheathed 27 mm source in water was calculated to be 0.215 +/- 0.001 cGy s(-1) mCi(-1), for PENELOPE, and 0.2312 +/- 0.0008 cGy s(-1) mCi(-1), for GEANT4. For the unsheathed 20 mm source, these values were 0.2908 +/- 0.0009 cGy s(-1) mCi(-1) and 0.311 0.001 cGy s(-1) mCi(-1), respectively. Also, a comparison with the limited data available on this new source is shown. We found non-negligible differences between the results obtained with PENELOPE and GEANT4. PMID:15000615
SCALE Monte Carlo Eigenvalue Methods and New Advancements
Goluoglu, Sedat; Leppanen, Jaakko; Petrie Jr, Lester M; Dunn, Michael E
2010-01-01
SCALE code system is developed and maintained by Oak Ridge National Laboratory to perform criticality safety, reactor analysis, radiation shielding, and spent fuel characterization for nuclear facilities and transportation/storage package designs. SCALE is a modular code system that includes several codes which use either Monte Carlo or discrete ordinates solution methodologies for solving relevant neutral particle transport equations. This paper describes some of the key capabilities of the Monte Carlo criticality safety codes within the SCALE code system.
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.
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.
NASA Astrophysics Data System (ADS)
Vidovič, Luka; Milanič, Matija; Majaron, Boris
2015-01-01
Pulsed photothermal radiometry (PPTR) allows noninvasive determination of laser-induced temperature depth profiles in optically scattering layered structures. The obtained profiles provide information on spatial distribution of selected chromophores such as melanin and hemoglobin in human skin. We apply the described approach to study time evolution of incidental bruises (hematomas) in human subjects. By combining numerical simulations of laser energy deposition in bruised skin with objective fitting of the predicted and measured PPTR signals, we can quantitatively characterize the key processes involved in bruise evolution (i.e., hemoglobin mass diffusion and biochemical decomposition). Simultaneous analysis of PPTR signals obtained at various times post injury provides an insight into the variations of these parameters during the bruise healing process. The presented methodology and results advance our understanding of the bruise evolution and represent an important step toward development of an objective technique for age determination of traumatic bruises in forensic medicine.
Vidovič, Luka; Milanič, Matija; Majaron, Boris
2015-01-01
Pulsed photothermal radiometry (PPTR) allows noninvasive determination of laser-induced temperature depth profiles in optically scattering layered structures. The obtained profiles provide information on spatial distribution of selected chromophores such as melanin and hemoglobin in human skin. We apply the described approach to study time evolution of incidental bruises (hematomas) in human subjects. By combining numerical simulations of laser energy deposition in bruised skin with objective fitting of the predicted and measured PPTR signals, we can quantitatively characterize the key processes involved in bruise evolution (i.e., hemoglobin mass diffusion and biochemical decomposition). Simultaneous analysis of PPTR signals obtained at various times post injury provides an insight into the variations of these parameters during the bruise healing process. The presented methodology and results advance our understanding of the bruise evolution and represent an important step toward development of an objective technique for age determination of traumatic bruises in forensic medicine. PMID:25554972
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.
NASA Astrophysics Data System (ADS)
Habib, A. S.; Shutt, A. L.; Regan, P. H.; Matthews, M. C.; Alsulaiti, H.; Bradley, D. A.
2014-02-01
Radioactive scale formation in various oil production facilities is acknowledged to pose a potential significant health and environmental issue. The presence of such an issue in Libyan oil fields was recognized as early as 1998. The naturally occurring radioactive materials (NORM) involved in this matter are radium isotopes (226Ra and 228Ra) and their decay products, precipitating into scales formed on the surfaces of production equipment. A field trip to a number of onshore Libyan oil fields has indicated the existence of elevated levels of specific activity in a number of locations in some of the more mature oil fields. In this study, oil scale samples collected from different parts of Libya have been characterized using gamma spectroscopy through use of a well shielded HPGe spectrometer. To avoid potential alpha-bearing dust inhalation and in accord with safe working practices at this University, the samples, contained in plastic bags and existing in different geometries, are not permitted to be opened. MCNP, a Monte Carlo simulation code, is being used to simulate the spectrometer and the scale samples in order to obtain the system absolute efficiency and then to calculate sample specific activities. The samples are assumed to have uniform densities and homogeneously distributed activity. Present results are compared to two extreme situations that were assumed in a previous study: (i) with the entire activity concentrated at a point on the sample surface proximal to the detector, simulating the sample lowest activity, and; (ii) with the entire activity concentrated at a point on the sample surface distal to the detector, simulating the sample highest activity.
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
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.
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
NASA Astrophysics Data System (ADS)
Manso, M.; Schiavon, N.; Queralt, I.; Arruda, A. M.; Sampaio, J. M.; Brunetti, A.
2015-05-01
In this work we evaluate the composition of a bronze alloy using X-ray fluorescence spectrometry (XRF) and Monte Carlo (MC) simulations. For this purpose, a 7th Century BC archeological vase from the SW Iberian Peninsula, displaying a well formed corrosion patina was analyzed by means of a portable X-ray fluorescence spectrometer. Realistic MC simulations of the experimental setup were performed with the XRMC code package which is based on an intensive use of variance-reduction techniques and uses XRAYLIB a constantly updated X-ray library of atomic data. A single layer model was applied for simulating XRF of polished/pristine bronze whereas a two-or-three-layer model was developed for bronze covered respectively by a corrosion patina alone or coupled with a superficial soil derived crust. These simulations took into account corrosion (cerussite (PbCO3), cuprite (Cu2O), malachite (Cu2CO3(OH)2), litharge (PbO)) and soil derived products (goethite (FeO(OH)) and quartz (SiO2)) identified by means of X-ray diffraction and Raman micro analytical techniques. Results confirm previous research indicating that the XRF/Monte Carlo protocol is well suited when a two-layered model is considered, whereas in areas where the patina + soil derived products' crust is too thick, X-rays from the alloy substrate are not able to exit the sample. Quantitative results based on MC simulations indicate that the vase is made of a lead-bronze alloy: Mn (0.2%), Fe (1.0%), Cu (81.8%), As (0.5%), Ag (0.6%), Sn (8.0%) and Pb (8.0%).
Overview of the MCU Monte Carlo Software Package
NASA Astrophysics Data System (ADS)
Kalugin, M. A.; Oleynik, D. S.; Shkarovsky, D. A.
2014-06-01
MCU (Monte Carlo Universal) is a project on development and practical use of a universal computer code for simulation of particle transport (neutrons, photons, electrons, positrons) in three-dimensional systems by means of the Monte Carlo method. This paper provides the information on the current state of the project. The developed libraries of constants are briefly described, and the potentialities of the MCU-5 package modules and the executable codes compiled from them are characterized. Examples of important problems of reactor physics solved with the code are presented.
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.
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).
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)
3D polymer gel dosimetry and Geant4 Monte Carlo characterization of novel needle based X-ray source
NASA Astrophysics Data System (ADS)
Liu, Y.; Sozontov, E.; Safronov, V.; Gutman, G.; Strumban, E.; Jiang, Q.; Li, S.
2010-11-01
In the recent years, there have been a few attempts to develop a low energy x-ray radiation sources alternative to conventional radioisotopes used in brachytherapy. So far, all efforts have been centered around the intent to design an interstitial miniaturized x-ray tube. Though direct irradiation of tumors looks very promising, the known insertable miniature x-ray tubes have many limitations: (a) difficulties with focusing and steering the electron beam to the target; (b)necessity to cool the target to increase x-ray production efficiency; (c)impracticability to reduce the diameter of the miniaturized x-ray tube below 4mm (the requirement to decrease the diameter of the x-ray tube and the need to have a cooling system for the target have are mutually exclusive); (c) significant limitations in changing shape and energy of the emitted radiation. The specific aim of this study is to demonstrate the feasibility of a new concept for an insertable low-energy needle x-ray device based on simulation with Geant4 Monte Carlo code and to measure the dose rate distribution for low energy (17.5 keV) x-ray radiation with the 3D polymer gel dosimetry.
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.
Baptista, Mariana Di Maria, Salvatore; Barros, Sílvia; Vaz, Pedro; Figueira, Catarina; Sarmento, Marta; Orvalho, Lurdes
2015-07-15
Purpose: Due to its capability to more accurately detect deep lesions inside the breast by removing the effect of overlying anatomy, digital breast tomosynthesis (DBT) has the potential to replace the standard mammography technique in clinical screening exams. However, the European Guidelines for DBT dosimetry are still a work in progress and there are little data available on organ doses other than to the breast. It is, therefore, of great importance to assess the dosimetric performance of DBT with respect to the one obtained with standard digital mammography (DM) systems. The aim of this work is twofold: (i) to study the dosimetric properties of a combined DBT/DM system (MAMMOMAT Inspiration Siemens{sup ®}) for a tungsten/rhodium (W/Rh) anode/filter combination and (ii) to evaluate organs doses during a DBT examination. Methods: For the first task, measurements were performed in manual and automatic exposure control (AEC) modes, using two homogeneous breast phantoms: a PMMA slab phantom and a 4 cm thick breast-shaped rigid phantom, with 50% of glandular tissue in its composition. Monte Carlo (MC) simulations were performed using Monte Carlo N-Particle eXtended v.2.7.0. A MC model was implemented to mimic DM and DBT acquisitions for a wide range of x-ray spectra (24 –34 kV). This was used to calculate mean glandular dose (MGD) and to compute series of backscatter factors (BSFs) that could be inserted into the DBT dosimetric formalism proposed by Dance et al. Regarding the second aim of the study, the implemented MC model of the clinical equipment, together with a female voxel phantom (“Laura”), was used to calculate organ doses considering a typical DBT acquisition. Results were compared with a standard two-view mammography craniocaudal (CC) acquisition. Results: Considering the AEC mode, the acquisition of a single CC view results in a MGD ranging from 0.53 ± 0.07 mGy to 2.41 ± 0.31 mGy in DM mode and from 0.77 ± 0.11 mGy to 2.28 ± 0.32 mGy in DBT mode
NASA Astrophysics Data System (ADS)
SU, J.; Sagdeev, R.; Usikov, D.; Chin, G.; Boyer, L.; Livengood, T. A.; McClanahan, T. P.; Murray, J.; Starr, R. D.
2013-12-01
Introduction: The leakage flux of lunar neutrons produced by precipitation of galactic cosmic ray (GCR) particles in the upper layer of the lunar regolith and measured by orbital instruments such as the Lunar Exploration Neutron Detector (LEND) is investigated by Monte Carlo simulation. Previous Monte Carlo (MC) simulations have been used to investigate neutron production and leakage from the lunar surface to assess the elemental composition of lunar soil [1-6] and its effect on the leakage neutron flux. We investigate effects on the emergent flux that depend on the physical distribution of hydrogen within the regolith. We use the software package GEANT4 [7] to calculate neutron production from spallation by GCR particles [8,9] in the lunar soil. Multiple layers of differing hydrogen/water at different depths in the lunar regolith model are introduced to examine enhancement or suppression of leakage neutron flux. We find that the majority of leakage thermal and epithermal neutrons are produced in 25 cm to 75 cm deep from the lunar surface. Neutrons produced in the shallow top layer retain more of their original energy due to fewer scattering interactions and escape from the lunar surface mostly as fast neutrons. This provides a diagnostic tool in interpreting leakage neutron flux enhancement or suppression due to hydrogen concentration distribution in lunar regolith. We also find that the emitting angular distribution of thermal and epithermal leakage neutrons can be described by cos3/2(theta) where the fast neutrons emitting angular distribution is cos(theta). The energy sensitivity and angular response of the LEND detectors SETN and CSETN are investigated using the leakage neutron spectrum from GEANT4 simulations. A simplified LRO model is used to benchmark MCNPX[10] and GEANT4 on CSETN absolute count rate corresponding to neutron flux from bombardment of 120MV solar potential GCR particles on FAN lunar soil. We are able to interpret the count rates of SETN and
NASA Astrophysics Data System (ADS)
Fracchiolla, F.; Lorentini, S.; Widesott, L.; Schwarz, M.
2015-11-01
We propose a method of creating and validating a Monte Carlo (MC) model of a proton Pencil Beam Scanning (PBS) machine using only commissioning measurements and avoiding the nozzle modeling. Measurements with a scintillating screen coupled with a CCD camera, ionization chamber and a Faraday Cup were used to model the beam in TOPAS without using any machine parameter information but the virtual source distance from the isocenter. Then the model was validated on simple Spread Out Bragg Peaks (SOBP) delivered in water phantom and with six realistic clinical plans (many involving 3 or more fields) on an anthropomorphic phantom. In particular the behavior of the moveable Range Shifter (RS) feature was investigated and its modeling has been proposed. The gamma analysis (3%,3 mm) was used to compare MC, TPS (XiO-ELEKTA) and measured 2D dose distributions (using radiochromic film). The MC modeling proposed here shows good results in the validation phase, both for simple irradiation geometry (SOBP in water) and for modulated treatment fields (on anthropomorphic phantoms). In particular head lesions were investigated and both MC and TPS data were compared with measurements. Treatment plans with no RS always showed a very good agreement with both of them (γ -Passing Rate (PR) > 95%). Treatment plans in which the RS was needed were also tested and validated. For these treatment plans MC results showed better agreement with measurements (γ -PR > 93%) than the one coming from TPS (γ -PR < 88%). This work shows how to simplify the MC modeling of a PBS machine for proton therapy treatments without accounting for any hardware components and proposes a more reliable RS modeling than the one implemented in our TPS. The validation process has shown how this code is a valid candidate for a completely independent treatment plan dose calculation algorithm. This makes the code an important future tool for the patient specific QA verification process.
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.
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.
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
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.
Monte Carlo simulation of scenario probability distributions
Glaser, R.
1996-10-23
Suppose a scenario of interest can be represented as a series of events. A final result R may be viewed then as the intersection of three events, A, B, and C. The probability of the result P(R) in this case is the product P(R) = P(A) P(B {vert_bar} A) P(C {vert_bar} A {intersection} B). An expert may be reluctant to estimate P(R) as a whole yet agree to supply his notions of the component probabilities in the form of prior distributions. Each component prior distribution may be viewed as the stochastic characterization of the expert`s uncertainty regarding the true value of the component probability. Mathematically, the component probabilities are treated as independent random variables and P(R) as their product; the induced prior distribution for P(R) is determined which characterizes the expert`s uncertainty regarding P(R). It may be both convenient and adequate to approximate the desired distribution by Monte Carlo simulation. Software has been written for this task that allows a variety of component priors that experts with good engineering judgment might feel comfortable with. The priors are mostly based on so-called likelihood classes. The software permits an expert to choose for a given component event probability one of six types of prior distributions, and the expert specifies the parameter value(s) for that prior. Each prior is unimodal. The expert essentially decides where the mode is, how the probability is distributed in the vicinity of the mode, and how rapidly it attenuates away. Limiting and degenerate applications allow the expert to be vague or precise.
Fracchiolla, F; Lorentini, S; Widesott, L; Schwarz, M
2015-11-01
We propose a method of creating and validating a Monte Carlo (MC) model of a proton Pencil Beam Scanning (PBS) machine using only commissioning measurements and avoiding the nozzle modeling. Measurements with a scintillating screen coupled with a CCD camera, ionization chamber and a Faraday Cup were used to model the beam in TOPAS without using any machine parameter information but the virtual source distance from the isocenter. Then the model was validated on simple Spread Out Bragg Peaks (SOBP) delivered in water phantom and with six realistic clinical plans (many involving 3 or more fields) on an anthropomorphic phantom. In particular the behavior of the moveable Range Shifter (RS) feature was investigated and its modeling has been proposed. The gamma analysis (3%,3 mm) was used to compare MC, TPS (XiO-ELEKTA) and measured 2D dose distributions (using radiochromic film). The MC modeling proposed here shows good results in the validation phase, both for simple irradiation geometry (SOBP in water) and for modulated treatment fields (on anthropomorphic phantoms). In particular head lesions were investigated and both MC and TPS data were compared with measurements. Treatment plans with no RS always showed a very good agreement with both of them (γ-Passing Rate (PR) > 95%). Treatment plans in which the RS was needed were also tested and validated. For these treatment plans MC results showed better agreement with measurements (γ-PR > 93%) than the one coming from TPS (γ-PR < 88%). This work shows how to simplify the MC modeling of a PBS machine for proton therapy treatments without accounting for any hardware components and proposes a more reliable RS modeling than the one implemented in our TPS. The validation process has shown how this code is a valid candidate for a completely independent treatment plan dose calculation algorithm. This makes the code an important future tool for the patient specific QA verification process. PMID
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
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
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.
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.
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.
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.
Ab initio Monte Carlo investigation of small lithium clusters.
Srinivas, S.
1999-06-16
Structural and thermal properties of small lithium clusters are studied using ab initio-based Monte Carlo simulations. The ab initio scheme uses a Hartree-Fock/density functional treatment of the electronic structure combined with a jump-walking Monte Carlo sampling of nuclear configurations. Structural forms of Li{sub 8} and Li{sub 9}{sup +} clusters are obtained and their thermal properties analyzed in terms of probability distributions of the cluster potential energy, average potential energy and configurational heat capacity all considered as a function of the cluster temperature. Details of the gradual evolution with temperature of the structural forms sampled are examined. Temperatures characterizing the onset of structural changes and isomer coexistence are identified for both clusters.
Monte Carlo Simulation Of H{sup -} Ion Transport
Diomede, P.; Longo, S.; Capitelli, M.
2009-03-12
In this work we study in detail the kinetics of H{sup -} ion swarms in velocity space: this provides a useful contrast to the usual literature in the field, where device features in configuration space are often included in detail but kinetic distributions are only marginally considered. To this aim a Monte Carlo model is applied, which includes several collision processes of H{sup -} ions with neutral particles as well as Coulomb collisions with positive ions. We characterize the full velocity distribution i.e. including its anisotropy, for different values of E/N, the atomic fraction and the H{sup +} mole fraction, which makes our results of interest for both source modeling and beam formation. A simple analytical theory, for highly dissociated hydrogen is formulated and checked by Monte Carlo calculations.
A surrogate accelerated multicanonical Monte Carlo method for uncertainty quantification
NASA Astrophysics Data System (ADS)
Wu, Keyi; Li, Jinglai
2016-09-01
In this work we consider a class of uncertainty quantification problems where the system performance or reliability is characterized by a scalar parameter y. The performance parameter y is random due to the presence of various sources of uncertainty in the system, and our goal is to estimate the probability density function (PDF) of y. We propose to use the multicanonical Monte Carlo (MMC) method, a special type of adaptive importance sampling algorithms, to compute the PDF of interest. Moreover, we develop an adaptive algorithm to construct local Gaussian process surrogates to further accelerate the MMC iterations. With numerical examples we demonstrate that the proposed method can achieve several orders of magnitudes of speedup over the standard Monte Carlo methods.
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.
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.
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.
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
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 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.
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
Coherent Scattering Imaging Monte Carlo Simulation
NASA Astrophysics Data System (ADS)
Hassan, Laila Abdulgalil Rafik
Conventional mammography has poor contrast between healthy and cancerous tissues due to the small difference in attenuation properties. Coherent scatter potentially provides more information because interference of coherently scattered radiation depends on the average intermolecular spacing, and can be used to characterize tissue types. However, typical coherent scatter analysis techniques are not compatible with rapid low dose screening techniques. Coherent scatter slot scan imaging is a novel imaging technique which provides new information with higher contrast. In this work a simulation of coherent scatter was performed for slot scan imaging to assess its performance and provide system optimization. In coherent scatter imaging, the coherent scatter is exploited using a conventional slot scan mammography system with anti-scatter grids tilted at the characteristic angle of cancerous tissues. A Monte Carlo simulation was used to simulate the coherent scatter imaging. System optimization was performed across several parameters, including source voltage, tilt angle, grid distances, grid ratio, and shielding geometry. The contrast increased as the grid tilt angle increased beyond the characteristic angle for the modeled carcinoma. A grid tilt angle of 16 degrees yielded the highest contrast and signal to noise ratio (SNR). Also, contrast increased as the source voltage increased. Increasing grid ratio improved contrast at the expense of decreasing SNR. A grid ratio of 10:1 was sufficient to give a good contrast without reducing the intensity to a noise level. The optimal source to sample distance was determined to be such that the source should be located at the focal distance of the grid. A carcinoma lump of 0.5x0.5x0.5 cm3 in size was detectable which is reasonable considering the high noise due to the usage of relatively small number of incident photons for computational reasons. A further study is needed to study the effect of breast density and breast thickness
Theory and Applications of Quantum Monte Carlo
NASA Astrophysics Data System (ADS)
Deible, Michael John
With the development of peta-scale computers and exa-scale only a few years away, the quantum Monte Carlo (QMC) method, with favorable scaling and inherent parrallelizability, is poised to increase its impact on the electronic structure community. The most widely used variation of QMC is the diffusion Monte Carlo (DMC) method. The accuracy of the DMC method is only limited by the trial wave function that it employs. The effect of the trial wave function is studied here by initially developing correlation-consistent Gaussian basis sets for use in DMC calculations. These basis sets give a low variance in variance Monte Carlo calculations and improved convergence in DMC. The orbital type used in the trial wave function is then investigated, and it is shown that Brueckner orbitals result in a DMC energy comparable to a DMC energy with orbitals from density functional theory and significantly lower than orbitals from Hartree-Fock theory. Three large weakly interacting systems are then studied; a water-16 isomer, a methane clathrate, and a carbon dioxide clathrate. The DMC method is seen to be in good agreement with MP2 calculations and provides reliable benchmarks. Several strongly correlated systems are then studied. An H4 model system that allows for a fine tuning of the multi-configurational character of the wave function shows when the accuracy of the DMC method with a single Slater-determinant trial function begins to deviate from multi-reference benchmarks. The weakly interacting face-to-face ethylene dimer is studied with and without a rotation around the pi bond, which is used to increase the multi-configurational nature of the wave function. This test shows that the effect of a multi-configurational wave function in weakly interacting systems causes DMC with a single Slater-determinant to be unable to achieve sub-chemical accuracy. The beryllium dimer is studied, and it is shown that a very large determinant expansion is required for DMC to predict a binding
Monte Carlo simulations of medical imaging modalities
Estes, G.P.
1998-09-01
Because continuous-energy Monte Carlo radiation transport calculations can be nearly exact simulations of physical reality (within data limitations, geometric approximations, transport algorithms, etc.), it follows that one should be able to closely approximate the results of many experiments from first-principles computations. This line of reasoning has led to various MCNP studies that involve simulations of medical imaging modalities and other visualization methods such as radiography, Anger camera, computerized tomography (CT) scans, and SABRINA particle track visualization. It is the intent of this paper to summarize some of these imaging simulations in the hope of stimulating further work, especially as computer power increases. Improved interpretation and prediction of medical images should ultimately lead to enhanced medical treatments. It is also reasonable to assume that such computations could be used to design new or more effective imaging instruments.
Coherent scatter imaging Monte Carlo simulation.
Hassan, Laila; MacDonald, Carolyn A
2016-07-01
Conventional mammography can suffer from poor contrast between healthy and cancerous tissues due to the small difference in attenuation properties. Coherent scatter slot scan imaging is an imaging technique which provides additional information and is compatible with conventional mammography. A Monte Carlo simulation of coherent scatter slot scan imaging was performed to assess its performance and provide system optimization. Coherent scatter could be exploited using a system similar to conventional slot scan mammography system with antiscatter grids tilted at the characteristic angle of cancerous tissues. System optimization was performed across several parameters, including source voltage, tilt angle, grid distances, grid ratio, and shielding geometry. The simulated carcinomas were detectable for tumors as small as 5 mm in diameter, so coherent scatter analysis using a wide-slot setup could be promising as an enhancement for screening mammography. Employing coherent scatter information simultaneously with conventional mammography could yield a conventional high spatial resolution image with additional coherent scatter information. PMID:27610397
Green's function Monte Carlo in nuclear physics
Carlson, J.
1990-01-01
We review the status of Green's Function Monte Carlo (GFMC) methods as applied to problems in nuclear physics. New methods have been developed to handle the spin and isospin degrees of freedom that are a vital part of any realistic nuclear physics problem, whether at the level of quarks or nucleons. We discuss these methods and then summarize results obtained recently for light nuclei, including ground state energies, three-body forces, charge form factors and the coulomb sum. As an illustration of the applicability of GFMC to quark models, we also consider the possible existence of bound exotic multi-quark states within the framework of flux-tube quark models. 44 refs., 8 figs., 1 tab.
Accuracy control in Monte Carlo radiative calculations
NASA Technical Reports Server (NTRS)
Almazan, P. Planas
1993-01-01
The general accuracy law that rules the Monte Carlo, ray-tracing algorithms used commonly for the calculation of the radiative entities in the thermal analysis of spacecraft are presented. These entities involve transfer of radiative energy either from a single source to a target (e.g., the configuration factors). or from several sources to a target (e.g., the absorbed heat fluxes). In fact, the former is just a particular case of the latter. The accuracy model is later applied to the calculation of some specific radiative entities. Furthermore, some issues related to the implementation of such a model in a software tool are discussed. Although only the relative error is considered through the discussion, similar results can be derived for the absolute error.
MORSE Monte Carlo radiation transport code system
Emmett, M.B.
1983-02-01
This report is an addendum to the MORSE report, ORNL-4972, originally published in 1975. This addendum contains descriptions of several modifications to the MORSE Monte Carlo Code, replacement pages containing corrections, Part II of the report which was previously unpublished, and a new Table of Contents. The modifications include a Klein Nishina estimator for gamma rays. Use of such an estimator required changing the cross section routines to process pair production and Compton scattering cross sections directly from ENDF tapes and writing a new version of subroutine RELCOL. Another modification is the use of free form input for the SAMBO analysis data. This required changing subroutines SCORIN and adding new subroutine RFRE. References are updated, and errors in the original report have been corrected. (WHK)
Exploring theory space with Monte Carlo reweighting
Gainer, James S.; Lykken, Joseph; Matchev, Konstantin T.; Mrenna, Stephen; Park, Myeonghun
2014-10-13
Theories of new physics often involve a large number of unknown parameters which need to be scanned. Additionally, a putative signal in a particular channel may be due to a variety of distinct models of new physics. This makes experimental attempts to constrain the parameter space of motivated new physics models with a high degree of generality quite challenging. We describe how the reweighting of events may allow this challenge to be met, as fully simulated Monte Carlo samples generated for arbitrary benchmark models can be effectively re-used. Specifically, we suggest procedures that allow more efficient collaboration between theorists andmore » experimentalists in exploring large theory parameter spaces in a rigorous way at the LHC.« less
Monte Carlo modeling and meteor showers
NASA Astrophysics Data System (ADS)
Kulikova, N. V.
1987-08-01
Prediction of short lived increases in the cosmic dust influx, the concentration in lower thermosphere of atoms and ions of meteor origin and the determination of the frequency of micrometeor impacts on spacecraft are all of scientific and practical interest and all require adequate models of meteor showers at an early stage of their existence. A Monte Carlo model of meteor matter ejection from a parent body at any point of space was worked out by other researchers. This scheme is described. According to the scheme, the formation of ten well known meteor streams was simulated and the possibility of genetic affinity of each of them with the most probable parent comet was analyzed. Some of the results are presented.
Quantum Monte Carlo simulations in novel geometries
NASA Astrophysics Data System (ADS)
Iglovikov, Vladimir
Quantum Monte Carlo simulations are giving increasing insight into the physics of strongly interacting bosons, spins, and fermions. Initial work focused on the simplest geometries, like a 2D square lattice. Increasingly, modern research is turning to more rich structures such as honeycomb lattice of graphene, the Lieb lattice of the CuO2 planes of cuprate superconductors, the triangular lattice, and coupled layers. These new geometries possess unique features which affect the physics in profound ways, eg a vanishing density of states and relativistic dispersion ("Dirac point'') of a honeycomb lattice, frustration on a triangular lattice, and a flat bands on a Lieb lattice. This thesis concerns both exploring the performance of QMC algorithms on different geometries(primarily via the "sign problem'') and also applying those algorithms to several interesting open problems.
Resist develop prediction by Monte Carlo simulation
NASA Astrophysics Data System (ADS)
Sohn, Dong-Soo; Jeon, Kyoung-Ah; Sohn, Young-Soo; Oh, Hye-Keun
2002-07-01
Various resist develop models have been suggested to express the phenomena from the pioneering work of Dill's model in 1975 to the recent Shipley's enhanced notch model. The statistical Monte Carlo method can be applied to the process such as development and post exposure bake. The motions of developer during development process were traced by using this method. We have considered that the surface edge roughness of the resist depends on the weight percentage of protected and de-protected polymer in the resist. The results are well agreed with other papers. This study can be helpful for the developing of new photoresist and developer that can be used to pattern the device features smaller than 100 nm.
Exploring theory space with Monte Carlo reweighting
Gainer, James S.; Lykken, Joseph; Matchev, Konstantin T.; Mrenna, Stephen; Park, Myeonghun
2014-10-13
Theories of new physics often involve a large number of unknown parameters which need to be scanned. Additionally, a putative signal in a particular channel may be due to a variety of distinct models of new physics. This makes experimental attempts to constrain the parameter space of motivated new physics models with a high degree of generality quite challenging. We describe how the reweighting of events may allow this challenge to be met, as fully simulated Monte Carlo samples generated for arbitrary benchmark models can be effectively re-used. Specifically, we suggest procedures that allow more efficient collaboration between theorists and experimentalists in exploring large theory parameter spaces in a rigorous way at the LHC.
Monte Carlo modeling and meteor showers
NASA Technical Reports Server (NTRS)
Kulikova, N. V.
1987-01-01
Prediction of short lived increases in the cosmic dust influx, the concentration in lower thermosphere of atoms and ions of meteor origin and the determination of the frequency of micrometeor impacts on spacecraft are all of scientific and practical interest and all require adequate models of meteor showers at an early stage of their existence. A Monte Carlo model of meteor matter ejection from a parent body at any point of space was worked out by other researchers. This scheme is described. According to the scheme, the formation of ten well known meteor streams was simulated and the possibility of genetic affinity of each of them with the most probable parent comet was analyzed. Some of the results are presented.
Noncovalent Interactions by Quantum Monte Carlo.
Dubecký, Matúš; Mitas, Lubos; Jurečka, Petr
2016-05-11
Quantum Monte Carlo (QMC) is a family of stochastic methods for solving quantum many-body problems such as the stationary Schrödinger equation. The review introduces basic notions of electronic structure QMC based on random walks in real space as well as its advances and adaptations to systems with noncovalent interactions. Specific issues such as fixed-node error cancellation, construction of trial wave functions, and efficiency considerations that allow for benchmark quality QMC energy differences are described in detail. Comprehensive overview of articles covers QMC applications to systems with noncovalent interactions over the last three decades. The current status of QMC with regard to efficiency, applicability, and usability by nonexperts together with further considerations about QMC developments, limitations, and unsolved challenges are discussed as well. PMID:27081724
Monte-Carlo Simulation Balancing in Practice
NASA Astrophysics Data System (ADS)
Huang, Shih-Chieh; Coulom, Rémi; Lin, Shun-Shii
Simulation balancing is a new technique to tune parameters of a playout policy for a Monte-Carlo game-playing program. So far, this algorithm had only been tested in a very artificial setting: it was limited to 5×5 and 6×6 Go, and required a stronger external program that served as a supervisor. In this paper, the effectiveness of simulation balancing is demonstrated in a more realistic setting. A state-of-the-art program, Erica, learned an improved playout policy on the 9×9 board, without requiring any external expert to provide position evaluations. The evaluations were collected by letting the program analyze positions by itself. The previous version of Erica learned pattern weights with the minorization-maximization algorithm. Thanks to simulation balancing, its playing strength was improved from a winning rate of 69% to 78% against Fuego 0.4.
Angular biasing in implicit Monte-Carlo
Zimmerman, G.B.
1994-10-20
Calculations of indirect drive Inertial Confinement Fusion target experiments require an integrated approach in which laser irradiation and radiation transport in the hohlraum are solved simultaneously with the symmetry, implosion and burn of the fuel capsule. The Implicit Monte Carlo method has proved to be a valuable tool for the two dimensional radiation transport within the hohlraum, but the impact of statistical noise on the symmetric implosion of the small fuel capsule is difficult to overcome. We present an angular biasing technique in which an increased number of low weight photons are directed at the imploding capsule. For typical parameters this reduces the required computer time for an integrated calculation by a factor of 10. An additional factor of 5 can also be achieved by directing even smaller weight photons at the polar regions of the capsule where small mass zones are most sensitive to statistical noise.
Chemical application of diffusion quantum Monte Carlo
NASA Technical Reports Server (NTRS)
Reynolds, P. J.; Lester, W. A., Jr.
1984-01-01
The diffusion quantum Monte Carlo (QMC) method gives a stochastic solution to the Schroedinger equation. This approach is receiving increasing attention in chemical applications as a result of its high accuracy. However, reducing statistical uncertainty remains a priority because chemical effects are often obtained as small differences of large numbers. As an example, the single-triplet splitting of the energy of the methylene molecule CH sub 2 is given. The QMC algorithm was implemented on the CYBER 205, first as a direct transcription of the algorithm running on the 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, are discussed. The computational time dependence obtained versus the number of basis functions is discussed and this is compared with that obtained from traditional quantum chemistry codes and that obtained from traditional computer architectures.
Monte Carlo simulations in Nuclear Medicine
Loudos, George K.
2007-11-26
Molecular imaging technologies provide unique abilities to localise signs of disease before symptoms appear, assist in drug testing, optimize and personalize therapy, and assess the efficacy of treatment regimes for different types of cancer. Monte Carlo simulation packages are used as an important tool for the optimal design of detector systems. In addition they have demonstrated potential to improve image quality and acquisition protocols. Many general purpose (MCNP, Geant4, etc) or dedicated codes (SimSET etc) have been developed aiming to provide accurate and fast results. Special emphasis will be given to GATE toolkit. The GATE code currently under development by the OpenGATE collaboration is the most accurate and promising code for performing realistic simulations. The purpose of this article is to introduce the non expert reader to the current status of MC simulations in nuclear medicine and briefly provide examples of current simulated systems, and present future challenges that include simulation of clinical studies and dosimetry applications.
Monte Carlo simulations in Nuclear Medicine
NASA Astrophysics Data System (ADS)
Loudos, George K.
2007-11-01
Molecular imaging technologies provide unique abilities to localise signs of disease before symptoms appear, assist in drug testing, optimize and personalize therapy, and assess the efficacy of treatment regimes for different types of cancer. Monte Carlo simulation packages are used as an important tool for the optimal design of detector systems. In addition they have demonstrated potential to improve image quality and acquisition protocols. Many general purpose (MCNP, Geant4, etc) or dedicated codes (SimSET etc) have been developed aiming to provide accurate and fast results. Special emphasis will be given to GATE toolkit. The GATE code currently under development by the OpenGATE collaboration is the most accurate and promising code for performing realistic simulations. The purpose of this article is to introduce the non expert reader to the current status of MC simulations in nuclear medicine and briefly provide examples of current simulated systems, and present future challenges that include simulation of clinical studies and dosimetry applications.
Optimized trial functions for quantum Monte Carlo
NASA Astrophysics Data System (ADS)
Huang, Sheng-Yu; Sun, Zhiwei; Lester, William A., Jr.
1990-01-01
An algorithm to optimize trial functions for fixed-node quantum Monte Carlo calculations has been developed based on variational random walks. The approach is applied to wave functions that are products of a simple Slater determinant and correlation factor explicitly dependent on interelectronic distance, and is found to provide improved ground-state total energies. A modification of the method for ground-states that makes use of a projection operator technique is shown to make possible the calculation of more accurate excited-state energies. In this optimization method the Young tableaux of the permutation group is used to facilitate the treatment of fermion properties and multiplets. Application to ground states of H2, Li2, H3, H+3, and to the first-excited singlets of H2, H3, and H4 are presented and discussed.
Optimized trial functions for quantum Monte Carlo
Huang, S.; Sun, Z.; Lester, W.A. Jr. )
1990-01-01
An algorithm to optimize trial functions for fixed-node quantum Monte Carlo calculations has been developed based on variational random walks. The approach is applied to wave functions that are products of a simple Slater determinant and correlation factor explicitly dependent on interelectronic distance, and is found to provide improved ground-state total energies. A modification of the method for ground-states that makes use of a projection operator technique is shown to make possible the calculation of more accurate excited-state energies. In this optimization method the Young tableaux of the permutation group is used to facilitate the treatment of fermion properties and multiplets. Application to ground states of H{sub 2}, Li{sub 2}, H{sub 3}, H{sup +}{sub 3}, and to the first-excited singlets of H{sub 2}, H{sub 3}, and H{sub 4} are presented and discussed.
abcpmc: Approximate Bayesian Computation for Population Monte-Carlo code
NASA Astrophysics Data System (ADS)
Akeret, Joel
2015-04-01
abcpmc is a Python Approximate Bayesian Computing (ABC) Population Monte Carlo (PMC) implementation based on Sequential Monte Carlo (SMC) with Particle Filtering techniques. It is extendable with k-nearest neighbour (KNN) or optimal local covariance matrix (OLCM) pertubation kernels and has built-in support for massively parallelized sampling on a cluster using MPI.
A Primer in Monte Carlo Integration Using Mathcad
ERIC Educational Resources Information Center
Hoyer, Chad E.; Kegerreis, Jeb S.
2013-01-01
The essentials of Monte Carlo integration are presented for use in an upper-level physical chemistry setting. A Mathcad document that aids in the dissemination and utilization of this information is described and is available in the Supporting Information. A brief outline of Monte Carlo integration is given, along with ideas and pedagogy for…
Monte Carlo Test Assembly for Item Pool Analysis and Extension
ERIC Educational Resources Information Center
Belov, Dmitry I.; Armstrong, Ronald D.
2005-01-01
A new test assembly algorithm based on a Monte Carlo random search is presented in this article. A major advantage of the Monte Carlo test assembly over other approaches (integer programming or enumerative heuristics) is that it performs a uniform sampling from the item pool, which provides every feasible item combination (test) with an equal…
Economic Risk Analysis: Using Analytical and Monte Carlo Techniques.
ERIC Educational Resources Information Center
O'Donnell, Brendan R.; Hickner, Michael A.; Barna, Bruce A.
2002-01-01
Describes the development and instructional use of a Microsoft Excel spreadsheet template that facilitates analytical and Monte Carlo risk analysis of investment decisions. Discusses a variety of risk assessment methods followed by applications of the analytical and Monte Carlo methods. Uses a case study to illustrate use of the spreadsheet tool…
The Monte Carlo Method. Popular Lectures in Mathematics.
ERIC Educational Resources Information Center
Sobol', I. M.
The Monte Carlo Method is a method of approximately solving mathematical and physical problems by the simulation of random quantities. The principal goal of this booklet is to suggest to specialists in all areas that they will encounter problems which can be solved by the Monte Carlo Method. Part I of the booklet discusses the simulation of random…
Accelerated GPU based SPECT Monte Carlo simulations
NASA Astrophysics Data System (ADS)
Garcia, Marie-Paule; Bert, Julien; Benoit, Didier; Bardiès, Manuel; Visvikis, Dimitris
2016-06-01
Monte Carlo (MC) modelling is widely used in the field of single photon emission computed tomography (SPECT) as it is a reliable technique to simulate very high quality scans. This technique provides very accurate modelling of the radiation transport and particle interactions in a heterogeneous medium. Various MC codes exist for nuclear medicine imaging simulations. Recently, new strategies exploiting the computing capabilities of graphical processing units (GPU) have been proposed. This work aims at evaluating the accuracy of such GPU implementation strategies in comparison to standard MC codes in the context of SPECT imaging. GATE was considered the reference MC toolkit and used to evaluate the performance of newly developed GPU Geant4-based Monte Carlo simulation (GGEMS) modules for SPECT imaging. Radioisotopes with different photon energies were used with these various CPU and GPU Geant4-based MC codes in order to assess the best strategy for each configuration. Three different isotopes were considered: 99m Tc, 111In and 131I, using a low energy high resolution (LEHR) collimator, a medium energy general purpose (MEGP) collimator and a high energy general purpose (HEGP) collimator respectively. Point source, uniform source, cylindrical phantom and anthropomorphic phantom acquisitions were simulated using a model of the GE infinia II 3/8" gamma camera. Both simulation platforms yielded a similar system sensitivity and image statistical quality for the various combinations. The overall acceleration factor between GATE and GGEMS platform derived from the same cylindrical phantom acquisition was between 18 and 27 for the different radioisotopes. Besides, a full MC simulation using an anthropomorphic phantom showed the full potential of the GGEMS platform, with a resulting acceleration factor up to 71. The good agreement with reference codes and the acceleration factors obtained support the use of GPU implementation strategies for improving computational efficiency
Monte Carlo modelling of TRIGA research reactor
NASA Astrophysics Data System (ADS)
El Bakkari, B.; Nacir, B.; El Bardouni, T.; El Younoussi, C.; Merroun, O.; Htet, A.; Boulaich, Y.; Zoubair, M.; Boukhal, H.; Chakir, M.
2010-10-01
The Moroccan 2 MW TRIGA MARK II research reactor at Centre des Etudes Nucléaires de la Maâmora (CENM) achieved initial criticality on May 2, 2007. The reactor is designed to effectively implement the various fields of basic nuclear research, manpower training, and production of radioisotopes for their use in agriculture, industry, and medicine. This study deals with the neutronic analysis of the 2-MW TRIGA MARK II research reactor at CENM and validation of the results by comparisons with the experimental, operational, and available final safety analysis report (FSAR) values. The study was prepared in collaboration between the Laboratory of Radiation and Nuclear Systems (ERSN-LMR) from Faculty of Sciences of Tetuan (Morocco) and CENM. The 3-D continuous energy Monte Carlo code MCNP (version 5) was used to develop a versatile and accurate full model of the TRIGA core. The model represents in detailed all components of the core with literally no physical approximation. Continuous energy cross-section data from the more recent nuclear data evaluations (ENDF/B-VI.8, ENDF/B-VII.0, JEFF-3.1, and JENDL-3.3) as well as S( α, β) thermal neutron scattering functions distributed with the MCNP code were used. The cross-section libraries were generated by using the NJOY99 system updated to its more recent patch file "up259". The consistency and accuracy of both the Monte Carlo simulation and neutron transport physics were established by benchmarking the TRIGA experiments. Core excess reactivity, total and integral control rods worth as well as power peaking factors were used in the validation process. Results of calculations are analysed and discussed.
Accelerated GPU based SPECT Monte Carlo simulations.
Garcia, Marie-Paule; Bert, Julien; Benoit, Didier; Bardiès, Manuel; Visvikis, Dimitris
2016-06-01
Monte Carlo (MC) modelling is widely used in the field of single photon emission computed tomography (SPECT) as it is a reliable technique to simulate very high quality scans. This technique provides very accurate modelling of the radiation transport and particle interactions in a heterogeneous medium. Various MC codes exist for nuclear medicine imaging simulations. Recently, new strategies exploiting the computing capabilities of graphical processing units (GPU) have been proposed. This work aims at evaluating the accuracy of such GPU implementation strategies in comparison to standard MC codes in the context of SPECT imaging. GATE was considered the reference MC toolkit and used to evaluate the performance of newly developed GPU Geant4-based Monte Carlo simulation (GGEMS) modules for SPECT imaging. Radioisotopes with different photon energies were used with these various CPU and GPU Geant4-based MC codes in order to assess the best strategy for each configuration. Three different isotopes were considered: (99m) Tc, (111)In and (131)I, using a low energy high resolution (LEHR) collimator, a medium energy general purpose (MEGP) collimator and a high energy general purpose (HEGP) collimator respectively. Point source, uniform source, cylindrical phantom and anthropomorphic phantom acquisitions were simulated using a model of the GE infinia II 3/8" gamma camera. Both simulation platforms yielded a similar system sensitivity and image statistical quality for the various combinations. The overall acceleration factor between GATE and GGEMS platform derived from the same cylindrical phantom acquisition was between 18 and 27 for the different radioisotopes. Besides, a full MC simulation using an anthropomorphic phantom showed the full potential of the GGEMS platform, with a resulting acceleration factor up to 71. The good agreement with reference codes and the acceleration factors obtained support the use of GPU implementation strategies for improving computational
Monte Carlo scatter correction for SPECT
NASA Astrophysics Data System (ADS)
Liu, Zemei
The goal of this dissertation is to present a quantitatively accurate and computationally fast scatter correction method that is robust and easily accessible for routine applications in SPECT imaging. A Monte Carlo based scatter estimation method is investigated and developed further. The Monte Carlo simulation program SIMIND (Simulating Medical Imaging Nuclear Detectors), was specifically developed to simulate clinical SPECT systems. The SIMIND scatter estimation (SSE) method was developed further using a multithreading technique to distribute the scatter estimation task across multiple threads running concurrently on multi-core CPU's to accelerate the scatter estimation process. An analytical collimator that ensures less noise was used during SSE. The research includes the addition to SIMIND of charge transport modeling in cadmium zinc telluride (CZT) detectors. Phenomena associated with radiation-induced charge transport including charge trapping, charge diffusion, charge sharing between neighboring detector pixels, as well as uncertainties in the detection process are addressed. Experimental measurements and simulation studies were designed for scintillation crystal based SPECT and CZT based SPECT systems to verify and evaluate the expanded SSE method. Jaszczak Deluxe and Anthropomorphic Torso Phantoms (Data Spectrum Corporation, Hillsborough, NC, USA) were used for experimental measurements and digital versions of the same phantoms employed during simulations to mimic experimental acquisitions. This study design enabled easy comparison of experimental and simulated data. The results have consistently shown that the SSE method performed similarly or better than the triple energy window (TEW) and effective scatter source estimation (ESSE) methods for experiments on all the clinical SPECT systems. The SSE method is proven to be a viable method for scatter estimation for routine clinical use.
Quantum Monte Carlo studies on small molecules
NASA Astrophysics Data System (ADS)
Galek, Peter T. A.; Handy, Nicholas C.; Lester, William A., Jr.
The Variational Monte Carlo (VMC) and Fixed-Node Diffusion Monte Carlo (FNDMC) methods have been examined, through studies on small molecules. New programs have been written which implement the (by now) standard algorithms for VMC and FNDMC. We have employed and investigated throughout our studies the accuracy of the common Slater-Jastrow trial wave function. Firstly, we have studied a range of sizes of the Jastrow correlation function of the Boys-Handy form, obtained using our optimization program with analytical derivatives of the central moments in the local energy. Secondly, we have studied the effects of Slater-type orbitals (STOs) that display the exact cusp behaviour at nuclei. The orbitals make up the all important trial determinant, which determines the fixed nodal surface. We report all-electron calculations for the ground state energies of Li2, Be2, H2O, NH3, CH4 and H2CO, in all cases but one with accuracy in excess of 95%. Finally, we report an investigation of the ground state energies, dissociation energies and ionization potentials of NH and NH+. Recent focus paid in the literature to these species allow for an extensive comparison with other ab initio methods. We obtain accurate properties for the species and reveal a favourable tendency for fixed-node and other systematic errors to cancel. As a result of our accurate predictions, we are able to obtain a value for the heat of formation of NH, which agrees to within less than 1 kcal mol-1 to other ab initio techniques and 0.2 kcal mol-1 of the experimental value.
Oborn, B. M.; Metcalfe, P. E.; Butson, M. J.; Rosenfeld, A. B.
2010-10-15
Purpose: The main focus of this work is to continue investigations into the Monte Carlo predicted skin doses seen in MRI-guided radiotherapy. In particular, the authors aim to characterize the 70 {mu}m skin doses over a larger range of magnetic field strength and x-ray field size than in the current literature. The effect of surface orientation on both the entry and exit sides is also studied. Finally, the use of exit bolus is also investigated for minimizing the negative effects of the electron return effect (ERE) on the exit skin dose. Methods: High resolution GEANT4 Monte Carlo simulations of a water phantom exposed to a 6 MV x-ray beam (Varian 2100C) have been performed. Transverse magnetic fields of strengths between 0 and 3 T have been applied to a 30x30x20 cm{sup 3} phantom. This phantom is also altered to have variable entry and exit surfaces with respect to the beam central axis and they range from -75 deg. to +75 deg. The exit bolus simulated is a 1 cm thick (water equivalent) slab located on the beam exit side. Results: On the entry side, significant skin doses at the beam central axis are reported for large positive surface angles and strong magnetic fields. However, over the entry surface angle range of -30 deg. to -60 deg., the entry skin dose is comparable to or less than the zero magnetic field skin dose, regardless of magnetic field strength and field size. On the exit side, moderate to high central axis skin dose increases are expected except at large positive surface angles. For exit bolus of 1 cm thickness, the central axis exit skin dose becomes an almost consistent value regardless of magnetic field strength or exit surface angle. This is due to the almost complete absorption of the ERE electrons by the bolus. Conclusions: There is an ideal entry angle range of -30 deg. to -60 deg. where entry skin dose is comparable to or less than the zero magnetic field skin dose. Other than this, the entry skin dose increases are significant, especially at
Vectorized Monte Carlo methods for reactor lattice analysis
NASA Technical Reports Server (NTRS)
Brown, F. B.
1984-01-01
Some of the new computational methods and equivalent mathematical representations of physics models used in the MCV code, a vectorized continuous-enery Monte Carlo code for use on the CYBER-205 computer are discussed. While the principal application of MCV is the neutronics analysis of repeating reactor lattices, the new methods used in MCV should be generally useful for vectorizing Monte Carlo for other applications. For background, a brief overview of the vector processing features of the CYBER-205 is included, followed by a discussion of the fundamentals of Monte Carlo vectorization. The physics models used in the MCV vectorized Monte Carlo code are then summarized. The new methods used in scattering analysis are presented along with details of several key, highly specialized computational routines. Finally, speedups relative to CDC-7600 scalar Monte Carlo are discussed.
Chen, Jinsong; Hubbard, Susan; Rubin, Yoram; Murray, Christopher J.; Roden, Eric E.; Majer, Ernest L.
2004-12-22
The paper demonstrates the use of ground-penetrating radar (GPR) tomographic data for estimating extractable Fe(II) and Fe(III) concentrations using a Markov chain Monte Carlo (MCMC) approach, based on data collected at the DOE South Oyster Bacterial Transport Site in Virginia. Analysis of multidimensional data including physical, geophysical, geochemical, and hydrogeological measurements collected at the site shows that GPR attenuation and lithofacies are most informative for the estimation. A statistical model is developed for integrating the GPR attenuation and lithofacies data. In the model, lithofacies is considered as a spatially correlated random variable and petrophysical models for linking GPR attenuation to geochemical parameters were derived from data at and near boreholes. Extractable Fe(II) and Fe(III) concentrations at each pixel between boreholes are estimated by conditioning to the co-located GPR data and the lithofacies measurements along boreholes through spatial correlation. Cross-validation results show that geophysical data, constrained by lithofacies, provided information about extractable Fe(II) and Fe(III) concentration in a minimally invasive manner and with a resolution unparalleled by other geochemical characterization methods. The developed model is effective and flexible, and should be applicable for estimating other geochemical parameters at other sites.
An empirical formula based on Monte Carlo simulation for diffuse reflectance from turbid media
NASA Astrophysics Data System (ADS)
Gnanatheepam, Einstein; Aruna, Prakasa Rao; Ganesan, Singaravelu
2016-03-01
Diffuse reflectance spectroscopy has been widely used in diagnostic oncology and characterization of laser irradiated tissue. However, still accurate and simple analytical equation does not exist for estimation of diffuse reflectance from turbid media. In this work, a diffuse reflectance lookup table for a range of tissue optical properties was generated using Monte Carlo simulation. Based on the generated Monte Carlo lookup table, an empirical formula for diffuse reflectance was developed using surface fitting method. The variance between the Monte Carlo lookup table surface and the surface obtained from the proposed empirical formula is less than 1%. The proposed empirical formula may be used for modeling of diffuse reflectance from tissue.
Iterative acceleration methods for Monte Carlo and deterministic criticality calculations
Urbatsch, T.J.
1995-11-01
If you have ever given up on a nuclear criticality calculation and terminated it because it took so long to converge, you might find this thesis of interest. The author develops three methods for improving the fission source convergence in nuclear criticality calculations for physical systems with high dominance ratios for which convergence is slow. The Fission Matrix Acceleration Method and the Fission Diffusion Synthetic Acceleration (FDSA) Method are acceleration methods that speed fission source convergence for both Monte Carlo and deterministic methods. The third method is a hybrid Monte Carlo method that also converges for difficult problems where the unaccelerated Monte Carlo method fails. The author tested the feasibility of all three methods in a test bed consisting of idealized problems. He has successfully accelerated fission source convergence in both deterministic and Monte Carlo criticality calculations. By filtering statistical noise, he has incorporated deterministic attributes into the Monte Carlo calculations in order to speed their source convergence. He has used both the fission matrix and a diffusion approximation to perform unbiased accelerations. The Fission Matrix Acceleration method has been implemented in the production code MCNP and successfully applied to a real problem. When the unaccelerated calculations are unable to converge to the correct solution, they cannot be accelerated in an unbiased fashion. A Hybrid Monte Carlo method weds Monte Carlo and a modified diffusion calculation to overcome these deficiencies. The Hybrid method additionally possesses reduced statistical errors.
Recent advances and future prospects for Monte Carlo
Brown, Forrest B
2010-01-01
The history of Monte Carlo methods is closely linked to that of computers: The first known Monte Carlo program was written in 1947 for the ENIAC; a pre-release of the first Fortran compiler was used for Monte Carlo In 1957; Monte Carlo codes were adapted to vector computers in the 1980s, clusters and parallel computers in the 1990s, and teraflop systems in the 2000s. Recent advances include hierarchical parallelism, combining threaded calculations on multicore processors with message-passing among different nodes. With the advances In computmg, Monte Carlo codes have evolved with new capabilities and new ways of use. Production codes such as MCNP, MVP, MONK, TRIPOLI and SCALE are now 20-30 years old (or more) and are very rich in advanced featUres. The former 'method of last resort' has now become the first choice for many applications. Calculations are now routinely performed on office computers, not just on supercomputers. Current research and development efforts are investigating the use of Monte Carlo methods on FPGAs. GPUs, and many-core processors. Other far-reaching research is exploring ways to adapt Monte Carlo methods to future exaflop systems that may have 1M or more concurrent computational processes.
NASA Astrophysics Data System (ADS)
Galindo, Jose Luis; Huertas, Rafael; Carrasco-Sanz, Ana; Lapresta, Alejandro; Galindo, Jorge; Vasco, Enrique
2016-07-01
The aim of this work is to analyze in more depth a model of particle deposition by characterizing different parameters such as profile density, bonds and perimeter, and substrate coverage, all being involved in the description of deposits as bulk. Thus, this study is an extension of a previous work on non-equilibrium interface-growth systems where two different interface-growth models, called Standard Adherence Rule Model and Potential Adherence Rule Model, were characterized. In this work, bulk characterization is implemented for the complete range of Peclet numbers. The zones of density profile (Near-Wall, Plateau, and Active-Growth) are studied by proposing an adjustment for each of them and determining the full-setting density profile depending on the Peclet number. The density profiles are compared with other one- and two-stage models. Furthermore, an algorithm is proposed to calculate the number of bonds of the particles and the perimeter that a substrate forms over time. Finally, to analyze the coating, its temporal behavior is adjusted to an exponential function by comparing the results with those found for Random Sequential Adsorption models which describe systems like colloidal particles on solid substrates, adsorption of proteins at mineral surfaces, or oxidation of one-dimensional polymer chains.
A radiating shock evaluated using Implicit Monte Carlo Diffusion
Cleveland, M.; Gentile, N.
2013-07-01
Implicit Monte Carlo [1] (IMC) has been shown to be very expensive when used to evaluate a radiation field in opaque media. Implicit Monte Carlo Diffusion (IMD) [2], which evaluates a spatial discretized diffusion equation using a Monte Carlo algorithm, can be used to reduce the cost of evaluating the radiation field in opaque media [2]. This work couples IMD to the hydrodynamics equations to evaluate opaque diffusive radiating shocks. The Lowrie semi-analytic diffusive radiating shock benchmark[a] is used to verify our implementation of the coupled system of equations. (authors)
Variance reduction in Monte Carlo analysis of rarefied gas diffusion.
NASA Technical Reports Server (NTRS)
Perlmutter, M.
1972-01-01
The problem of rarefied diffusion between parallel walls is solved using the Monte Carlo method. The diffusing molecules are evaporated or emitted from one of the two parallel walls and diffuse through another molecular species. The Monte Carlo analysis treats the diffusing molecule as undergoing a Markov random walk, and the local macroscopic properties are found as the expected value of the random variable, the random walk payoff. By biasing the transition probabilities and changing the collision payoffs, the expected Markov walk payoff is retained but its variance is reduced so that the Monte Carlo result has a much smaller error.
Linear Scaling Quantum Monte Carlo Calculations
NASA Astrophysics Data System (ADS)
Williamson, Andrew
2002-03-01
New developments to the quantum Monte Carlo approach are presented that improve the scaling of the time required to calculate the total energy of a configuration of electronic coordinates from N^3 to nearly linear[1]. The first factor of N is achieved by applying a unitary transform to the set of single particle orbitals used to construct the Slater determinant, creating a set of maximally localized Wannier orbitals. These localized functions are then truncated beyond a given cutoff radius to introduce sparsity into the Slater determinant. The second factor of N is achieved by evaluating the maximally localized Wannier orbitals on a cubic spline grid, which removes the size dependence of the basis set (e.g. plane waves, Gaussians) typically used to expand the orbitals. Application of this method to the calculation of the binding energy of carbon fullerenes and silicon nanostructures will be presented. An extension of the approach to deal with excited states of systems will also be presented in the context of the calculation of the excitonic gap of a variety of systems. This work was performed under the auspices of the U.S. Dept. of Energy at the University of California/LLNL under contract no. W-7405-Eng-48. [1] A.J. Williamson, R.Q. Hood and J.C. Grossman, Phys. Rev. Lett. 87 246406 (2001)
Computing Entanglement Entropy in Quantum Monte Carlo
NASA Astrophysics Data System (ADS)
Melko, Roger
2012-02-01
The scaling of entanglement entropy in quantum many-body wavefunctions is expected to be a fruitful resource for studying quantum phases and phase transitions in condensed matter. However, until the recent development of estimators for Renyi entropy in quantum Monte Carlo (QMC), we have been in the dark about the behaviour of entanglement in all but the simplest two-dimensional models. In this talk, I will outline the measurement techniques that allow access to the Renyi entropies in several different QMC methodologies. I will then discuss recent simulation results demonstrating the richness of entanglement scaling in 2D, including: the prevalence of the ``area law''; topological entanglement entropy in a gapped spin liquid; anomalous subleading logarithmic terms due to Goldstone modes; universal scaling at critical points; and examples of emergent conformal-like scaling in several gapless wavefunctions. Finally, I will explore the idea that ``long range entanglement'' may complement the notion of ``long range order'' for quantum phases and phase transitions which lack a conventional order parameter description.
Error modes in implicit Monte Carlo
Martin, William Russell,; Brown, F. B.
2001-01-01
The Implicit Monte Carlo (IMC) method of Fleck and Cummings [1] has been used for years to analyze radiative transfer problems, such as those encountered in stellar atmospheres or inertial confinement fusion. Larsen and Mercier [2] have shown that the IMC method violates a maximum principle that is satisfied by the exact solution to the radiative transfer equation. Except for [2] and related papers regarding the maximum principle, there have been no other published results regarding the analysis of errors or convergence properties for the IMC method. This work presents an exact error analysis for the IMC method by using the analytical solutions for infinite medium geometry (0-D) to determine closed form expressions for the errors. The goal is to gain insight regarding the errors inherent in the IMC method by relating the exact 0-D errors to multi-dimensional geometry. Additional work (not described herein) has shown that adding a leakage term (i.e., a 'buckling' term) to the 0-D equations has relatively little effect on the IMC errors analyzed in this paper, so that the 0-D errors should provide useful guidance for the errors observed in multi-dimensional simulations.
Improved method for implicit Monte Carlo
Brown, F. B.; Martin, W. R.
2001-01-01
The Implicit Monte Carlo (IMC) method has been used for over 30 years to analyze radiative transfer problems, such as those encountered in stellar atmospheres or inertial confinement fusion. Reference [2] provided an exact error analysis of IMC for 0-D problems and demonstrated that IMC can exhibit substantial errors when timesteps are large. These temporal errors are inherent in the method and are in addition to spatial discretization errors and approximations that address nonlinearities (due to variation of physical constants). In Reference [3], IMC and four other methods were analyzed in detail and compared on both theoretical grounds and the accuracy of numerical tests. As discussed in, two alternative schemes for solving the radiative transfer equations, the Carter-Forest (C-F) method and the Ahrens-Larsen (A-L) method, do not exhibit the errors found in IMC; for 0-D, both of these methods are exact for all time, while for 3-D, A-L is exact for all time and C-F is exact within a timestep. These methods can yield substantially superior results to IMC.
Monte Carlo Production Management at CMS
NASA Astrophysics Data System (ADS)
Boudoul, G.; Franzoni, G.; Norkus, A.; Pol, A.; Srimanobhas, P.; Vlimant, J.-R.
2015-12-01
The analysis of the LHC data at the Compact Muon Solenoid (CMS) experiment requires the production of a large number of simulated events. During the RunI of LHC (20102012), CMS has produced over 12 Billion simulated events, organized in approximately sixty different campaigns each emulating specific detector conditions and LHC running conditions (pile up). In order to aggregate the information needed for the configuration and prioritization of the events production, assure the book-keeping of all the processing requests placed by the physics analysis groups, and to interface with the CMS production infrastructure, the web- based service Monte Carlo Management (McM) has been developed and put in production in 2013. McM is based on recent server infrastructure technology (CherryPy + AngularJS) and relies on a CouchDB database back-end. This contribution covers the one and half year of operational experience managing samples of simulated events for CMS, the evolution of its functionalities and the extension of its capability to monitor the status and advancement of the events production.
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
Finding Planet Nine: a Monte Carlo approach
NASA Astrophysics Data System (ADS)
de la Fuente Marcos, C.; de la Fuente Marcos, R.
2016-06-01
Planet Nine is a hypothetical planet located well beyond Pluto that has been proposed in an attempt to explain the observed clustering in physical space of the perihelia of six extreme trans-Neptunian objects or ETNOs. The predicted approximate values of its orbital elements include a semimajor axis of 700 au, an eccentricity of 0.6, an inclination of 30°, and an argument of perihelion of 150°. Searching for this putative planet is already under way. Here, we use a Monte Carlo approach to create a synthetic population of Planet Nine orbits and study its visibility statistically in terms of various parameters and focusing on the aphelion configuration. Our analysis shows that, if Planet Nine exists and is at aphelion, it might be found projected against one out of the four specific areas in the sky. Each area is linked to a particular value of the longitude of the ascending node and two of them are compatible with an apsidal anti-alignment scenario. In addition and after studying the current statistics of ETNOs, a cautionary note on the robustness of the perihelia clustering is presented.
Accelerated Monte Carlo Methods for Coulomb Collisions
NASA Astrophysics Data System (ADS)
Rosin, Mark; Ricketson, Lee; Dimits, Andris; Caflisch, Russel; Cohen, Bruce
2014-03-01
We present a new highly efficient multi-level Monte Carlo (MLMC) simulation algorithm for Coulomb collisions in a plasma. The scheme, initially developed and used successfully for applications in financial mathematics, is applied here to kinetic plasmas for the first time. The method is based on a Langevin treatment of the Landau-Fokker-Planck equation and has a rich history derived from the works of Einstein and Chandrasekhar. The MLMC scheme successfully reduces the computational cost of achieving an RMS error ɛ in the numerical solution to collisional plasma problems from (ɛ-3) - for the standard state-of-the-art Langevin and binary collision algorithms - to a theoretically optimal (ɛ-2) scaling, when used in conjunction with an underlying Milstein discretization to the Langevin equation. In the test case presented here, the method accelerates simulations by factors of up to 100. We summarize the scheme, present some tricks for improving its efficiency yet further, and discuss the method's range of applicability. Work performed for US DOE by LLNL under contract DE-AC52- 07NA27344 and by UCLA under grant DE-FG02-05ER25710.
Monte Carlo Simulation of Critical Casimir Forces
NASA Astrophysics Data System (ADS)
Vasilyev, Oleg A.
2015-03-01
In the vicinity of the second order phase transition point long-range critical fluctuations of the order parameter appear. The second order phase transition in a critical binary mixture in the vicinity of the demixing point belongs to the universality class of the Ising model. The superfluid transition in liquid He belongs to the universality class of the XY model. The confinement of long-range fluctuations causes critical Casimir forces acting on confining surfaces or particles immersed in the critical substance. Last decade critical Casimir forces in binary mixtures and liquid helium were studied experimentally. The critical Casimir force in a film of a given thickness scales as a universal scaling function of the ratio of the film thickness to the bulk correlation length divided over the cube of the film thickness. Using Monte Carlo simulations we can compute critical Casimir forces and their scaling functions for lattice Ising and XY models which correspond to experimental results for the binary mixture and liquid helium, respectively. This chapter provides the description of numerical methods for computation of critical Casimir interactions for lattice models for plane-plane, plane-particle, and particle-particle geometries.
Commensurabilities between ETNOs: a Monte Carlo survey
NASA Astrophysics Data System (ADS)
de la Fuente Marcos, C.; de la Fuente Marcos, R.
2016-04-01
Many asteroids in the main and trans-Neptunian belts are trapped in mean motion resonances with Jupiter and Neptune, respectively. As a side effect, they experience accidental commensurabilities among themselves. These commensurabilities define characteristic patterns that can be used to trace the source of the observed resonant behaviour. Here, we explore systematically the existence of commensurabilities between the known ETNOs using their heliocentric and barycentric semimajor axes, their uncertainties, and Monte Carlo techniques. We find that the commensurability patterns present in the known ETNO population resemble those found in the main and trans-Neptunian belts. Although based on small number statistics, such patterns can only be properly explained if most, if not all, of the known ETNOs are subjected to the resonant gravitational perturbations of yet undetected trans-Plutonian planets. We show explicitly that some of the statistically significant commensurabilities are compatible with the Planet Nine hypothesis; in particular, a number of objects may be trapped in the 5:3 and 3:1 mean motion resonances with a putative Planet Nine with semimajor axis ˜700 au.
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.
Extending canonical Monte Carlo methods: II
NASA Astrophysics Data System (ADS)
Velazquez, L.; Curilef, S.
2010-04-01
We have previously presented a methodology for extending canonical Monte Carlo methods inspired by a suitable extension of the canonical fluctuation relation C = β2langδE2rang compatible with negative heat capacities, C < 0. Now, we improve this methodology by including the finite size effects that reduce the precision of a direct determination of the microcanonical caloric curve β(E) = ∂S(E)/∂E, as well as by carrying out a better implementation of the MC schemes. We show that, despite the modifications considered, the extended canonical MC methods lead to an impressive overcoming of the so-called supercritical slowing down observed close to the region of the temperature driven first-order phase transition. In this case, the size dependence of the decorrelation time τ is reduced from an exponential growth to a weak power-law behavior, \\tau (N)\\propto N^{\\alpha } , as is shown in the particular case of the 2D seven-state Potts model where the exponent α = 0.14-0.18.
Commensurabilities between ETNOs: a Monte Carlo survey
NASA Astrophysics Data System (ADS)
de la Fuente Marcos, C.; de la Fuente Marcos, R.
2016-07-01
Many asteroids in the main and trans-Neptunian belts are trapped in mean motion resonances with Jupiter and Neptune, respectively. As a side effect, they experience accidental commensurabilities among themselves. These commensurabilities define characteristic patterns that can be used to trace the source of the observed resonant behaviour. Here, we explore systematically the existence of commensurabilities between the known ETNOs using their heliocentric and barycentric semimajor axes, their uncertainties, and Monte Carlo techniques. We find that the commensurability patterns present in the known ETNO population resemble those found in the main and trans-Neptunian belts. Although based on small number statistics, such patterns can only be properly explained if most, if not all, of the known ETNOs are subjected to the resonant gravitational perturbations of yet undetected trans-Plutonian planets. We show explicitly that some of the statistically significant commensurabilities are compatible with the Planet Nine hypothesis; in particular, a number of objects may be trapped in the 5:3 and 3:1 mean motion resonances with a putative Planet Nine with semimajor axis ˜700 au.
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.
Monte Carlo simulation of chromatin stretching.
Aumann, Frank; Lankas, Filip; Caudron, Maïwen; Langowski, Jörg
2006-04-01
We present Monte Carlo (MC) simulations of the stretching of a single chromatin fiber. The model approximates the DNA by a flexible polymer chain with Debye-Hückel electrostatics and uses a two-angle zigzag model for the geometry of the linker DNA connecting the nucleosomes. The latter are represented by flat disks interacting via an attractive Gay-Berne potential. Our results show that the stiffness of the chromatin fiber strongly depends on the linker DNA length. Furthermore, changing the twisting angle between nucleosomes from 90 degrees to 130 degrees increases the stiffness significantly. An increase in the opening angle from 22 degrees to 34 degrees leads to softer fibers for small linker lengths. We observe that fibers containing a linker histone at each nucleosome are stiffer compared to those without the linker histone. The simulated persistence lengths and elastic moduli agree with experimental data. Finally, we show that the chromatin fiber does not behave as an isotropic elastic rod, but its rigidity depends on the direction of deformation: Chromatin is much more resistant to stretching than to bending. PMID:16711856
Monte Carlo simulation of chromatin stretching
NASA Astrophysics Data System (ADS)
Aumann, Frank; Lankas, Filip; Caudron, Maïwen; Langowski, Jörg
2006-04-01
We present Monte Carlo (MC) simulations of the stretching of a single 30nm chromatin fiber. The model approximates the DNA by a flexible polymer chain with Debye-Hückel electrostatics and uses a two-angle zigzag model for the geometry of the linker DNA connecting the nucleosomes. The latter are represented by flat disks interacting via an attractive Gay-Berne potential. Our results show that the stiffness of the chromatin fiber strongly depends on the linker DNA length. Furthermore, changing the twisting angle between nucleosomes from 90° to 130° increases the stiffness significantly. An increase in the opening angle from 22° to 34° leads to softer fibers for small linker lengths. We observe that fibers containing a linker histone at each nucleosome are stiffer compared to those without the linker histone. The simulated persistence lengths and elastic moduli agree with experimental data. Finally, we show that the chromatin fiber does not behave as an isotropic elastic rod, but its rigidity depends on the direction of deformation: Chromatin is much more resistant to stretching than to bending.
Ghiasi, Hosein
2013-01-01
Aim The aim of this work was to map the characteristics of (n,γ) and (γ,n) reactions in a high energy photon radiation therapy. Background Photoneutrons produced in the high energy X-Ray radiation therapy may damage patients and staff. It is due to high RBE of the produced neutrons according to their energy and isotropic emission. Characterization of the photoneutrons can help us in appropriate shielding. Materials and methods This study focused on the photoneutron and capture gamma ray phenomena. Characteristics such as dose value, fluence and spectra of both the neutrons and the by produced prompt gamma ray were described. Results and discussion Neutron and prompt gamma spectra in different points showed the neutrons to be thermalized when increasing the distance from the linac. Energy of the neutrons changed from about 0.6 MeV at the isocentre to around 10−08 MeV at the outer door position. Although the neutrons were found as fast neutrons, their spectra showed they were thermal neutrons at the outer door position. Additionally, it was seen that the energy of the gamma rays is higher than the scattered X-ray energy. The energy of gamma rays was seen to be up to 10 MeV while the linac photons had energy lower than 1 MeV. Neutron source strength obtained in this work was in good agreement with the published data, which may be a confirmation of our simulation accuracy. Conclusion The study showed that the Monte Carlo simulation can be applied in the radiotherapy and industrial radiation works as a useful and precise estimator. We also concluded that the dose from the prompt gamma ray at the outer door location is higher than the scattered radiation from the linac and should be considered in the shielding. PMID:24936317
Balmer, Jennifer A; Mykhaylyk, Oleksandr O; Schmid, Andreas; Armes, Steven P; Fairclough, J Patrick A; Ryan, Anthony J
2011-07-01
A two-population model based on standard small-angle X-ray scattering (SAXS) equations is verified for the analysis of core-shell structures comprising spherical colloidal particles with particulate shells. First, Monte Carlo simulations of core-shell structures are performed to demonstrate the applicability of the model. Three possible shell packings are considered: ordered silica shells due to either charge-dependent repulsive or size-dependent Lennard-Jones interactions or randomly arranged silica particles. In most cases, the two-population model produces an excellent fit to calculated SAXS patterns for the simulated core-shell structures, together with a good correlation between the fitting parameters and structural parameters used for the simulation. The limits of application are discussed, and then, this two-population model is applied to the analysis of well-defined core-shell vinyl polymer/silica nanocomposite particles, where the shell comprises a monolayer of spherical silica nanoparticles. Comprehensive SAXS analysis of a series of poly(styrene-co-n-butyl acrylate)/silica colloidal nanocomposite particles (prepared by the in situ emulsion copolymerization of styrene and n-butyl acrylate in the presence of a glycerol-functionalized silica sol) allows the overall core-shell particle diameter, the copolymer latex core diameter and polydispersity, the mean silica shell thickness, the mean silica diameter and polydispersity, the volume fractions of the two components, the silica packing density, and the silica shell structure to be obtained. These experimental SAXS results are consistent with electron microscopy, dynamic light scattering, thermogravimetry, helium pycnometry, and BET surface area studies. The high electron density contrast between the (co)polymer and the silica components, together with the relatively low polydispersity of these core-shell nanocomposite particles, makes SAXS ideally suited for the characterization of this system. Moreover
Properties of reactive oxygen species by quantum Monte Carlo
Zen, Andrea; Trout, Bernhardt L.; Guidoni, Leonardo
2014-07-07
The electronic properties of the oxygen molecule, in its singlet and triplet states, and of many small oxygen-containing radicals and anions have important roles in different fields of chemistry, biology, and atmospheric science. Nevertheless, the electronic structure of such species is a challenge for ab initio computational approaches because of the difficulties to correctly describe the statical and dynamical correlation effects in presence of one or more unpaired electrons. Only the highest-level quantum chemical approaches can yield reliable characterizations of their molecular properties, such as binding energies, equilibrium structures, molecular vibrations, charge distribution, and polarizabilities. In this work we use the variational Monte Carlo (VMC) and the lattice regularized Monte Carlo (LRDMC) methods to investigate the equilibrium geometries and molecular properties of oxygen and oxygen reactive species. Quantum Monte Carlo methods are used in combination with the Jastrow Antisymmetrized Geminal Power (JAGP) wave function ansatz, which has been recently shown to effectively describe the statical and dynamical correlation of different molecular systems. In particular, we have studied the oxygen molecule, the superoxide anion, the nitric oxide radical and anion, the hydroxyl and hydroperoxyl radicals and their corresponding anions, and the hydrotrioxyl radical. Overall, the methodology was able to correctly describe the geometrical and electronic properties of these systems, through compact but fully-optimised basis sets and with a computational cost which scales as N{sup 3} − N{sup 4}, where N is the number of electrons. This work is therefore opening the way to the accurate study of the energetics and of the reactivity of large and complex oxygen species by first principles.
Properties of reactive oxygen species by quantum Monte Carlo.
Zen, Andrea; Trout, Bernhardt L; Guidoni, Leonardo
2014-07-01
The electronic properties of the oxygen molecule, in its singlet and triplet states, and of many small oxygen-containing radicals and anions have important roles in different fields of chemistry, biology, and atmospheric science. Nevertheless, the electronic structure of such species is a challenge for ab initio computational approaches because of the difficulties to correctly describe the statical and dynamical correlation effects in presence of one or more unpaired electrons. Only the highest-level quantum chemical approaches can yield reliable characterizations of their molecular properties, such as binding energies, equilibrium structures, molecular vibrations, charge distribution, and polarizabilities. In this work we use the variational Monte Carlo (VMC) and the lattice regularized Monte Carlo (LRDMC) methods to investigate the equilibrium geometries and molecular properties of oxygen and oxygen reactive species. Quantum Monte Carlo methods are used in combination with the Jastrow Antisymmetrized Geminal Power (JAGP) wave function ansatz, which has been recently shown to effectively describe the statical and dynamical correlation of different molecular systems. In particular, we have studied the oxygen molecule, the superoxide anion, the nitric oxide radical and anion, the hydroxyl and hydroperoxyl radicals and their corresponding anions, and the hydrotrioxyl radical. Overall, the methodology was able to correctly describe the geometrical and electronic properties of these systems, through compact but fully-optimised basis sets and with a computational cost which scales as N(3) - N(4), where N is the number of electrons. This work is therefore opening the way to the accurate study of the energetics and of the reactivity of large and complex oxygen species by first principles. PMID:25005287
Properties of reactive oxygen species by quantum Monte Carlo
NASA Astrophysics Data System (ADS)
Zen, Andrea; Trout, Bernhardt L.; Guidoni, Leonardo
2014-07-01
The electronic properties of the oxygen molecule, in its singlet and triplet states, and of many small oxygen-containing radicals and anions have important roles in different fields of chemistry, biology, and atmospheric science. Nevertheless, the electronic structure of such species is a challenge for ab initio computational approaches because of the difficulties to correctly describe the statical and dynamical correlation effects in presence of one or more unpaired electrons. Only the highest-level quantum chemical approaches can yield reliable characterizations of their molecular properties, such as binding energies, equilibrium structures, molecular vibrations, charge distribution, and polarizabilities. In this work we use the variational Monte Carlo (VMC) and the lattice regularized Monte Carlo (LRDMC) methods to investigate the equilibrium geometries and molecular properties of oxygen and oxygen reactive species. Quantum Monte Carlo methods are used in combination with the Jastrow Antisymmetrized Geminal Power (JAGP) wave function ansatz, which has been recently shown to effectively describe the statical and dynamical correlation of different molecular systems. In particular, we have studied the oxygen molecule, the superoxide anion, the nitric oxide radical and anion, the hydroxyl and hydroperoxyl radicals and their corresponding anions, and the hydrotrioxyl radical. Overall, the methodology was able to correctly describe the geometrical and electronic properties of these systems, through compact but fully-optimised basis sets and with a computational cost which scales as N3 - N4, where N is the number of electrons. This work is therefore opening the way to the accurate study of the energetics and of the reactivity of large and complex oxygen species by first principles.
Monte Carlo variance reduction approaches for non-Boltzmann tallies
Booth, T.E.
1992-12-01
Quantities that depend on the collective effects of groups of particles cannot be obtained from the standard Boltzmann transport equation. Monte Carlo estimates of these quantities are called non-Boltzmann tallies and have become increasingly important recently. Standard Monte Carlo variance reduction techniques were designed for tallies based on individual particles rather than groups of particles. Experience with non-Boltzmann tallies and analog Monte Carlo has demonstrated the severe limitations of analog Monte Carlo for many non-Boltzmann tallies. In fact, many calculations absolutely require variance reduction methods to achieve practical computation times. Three different approaches to variance reduction for non-Boltzmann tallies are described and shown to be unbiased. The advantages and disadvantages of each of the approaches are discussed.
COMPARISON OF MONTE CARLO METHODS FOR NONLINEAR RADIATION TRANSPORT
W. R. MARTIN; F. B. BROWN
2001-03-01
Five Monte Carlo methods for solving the nonlinear thermal radiation transport equations are compared. The methods include the well-known Implicit Monte Carlo method (IMC) developed by Fleck and Cummings, an alternative to IMC developed by Carter and Forest, an ''exact'' method recently developed by Ahrens and Larsen, and two methods recently proposed by Martin and Brown. The five Monte Carlo methods are developed and applied to the radiation transport equation in a medium assuming local thermodynamic equilibrium. Conservation of energy is derived and used to define appropriate material energy update equations for each of the methods. Details of the Monte Carlo implementation are presented, both for the random walk simulation and the material energy update. Simulation results for all five methods are obtained for two infinite medium test problems and a 1-D test problem, all of which have analytical solutions. Conclusions regarding the relative merits of the various schemes are presented.
OBJECT KINETIC MONTE CARLO SIMULATIONS OF CASCADE ANNEALING IN TUNGSTEN
Nandipati, Giridhar; Setyawan, Wahyu; Heinisch, Howard L.; Roche, Kenneth J.; Kurtz, Richard J.; Wirth, Brian D.
2014-03-31
The objective of this work is to study the annealing of primary cascade damage created by primary knock-on atoms (PKAs) of various energies, at various temperatures in bulk tungsten using the object kinetic Monte Carlo (OKMC) method.
Monte Carlo techniques for analyzing deep penetration problems
Cramer, S.N.; Gonnord, J.; Hendricks, J.S.
1985-01-01
A review of current methods and difficulties in Monte Carlo deep-penetration calculations is presented. Statistical uncertainty is discussed, and recent adjoint optimization of splitting, Russian roulette, and exponential transformation biasing is reviewed. 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 multi-group 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. 29 refs.
Enhancements in Continuous-Energy Monte Carlo Capabilities in SCALE
Bekar, Kursat B; Celik, Cihangir; Wiarda, Dorothea; Peplow, Douglas E.; Rearden, Bradley T; Dunn, Michael E
2013-01-01
Monte Carlo tools in SCALE are commonly used in criticality safety calculations as well as sensitivity and uncertainty analysis, depletion, and criticality alarm system analyses. Recent improvements in the continuous-energy data generated by the AMPX code system and significant advancements in the continuous-energy treatment in the KENO Monte Carlo eigenvalue codes facilitate the use of SCALE Monte Carlo codes to model geometrically complex systems with enhanced solution fidelity. The addition of continuous-energy treatment to the SCALE Monaco code, which can be used with automatic variance reduction in the hybrid MAVRIC sequence, provides significant enhancements, especially for criticality alarm system modeling. This paper describes some of the advancements in continuous-energy Monte Carlo codes within the SCALE code system.
DETERMINING UNCERTAINTY IN PHYSICAL PARAMETER MEASUREMENTS BY MONTE CARLO SIMULATION
A statistical approach, often called Monte Carlo Simulation, has been used to examine propagation of error with measurement of several parameters important in predicting environmental transport of chemicals. These parameters are vapor pressure, water solubility, octanol-water par...
Combinatorial geometry domain decomposition strategies for Monte Carlo simulations
Li, G.; Zhang, B.; Deng, L.; Mo, Z.; Liu, Z.; Shangguan, D.; Ma, Y.; Li, S.; Hu, Z.
2013-07-01
Analysis and modeling of nuclear reactors can lead to memory overload for a single core processor when it comes to refined modeling. A method to solve this problem is called 'domain decomposition'. In the current work, domain decomposition algorithms for a combinatorial geometry Monte Carlo transport code are developed on the JCOGIN (J Combinatorial Geometry Monte Carlo transport INfrastructure). Tree-based decomposition and asynchronous communication of particle information between domains are described in the paper. Combination of domain decomposition and domain replication (particle parallelism) is demonstrated and compared with that of MERCURY code. A full-core reactor model is simulated to verify the domain decomposition algorithms using the Monte Carlo particle transport code JMCT (J Monte Carlo Transport Code), which has being developed on the JCOGIN infrastructure. Besides, influences of the domain decomposition algorithms to tally variances are discussed. (authors)
Radiation source modeling for Monte Carlo based treatment planning systems
NASA Astrophysics Data System (ADS)
Garnica Garza, Hector Mauricio
prediction of the equation above. Since we do not know what the total fluence per monitor unit is striking the detector, we use two screen-film systems, with different quantum absorption efficiencies to determine the a parameter. The detectors used are a 1mm copper plate attached to a Lanex Regular Gd2O 2S screen and a 1mm Aluminum plate attached to the same type of screen. These two detectors were characterized by means of Monte Carlo simulation.
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 methods and applications in nuclear physics
Carlson, J.
1990-01-01
Monte Carlo methods for studying few- and many-body quantum systems are introduced, with special emphasis given to their applications in nuclear physics. Variational and Green's function Monte Carlo methods are presented in some detail. The status of calculations of light nuclei is reviewed, including discussions of the three-nucleon-interaction, charge and magnetic form factors, the coulomb sum rule, and studies of low-energy radiative transitions. 58 refs., 12 figs.
Shift: A Massively Parallel Monte Carlo Radiation Transport Package
Pandya, Tara M; Johnson, Seth R; Davidson, Gregory G; Evans, Thomas M; Hamilton, Steven P
2015-01-01
This paper discusses the massively-parallel Monte Carlo radiation transport package, Shift, developed at Oak Ridge National Laboratory. It reviews the capabilities, implementation, and parallel performance of this code package. Scaling results demonstrate very good strong and weak scaling behavior of the implemented algorithms. Benchmark results from various reactor problems show that Shift results compare well to other contemporary Monte Carlo codes and experimental results.
Study of the Transition Flow Regime using Monte Carlo Methods
NASA Technical Reports Server (NTRS)
Hassan, H. A.
1999-01-01
This NASA Cooperative Agreement presents a study of the Transition Flow Regime Using Monte Carlo Methods. The topics included in this final report are: 1) New Direct Simulation Monte Carlo (DSMC) procedures; 2) The DS3W and DS2A Programs; 3) Papers presented; 4) Miscellaneous Applications and Program Modifications; 5) Solution of Transitional Wake Flows at Mach 10; and 6) Turbulence Modeling of Shock-Dominated Fows with a k-Enstrophy Formulation.
Development of Monte Carlo Capability for Orion Parachute Simulations
NASA Technical Reports Server (NTRS)
Moore, James W.
2011-01-01
Parachute test programs employ Monte Carlo simulation techniques to plan testing and make critical decisions related to parachute loads, rate-of-descent, or other parameters. This paper describes the development and use of a MATLAB-based Monte Carlo tool for three parachute drop test simulations currently used by NASA. The Decelerator System Simulation (DSS) is a legacy 6 Degree-of-Freedom (DOF) simulation used to predict parachute loads and descent trajectories. The Decelerator System Simulation Application (DSSA) is a 6-DOF simulation that is well suited for modeling aircraft extraction and descent of pallet-like test vehicles. The Drop Test Vehicle Simulation (DTVSim) is a 2-DOF trajectory simulation that is convenient for quick turn-around analysis tasks. These three tools have significantly different software architectures and do not share common input files or output data structures. Separate Monte Carlo tools were initially developed for each simulation. A recently-developed simulation output structure enables the use of the more sophisticated DSSA Monte Carlo tool with any of the core-simulations. The task of configuring the inputs for the nominal simulation is left to the existing tools. Once the nominal simulation is configured, the Monte Carlo tool perturbs the input set according to dispersion rules created by the analyst. These rules define the statistical distribution and parameters to be applied to each simulation input. Individual dispersed parameters are combined to create a dispersed set of simulation inputs. The Monte Carlo tool repeatedly executes the core-simulation with the dispersed inputs and stores the results for analysis. The analyst may define conditions on one or more output parameters at which to collect data slices. The tool provides a versatile interface for reviewing output of large Monte Carlo data sets while preserving the capability for detailed examination of individual dispersed trajectories. The Monte Carlo tool described in
Monte Carlo Hybrid Applied to Binary Stochastic Mixtures
Energy Science and Technology Software Center (ESTSC)
2008-08-11
The purpose of this set of codes isto use an inexpensive, approximate deterministic flux distribution to generate weight windows, wihich will then be used to bound particle weights for the Monte Carlo code run. The process is not automated; the user must run the deterministic code and use the output file as a command-line argument for the Monte Carlo code. Two sets of text input files are included as test problems/templates.
DPEMC: A Monte Carlo for double diffraction
NASA Astrophysics Data System (ADS)
Boonekamp, M.; Kúcs, T.
2005-05-01
We extend the POMWIG Monte Carlo generator developed by B. Cox and J. Forshaw, to include new models of central production through inclusive and exclusive double Pomeron exchange in proton-proton collisions. Double photon exchange processes are described as well, both in proton-proton and heavy-ion collisions. In all contexts, various models have been implemented, allowing for comparisons and uncertainty evaluation and enabling detailed experimental simulations. Program summaryTitle of the program:DPEMC, version 2.4 Catalogue identifier: ADVF Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADVF Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Computer: any computer with the FORTRAN 77 compiler under the UNIX or Linux operating systems Operating system: UNIX; Linux Programming language used: FORTRAN 77 High speed storage required:<25 MB No. of lines in distributed program, including test data, etc.: 71 399 No. of bytes in distributed program, including test data, etc.: 639 950 Distribution format: tar.gz Nature of the physical problem: Proton diffraction at hadron colliders can manifest itself in many forms, and a variety of models exist that attempt to describe it [A. Bialas, P.V. Landshoff, Phys. Lett. B 256 (1991) 540; A. Bialas, W. Szeremeta, Phys. Lett. B 296 (1992) 191; A. Bialas, R.A. Janik, Z. Phys. C 62 (1994) 487; M. Boonekamp, R. Peschanski, C. Royon, Phys. Rev. Lett. 87 (2001) 251806; Nucl. Phys. B 669 (2003) 277; R. Enberg, G. Ingelman, A. Kissavos, N. Timneanu, Phys. Rev. Lett. 89 (2002) 081801; R. Enberg, G. Ingelman, L. Motyka, Phys. Lett. B 524 (2002) 273; R. Enberg, G. Ingelman, N. Timneanu, Phys. Rev. D 67 (2003) 011301; B. Cox, J. Forshaw, Comput. Phys. Comm. 144 (2002) 104; B. Cox, J. Forshaw, B. Heinemann, Phys. Lett. B 540 (2002) 26; V. Khoze, A. Martin, M. Ryskin, Phys. Lett. B 401 (1997) 330; Eur. Phys. J. C 14 (2000) 525; Eur. Phys. J. C 19 (2001) 477; Erratum, Eur. Phys. J. C 20 (2001) 599; Eur
Extending Diffusion Monte Carlo to Internal Coordinates
NASA Astrophysics Data System (ADS)
Petit, Andrew S.; McCoy, Anne B.
2013-06-01
Diffusion Monte Carlo (DMC) is a powerful technique for studying the properties of molecules and clusters that undergo large-amplitude, zero-point vibrational motions. However, the overall applicability of the method is limited by the need to work in Cartesian coordinates and therefore have available a full-dimensional potential energy surface (PES). As a result, the development of a reduced-dimensional DMC methodology has the potential to significantly extend the range of problems that DMC can address by allowing the calculations to be performed in the subset of coordinates that is physically relevant to the questions being asked, thereby eliminating the need for a full-dimensional PES. As a first step towards this goal, we describe here an internal coordinate extension of DMC that places no constraints on the choice of internal coordinates other than requiring them all to be independent. Using H_3^+ and its isotopologues as model systems, we demonstrate that the methodology is capable of successfully describing the ground state properties of highly fluxional molecules as well as, in conjunction with the fixed-node approximation, the ν=1 vibrationally excited states. The calculations of the fundamentals of H_3^+ and its isotopologues provided general insights into the properties of the nodal surfaces of vibrationally excited states. Specifically, we will demonstrate that analysis of ground state probability distributions can point to the set of coordinates that are less strongly coupled and therefore more suitable for use as nodal coordinates in the fixed-node approximation. In particular, we show that nodal surfaces defined in terms of the curvilinear normal mode coordinates are reasonable for the fundamentals of H_2D^+ and D_2H^+ despite both molecules being highly fluxional.
Lattice Monte Carlo simulations of polymer melts
NASA Astrophysics Data System (ADS)
Hsu, Hsiao-Ping
2014-12-01
We use Monte Carlo simulations to study polymer melts consisting of fully flexible and moderately stiff chains in the bond fluctuation model at a volume fraction 0.5. In order to reduce the local density fluctuations, we test a pre-packing process for the preparation of the initial configurations of the polymer melts, before the excluded volume interaction is switched on completely. This process leads to a significantly faster decrease of the number of overlapping monomers on the lattice. This is useful for simulating very large systems, where the statistical properties of the model with a marginally incomplete elimination of excluded volume violations are the same as those of the model with strictly excluded volume. We find that the internal mean square end-to-end distance for moderately stiff chains in a melt can be very well described by a freely rotating chain model with a precise estimate of the bond-bond orientational correlation between two successive bond vectors in equilibrium. The plot of the probability distributions of the reduced end-to-end distance of chains of different stiffness also shows that the data collapse is excellent and described very well by the Gaussian distribution for ideal chains. However, while our results confirm the systematic deviations between Gaussian statistics for the chain structure factor Sc(q) [minimum in the Kratky-plot] found by Wittmer et al. [EPL 77, 56003 (2007)] for fully flexible chains in a melt, we show that for the available chain length these deviations are no longer visible, when the chain stiffness is included. The mean square bond length and the compressibility estimated from collective structure factors depend slightly on the stiffness of the chains.
Monte-Carlo simulation of Callisto's exosphere
NASA Astrophysics Data System (ADS)
Vorburger, A.; Wurz, P.; Lammer, H.; Barabash, S.; Mousis, O.
2015-12-01
We model Callisto's exosphere based on its ice as well as non-ice surface via the use of a Monte-Carlo exosphere model. For the ice component we implement two putative compositions that have been computed from two possible extreme formation scenarios of the satellite. One composition represents the oxidizing state and is based on the assumption that the building blocks of Callisto were formed in the protosolar nebula and the other represents the reducing state of the gas, based on the assumption that the satellite accreted from solids condensed in the jovian sub-nebula. For the non-ice component we implemented the compositions of typical CI as well as L type chondrites. Both chondrite types have been suggested to represent Callisto's non-ice composition best. As release processes we consider surface sublimation, ion sputtering and photon-stimulated desorption. Particles are followed on their individual trajectories until they either escape Callisto's gravitational attraction, return to the surface, are ionized, or are fragmented. Our density profiles show that whereas the sublimated species dominate close to the surface on the sun-lit side, their density profiles (with the exception of H and H2) decrease much more rapidly than the sputtered particles. The Neutral gas and Ion Mass (NIM) spectrometer, which is part of the Particle Environment Package (PEP), will investigate Callisto's exosphere during the JUICE mission. Our simulations show that NIM will be able to detect sublimated and sputtered particles from both the ice and non-ice surface. NIM's measured chemical composition will allow us to distinguish between different formation scenarios.
Quantum Monte Carlo calculations on positronium compounds
NASA Astrophysics Data System (ADS)
Jiang, Nan
The stability of compounds containing one or more positrons in addition to electrons and nuclei has been the focus of extensive scientific investigations. Interest in these compounds stems from the important role they play in the process of positron annihilation, which has become a useful technique in material science studies. Knowledge of these compounds comes mostly from calculations which are presently less difficult than laboratory experiments. Owing to the small binding energies of these compounds, quantum chemistry methods beyond the molecular orbital approximation must be used. Among them, the quantum Monte Carlo (QMC) method is most appealing because it is easy to implement, gives exact results within the fixed nodes approximation, and makes good use of existing approximate wavefunctions. Applying QMC to small systems like PsH for binding energy calculation is straightforward. To apply it to systems with heavier atoms, to systems for which the center-of-mass motion needs to be separated, and to calculate annihilation rates, special techniques must be developed. In this project a detailed study and several advancements to the QMC method are carried out. Positronium compounds PsH, Ps2, PsO, and Ps2O are studied with algorithms we developed. Results for PsH and Ps2 agree with the best accepted to date. Results for PsO confirm the stability of this compound, and are in fair agreement with an earlier calculation. Results for Ps2O establish the stability of this compound and give an approximate annihilation rate for the first time. Discussions will include an introduction to QMC methods, an in-depth discussion on the QMC formalism, presentation of new algorithms developed in this study, and procedures and results of QMC calculations on the above mentioned positronium compounds.
Monte carlo sampling of fission multiplicity.
Hendricks, J. S.
2004-01-01
Two new methods have been developed for fission multiplicity modeling in Monte Carlo calculations. The traditional method of sampling neutron multiplicity from fission is to sample the number of neutrons above or below the average. For example, if there are 2.7 neutrons per fission, three would be chosen 70% of the time and two would be chosen 30% of the time. For many applications, particularly {sup 3}He coincidence counting, a better estimate of the true number of neutrons per fission is required. Generally, this number is estimated by sampling a Gaussian distribution about the average. However, because the tail of the Gaussian distribution is negative and negative neutrons cannot be produced, a slight positive bias can be found in the average value. For criticality calculations, the result of rejecting the negative neutrons is an increase in k{sub eff} of 0.1% in some cases. For spontaneous fission, where the average number of neutrons emitted from fission is low, the error also can be unacceptably large. If the Gaussian width approaches the average number of fissions, 10% too many fission neutrons are produced by not treating the negative Gaussian tail adequately. The first method to treat the Gaussian tail is to determine a correction offset, which then is subtracted from all sampled values of the number of neutrons produced. This offset depends on the average value for any given fission at any energy and must be computed efficiently at each fission from the non-integrable error function. The second method is to determine a corrected zero point so that all neutrons sampled between zero and the corrected zero point are killed to compensate for the negative Gaussian tail bias. Again, the zero point must be computed efficiently at each fission. Both methods give excellent results with a negligible computing time penalty. It is now possible to include the full effects of fission multiplicity without the negative Gaussian tail bias.
Monte Carlo study of microdosimetric diamond detectors
NASA Astrophysics Data System (ADS)
Solevi, Paola; Magrin, Giulio; Moro, Davide; Mayer, Ramona
2015-09-01
Ion-beam therapy provides a high dose conformity and increased radiobiological effectiveness with respect to conventional radiation-therapy. Strict constraints on the maximum uncertainty on the biological weighted dose and consequently on the biological weighting factor require the determination of the radiation quality, defined as the types and energy spectra of the radiation at a specific point. However the experimental determination of radiation quality, in particular for an internal target, is not simple and the features of ion interactions and treatment delivery require dedicated and optimized detectors. Recently chemical vapor deposition (CVD) diamond detectors have been suggested as ion-beam therapy microdosimeters. Diamond detectors can be manufactured with small cross sections and thin shapes, ideal to cope with the high fluence rate. However the sensitive volume of solid state detectors significantly deviates from conventional microdosimeters, with a diameter that can be up to 1000 times the height. This difference requires a redefinition of the concept of sensitive thickness and a deep study of the secondary to primary radiation, of the wall effects and of the impact of the orientation of the detector with respect to the radiation field. The present work intends to study through Monte Carlo simulations the impact of the detector geometry on the determination of radiation quality quantities, in particular on the relative contribution of primary and secondary radiation. The dependence of microdosimetric quantities such as the unrestricted linear energy L and the lineal energy y are investigated for different detector cross sections, by varying the particle type (carbon ions and protons) and its 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 study of microdosimetric diamond detectors.
Solevi, Paola; Magrin, Giulio; Moro, Davide; Mayer, Ramona
2015-09-21
Ion-beam therapy provides a high dose conformity and increased radiobiological effectiveness with respect to conventional radiation-therapy. Strict constraints on the maximum uncertainty on the biological weighted dose and consequently on the biological weighting factor require the determination of the radiation quality, defined as the types and energy spectra of the radiation at a specific point. However the experimental determination of radiation quality, in particular for an internal target, is not simple and the features of ion interactions and treatment delivery require dedicated and optimized detectors. Recently chemical vapor deposition (CVD) diamond detectors have been suggested as ion-beam therapy microdosimeters. Diamond detectors can be manufactured with small cross sections and thin shapes, ideal to cope with the high fluence rate. However the sensitive volume of solid state detectors significantly deviates from conventional microdosimeters, with a diameter that can be up to 1000 times the height. This difference requires a redefinition of the concept of sensitive thickness and a deep study of the secondary to primary radiation, of the wall effects and of the impact of the orientation of the detector with respect to the radiation field. The present work intends to study through Monte Carlo simulations the impact of the detector geometry on the determination of radiation quality quantities, in particular on the relative contribution of primary and secondary radiation. The dependence of microdosimetric quantities such as the unrestricted linear energy L and the lineal energy y are investigated for different detector cross sections, by varying the particle type (carbon ions and protons) and its energy. PMID:26309235
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.
Quantum Monte Carlo Endstation for Petascale Computing
David Ceperley
2011-03-02
CUDA GPU platform. We restructured the CPU algorithms to express additional parallelism, minimize GPU-CPU communication, and efficiently utilize the GPU memory hierarchy. Using mixed precision on GT200 GPUs and MPI for intercommunication and load balancing, we observe typical full-application speedups of approximately 10x to 15x relative to quad-core Xeon CPUs alone, while reproducing the double-precision CPU results within statistical error. We developed an all-electron quantum Monte Carlo (QMC) method for solids that does not rely on pseudopotentials, and used it to construct a primary ultra-high-pressure calibration based on the equation of state of cubic boron nitride. We computed the static contribution to the free energy with the QMC method and obtained the phonon contribution from density functional theory, yielding a high-accuracy calibration up to 900 GPa usable directly in experiment. We computed the anharmonic Raman frequency shift with QMC simulations as a function of pressure and temperature, allowing optical pressure calibration. In contrast to present experimental approaches, small systematic errors in the theoretical EOS do not increase with pressure, and no extrapolation is needed. This all-electron method is applicable to first-row solids, providing a new reference for ab initio calculations of solids and benchmarks for pseudopotential accuracy. We compared experimental and theoretical results on the momentum distribution and the quasiparticle renormalization factor in sodium. From an x-ray Compton-profile measurement of the valence-electron momentum density, we derived its discontinuity at the Fermi wavevector finding an accurate measure of the renormalization factor that we compared with quantum-Monte-Carlo and G0W0 calculations performed both on crystalline sodium and on the homogeneous electron gas. Our calculated results are in good agreement with the experiment. We have been studying the heat of formation for various Kubas complexes of molecular
Implications of Monte Carlo Statistical Errors in Criticality Safety Assessments
Pevey, Ronald E.
2005-09-15
Most criticality safety calculations are performed using Monte Carlo techniques because of Monte Carlo's ability to handle complex three-dimensional geometries. For Monte Carlo calculations, the more histories sampled, the lower the standard deviation of the resulting estimates. The common intuition is, therefore, that the more histories, the better; as a result, analysts tend to run Monte Carlo analyses as long as possible (or at least to a minimum acceptable uncertainty). For Monte Carlo criticality safety analyses, however, the optimization situation is complicated by the fact that procedures usually require that an extra margin of safety be added because of the statistical uncertainty of the Monte Carlo calculations. This additional safety margin affects the impact of the choice of the calculational standard deviation, both on production and on safety. This paper shows that, under the assumptions of normally distributed benchmarking calculational errors and exact compliance with the upper subcritical limit (USL), the standard deviation that optimizes production is zero, but there is a non-zero value of the calculational standard deviation that minimizes the risk of inadvertently labeling a supercritical configuration as subcritical. Furthermore, this value is shown to be a simple function of the typical benchmarking step outcomes--the bias, the standard deviation of the bias, the upper subcritical limit, and the number of standard deviations added to calculated k-effectives before comparison to the USL.
Application of Monte Carlo Methods in Molecular Targeted Radionuclide Therapy
Hartmann Siantar, C; Descalle, M-A; DeNardo, G L; Nigg, D W
2002-02-19
Targeted radionuclide therapy promises to expand the role of radiation beyond the treatment of localized tumors. This novel form of therapy targets metastatic cancers by combining radioactive isotopes with tumor-seeking molecules such as monoclonal antibodies and custom-designed synthetic agents. Ultimately, like conventional radiotherapy, the effectiveness of targeted radionuclide therapy is limited by the maximum dose that can be given to a critical, normal tissue, such as bone marrow, kidneys, and lungs. Because radionuclide therapy relies on biological delivery of radiation, its optimization and characterization are necessarily different than for conventional radiation therapy. We have initiated the development of a new, Monte Carlo transport-based treatment planning system for molecular targeted radiation therapy as part of the MINERVA treatment planning system. This system calculates patient-specific radiation dose estimates using a set of computed tomography scans to describe the 3D patient anatomy, combined with 2D (planar image) and 3D (SPECT, or single photon emission computed tomography) to describe the time-dependent radiation source. The accuracy of such a dose calculation is limited primarily by the accuracy of the initial radiation source distribution, overlaid on the patient's anatomy. This presentation provides an overview of MINERVA functionality for molecular targeted radiation therapy, and describes early validation and implementation results of Monte Carlo simulations.
Russian roulette efficiency in Monte Carlo resonant absorption calculations
Ghassoun; Jehouani
2000-10-01
The resonant absorption calculation in media containing heavy resonant nuclei is one of the most difficult problems treated in reactor physics. Deterministic techniques need many approximations to solve this kind of problem. On the other hand, the Monte Carlo method is a reliable mathematical tool for evaluating the neutron resonance escape probability. But it suffers from large statistical deviations of results and long computation times. In order to overcome this problem, we have used the Splitting and Russian Roulette technique coupled separately to the survival biasing and to the importance sampling for the energy parameter. These techniques have been used to calculate the neutron resonance absorption in infinite homogenous media containing hydrogen and uranium characterized by the dilution (ratio of the concentrations of hydrogen to uranium). The punctual neutron source energy is taken at Es = 2 MeV and Es = 676.45 eV, whereas the energy cut-off is fixed at Ec = 2.768 eV. The results show a large reduction of computation time and statistical deviation, without altering the mean resonance escape probability compared to the usual analog simulation. The Splitting and Russian Roulette coupled to the survival biasing method is found to be the best methods for studying the neutron resonant absorption, particularly for high energies. A comparison is done between the Monte Carlo and deterministic methods based on the numerical solution of the neutron slowing down equations by the iterative method results for several dilutions. PMID:11003535
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.