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.
Adiabatic optimization versus diffusion Monte Carlo methods
Jarret, Michael; Jordan, Stephen P.; Lackey, Brad
2016-10-01
Most experimental and theoretical studies of adiabatic optimization use stoquastic Hamiltonians, whose ground states are expressible using only real nonnegative amplitudes. This raises a question as to whether classical Monte Carlo methods can simulate stoquastic adiabatic algorithms with polynomial overhead. Here we analyze diffusion Monte Carlo algorithms. We argue that, based on differences between L1 and L2 normalized states, these algorithms suffer from certain obstructions preventing them from efficiently simulating stoquastic adiabatic evolution in generality. In practice however, we obtain good performance by introducing a method that we call Substochastic Monte Carlo. In fact, our simulations are good classical optimization algorithms in their own right, competitive with the best previously known heuristic solvers for MAX-k -SAT at k =2 ,3 ,4 .
Diffusion quantum Monte Carlo for molecules
Lester, W.A. Jr.
1986-07-01
A quantum mechanical Monte Carlo method has been used for the treatment of molecular problems. The imaginary-time Schroedinger equation written with a shift in zero energy (E/sub T/ - V(R)) can be interpreted as a generalized diffusion equation with a position-dependent rate or branching term. Since diffusion is the continuum limit of a random walk, one may simulate the Schroedinger equation with a function psi (note, not psi/sup 2/) as a density of ''walks.'' The walks undergo an exponential birth and death as given by the rate term. 16 refs., 2 tabs.
Chemical application of diffusion quantum Monte Carlo
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 diffusion Monte Carlo for frequency-dependent radiative transfer
Densmore, Jeffrey D [Los Alamos National Laboratory; Kelly, Thompson G [Los Alamos National Laboratory; Urbatish, Todd J [Los Alamos National Laboratory
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.
Accurate barrier heights using diffusion Monte Carlo
Krongchon, Kittithat; Wagner, Lucas K
2016-01-01
Fixed node diffusion Monte Carlo (DMC) has been performed on a test set of forward and reverse barrier heights for 19 non-hydrogen-transfer reactions, and the nodal error has been assessed. The DMC results are robust to changes in the nodal surface, as assessed by using different mean-field techniques to generate single determinant wave functions. Using these single determinant nodal surfaces, DMC results in errors of 1.5(5) kcal/mol on barrier heights. Using the large data set of DMC energies, we attempted to find good descriptors of the fixed node error. It does not correlate with a number of descriptors including change in density, but does correlate with the gap between the highest occupied and lowest unoccupied orbital energies in the mean-field calculation.
Diffusion Monte Carlo in internal coordinates.
Petit, Andrew S; McCoy, Anne B
2013-08-15
An internal coordinate extension of diffusion Monte Carlo (DMC) is described as a first step toward a generalized reduced-dimensional DMC approach. The method places no constraints on the choice of internal coordinates other than the requirement that they all be independent. Using H(3)(+) and its isotopologues as model systems, the methodology is shown to be capable of successfully describing the ground state properties of molecules that undergo large amplitude, zero-point vibrational motions. Combining the approach developed here with the fixed-node approximation allows vibrationally excited states to be treated. Analysis of the ground state probability distribution is shown to provide important insights into the set of internal coordinates that are less strongly coupled and therefore more suitable for use as the nodal coordinates for the fixed-node DMC calculations. In particular, the curvilinear normal mode coordinates are found to provide reasonable nodal surfaces for the fundamentals of H(2)D(+) and D(2)H(+) despite both molecules being highly fluxional.
Information-Geometric Markov Chain Monte Carlo Methods Using Diffusions
Samuel Livingstone
2014-06-01
Full Text Available Recent work incorporating geometric ideas in Markov chain Monte Carlo is reviewed in order to highlight these advances and their possible application in a range of domains beyond statistics. A full exposition of Markov chains and their use in Monte Carlo simulation for statistical inference and molecular dynamics is provided, with particular emphasis on methods based on Langevin diffusions. After this, geometric concepts in Markov chain Monte Carlo are introduced. A full derivation of the Langevin diffusion on a Riemannian manifold is given, together with a discussion of the appropriate Riemannian metric choice for different problems. A survey of applications is provided, and some open questions are discussed.
Introduction to the variational and diffusion Monte Carlo methods
Toulouse, Julien; Umrigar, C J
2015-01-01
We provide a pedagogical introduction to the two main variants of real-space quantum Monte Carlo methods for electronic-structure calculations: variational Monte Carlo (VMC) and diffusion Monte Carlo (DMC). Assuming no prior knowledge on the subject, we review in depth the Metropolis-Hastings algorithm used in VMC for sampling the square of an approximate wave function, discussing details important for applications to electronic systems. We also review in detail the more sophisticated DMC algorithm within the fixed-node approximation, introduced to avoid the infamous Fermionic sign problem, which allows one to sample a more accurate approximation to the ground-state wave function. Throughout this review, we discuss the statistical methods used for evaluating expectation values and statistical uncertainties. In particular, we show how to estimate nonlinear functions of expectation values and their statistical uncertainties.
Fixed-Node Diffusion Monte Carlo of Lithium Systems
Rasch, Kevin
2015-01-01
We study lithium systems over a range of number of atoms, e.g., atomic anion, dimer, metallic cluster, and body-centered cubic crystal by the diffusion Monte Carlo method. The calculations include both core and valence electrons in order to avoid any possible impact by pseudo potentials. The focus of the study is the fixed-node errors, and for that purpose we test several orbital sets in order to provide the most accurate nodal hyper surfaces. We compare our results to other high accuracy calculations wherever available and to experimental results so as to quantify the the fixed-node errors. The results for these Li systems show that fixed-node quantum Monte Carlo achieves remarkably high accuracy total energies and recovers 97-99 % of the correlation energy.
Synchronous parallel kinetic Monte Carlo Diffusion in Heterogeneous Systems
Martinez Saez, Enrique [Los Alamos National Laboratory; Hetherly, Jeffery [Los Alamos National Laboratory; Caro, Jose A [Los Alamos National Laboratory
2010-12-06
A new hybrid Molecular Dynamics-kinetic Monte Carlo algorithm has been developed in order to study the basic mechanisms taking place in diffusion in concentrated alloys under the action of chemical and stress fields. Parallel implementation of the k-MC part based on a recently developed synchronous algorithm [1. Compo Phys. 227 (2008) 3804-3823] resorting on the introduction of a set of null events aiming at synchronizing the time for the different subdomains, added to the parallel efficiency of MD, provides the computer power required to evaluate jump rates 'on the flight', incorporating in this way the actual driving force emerging from chemical potential gradients, and the actual environment-dependent jump rates. The time gain has been analyzed and the parallel performance reported. The algorithm is tested on simple diffusion problems to verify its accuracy.
Hellman-Feynman operator sampling in diffusion Monte Carlo calculations.
Gaudoin, R; Pitarke, J M
2007-09-21
Diffusion Monte Carlo (DMC) calculations typically yield highly accurate results in solid-state and quantum-chemical calculations. However, operators that do not commute with the Hamiltonian are at best sampled correctly up to second order in the error of the underlying trial wave function once simple corrections have been applied. This error is of the same order as that for the energy in variational calculations. Operators that suffer from these problems include potential energies and the density. This Letter presents a new method, based on the Hellman-Feynman theorem, for the correct DMC sampling of all operators diagonal in real space. Our method is easy to implement in any standard DMC code.
High-Pressure Hydrogen Sulfide by Diffusion Quantum Monte Carlo
Azadi, Sam
2016-01-01
We use the diffusion quantum Monte Carlo to revisit the enthalpy-pressure phase diagram of the various products from the different proposed decompositions of H$_2$S at pressures above 150~GPa. Our results entails a revision of the ground-state enthalpy-pressure phase diagram. Specifically, we find that the C2/c HS$_2$ structure is persistent up to 440~GPa before undergoing a phase transition into the C2/m phase. Contrary to density functional theory, our calculations suggest that the C2/m phase of HS is more stable than the I4$_1$/amd HS structure over the whole pressure range from 150 to 400 GPa. Moreover, we predict that the Im-3m phase is the most likely candidate for H$_3$S, which is consistent with recent experimental x-ray diffraction measurements.
Lattice Monte Carlo simulation of Galilei variant anomalous diffusion
Guo, Gang, E-mail: hndzgg@aliyun.com [School of Information System and Management, National University of Defense Technology, Changsha, 410073 (China); Institute of Computer Science, University of Rostock, Albert Einstein Str. 22, Rostock, 18059 (Germany); Bittig, Arne, E-mail: arne.bittig@uni-rostock.de [Institute of Computer Science, University of Rostock, Albert Einstein Str. 22, Rostock, 18059 (Germany); Uhrmacher, Adelinde, E-mail: lin@informatik.uni-rostock.de [Institute of Computer Science, University of Rostock, Albert Einstein Str. 22, Rostock, 18059 (Germany)
2015-05-01
The observation of an increasing number of anomalous diffusion phenomena motivates the study to reveal the actual reason for such stochastic processes. When it is difficult to get analytical solutions or necessary to track the trajectory of particles, lattice Monte Carlo (LMC) simulation has been shown to be particularly useful. To develop such an LMC simulation algorithm for the Galilei variant anomalous diffusion, we derive explicit solutions for the conditional and unconditional first passage time (FPT) distributions with double absorbing barriers. According to the theory of random walks on lattices and the FPT distributions, we propose an LMC simulation algorithm and prove that such LMC simulation can reproduce both the mean and the mean square displacement exactly in the long-time limit. However, the error introduced in the second moment of the displacement diverges according to a power law as the simulation time progresses. We give an explicit criterion for choosing a small enough lattice step to limit the error within the specified tolerance. We further validate the LMC simulation algorithm and confirm the theoretical error analysis through numerical simulations. The numerical results agree with our theoretical predictions very well.
Diffusion Monte Carlo methods applied to Hamaker Constant evaluations
Hongo, Kenta
2016-01-01
We applied diffusion Monte Carlo (DMC) methods to evaluate Hamaker constants of liquids for wettabilities, with practical size of a liquid molecule, Si$_6$H$_{12}$ (cyclohexasilane). The evaluated constant would be justified in the sense that it lies within the expected dependence on molecular weights among similar kinds of molecules, though there is no reference experimental values available for this molecule. Comparing the DMC with vdW-DFT evaluations, we clarified that some of the vdW-DFT evaluations could not describe correct asymptotic decays and hence Hamaker constants even though they gave reasonable binding lengths and energies, and vice versa for the rest of vdW-DFTs. We also found the advantage of DMC for this practical purpose over CCSD(T) because of the large amount of BSSE/CBS corrections required for the latter under the limitation of basis set size applicable to the practical size of a liquid molecule, while the former is free from such limitations to the extent that only the nodal structure of...
Monte Carlo simulation of electron back diffusion in argon
Radmilović, M.; Stojanović, V.; Petrović, Z. Lj.
1999-10-01
Monte Carlo simulation was applied to study the back-diffusion of electrons in argon at low and moderate values of E/N from 10Td to 10 kTd. Simulations were performed for gaps of 1 cm and for pressures corresponding to the breakdown voltages taken from experimental Paschen curves. Effects of inelastic collisions, ionization, reflection of electrons and anisotropic scattering as well as anisotropic initial and reflected angular distributions of electrons were included. A complete and detailed set of electron scattering cross sections that describes well electron transport in argon was used. We found a very good agreement of the results of simulations with the experimental data for well defined initial conditions, and with several models available in the literature.(A.V. Phelps and Z.LJ. Petrović), Plasma Sources Sci. Tehnol. 8, R21 (1999). While effect of reflection may be large, for realistic values of reflection coefficient and for realistic secondary electron productions the effect may be neglected for the accuracy required in gas discharge modeling.
A diffusion quantum Monte Carlo study of geometries and harmonic frequencies of molecules
Lu, Shih-I.
2004-01-01
This article describes an approach in determination of equilibrium geometries and harmonic frequencies of molecules by the Ornstein-Uhlenbeck diffusion quantum Monte Carlo method based on the floating spherical Gaussians. In conjunction with a projected and renormalized Hellmann-Feynman gradient and an electronic energy at variational Monte Carlo and diffusion quantum Monte Carlo, respectively, the quasi-Newton algorithm implemented with the Broyden-Fletcher-Goldfarb-Shanno updated Hessian was used to find the optimized molecular geometry. We applied this approach to N2 and H2O molecules. The geometry and harmonic frequencies calculated were consistent with some sophisticated ab initio calculated values within reasonable statistical uncertainty.
Communication: Water on hexagonal boron nitride from diffusion Monte Carlo
Al-Hamdani, Yasmine S.; Ma, Ming; Michaelides, Angelos, E-mail: angelos.michaelides@ucl.ac.uk [Thomas Young Centre and London Centre for Nanotechnology, 17–19 Gordon Street, London WC1H 0AH (United Kingdom); Department of Chemistry, University College London, 20 Gordon Street, London WC1H 0AJ (United Kingdom); Alfè, Dario [Thomas Young Centre and London Centre for Nanotechnology, 17–19 Gordon Street, London WC1H 0AH (United Kingdom); Department of Earth Sciences, University College London, Gower Street, London WC1E 6BT (United Kingdom); Lilienfeld, O. Anatole von [Institute of Physical Chemistry and National Center for Computational Design and Discovery of Novel Materials, Department of Chemistry, University of Basel, Klingelbergstrasse 80, CH-4056 Basel (Switzerland); Argonne Leadership Computing Facility, Argonne National Laboratories, 9700 S. Cass Avenue Argonne, Lemont, Illinois 60439 (United States)
2015-05-14
Despite a recent flurry of experimental and simulation studies, an accurate estimate of the interaction strength of water molecules with hexagonal boron nitride is lacking. Here, we report quantum Monte Carlo results for the adsorption of a water monomer on a periodic hexagonal boron nitride sheet, which yield a water monomer interaction energy of −84 ± 5 meV. We use the results to evaluate the performance of several widely used density functional theory (DFT) exchange correlation functionals and find that they all deviate substantially. Differences in interaction energies between different adsorption sites are however better reproduced by DFT.
Lu, Shih-I.
2004-06-01
Application of the Ornstein-Uhlenbeck diffusion quantum Monte Carlo method in combination with a trial wave function constructed from the floating spherical Gaussian orbitals and spherical Gaussian geminals to studies on the equilibrium structures and harmonic frequencies of ethane and ozone is presented. These Monte Carlo computed results are compared with those of experiments as well as the coupled cluster methods with the correlation consistent basis sets for the two molecules. For ozone, we also compare the Monte Carlo results with the results from multireference calculations.
Hall, Eric
2016-01-09
The Monte Carlo (and Multi-level Monte Carlo) finite element method can be used to approximate observables of solutions to diffusion equations with lognormal distributed diffusion coefficients, e.g. modeling ground water flow. Typical models use lognormal diffusion coefficients with H´ older regularity of order up to 1/2 a.s. This low regularity implies that the high frequency finite element approximation error (i.e. the error from frequencies larger than the mesh frequency) is not negligible and can be larger than the computable low frequency error. We address how the total error can be estimated by the computable error.
Sandberg, Mattias
2015-01-07
The Monte Carlo (and Multi-level Monte Carlo) finite element method can be used to approximate observables of solutions to diffusion equations with log normal distributed diffusion coefficients, e.g. modelling ground water flow. Typical models use log normal diffusion coefficients with H¨older regularity of order up to 1/2 a.s. This low regularity implies that the high frequency finite element approximation error (i.e. the error from frequencies larger than the mesh frequency) is not negligible and can be larger than the computable low frequency error. This talk will address how the total error can be estimated by the computable error.
Diffusion and exchange of adsorbed polymers studied by Monte Carlo simulations
Klein Wolterink, J.; Barkema, G.T.; Cohen Stuart, M.A.
2005-01-01
Monte Carlo simulations are performed of adsorbed polymers with various polymer lengths N and adsorption energies ¿s. Exchange times and the rates of lateral diffusion (along the surface) are investigated as a function of N and ¿s. Lateral diffusion is found to be a combination of reptation (diffusi
On the convergence of diffusion Monte Carlo in non-Euclidean spaces. I. Free diffusion
Curotto, E.; Mella, Massimo
2015-03-01
We develop a set of diffusion Monte Carlo algorithms for general compactly supported Riemannian manifolds that converge weakly to second order with respect to the time step. The approaches are designed to work for cases that include non-orthogonal coordinate systems, nonuniform metric tensors, manifold boundaries, and multiply connected spaces. The methods do not require specially designed coordinate charts and can in principle work with atlases of charts. Several numerical tests for free diffusion in compactly supported Riemannian manifolds are carried out for spaces relevant to the chemical physics community. These include the circle, the 2-sphere, and the ellipsoid of inertia mapped with traditional angles. In all cases, we observe second order convergence, and in the case of the sphere, we gain insight into the function of the advection term that is generated by the curved nature of the space.
Huiszoon, C.; Briels, W.J.
1993-01-01
The differential diffusion Monte Carlo method, involving correlated random walks, is used to calculate the static polarizabilities of molecular hydrogen and helium by application of a finite electrostatic field. The results are for molecular hydrogen (alpha)=4.60(3) au; (alpha)|=6.38(5) au; for heli
A Monte Carlo synthetic-acceleration method for solving the thermal radiation diffusion equation
Evans, Thomas M., E-mail: evanstm@ornl.gov [Oak Ridge National Laboratory, 1 Bethel Valley Rd., Oak Ridge, TN 37831 (United States); Mosher, Scott W., E-mail: moshersw@ornl.gov [Oak Ridge National Laboratory, 1 Bethel Valley Rd., Oak Ridge, TN 37831 (United States); Slattery, Stuart R., E-mail: sslattery@wisc.edu [University of Wisconsin–Madison, 1500 Engineering Dr., Madison, WI 53716 (United States); Hamilton, Steven P., E-mail: hamiltonsp@ornl.gov [Oak Ridge National Laboratory, 1 Bethel Valley Rd., Oak Ridge, TN 37831 (United States)
2014-02-01
We present a novel synthetic-acceleration-based Monte Carlo method for solving the equilibrium thermal radiation diffusion equation in three spatial dimensions. The algorithm performance is compared against traditional solution techniques using a Marshak benchmark problem and a more complex multiple material problem. Our results show that our Monte Carlo method is an effective solver for sparse matrix systems. For solutions converged to the same tolerance, it performs competitively with deterministic methods including preconditioned conjugate gradient and GMRES. We also discuss various aspects of preconditioning the method and its general applicability to broader classes of problems.
Kinetic Monte Carlo Simulation of Oxygen and Cation Diffusion in Yttria-Stabilized Zirconia
Good, Brian
2011-01-01
Yttria-stabilized zirconia (YSZ) is of interest to the aerospace community, notably for its application as a thermal barrier coating for turbine engine components. In such an application, diffusion of both oxygen ions and cations is of concern. Oxygen diffusion can lead to deterioration of a coated part, and often necessitates an environmental barrier coating. Cation diffusion in YSZ is much slower than oxygen diffusion. However, such diffusion is a mechanism by which creep takes place, potentially affecting the mechanical integrity and phase stability of the coating. In other applications, the high oxygen diffusivity of YSZ is useful, and makes the material of interest for use as a solid-state electrolyte in fuel cells. The kinetic Monte Carlo (kMC) method offers a number of advantages compared with the more widely known molecular dynamics simulation method. In particular, kMC is much more efficient for the study of processes, such as diffusion, that involve infrequent events. We describe the results of kinetic Monte Carlo computer simulations of oxygen and cation diffusion in YSZ. Using diffusive energy barriers from ab initio calculations and from the literature, we present results on the temperature dependence of oxygen and cation diffusivity, and on the dependence of the diffusivities on yttria concentration and oxygen sublattice vacancy concentration. We also present results of the effect on diffusivity of oxygen vacancies in the vicinity of the barrier cations that determine the oxygen diffusion energy barriers.
Using hybrid implicit Monte Carlo diffusion to simulate gray radiation hydrodynamics
Cleveland, Mathew A., E-mail: cleveland7@llnl.gov; Gentile, Nick
2015-06-15
This work describes how to couple a hybrid Implicit Monte Carlo Diffusion (HIMCD) method with a Lagrangian hydrodynamics code to evaluate the coupled radiation hydrodynamics equations. This HIMCD method dynamically applies Implicit Monte Carlo Diffusion (IMD) [1] to regions of a problem that are opaque and diffusive while applying standard Implicit Monte Carlo (IMC) [2] to regions where the diffusion approximation is invalid. We show that this method significantly improves the computational efficiency as compared to a standard IMC/Hydrodynamics solver, when optically thick diffusive material is present, while maintaining accuracy. Two test cases are used to demonstrate the accuracy and performance of HIMCD as compared to IMC and IMD. The first is the Lowrie semi-analytic diffusive shock [3]. The second is a simple test case where the source radiation streams through optically thin material and heats a thick diffusive region of material causing it to rapidly expand. We found that HIMCD proves to be accurate, robust, and computationally efficient for these test problems.
Metropolis Methods for Quantum Monte Carlo Simulations
Ceperley, D. M.
2003-01-01
Since its first description fifty years ago, the Metropolis Monte Carlo method has been used in a variety of different ways for the simulation of continuum quantum many-body systems. This paper will consider some of the generalizations of the Metropolis algorithm employed in quantum Monte Carlo: Variational Monte Carlo, dynamical methods for projector monte carlo ({\\it i.e.} diffusion Monte Carlo with rejection), multilevel sampling in path integral Monte Carlo, the sampling of permutations, ...
Gabrieli, Andrea; Demontis, Pierfranco; Pazzona, Federico G; Suffritti, Giuseppe B
2011-05-01
Understanding the behaviors of molecules in tight confinement is a challenging task. Standard simulation tools like kinetic Monte Carlo have proven to be very effective in the study of adsorption and diffusion phenomena in microporous materials, but they turn out to be very inefficient when simulation time and length scales are extended. In this paper we have explored the possibility of application of a discrete version of the synchronous parallel kinetic Monte Carlo algorithm introduced by Martínez et al. [J. Comput. Phys. 227, 3804 (2008)] to the study of aromatic hydrocarbons diffusion in zeolites. The efficiency of this algorithm is investigated as a function of the number of processors and domain size. We show that with an accurate choice of domains size it is possible to achieve very good efficiencies thus permitting us to effectively extend space and time scales of the simulated system. © 2011 American Physical Society
Diffusion Quantum Monte Carlo Study of Martensitic Phase Transition: The Case of Phosphorene
Reeves, Kyle G; Kanai, Yosuke
2016-01-01
Recent technical advances in dealing with finite-size errors make quantum Monte Carlo methods quite appealing for treating extended systems in electronic structure calculations, especially when commonly-used density functional theory (DFT) methods might not be satisfactory. We present a theoretical study of martensitic phase transition of a two-dimensional phosphorene by employing diffusion Monte Carlo (DMC) approach to investigate the energetics of this phase transition. The DMC calculation supports DFT prediction of having a rather diffusive barrier that is characterized by having two transition states, in addition to confirming that the so-called black and blue phases of phosphorene are essentially degenerate. At the same time, the calculation shows the importance of treating correlation energy accurately for describing the energy changes in the martensitic phase transition, as is already widely appreciated for chemical bond formation/dissociation. Building on the atomistic characterization of the phase tr...
Efficient implementation of the Hellmann-Feynman theorem in a diffusion Monte Carlo calculation.
Vitiello, S A
2011-02-07
Kinetic and potential energies of systems of (4)He atoms in the solid phase are computed at T = 0. Results at two densities of the liquid phase are presented as well. Calculations are performed by the multiweight extension to the diffusion Monte Carlo method that allows the application of the Hellmann-Feynman theorem in a robust and efficient way. This is a general method that can be applied in other situations of interest as well.
Comparing analytical and Monte Carlo optical diffusion models in phosphor-based X-ray detectors
Kalyvas, N.; Liaparinos, P.
2014-03-01
Luminescent materials are employed as radiation to light converters in detectors of medical imaging systems, often referred to as phosphor screens. Several processes affect the light transfer properties of phosphors. Amongst the most important is the interaction of light. Light attenuation (absorption and scattering) can be described either through "diffusion" theory in theoretical models or "quantum" theory in Monte Carlo methods. Although analytical methods, based on photon diffusion equations, have been preferentially employed to investigate optical diffusion in the past, Monte Carlo simulation models can overcome several of the analytical modelling assumptions. The present study aimed to compare both methodologies and investigate the dependence of the analytical model optical parameters as a function of particle size. It was found that the optical photon attenuation coefficients calculated by analytical modeling are decreased with respect to the particle size (in the region 1- 12 μm). In addition, for particles sizes smaller than 6μm there is no simultaneous agreement between the theoretical modulation transfer function and light escape values with respect to the Monte Carlo data.
Kinetic Monte Carlo Simulation of Cation Diffusion in Low-K Ceramics
Good, Brian
2013-01-01
Low thermal conductivity (low-K) ceramic materials are of interest to the aerospace community for use as the thermal barrier component of coating systems for turbine engine components. In particular, zirconia-based materials exhibit both low thermal conductivity and structural stability at high temperature, making them suitable for such applications. Because creep is one of the potential failure modes, and because diffusion is a mechanism by which creep takes place, we have performed computer simulations of cation diffusion in a variety of zirconia-based low-K materials. The kinetic Monte Carlo simulation method is an alternative to the more widely known molecular dynamics (MD) method. It is designed to study "infrequent-event" processes, such as diffusion, for which MD simulation can be highly inefficient. We describe the results of kinetic Monte Carlo computer simulations of cation diffusion in several zirconia-based materials, specifically, zirconia doped with Y, Gd, Nb and Yb. Diffusion paths are identified, and migration energy barriers are obtained from density functional calculations and from the literature. We present results on the temperature dependence of the diffusivity, and on the effects of the presence of oxygen vacancies in cation diffusion barrier complexes as well.
Diffusion coefficients for LMFBR cells calculated with MOC and Monte Carlo methods
Rooijen, W.F.G. van, E-mail: rooijen@u-fukui.ac.j [Research Institute of Nuclear Energy, University of Fukui, Bunkyo 3-9-1, Fukui-shi, Fukui-ken 910-8507 (Japan); Chiba, G., E-mail: chiba.go@jaea.go.j [Japan Atomic Energy Agency, 2-4 Shirakata Shirane, Tokai-mura, Naka-gun, Ibaraki-ken 319-1195 (Japan)
2011-01-15
The present work discusses the calculation of the diffusion coefficient of a lattice of hexagonal cells, with both 'sodium present' and 'sodium absent' conditions. Calculations are performed in the framework of lattice theory (also known as fundamental mode approximation). Unlike the classical approaches, our heterogeneous leakage model allows the calculation of diffusion coefficients under all conditions, even if planar voids are present in the lattice. Equations resulting from this model are solved using the method of characteristics (MOC). Independent confirmation of the MOC result comes from Monte Carlo calculations, in which the diffusion coefficient is obtained without any of the assumptions of lattice theory. It is shown by comparison to the Monte Carlo results that the MOC solution yields correct values of the diffusion coefficient under all conditions, even in cases where the classic calculation of the diffusion coefficient fails. This work is a first step in the development of a robust method to calculate the diffusion coefficient of lattice cells. Adoption into production codes will require more development and validation of the method.
Tringe, J.W., E-mail: tringe2@llnl.gov [Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, CA (United States); Ileri, N. [Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, CA (United States); Department of Chemical Engineering & Materials Science, University of California, Davis, CA (United States); Levie, H.W. [Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, CA (United States); Stroeve, P.; Ustach, V.; Faller, R. [Department of Chemical Engineering & Materials Science, University of California, Davis, CA (United States); Renaud, P. [Swiss Federal Institute of Technology, Lausanne, (EPFL) (Switzerland)
2015-08-18
Highlights: • WGA proteins in nanochannels modeled by Molecular Dynamics and Monte Carlo. • Protein surface coverage characterized by atomic force microscopy. • Models indicate transport characteristics depend strongly on surface coverage. • Results resolve of a four orders of magnitude difference in diffusion coefficient values. - Abstract: We use Molecular Dynamics and Monte Carlo simulations to examine molecular transport phenomena in nanochannels, explaining four orders of magnitude difference in wheat germ agglutinin (WGA) protein diffusion rates observed by fluorescence correlation spectroscopy (FCS) and by direct imaging of fluorescently-labeled proteins. We first use the ESPResSo Molecular Dynamics code to estimate the surface transport distance for neutral and charged proteins. We then employ a Monte Carlo model to calculate the paths of protein molecules on surfaces and in the bulk liquid transport medium. Our results show that the transport characteristics depend strongly on the degree of molecular surface coverage. Atomic force microscope characterization of surfaces exposed to WGA proteins for 1000 s show large protein aggregates consistent with the predicted coverage. These calculations and experiments provide useful insight into the details of molecular motion in confined geometries.
Seidenberger, Katrin; Wilhelm, Florian; Scholta, Joachim [Zentrum fuer Sonnenenergie- und Wasserstoff-Forschung Baden-Wuerttemberg (ZSW), Ulm (Germany)
2011-04-15
The life of a fuel cell is determined by the life of its components. A Monte Carlo model developed by Zentrum fuer Sonnenenergie- und Wasserstoff-Forschung Baden-Wuerttemberg (ZWS) focuses on the gas diffusion layer (GDL). The simulation program assumes a medium-scale water distribution, thus enabling the detection of water accumulation in the GDL. The results can be compared with experimental data, e.g. from synchrotron tomography measurements, and verified.
The importance of axonal undulation in diffusion MR measurements: a Monte Carlo simulation study.
Nilsson, Markus; Lätt, Jimmy; Ståhlberg, Freddy; van Westen, Danielle; Hagslätt, Håkan
2012-05-01
Many axons follow wave-like undulating courses. This is a general feature of extracranial nerve segments, but is also found in some intracranial nervous tissue. The importance of axonal undulation has previously been considered, for example, in the context of biomechanics, where it has been shown that posture affects undulation properties. However, the importance of axonal undulation in the context of diffusion MR measurements has not been investigated. Using an analytical model and Monte Carlo simulations of water diffusion, this study compared undulating and straight axons in terms of diffusion propagators, diffusion-weighted signal intensities and parameters derived from diffusion tensor imaging, such as the mean diffusivity (MD), the eigenvalues and the fractional anisotropy (FA). All parameters were strongly affected by the presence of undulation. The diffusivity perpendicular to the undulating axons increased with the undulation amplitude, thus resembling that of straight axons with larger diameters. Consequently, models assuming straight axons for the estimation of the axon diameter from diffusion MR measurements might overestimate the diameter if undulation is present. FA decreased from approximately 0.7 to 0.5 when axonal undulation was introduced into the simulation model structure. Our results indicate that axonal undulation may play a role in diffusion measurements when investigating, for example, the optic and sciatic nerves and the spinal cord. The simulations also demonstrate that the stretching or compression of neuronal tissue comprising undulating axons alters the observed water diffusivity, suggesting that posture may be of importance for the outcome of diffusion MRI measurements.
Kerisit, Sebastien N.; Pierce, Eric M.; Ryan, Joseph V.
2015-01-01
Borosilicate nuclear waste glasses develop complex altered layers as a result of coupled processes such as hydrolysis of network species, condensation of Si species, and diffusion. However, diffusion has often been overlooked in Monte Carlo models of the aqueous corrosion of borosilicate glasses. Therefore, three different models for dissolved Si diffusion in the altered layer were implemented in a Monte Carlo model and evaluated for glasses in the compositional range (75-x) mol% SiO2 (12.5+x/2) mol% B2O3 and (12.5+x/2) mol% Na2O, where 0 ≤ x ≤ 20%, and corroded in static conditions at a surface-to-volume ratio of 1000 m-1. The three models considered instantaneous homogenization (M1), linear concentration gradients (M2), and concentration profiles determined by solving Fick’s 2nd law using a finite difference method (M3). Model M3 revealed that concentration profiles in the altered layer are not linear and show changes in shape and magnitude as corrosion progresses, unlike those assumed in model M2. Furthermore, model M3 showed that, for borosilicate glasses with a high forward dissolution rate compared to the diffusion rate, the gradual polymerization and densification of the altered layer is significantly delayed compared to models M1 and M2. Models M1 and M2 were found to be appropriate models only for glasses with high release rates such as simple borosilicate glasses with low ZrO2 content.
Iba, Yukito
2000-01-01
``Extended Ensemble Monte Carlo''is a generic term that indicates a set of algorithms which are now popular in a variety of fields in physics and statistical information processing. Exchange Monte Carlo (Metropolis-Coupled Chain, Parallel Tempering), Simulated Tempering (Expanded Ensemble Monte Carlo), and Multicanonical Monte Carlo (Adaptive Umbrella Sampling) are typical members of this family. Here we give a cross-disciplinary survey of these algorithms with special emphasis on the great f...
An Extension of Implicit Monte Carlo Diffusion: Multigroup and The Difference Formulation
Cleveland, M A; Gentile, N; Palmer, T S
2010-04-19
Implicit Monte Carlo (IMC) and Implicit Monte Carlo Diffusion (IMD) are approaches to the numerical solution of the equations of radiative transfer. IMD was previously derived and numerically tested on grey, or frequency-integrated problems. In this research, we extend Implicit Monte Carlo Diffusion (IMD) to account for frequency dependence, and we implement the difference formulation as a source manipulation variance reduction technique. We derive the relevant probability distributions and present the frequency dependent IMD algorithm, with and without the difference formulation. The IMD code with and without the difference formulation was tested using both grey and frequency dependent benchmark problems. The Su and Olson semi-analytic Marshak wave benchmark was used to demonstrate the validity of the code for grey problems. The Su and Olson semi-analytic picket fence benchmark was used for the frequency dependent problems. The frequency dependent IMD algorithm reproduces the results of both Su and Olson benchmark problems. Frequency group refinement studies indicate that the computational cost of refining the group structure is likely less than that of group refinement in deterministic solutions of the radiation diffusion methods. Our results show that applying the difference formulation to the IMD algorithm can result in an overall increase in the figure of merit for frequency dependent problems. However, the creation of negatively weighted particles from the difference formulation can cause significant numerical instabilities in regions of the problem with sharp spatial gradients in the solution. An adaptive implementation of the difference formulation may be necessary to focus its use in regions that are at or near thermal equilibrium.
Radon detection in conical diffusion chambers: Monte Carlo calculations and experiment
Rickards, J.; Golzarri, J. I.; Espinosa, G., E-mail: espinosa@fisica.unam.mx [Instituto de Física, Universidad Nacional Autónoma de México Circuito de la Investigación Científica, Ciudad Universitaria México, D.F. 04520, México (Mexico); Vázquez-López, C. [Departamento de Física, Centro de Investigación y de Estudios Avanzados del IPN Ave. IPN 2508, Col. San Pedro Zacatenco, México 07360, DF, México (Mexico)
2015-07-23
The operation of radon detection diffusion chambers of truncated conical shape was studied using Monte Carlo calculations. The efficiency was studied for alpha particles generated randomly in the volume of the chamber, and progeny generated randomly on the interior surface, which reach track detectors placed in different positions within the chamber. Incidence angular distributions, incidence energy spectra and path length distributions are calculated. Cases studied include different positions of the detector within the chamber, varying atmospheric pressure, and introducing a cutoff incidence angle and energy.
Fixed-node diffusion Monte Carlo study of the structures of m-benzyne
Al-Saidi, W A
2008-01-01
Diffusion Monte Carlo (DMC) calculations are performed on the monocyclic and bicyclic forms of m-benzyne, which are the equilibrium structures at the CCSD(T) and CCSD levels of coupled cluster theory. We employed multi-configuration self-consistent field trial wave functions which are constructed from a carefully selected 8-electrons-in-8-orbitals complete active space [CAS(8,8)], with CSF coefficients that are reoptimized in the presence of a Jastrow factor. The DMC calculations show that the monocyclic structure is lower in energy than the bicyclic structure by 1.9(2) kcal/mole, in excellent agreement with the best coupled cluster results.
Sample Duplication Method for Monte Carlo Simulation of Large Reaction-Diffusion System
张红东; 陆建明; 杨玉良
1994-01-01
The sample duplication method for the Monte Carlo simulation of large reaction-diffusion system is proposed in this paper. It is proved that the sample duplication method will effectively raise the efficiency and statistical precision of the simulation without changing the kinetic behaviour of the reaction-diffusion system and the critical condition for the bifurcation of the steady-states. The method has been applied to the simulation of spatial and time dissipative structure of Brusselator under the Dirichlet boundary condition. The results presented in this paper definitely show that the sample duplication method provides a very efficient way to sol-’e the master equation of large reaction-diffusion system. For the case of two-dimensional system, it is found that the computation time is reduced at least by a factor of two orders of magnitude compared to the algorithm reported in literature.
Lutsyshyn, Y.; Halley, J. W.
2011-01-01
We present the results of diffusion Monte Carlo calculations of the elastic transmission of a low-energy beam of helium atoms through a suspended slab of superfluid helium. These calculations represent a significant improvement on variational Monte Carlo methods which were previously used to study this problem. The results are consistent with the existence of a condensate-mediated transmission mechanism, which would result in very fast transmission of pulses through a slab.
Zhang, Yongfeng; Jiang, Chao; Bai, Xianming
2017-01-01
This report presents an accelerated kinetic Monte Carlo (KMC) method to compute the diffusivity of hydrogen in hcp metals and alloys, considering both thermally activated hopping and quantum tunneling. The acceleration is achieved by replacing regular KMC jumps in trapping energy basins formed by neighboring tetrahedral interstitial sites, with analytical solutions for basin exiting time and probability. Parameterized by density functional theory (DFT) calculations, the accelerated KMC method is shown to be capable of efficiently calculating hydrogen diffusivity in α-Zr and Zircaloy, without altering the kinetics of long-range diffusion. Above room temperature, hydrogen diffusion in α-Zr and Zircaloy is dominated by thermal hopping, with negligible contribution from quantum tunneling. The diffusivity predicted by this DFT + KMC approach agrees well with that from previous independent experiments and theories, without using any data fitting. The diffusivity along is found to be slightly higher than that along , with the anisotropy saturated at about 1.20 at high temperatures, resolving contradictory results in previous experiments. Demonstrated using hydrogen diffusion in α-Zr, the same method can be extended for on-lattice diffusion in hcp metals, or systems with similar trapping basins. PMID:28106154
An Ab Initio and Kinetic Monte Carlo Simulation Study of Lithium Ion Diffusion on Graphene
Kehua Zhong
2017-07-01
Full Text Available The Li+ diffusion coefficients in Li+-adsorbed graphene systems were determined by combining first-principle calculations based on density functional theory with Kinetic Monte Carlo simulations. The calculated results indicate that the interactions between Li ions have a very important influence on lithium diffusion. Based on energy barriers directly obtained from first-principle calculations for single-Li+ and two-Li+ adsorbed systems, a new equation predicting energy barriers with more than two Li ions was deduced. Furthermore, it is found that the temperature dependence of Li+ diffusion coefficients fits well to the Arrhenius equation, rather than meeting the equation from electrochemical impedance spectroscopy applied to estimate experimental diffusion coefficients. Moreover, the calculated results also reveal that Li+ concentration dependence of diffusion coefficients roughly fits to the equation from electrochemical impedance spectroscopy in a low concentration region; however, it seriously deviates from the equation in a high concentration region. So, the equation from electrochemical impedance spectroscopy technique could not be simply used to estimate the Li+ diffusion coefficient for all Li+-adsorbed graphene systems with various Li+ concentrations. Our work suggests that interactions between Li ions, and among Li ion and host atoms will influence the Li+ diffusion, which determines that the Li+ intercalation dependence of Li+ diffusion coefficient should be changed and complex.
Zhang, Yongfeng; Jiang, Chao; Bai, Xianming
2017-01-01
This report presents an accelerated kinetic Monte Carlo (KMC) method to compute the diffusivity of hydrogen in hcp metals and alloys, considering both thermally activated hopping and quantum tunneling. The acceleration is achieved by replacing regular KMC jumps in trapping energy basins formed by neighboring tetrahedral interstitial sites, with analytical solutions for basin exiting time and probability. Parameterized by density functional theory (DFT) calculations, the accelerated KMC method is shown to be capable of efficiently calculating hydrogen diffusivity in α-Zr and Zircaloy, without altering the kinetics of long-range diffusion. Above room temperature, hydrogen diffusion in α-Zr and Zircaloy is dominated by thermal hopping, with negligible contribution from quantum tunneling. The diffusivity predicted by this DFT + KMC approach agrees well with that from previous independent experiments and theories, without using any data fitting. The diffusivity along is found to be slightly higher than that along , with the anisotropy saturated at about 1.20 at high temperatures, resolving contradictory results in previous experiments. Demonstrated using hydrogen diffusion in α-Zr, the same method can be extended for on-lattice diffusion in hcp metals, or systems with similar trapping basins.
Monte Carlo methods for electromagnetics
Sadiku, Matthew NO
2009-01-01
Until now, novices had to painstakingly dig through the literature to discover how to use Monte Carlo techniques for solving electromagnetic problems. Written by one of the foremost researchers in the field, Monte Carlo Methods for Electromagnetics provides a solid understanding of these methods and their applications in electromagnetic computation. Including much of his own work, the author brings together essential information from several different publications.Using a simple, clear writing style, the author begins with a historical background and review of electromagnetic theory. After addressing probability and statistics, he introduces the finite difference method as well as the fixed and floating random walk Monte Carlo methods. The text then applies the Exodus method to Laplace's and Poisson's equations and presents Monte Carlo techniques for handing Neumann problems. It also deals with whole field computation using the Markov chain, applies Monte Carlo methods to time-varying diffusion problems, and ...
Smart darting diffusion Monte Carlo: Applications to lithium ion-Stockmayer clusters.
Christensen, H M; Jake, L C; Curotto, E
2016-05-07
In a recent investigation [K. Roberts et al., J. Chem. Phys. 136, 074104 (2012)], we have shown that, for a sufficiently complex potential, the Diffusion Monte Carlo (DMC) random walk can become quasiergodic, and we have introduced smart darting-like moves to improve the sampling. In this article, we systematically characterize the bias that smart darting moves introduce in the estimate of the ground state energy of a bosonic system. We then test a simple approach to eliminate completely such bias from the results. The approach is applied for the determination of the ground state of lithium ion-n-dipoles clusters in the n = 8-20 range. For these, the smart darting diffusion Monte Carlo simulations find the same ground state energy and mixed-distribution as the traditional approach for n systems we find that while the ground state energies agree quantitatively with or without smart darting moves, the mixed-distributions can be significantly different. Some evidence is offered to conclude that introducing smart darting-like moves in traditional DMC simulations may produce a more reliable ground state mixed-distribution.
A Monte Carlo study of radon detection in cylindrical diffusion chambers
Rickards, Jorge, E-mail: rickards@fisica.unam.m [Instituto de Fisica, Universidad Nacional Autonoma de Mexico, Circuito de la Investigacion Cientifica, Ciudad Universitaria, Delegacion Coyoacan, 04520 Mexico, D.F. (Mexico); Golzarri, Jose-Ignacio, E-mail: golzarri@fisica.unam.m [Instituto de Fisica, Universidad Nacional Autonoma de Mexico, Circuito de la Investigacion Cientifica, Ciudad Universitaria, Delegacion Coyoacan, 04520 Mexico, D.F. (Mexico); Espinosa, Guillermo, E-mail: espinosa@fisica.unam.m [Instituto de Fisica, Universidad Nacional Autonoma de Mexico, Circuito de la Investigacion Cientifica, Ciudad Universitaria, Delegacion Coyoacan, 04520 Mexico, D.F. (Mexico)
2010-05-15
The functioning of radon diffusion chambers was studied using the Monte Carlo code RAMMX developed here. The alpha particles from radon are assumed randomly produced in the volume of the cylinder, and those from the progeny are assumed to originate randomly at the cylindrical surface. The energy spectrum, the distribution of incident angles, and the distribution of path lengths of the alpha particles on the detector were obtained. These quantities vary depending on input parameters such as initial alpha particle energy, radius and depth of the diffusion chamber, detector size and atmospheric pressure. The calculated energy spectrum for both {sup 222}Rn and {sup 220}Rn was compared with experiment, permitting the identification of each peak and its origin, and a better understanding of radon monitoring. Three aspects not considered in previous calculations are progeny alphas coming from surfaces of the monitor, taking into account the atmospheric pressure, and including the isotope {sup 220}Rn.
Kondrashova, Daria; Valiullin, Rustem; Kärger, Jörg; Bunde, Armin
2017-07-01
Nanoporous silicon consisting of tubular pores imbedded in a silicon matrix has found many technological applications and provides a useful model system for studying phase transitions under confinement. Recently, a model for mass transfer in these materials has been elaborated [Kondrashova et al., Sci. Rep. 7, 40207 (2017)], which assumes that adjacent channels can be connected by "bridges" (with probability pbridge) which allows diffusion perpendicular to the channels. Along the channels, diffusion can be slowed down by "necks" which occur with probability pneck. In this paper we use Monte-Carlo simulations to study diffusion along the channels and perpendicular to them, as a function of pbridge and pneck, and find remarkable correlations between the diffusivities in longitudinal and radial directions. For clarifying the diffusivity in radial direction, which is governed by the concentration of bridges, we applied percolation theory. We determine analytically how the critical concentration of bridges depends on the size of the system and show that it approaches zero in the thermodynamic limit. Our analysis suggests that the critical properties of the model, including the diffusivity in radial direction, are in the universality class of two-dimensional lattice percolation, which is confirmed by our numerical study.
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.
Bardenet, R.
2012-01-01
ISBN:978-2-7598-1032-1; International audience; Bayesian inference often requires integrating some function with respect to a posterior distribution. Monte Carlo methods are sampling algorithms that allow to compute these integrals numerically when they are not analytically tractable. We review here the basic principles and the most common Monte Carlo algorithms, among which rejection sampling, importance sampling and Monte Carlo Markov chain (MCMC) methods. We give intuition on the theoretic...
Monte Carlo simulation on the diffusion of polymer in narrow periodical channels
Chen, Ying-Cai; Zhou, Yan-Li; Wang, Chao
2017-08-01
Diffusion of polymer in narrow periodical channels, patterned alternately into part α and part β with the same length lp/2, was studied by using Monte Carlo simulation. The interaction between polymer and channel α is purely repulsive, while that between polymer and channel β is attractive. Results show that the diffusion of polymer is remarkably affected by the periodicity of channel, and the diffusion constant D changes periodically with the polymer length N. At the peaks of D, the projected length of polymer along the channel is an even multiple of lp/2, and the diffusion of polymer in periodical channel is nearly the same as that of polymer in homogeneous channel. While at the valleys of D, the projected length of polymer is an odd multiple of lp/2, and polymer is in a trapped state for a long time and it rapidly jumps to other trapped regions during the diffusion process. The physical mechanisms are discussed from the view of polymer-channel interaction energy landscape.
On the use of SERPENT Monte Carlo code to generate few group diffusion constants
Piovezan, Pamela, E-mail: pamela.piovezan@ctmsp.mar.mil.b [Centro Tecnologico da Marinha em Sao Paulo (CTMSP), Sao Paulo, SP (Brazil); Carluccio, Thiago; Domingos, Douglas Borges; Rossi, Pedro Russo; Mura, Luiz Felipe, E-mail: fermium@cietec.org.b, E-mail: thiagoc@ipen.b [Fermium Tecnologia Nuclear, Sao Paulo, SP (Brazil); Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)
2011-07-01
The accuracy of diffusion reactor codes strongly depends on the quality of the groups constants processing. For many years, the generation of such constants was based on 1-D infinity cell transport calculations. Some developments using collision probability or the method of characteristics allow, nowadays, 2-D assembly group constants calculations. However, these 1-D and 2-D codes how some limitations as , for example, on complex geometries and in the neighborhood of heavy absorbers. On the other hand, since Monte Carlos (MC) codes provide accurate neutro flux distributions, the possibility of using these solutions to provide group constants to full-core reactor diffusion simulators has been recently investigated, especially for the cases in which the geometry and reactor types are beyond the capability of the conventional deterministic lattice codes. The two greatest difficulties on the use of MC codes to group constant generation are the computational costs and the methodological incompatibility between analog MC particle transport simulation and deterministic transport methods based in several approximations. The SERPENT code is a 3-D continuous energy MC transport code with built-in burnup capability that was specially optimized to generate these group constants. In this work, we present the preliminary results of using the SERPENT MC code to generate 3-D two-group diffusion constants for a PWR like assembly. These constants were used in the CITATION diffusion code to investigate the effects of the MC group constants determination on the neutron multiplication factor diffusion estimate. (author)
Hop-Diffusion Monte Carlo for Epipolar Geometry Estimation between Very Wide-Baseline Images.
Brahmachari, Aveek S; Sarkar, Sudeep
2013-03-01
We present a Monte Carlo approach for epipolar geometry estimation that efficiently searches for minimal sets of inlier correspondences in the presence of many outliers in the putative correspondence set, a condition that is prevalent when we have wide baselines, significant scale changes, rotations in depth, occlusion, and repeated patterns. The proposed Monte Carlo algorithm uses Balanced LOcal and Global Search (BLOGS) to find the best minimal set of correspondences. The local search is a diffusion process using Joint Feature Distributions that captures the dependencies among the correspondences. And, the global search is a hopping search process across the minimal set space controlled by photometric properties. Using a novel experimental protocol that involves computing errors for manually marked ground truth points and images with outlier rates as high as 90 percent, we find that BLOGS is better than related approaches such as MAPSAC, NAPSAC, and BEEM. BLOGS results are of similar quality as other approaches, but BLOGS generate them in 10 times fewer iterations. The time per iteration for BLOGS is also the lowest among the ones we studied.
Calculating potential energy curves with fixed-node diffusion Monte Carlo: CO and N2
Powell, Andrew D.; Dawes, Richard
2016-12-01
This study reports on the prospect for the routine use of Quantum Monte Carlo (QMC) for the electronic structure problem, applying fixed-node Diffusion Monte Carlo (DMC) to generate highly accurate Born-Oppenheimer potential energy curves (PECs) for small molecular systems. The singlet ground electronic states of CO and N2 were used as test cases. The PECs obtained by DMC employing multiconfigurational trial wavefunctions were compared with those obtained by conventional high-accuracy electronic structure methods such as multireference configuration interaction and/or the best available empirical spectroscopic curves. The goal was to test whether a straightforward procedure using available QMC codes could be applied robustly and reliably. Results obtained with DMC codes were found to be in close agreement with the benchmark PECs, and the n3 scaling with the number of electrons (compared with n7 or worse for conventional high-accuracy quantum chemistry) could be advantageous depending on the system size. Due to a large pre-factor in the scaling, for the small systems tested here, it is currently still much more computationally intensive to compute PECs with QMC. Nevertheless, QMC algorithms are particularly well-suited to large-scale parallelization and are therefore likely to become more relevant for future massively parallel hardware architectures.
Dunn, William L
2012-01-01
Exploring Monte Carlo Methods is a basic text that describes the numerical methods that have come to be known as "Monte Carlo." The book treats the subject generically through the first eight chapters and, thus, should be of use to anyone who wants to learn to use Monte Carlo. The next two chapters focus on applications in nuclear engineering, which are illustrative of uses in other fields. Five appendices are included, which provide useful information on probability distributions, general-purpose Monte Carlo codes for radiation transport, and other matters. The famous "Buffon's needle proble
Self-learning kinetic Monte Carlo simulations of Al diffusion in Mg
Nandipati, Giridhar; Govind, Niranjan; Andersen, Amity; Rohatgi, Aashish
2016-03-16
Atomistic on-lattice self-learning kinetic Monte Carlo (SLKMC) method was used to examine the vacancy-mediated diffusion of an Al atom in pure hcp Mg. Local atomic environment dependent activation barriers for vacancy-atom exchange processes were calculated on-the-fly using climbing image nudged-elastic band method (CI-NEB) and using a Mg-Al binary modified embedded-atom method (MEAM) interatomic potential. Diffusivities of vacancy and Al atom in pure Mg were obtained from SLKMC simulations and are compared with values available in the literature that are obtained from experiments and first-principle calculations. Al Diffusivities obtained from SLKMC simulations are lower, due to larger activation barriers and lower diffusivity prefactors, than those available in the literature but have same order of magnitude. We present all vacancy-Mg and vacancy-Al atom exchange processes and their activation barriers that were identified in SLKMC simulations. We will describe a simple mapping scheme to map a hcp lattice on to a simple cubic lattice that would enable hcp lattices to be simulated in an on-lattice KMC framework. We also present the pattern recognition scheme used in SLKMC simulations.
Tubiana, Jerome; Kass, Alex J.; Newman, Maya Y.; Levitz, David
2015-07-01
Detecting pre-cancer in epithelial tissues such as the cervix is a challenging task in low-resources settings. In an effort to achieve low cost cervical cancer screening and diagnostic method for use in low resource settings, mobile colposcopes that use a smartphone as their engine have been developed. Designing image analysis software suited for this task requires proper modeling of light propagation from the abnormalities inside tissues to the camera of the smartphones. Different simulation methods have been developed in the past, by solving light diffusion equations, or running Monte Carlo simulations. Several algorithms exist for the latter, including MCML and the recently developed MCX. For imaging purpose, the observable parameter of interest is the reflectance profile of a tissue under some specific pattern of illumination and optical setup. Extensions of the MCX algorithm to simulate this observable under these conditions were developed. These extensions were validated against MCML and diffusion theory for the simple case of contact measurements, and reflectance profiles under colposcopy imaging geometry were also simulated. To validate this model, the diffuse reflectance profiles of tissue phantoms were measured with a spectrometer under several illumination and optical settings for various homogeneous tissues phantoms. The measured reflectance profiles showed a non-trivial deviation across the spectrum. Measurements of an added absorber experiment on a series of phantoms showed that absorption of dye scales linearly when fit to both MCX and diffusion models. More work is needed to integrate a pupil into the experiment.
Ramilowski, Jordan A; Farrelly, David
2010-10-21
The fixed-node diffusion Monte Carlo (DMC) algorithm is a powerful way of computing excited state energies in a remarkably diverse number of contexts in quantum chemistry and physics. The main difficulty in implementing the procedure lies in obtaining a good estimate of the nodal surface of the excited state in question. Although the nodal surface can sometimes be obtained from symmetry or by making approximations this is not always the case. In any event, nodal surfaces are usually obtained in an ad hoc way. In fact, the search for nodal surfaces can be formulated as an optimization problem within the DMC procedure itself. Here we investigate the use of a genetic algorithm to systematically and automatically compute nodal surfaces. Application is made to the computation of excited states of the HCN-(4)He complex and to the computation of tunneling splittings in the hydrogen bonded HCl-HCl complex.
Phase Stability of TiO$_2$ Polymorphs from Diffusion Quantum Monte Carlo
Luo, Ye; Shulenburger, Luke; Krogel, Jaron T; Heinonen, Olle; Kent, Paul R C
2016-01-01
Titanium dioxide, TiO$_2$, has multiple applications in catalysis, energy conversion and memristive devices because of its electronic structure. Most of these applications utilize the naturally existing phases: rutile, anatase and brookite. Despite the simple form of TiO$_2$ and its wide uses, there is long-standing disagreement between theory and experiment on the energetic ordering of these phases that has never been resolved. We present the first analysis of phase stability at zero temperature using the highly accurate many-body fixed node diffusion Quantum Monte Carlo (QMC) method. We also include the effects of temperature by calculating the Helmholtz free energy including both internal energy and vibrational contributions from density functional perturbation theory based quasi harmonic phonon calculations. Our QMC calculations find that anatase is the most stable phase at zero temperature, consistent with many previous mean-field calculations. However, at elevated temperatures, rutile becomes the most s...
Monte Carlo Study of Temperature-dependent Non-diffusive Thermal Transport in Si Nanowires
Ma, Lei; Liu, Mengmeng; Zhao, Xuxin; Wu, Qixing; Sun, Hongyuan
2016-01-01
Non-diffusive thermal transport has gained extensive research interest recently due to its important implications on fundamental understanding of material phonon mean free path distributions and many nanoscale energy applications. In this work, we systematically investigate the role of boundary scattering and nanowire length on the nondiffusive thermal transport in thin silicon nanowires by rigorously solving the phonon Boltzmann transport equation using a variance reduced Monte Carlo technique across a range of temperatures. The simulations use the complete phonon dispersion and spectral lifetime data obtained from first-principle density function theory calculations as input without any adjustable parameters. Our BTE simulation results show that the nanowire length plays an important role in determining the thermal conductivity of silicon nanowires. In addition, our simulation results suggest significant phonon confinement effect for the previously measured silicon nanowires. These findings are important fo...
Diffusion Monte Carlo ab initio calculations to study wetting properties of graphene
Wu, Yanbin; Zheng, Huihuo; Wagner, Lucas; Aluru, N. R.
2013-11-01
For applications of graphene in water, including for example desalination and DNA sequencing, it is critical to understand the wetting properties of graphene. In this work, we investigate the wetting properties using data from highly accurate diffusion quantum Monte Carlo (DMC) calculations, which treat electron correlation explicitly. Our DMC data show a strong graphene-water interaction, indicating graphene surface is more hydrophilic than previously believed. This has been recently confirmed by experiments [Li et al. Nat. Mater. 2013, doi:10.1038/nmat3709]. The unusually strong interaction can be attributed to weak bonding formed between graphene and water. Besides its inadequate description of dispersion interactions as commonly reported in the literature, density function theory (DFT) fails to describe the correct charge transfer, which leads to an underestimate of graphene-water binding energy. Our DMC calculations can provide insight to experimentalists seeking to understand water-graphene interfaces and to theorists improving DFT for weakly bound systems.
Monte Carlo simulation of diffuse attenuation coefficient in presence of non uniform profiles
Desa, E.S.; Desai, R.G.P.; Desa, B.A.E.
This paper presents a Monte Carlo simulation of the vertical depth structure of the downward attenuation coefficient (K sub(d)), and the irradiance reflectance (R) for a given profile of chlorophyll. The results are in quantitaive agreement...
Barrier heights of hydrogen-transfer reactions with diffusion quantum monte carlo method.
Zhou, Xiaojun; Wang, Fan
2017-04-30
Hydrogen-transfer reactions are an important class of reactions in many chemical and biological processes. Barrier heights of H-transfer reactions are underestimated significantly by popular exchange-correlation functional with density functional theory (DFT), while coupled-cluster (CC) method is quite expensive and can be applied only to rather small systems. Quantum Monte-Carlo method can usually provide reliable results for large systems. Performance of fixed-node diffusion quantum Monte-Carlo method (FN-DMC) on barrier heights of the 19 H-transfer reactions in the HTBH38/08 database is investigated in this study with the trial wavefunctions of the single-Slater-Jastrow form and orbitals from DFT using local density approximation. Our results show that barrier heights of these reactions can be calculated rather accurately using FN-DMC and the mean absolute error is 1.0 kcal/mol in all-electron calculations. Introduction of pseudopotentials (PP) in FN-DMC calculations improves efficiency pronouncedly. According to our results, error of the employed PPs is smaller than that of the present CCSD(T) and FN-DMC calculations. FN-DMC using PPs can thus be applied to investigate H-transfer reactions involving larger molecules reliably. In addition, bond dissociation energies of the involved molecules using FN-DMC are in excellent agreement with reference values and they are even better than results of the employed CCSD(T) calculations using the aug-cc-pVQZ basis set. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Mean field simulation for Monte Carlo integration
Del Moral, Pierre
2013-01-01
In the last three decades, there has been a dramatic increase in the use of interacting particle methods as a powerful tool in real-world applications of Monte Carlo simulation in computational physics, population biology, computer sciences, and statistical machine learning. Ideally suited to parallel and distributed computation, these advanced particle algorithms include nonlinear interacting jump diffusions; quantum, diffusion, and resampled Monte Carlo methods; Feynman-Kac particle models; genetic and evolutionary algorithms; sequential Monte Carlo methods; adaptive and interacting Marko
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.
The Martian diffuse aurora: Monte Carlo simulations and comparison with IUVS-MAVEN observations
Gerard, J. C. M. C.; Soret, L.; Schneider, N. M.; Shematovich, V.; Bisikalo, D.; Bougher, S. W.; Jain, S.; Lillis, R. J.; Mitchell, D. L.; Jakosky, B. M.; Deighan, J.; Larson, D. E.
2016-12-01
A new type of Martian aurora, characterized by an extended spatial distribution, an altitude lower than the discrete aurora and electron precipitation up to 200 keV has been observed following solar activity on several occasions with the IUVS on board the MAVEN spacecraft. We describe the results of Monte Carlo simulations of the production of several ultraviolet and visible auroral emissions for initial electron energies from 0.1 to 200 keV. These include the CO2+ ultraviolet doublet (UVD) at 288.3 and 289.6 nm and the Fox-Duffendack-Barker (FDB) bands, CO Cameron and Fourth Positive bands, OI 130.4 and 297.2 nm and CI 156.1 nm and 165.7 nm multiplets. We calculate the nadir and limb intensities of several of these emissions for a unit precipitated energy flux. Our results indicate that electrons in the range 100-200 keV produce maximum CO2+ UVD emission near 75 km. We combine SWEA and SEP electron energy spectra measured during diffuse aurora to calculate the volume emission rates and compare with IUVS observations of the emission limb profiles. The strongest predicted emissions are the CO2+ FDB, UVD and the CO Cameron bands. The metastable a 3Π state which radiates the Cameron bands is deactivated by collisions below 110 km. As a consequence, we show that the CO2+ UVD to the Cameron bands ratio increases at low altitude in the energetic diffuse aurora.
Monte Carlo simulations for a Lotka-type model with reactant surface diffusion and interactions.
Zvejnieks, G; Kuzovkov, V N
2001-05-01
The standard Lotka-type model, which was introduced for the first time by Mai et al. [J. Phys. A 30, 4171 (1997)] for a simplified description of autocatalytic surface reactions, is generalized here for a case of mobile and energetically interacting reactants. The mathematical formalism is proposed for determining the dependence of transition rates on the interaction energy (and temperature) for the general mathematical model, and the Lotka-type model, in particular. By means of Monte Carlo computer simulations, we have studied the impact of diffusion (with and without energetic interactions between reactants) on oscillatory properties of the A+B-->2B reaction. The diffusion leads to a desynchronization of oscillations and a subsequent decrease of oscillation amplitude. The energetic interaction between reactants has a dual effect depending on the type of mobile reactants. In the limiting case of mobile reactants B the repulsion results in a decrease of amplitudes. However, these amplitudes increase if reactants A are mobile and repulse each other. A simplified interpretation of the obtained results is given.
A Monte Carlo Synthetic-Acceleration Method for Solving the Thermal Radiation Diffusion Equation
Evans, Thomas M [ORNL; Mosher, Scott W [ORNL; Slattery, Stuart [University of Wisconsin, Madison
2014-01-01
We present a novel synthetic-acceleration based Monte Carlo method for solving the equilibrium thermal radiation diusion equation in three dimensions. The algorithm performance is compared against traditional solution techniques using a Marshak benchmark problem and a more complex multiple material problem. Our results show that not only can our Monte Carlo method be an eective solver for sparse matrix systems, but also that it performs competitively with deterministic methods including preconditioned Conjugate Gradient while producing numerically identical results. We also discuss various aspects of preconditioning the method and its general applicability to broader classes of problems.
Quantum Monte Carlo simulation
Wang, Yazhen
2011-01-01
Contemporary scientific studies often rely on the understanding of complex quantum systems via computer simulation. This paper initiates the statistical study of quantum simulation and proposes a Monte Carlo method for estimating analytically intractable quantities. We derive the bias and variance for the proposed Monte Carlo quantum simulation estimator and establish the asymptotic theory for the estimator. The theory is used to design a computational scheme for minimizing the mean square er...
Monte Carlo transition probabilities
Lucy, L. B.
2001-01-01
Transition probabilities governing the interaction of energy packets and matter are derived that allow Monte Carlo NLTE transfer codes to be constructed without simplifying the treatment of line formation. These probabilities are such that the Monte Carlo calculation asymptotically recovers the local emissivity of a gas in statistical equilibrium. Numerical experiments with one-point statistical equilibrium problems for Fe II and Hydrogen confirm this asymptotic behaviour. In addition, the re...
Sasanka ARE; Markos A.KATSOULAKIS; Anders SZEPESSY
2009-01-01
Kinetic Monte Carlo methods provide a powerful computational tool for the simulation of microscopic processes such as the diffusion of interacting particles on a surface, at a detailed atomistic level. However such algorithms are typically computationally expensive and are restricted to fairly small spatiotemporal scales. One approach towards overcoming this problem was the development of coarse-grained Monte Carlo algorithms. In recent literature, these methods were shown to be capable of efficiently describing much larger length scales while still incorporating information on microscopic interactions and fluctuations. In this paper, a coarse-grained Langevin system of stochastic differential equations as approximations of diffusion of interacting particles is derived, based on these earlier coarse-grained models. The authors demonstrate the asymptotic equivalence of transient and long time behavior of the Langevin approximation and the underlying microscopic process, using asymptotics methods such as large deviations for interacting particles systems, and furthermore, present corresponding numerical simulations, comparing statistical quantities like mean paths, auto correlations and power spectra of the microscopic and the approximating Langevin processes. Finally, it is shown that the Langevin approximations presented here are much more computationally efficient than conventional Kinetic Monte Carlo methods, since in addition to the reduction in the number of spatial degrees of freedom in coarse-grained Monte Carlo methods, the Langevin system of stochastic differential equations allows for multiple particle moves in a single timestep.
Monte Carlo Study of the Diffusion of CO Molecules inside Anthraquinone Hexagons on Cu(111)
Kim, Kwangmoo; Einstein, T. L.; Wyrick, Jon; Bartels, Ludwig
2010-03-01
Using Monte Carlo calculations of the two-di-men-sion-al (2D) lattice gas model, we study the diffusion of CO molecules inside anthraquinone (AQ) hexagons on a Cu(111) plane. We use experimentally-derived CO-CO interactionsfootnotetextK.L. Wong, , L. Bartels, J. Chem.Phys.123, 201102 (2005) and the analytic expression for the long-range surface-state- mediated interactionsfootnotetextK. Berland, TLE, and P. Hyldgaard, Phys.Rev. B 80, 155431 (2009) to describe the CO-AQ interactions. We assume that the CO-CO interactions are not affected by the presence of AQ's and that the CO-AQ interactions can be controlled by varying the intra-surface-state (ISS) reflectance r and the ISS phase shift δ of the indirect-electronic adsorbate-pair interactions. Comparing our results with experimental observations, we find that not only pair but also surface-state-mediated trio interactionsfootnotetextP. Hyldgaard and T.L. Einstein, EPL 59, 265 (2002) are needed to understand the data.
Fredriksson, Ingemar; Burdakov, Oleg; Larsson, Marcus; Strömberg, Tomas
2013-12-01
The tissue fraction of red blood cells (RBCs) and their oxygenation and speed-resolved perfusion are estimated in absolute units by combining diffuse reflectance spectroscopy (DRS) and laser Doppler flowmetry (LDF). The DRS spectra (450 to 850 nm) are assessed at two source-detector separations (0.4 and 1.2 mm), allowing for a relative calibration routine, whereas LDF spectra are assessed at 1.2 mm in the same fiber-optic probe. Data are analyzed using nonlinear optimization in an inverse Monte Carlo technique by applying an adaptive multilayered tissue model based on geometrical, scattering, and absorbing properties, as well as RBC flow-speed information. Simulations of 250 tissue-like models including up to 2000 individual blood vessels were used to evaluate the method. The absolute root mean square (RMS) deviation between estimated and true oxygenation was 4.1 percentage units, whereas the relative RMS deviations for the RBC tissue fraction and perfusion were 19% and 23%, respectively. Examples of in vivo measurements on forearm and foot during common provocations are presented. The method offers several advantages such as simultaneous quantification of RBC tissue fraction and oxygenation and perfusion from the same, predictable, sampling volume. The perfusion estimate is speed resolved, absolute (% RBC×mm/s), and more accurate due to the combination with DRS.
Heinisch, H.L.; Trinkaus, H.; Singh, Bachu Narain
2007-01-01
and confirmed by kinetic Monte Carlo (KMC) simulations. Here we report on KMC simulations investigating a different transition from 1D to 3D diffusion of 1D gliding loops for which their 1D migration is interrupted by occasional 2D migration due to conservative climb by dislocation core diffusion within a plane...... transverse to their 1D glide direction. Their transition from 1D to 3D kinetics is significantly different from that due to direction changes. The KMC results are compared to an analytical description of this diffusion mode in the form of a master curve relating the 1D normalized sink strength...
Shulenburger, Luke; Desjarlais, M P
2015-01-01
Motivated by the disagreement between recent diffusion Monte Carlo calculations and experiments on the phase transition pressure between the ambient and beta-Sn phases of silicon, we present a study of the HCP to BCC phase transition in beryllium. This lighter element provides an oppor- tunity for directly testing many of the approximations required for calculations on silicon and may suggest a path towards increasing the practical accuracy of diffusion Monte Carlo calculations of solids in general. We demonstrate that the single largest approximation in these calculations is the pseudopotential approximation. After removing this we find excellent agreement with experiment for the ambient HCP phase and results similar to careful calculations using density functional theory for the phase transition pressure.
Approaching Chemical Accuracy with Quantum Monte Carlo
Petruzielo, Frank R.; Toulouse, Julien; Umrigar, C. J.
2012-01-01
International audience; 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 agreem...
McCoy, Anne B.; Ford, Jason E.; Marlett, Melanie L.; Petit, Andrew S.
2014-06-01
In this work, an extension to diffusion Monte Carlo (DMC) is proposed, allowing for the simultaneous calculation of the energy and wave function of multiple rotationally excited states of floppy molecules. The total wave function is expanded into a set of Dirac δ-functions called walkers, while the rotational portion of the wave function is expanded in a symmetric top basis set. Each walker is given a rotational state vector containing coefficients for all states of interest. The positions of the atoms and the coefficients in the state vector evolve according to the split operator approximation of the quantum propagator. The method was benchmarked by comparing calculated rotation-vibration energies for H_3^+, H_2D^+, and H_3O^+ to experimental values. For low to moderate values of J, the resulting energies are within the statistical uncertainty of the calculation. Rotation-vibration coupling is captured through flexibility introduced in the form of the vibrational wave function. This coupling is found to increase with increasing J-values. Based on the success achieved through these systems, the method was applied to CH_5^+ and its deuterated isotopologues for v = 0, J ≥ 10. Based on these calculations, the energy level structure of CH_5^+ is found to resemble that for a of a spherical top, and excitations up to J = 10 displayed insignificant rotation-vibration coupling. Extensions of this approach that explicitly account for vibrations will also be discussed. ` A. S. Petit, J. E. Ford and A. B. McCoy, J. Phys. Chem. A, in press, K. D. Jordan Festschrift, DOI: 10.1021/jp408821a
Hrivnacova, I; Berejnov, V V; Brun, R; Carminati, F; Fassò, A; Futo, E; Gheata, A; Caballero, I G; Morsch, Andreas
2003-01-01
The concept of Virtual Monte Carlo (VMC) has been developed by the ALICE Software Project to allow different Monte Carlo simulation programs to run without changing the user code, such as the geometry definition, the detector response simulation or input and output formats. Recently, the VMC classes have been integrated into the ROOT framework, and the other relevant packages have been separated from the AliRoot framework and can be used individually by any other HEP project. The general concept of the VMC and its set of base classes provided in ROOT will be presented. Existing implementations for Geant3, Geant4 and FLUKA and simple examples of usage will be described.
Self-consistent kinetic lattice Monte Carlo
Horsfield, A.; Dunham, S.; Fujitani, Hideaki
1999-07-01
The authors present a brief description of a formalism for modeling point defect diffusion in crystalline systems using a Monte Carlo technique. The main approximations required to construct a practical scheme are briefly discussed, with special emphasis on the proper treatment of charged dopants and defects. This is followed by tight binding calculations of the diffusion barrier heights for charged vacancies. Finally, an application of the kinetic lattice Monte Carlo method to vacancy diffusion is presented.
Zhu, Caigang; Liu, Quan
2012-01-01
We present a hybrid method that combines a multilayered scaling method and a perturbation method to speed up the Monte Carlo simulation of diffuse reflectance from a multilayered tissue model with finite-size tumor-like heterogeneities. The proposed method consists of two steps. In the first step, a set of photon trajectory information generated from a baseline Monte Carlo simulation is utilized to scale the exit weight and exit distance of survival photons for the multilayered tissue model. In the second step, another set of photon trajectory information, including the locations of all collision events from the baseline simulation and the scaling result obtained from the first step, is employed by the perturbation Monte Carlo method to estimate diffuse reflectance from the multilayered tissue model with tumor-like heterogeneities. Our method is demonstrated to shorten simulation time by several orders of magnitude. Moreover, this hybrid method works for a larger range of probe configurations and tumor models than the scaling method or the perturbation method alone.
Hart, Vern P; Doyle, Timothy E
2013-09-01
A Monte Carlo method was derived from the optical scattering properties of spheroidal particles and used for modeling diffuse photon migration in biological tissue. The spheroidal scattering solution used a separation of variables approach and numerical calculation of the light intensity as a function of the scattering angle. A Monte Carlo algorithm was then developed which utilized the scattering solution to determine successive photon trajectories in a three-dimensional simulation of optical diffusion and resultant scattering intensities in virtual tissue. Monte Carlo simulations using isotropic randomization, Henyey-Greenstein phase functions, and spherical Mie scattering were additionally developed and used for comparison to the spheroidal method. Intensity profiles extracted from diffusion simulations showed that the four models differed significantly. The depth of scattering extinction varied widely among the four models, with the isotropic, spherical, spheroidal, and phase function models displaying total extinction at depths of 3.62, 2.83, 3.28, and 1.95 cm, respectively. The results suggest that advanced scattering simulations could be used as a diagnostic tool by distinguishing specific cellular structures in the diffused signal. For example, simulations could be used to detect large concentrations of deformed cell nuclei indicative of early stage cancer. The presented technique is proposed to be a more physical description of photon migration than existing phase function methods. This is attributed to the spheroidal structure of highly scattering mitochondria and elongation of the cell nucleus, which occurs in the initial phases of certain cancers. The potential applications of the model and its importance to diffusive imaging techniques are discussed.
Zhdanov, Vladimir P
2002-03-01
Discussing the effect of adsorbate-adsorbate lateral interactions on the kinetics of heterogeneous catalytic reactions, Zvejnieks and Kuzovkov [Phys. Rev. E 63, 051104 (2001)] conclude that in the case of adsorbed particles the Metropolis Monte Carlo dynamics is meaningless and propose to use their own dynamics, which is equivalent to the Glauber dynamics. In this Comment, I show that these and other conclusions and prescriptions by Zvejnieks and Kuzovkov are not in line with the general principles of simulations of rate processes in adsorbed overlayers.
Cecilia Maya
2004-12-01
Full Text Available El método Monte Carlo se aplica a varios casos de valoración de opciones financieras. El método genera una buena aproximación al comparar su precisión con la de otros métodos numéricos. La estimación que produce la versión Cruda de Monte Carlo puede ser aún más exacta si se recurre a metodologías de reducción de la varianza entre las cuales se sugieren la variable antitética y de la variable de control. Sin embargo, dichas metodologías requieren un esfuerzo computacional mayor por lo cual las mismas deben ser evaluadas en términos no sólo de su precisión sino también de su eficiencia.
Monte Carlo and nonlinearities
Dauchet, Jérémi; Blanco, Stéphane; Caliot, Cyril; Charon, Julien; Coustet, Christophe; Hafi, Mouna El; Eymet, Vincent; Farges, Olivier; Forest, Vincent; Fournier, Richard; Galtier, Mathieu; Gautrais, Jacques; Khuong, Anaïs; Pelissier, Lionel; Piaud, Benjamin; Roger, Maxime; Terrée, Guillaume; Weitz, Sebastian
2016-01-01
The Monte Carlo method is widely used to numerically predict systems behaviour. However, its powerful incremental design assumes a strong premise which has severely limited application so far: the estimation process must combine linearly over dimensions. Here we show that this premise can be alleviated by projecting nonlinearities on a polynomial basis and increasing the configuration-space dimension. Considering phytoplankton growth in light-limited environments, radiative transfer in planetary atmospheres, electromagnetic scattering by particles and concentrated-solar-power-plant productions, we prove the real world usability of this advance on four test-cases that were so far regarded as impracticable by Monte Carlo approaches. We also illustrate an outstanding feature of our method when applied to sharp problems with interacting particles: handling rare events is now straightforward. Overall, our extension preserves the features that made the method popular: addressing nonlinearities does not compromise o...
Wollaber, Allan Benton [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2016-06-16
This is a powerpoint presentation which serves as lecture material for the Parallel Computing summer school. It goes over the fundamentals of the Monte Carlo calculation method. The material is presented according to the following outline: Introduction (background, a simple example: estimating π), Why does this even work? (The Law of Large Numbers, The Central Limit Theorem), How to sample (inverse transform sampling, rejection), and An example from particle transport.
Alexandrakis, G; Farrell, T J; Patterson, M S
2000-05-01
We propose a hybrid Monte Carlo (MC) diffusion model for calculating the spatially resolved reflectance amplitude and phase delay resulting from an intensity-modulated pencil beam vertically incident on a two-layer turbid medium. The model combines the accuracy of MC at radial distances near the incident beam with the computational efficiency afforded by a diffusion calculation at further distances. This results in a single forward calculation several hundred times faster than pure MC, depending primarily on model parameters. Model predictions are compared with MC data for two cases that span the extremes of physiologically relevant optical properties: skin overlying fat and skin overlying muscle, both in the presence of an exogenous absorber. It is shown that good agreement can be achieved for radial distances from 0.5 to 20 mm in both cases. However, in the skin-on-muscle case the choice of model parameters and the definition of the diffusion coefficient can lead to some interesting discrepancies.
Adaptive Multilevel Monte Carlo Simulation
Hoel, H
2011-08-23
This work generalizes a multilevel forward Euler Monte Carlo method introduced in Michael B. Giles. (Michael Giles. Oper. Res. 56(3):607–617, 2008.) for the approximation of expected values depending on the solution to an Itô stochastic differential equation. The work (Michael Giles. Oper. Res. 56(3):607– 617, 2008.) proposed and analyzed a forward Euler multilevelMonte Carlo method based on a hierarchy of uniform time discretizations and control variates to reduce the computational effort required by a standard, single level, Forward Euler Monte Carlo method. This work introduces an adaptive hierarchy of non uniform time discretizations, generated by an adaptive algorithmintroduced in (AnnaDzougoutov et al. Raùl Tempone. Adaptive Monte Carlo algorithms for stopped diffusion. In Multiscale methods in science and engineering, volume 44 of Lect. Notes Comput. Sci. Eng., pages 59–88. Springer, Berlin, 2005; Kyoung-Sook Moon et al. Stoch. Anal. Appl. 23(3):511–558, 2005; Kyoung-Sook Moon et al. An adaptive algorithm for ordinary, stochastic and partial differential equations. In Recent advances in adaptive computation, volume 383 of Contemp. Math., pages 325–343. Amer. Math. Soc., Providence, RI, 2005.). This form of the adaptive algorithm generates stochastic, path dependent, time steps and is based on a posteriori error expansions first developed in (Anders Szepessy et al. Comm. Pure Appl. Math. 54(10):1169– 1214, 2001). Our numerical results for a stopped diffusion problem, exhibit savings in the computational cost to achieve an accuracy of ϑ(TOL),from(TOL−3), from using a single level version of the adaptive algorithm to ϑ(((TOL−1)log(TOL))2).
Ancora, Daniele; Zacharopoulos, Athanasios; Ripoll, Jorge; Zacharakis, Giannis
2015-07-01
One of the major challenges within Optical Imaging, photon propagation through clear layers embedded between scattering tissues, can be now efficiently modelled in real-time thanks to the Monte Carlo approach based on GPU. Because of its nature, the photon propagation problem can be very easily parallelized and ran on low cost hardware, avoiding the need for expensive Super Computers. A comparison between Diffusion and MC photon propagation theory is presented in this work with application to neuroimaging, investigating low scattering regions in a mouse-like phantom. Regions such as the Cerebral Spinal Fluid, are currently not taken into account in the classical computational models because of the impossibility to accurately simulate light propagation using fast Diffusive Equation approaches, leading to inaccuracies during the reconstruction process. The goal of the study presented here, is to reduce and further improve the computation accuracy of the reconstructed solution in a highly realistic scenario in the case of neuroimaging in preclinical mouse models.
LMC: Logarithmantic Monte Carlo
Mantz, Adam B.
2017-06-01
LMC is a Markov Chain Monte Carlo engine in Python that implements adaptive Metropolis-Hastings and slice sampling, as well as the affine-invariant method of Goodman & Weare, in a flexible framework. It can be used for simple problems, but the main use case is problems where expensive likelihood evaluations are provided by less flexible third-party software, which benefit from parallelization across many nodes at the sampling level. The parallel/adaptive methods use communication through MPI, or alternatively by writing/reading files, and mostly follow the approaches pioneered by CosmoMC (ascl:1106.025).
Ko, Hyunseok; Szlufarska, Izabela; Morgan, Dane
2016-01-01
The diffusion of silver (Ag) impurities in high energy grain boundaries (HEGBs) of cubic (3C) silicon carbide (SiC) is studied using an ab initio based kinetic Monte Carlo (kMC) model. This study assesses the hypothesis that the HEGB diffusion is responsible for Ag release in Tristructural-Isotropic fuel particles, and provides a specific example to increase understanding of impurity diffusion in highly disordered grain boundaries. The HEGB environment was modeled by an amorphous SiC. The structure and stability of Ag defects were calculated using density functional theory code. The defect energetics suggested that the fastest diffusion takes place via an interstitial mechanism in a-SiC. The formation energy of Ag interstitials and the kinetic resolved activation energies between them were well approximated with Gaussian distributions that were then sampled in the kMC. The diffusion of Ag was simulated with the effective medium model using kMC. At 1200-1600C, Ag in a HEGB is predicted to exhibit an Arrhenius ...
Good, Brian S.
2011-01-01
Yttria-stabilized zirconia s high oxygen diffusivity and corresponding high ionic conductivity, and its structural stability over a broad range of temperatures, have made the material of interest for use in a number of applications, for example, as solid electrolytes in fuel cells. At low concentrations, the stabilizing yttria also serves to increase the oxygen diffusivity through the presence of corresponding oxygen vacancies, needed to maintain charge neutrality. At higher yttria concentration, however, diffusivity is impeded by the larger number of relatively high energy migration barriers associated with yttrium cations. In addition, there is evidence that oxygen vacancies preferentially occupy nearest-neighbor sites around either dopant or Zr cations, further affecting vacancy diffusion. We present the results of ab initio calculations that indicate that it is energetically favorable for oxygen vacancies to occupy nearest-neighbor sites adjacent to Y ions, and that the presence of vacancies near either species of cation lowers the migration barriers. Kinetic Monte Carlo results from simulations incorporating this effect are presented and compared with results from simulations in which the effect is not present.
Atomistic Monte Carlo simulations of the diffusion of P and C near grain boundaries in BCC iron
Binkele, P.; Kizler, P. [MPA, Univ. Stuttgart, Stuttgart (Germany); Schmauder, S. [IMWF, Univ. Stuttgart, Stuttgart (Germany)
2004-07-01
It is well known that thermal ageing of steels can be caused by the segregation of phosphorus (P) and carbon (C) to grain boundaries. Atomistic Monte Carlo simulations of the diffusion of P and C to grain boundaries in bcc iron will allow, if validated, predictions of the time-dependent segregation. Simulations of the Fe-P-C system are presented, where the diffusion of Fe and P is realized via a vacancy mechanism and the diffusion of C is realized via an interstitial mechanism. Time-dependent segregations have been simulated for different temperatures and start conditions and are found to follow Johnson-Mehl-Avrami laws. A comparison of the simulation results with available AES (Auger Electron Spectroscopy) data shows close agreement with respect to P segregation. In simulations starting with a pre-filled grain boundary in increase of P and a decrease of C in the grain boundary are found where the decrease of C proceeds significantly faster than the increase of P for any temperature. The temperature-dependent ratios of the different speeds of P- and C-segregation, due to their different diffusion mechanisms, are calculated as a result of the simulations. (orig.)
Zhaoyuan Liu; Kord Smith; Benoit Forget; Javier Ortensi
2016-05-01
A new method for computing homogenized assembly neutron transport cross sections and dif- fusion coefficients that is both rigorous and computationally efficient is proposed in this paper. In the limit of a homogeneous hydrogen slab, the new method is equivalent to the long-used, and only-recently-published CASMO transport method. The rigorous method is used to demonstrate the sources of inaccuracy in the commonly applied “out-scatter” transport correction. It is also demonstrated that the newly developed method is directly applicable to lattice calculations per- formed by Monte Carlo and is capable of computing rigorous homogenized transport cross sections for arbitrarily heterogeneous lattices. Comparisons of several common transport cross section ap- proximations are presented for a simple problem of infinite medium hydrogen. The new method has also been applied in computing 2-group diffusion data for an actual PWR lattice from BEAVRS benchmark.
Szyniszewski, M.; Mostaani, E.; Drummond, N. D.; Fal'ko, V. I.
2017-02-01
Excitonic effects play a particularly important role in the optoelectronic behavior of two-dimensional (2D) semiconductors. To facilitate the interpretation of experimental photoabsorption and photoluminescence spectra we provide statistically exact diffusion quantum Monte Carlo binding-energy data for Mott-Wannier models of excitons, trions, and biexcitons in 2D semiconductors. We also provide contact pair densities to allow a description of contact (exchange) interactions between charge carriers using first-order perturbation theory. Our data indicate that the binding energy of a trion is generally larger than that of a biexciton in 2D semiconductors. We provide interpolation formulas giving the binding energy and contact density of 2D semiconductors as functions of the electron and hole effective masses and the in-plane polarizability.
Domin, D.; Braida, Benoit; Lester Jr., William A.
2008-05-30
This study explores the use of breathing orbital valence bond (BOVB) trial wave functions for diffusion Monte Carlo (DMC). The approach is applied to the computation of the carbon-hydrogen (C-H) bond dissociation energy (BDE) of acetylene. DMC with BOVB trial wave functions yields a C-H BDE of 132.4 {+-} 0.9 kcal/mol, which is in excellent accord with the recommended experimental value of 132.8 {+-} 0.7 kcal/mol. These values are to be compared with DMC results obtained with single determinant trial wave functions, using Hartree-Fock orbitals (137.5 {+-} 0.5 kcal/mol) and local spin density (LDA) Kohn-Sham orbitals (135.6 {+-} 0.5 kcal/mol).
Fuchs, M.; Ireta, J.; Scheffler, M.; Filippi, C.
2006-03-01
Dispersion (Van der Waals) forces are important in many molecular phenomena such as self-assembly of molecular crystals or peptide folding. Calculating this nonlocal correlation effect requires accurate electronic structure methods. Usual density-functional theory with generalized gradient functionals (GGA-DFT) fails unless empirical corrections are added that still need extensive validation. Quantum chemical methods like MP2 and coupled cluster are more accurate, yet limited to rather small systems by their unfavorable computational scaling. Diffusion Monte Carlo (DMC) can provide accurate molecular total energies and remains feasible also for larger systems. Here we apply the fixed-node DMC method to (bio-)molecular model systems where dispersion forces are significant: (dimethyl-) formamide and benzene dimers, and adenine-thymine DNA base pairs. Our DMC binding energies agree well with data from coupled cluster (CCSD(T)), in particular for stacked geometries where GGA-DFT fails qualitatively and MP2 predicts too strong binding.
Marcus, Ryan C. [Los Alamos National Laboratory
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.
Kara, Abdelkader; Yildirim, Handan; Rahman, Talat S [Department of Physics, University of Central Florida, Orlando, FL 32816-2385 (United States); Trushin, Oleg [Institute of Physics and Technology of RAS, Yaroslavl Branch, Yaroslavl 150007 (Russian Federation)
2009-02-25
We report developments of the kinetic Monte Carlo (KMC) method with improved accuracy and increased versatility for the description of atomic diffusivity on metal surfaces. The on-lattice constraint built into our recently proposed self-learning KMC (SLKMC) (Trushin et al 2005 Phys. Rev. B 72 115401) is released, leaving atoms free to occupy 'off-lattice' positions to accommodate several processes responsible for small-cluster diffusion, periphery atom motion and heteroepitaxial growth. This technique combines the ideas embedded in the SLKMC method with a new pattern-recognition scheme fitted to an off-lattice model in which relative atomic positions are used to characterize and store configurations. Application of a combination of the 'drag' and the repulsive bias potential (RBP) methods for saddle point searches allows the treatment of concerted cluster, and multiple- and single-atom, motions on an equal footing. This tandem approach has helped reveal several new atomic mechanisms which contribute to cluster migration. We present applications of this off-lattice SLKMC to the diffusion of 2D islands of Cu (containing 2-30 atoms) on Cu and Ag(111), using the interatomic potential from the embedded-atom method. For the hetero-system Cu/Ag(111), this technique has uncovered mechanisms involving concerted motions such as shear, breathing and commensurate-incommensurate occupancies. Although the technique introduces complexities in storage and retrieval, it does not introduce noticeable extra computational cost.
Approaching Chemical Accuracy with Quantum Monte Carlo
Petruzielo, F R; Umrigar, C J
2012-01-01
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.
Lu, Shih-I.
2004-02-01
This article accesses the performance of the Ornstein-Uhlenbeck diffusion quantum Monte Carlo with regard to the calculation of molecular geometries and harmonic frequencies of H2, LiH, HF, Li2, LiF, CO, N2, and F2 molecules. A comparison of the results for the eight first-row diatomic molecules from experiments, CCSD(T)/6-311G(3df,3pd) and CCSD(T)/cc-pV5Z levels of theory as well as our work is given. The results presented show that quantum Monte Carlo is becoming powerful tools for ab initio electronic structure calculations.
Lectures on Monte Carlo methods
Madras, Neal
2001-01-01
Monte Carlo methods form an experimental branch of mathematics that employs simulations driven by random number generators. These methods are often used when others fail, since they are much less sensitive to the "curse of dimensionality", which plagues deterministic methods in problems with a large number of variables. Monte Carlo methods are used in many fields: mathematics, statistics, physics, chemistry, finance, computer science, and biology, for instance. This book is an introduction to Monte Carlo methods for anyone who would like to use these methods to study various kinds of mathemati
Quantum Monte Carlo with variable spins.
Melton, Cody A; Bennett, M Chandler; Mitas, Lubos
2016-06-28
We investigate the inclusion of variable spins in electronic structure quantum Monte Carlo, with a focus on diffusion Monte Carlo with Hamiltonians that include spin-orbit interactions. Following our previous introduction of fixed-phase spin-orbit diffusion Monte Carlo, we thoroughly discuss the details of the method and elaborate upon its technicalities. We present a proof for an upper-bound property for complex nonlocal operators, which allows for the implementation of T-moves to ensure the variational property. We discuss the time step biases associated with our particular choice of spin representation. Applications of the method are also presented for atomic and molecular systems. We calculate the binding energies and geometry of the PbH and Sn2 molecules, as well as the electron affinities of the 6p row elements in close agreement with experiments.
Quantum Monte Carlo with Variable Spins
Melton, Cody A; Mitas, Lubos
2016-01-01
We investigate the inclusion of variable spins in electronic structure quantum Monte Carlo, with a focus on diffusion Monte Carlo with Hamiltonians that include spin-orbit interactions. Following our previous introduction of fixed-phase spin-orbit diffusion Monte Carlo (FPSODMC), we thoroughly discuss the details of the method and elaborate upon its technicalities. We present a proof for an upper-bound property for complex nonlocal operators, which allows for the implementation of T-moves to ensure the variational property. We discuss the time step biases associated with our particular choice of spin representation. Applications of the method are also presented for atomic and molecular systems. We calculate the binding energies and geometry of the PbH and Sn$_2$ molecules, as well as the electron affinities of the 6$p$ row elements in close agreement with experiments.
Monte Carlo methods in AB initio quantum chemistry quantum Monte Carlo for molecules
Lester, William A; Reynolds, PJ
1994-01-01
This book presents the basic theory and application of the Monte Carlo method to the electronic structure of atoms and molecules. It assumes no previous knowledge of the subject, only a knowledge of molecular quantum mechanics at the first-year graduate level. A working knowledge of traditional ab initio quantum chemistry is helpful, but not essential.Some distinguishing features of this book are: Clear exposition of the basic theory at a level to facilitate independent study. Discussion of the various versions of the theory: diffusion Monte Carlo, Green's function Monte Carlo, and release n
Monte Carlo integration on GPU
Kanzaki, J.
2010-01-01
We use a graphics processing unit (GPU) for fast computations of Monte Carlo integrations. Two widely used Monte Carlo integration programs, VEGAS and BASES, are parallelized on GPU. By using $W^{+}$ plus multi-gluon production processes at LHC, we test integrated cross sections and execution time for programs in FORTRAN and C on CPU and those on GPU. Integrated results agree with each other within statistical errors. Execution time of programs on GPU run about 50 times faster than those in C...
Diffusion of small Cu islands on the Ni(111) surface: A self-learning kinetic Monte Carlo study
Acharya, Shree Ram; Shah, Syed Islamuddin; Rahman, Talat S.
2017-08-01
We elucidate the diffusion kinetics of a heteroepitaxial system consisting of two-dimensional small (1-8 atoms) Cu islands on the Ni(111) surface at (100-600) K using the Self-Learning Kinetic Monte Carlo (SLKMC-II) method. Study of the statics of the system shows that compact CuN (3≤N≤8) clusters made up of triangular units on fcc occupancy sites are the energetically most stable structures of those clusters. Interestingly, we find a correlation between the height of the activation energy barrier (Ea) and the location of the transition state (TS). The Ea of processes for Cu islands on the Ni(111) surface are in general smaller than those of their counterpart Ni islands on the same surface. We find this difference to correlate with the relative strength of the lateral interaction of the island atoms in the two systems. While our database consists of hundreds of possible processes, we identify and discuss the energetics of those that are the most dominant, or are rate-limiting, or most contributory to the diffusion of the islands. Since the Ea of single- and multi-atom processes that convert compact island shapes into non-compact ones are larger (with a significantly smaller Ea for their reverse processes) than that for the collective (concerted) motion of the island, the later dominate in the system kinetics - except for the cases of the dimer, pentamer and octamer. Short-jump involving one atom, long jump dimer-shearing, and long-jump corner shearing (via a single-atom) are, respectively, the dominating processes in the diffusion of the dimer, pentamer and octamer. Furthermore single-atom corner-rounding are the rate-limiting processes for the pentamer and octamer islands. Comparison of the energetics of selected processes and lateral interactions obtained from semi-empirical interatomic potentials with those from density functional theory show minor quantitative differences and overall qualitative agreement.
Santana, Juan A.; Krogel, Jaron T.; Kent, Paul R. C.; Reboredo, Fernando A.
2016-05-01
We have applied the diffusion quantum Monte Carlo (DMC) method to calculate the cohesive energy and the structural parameters of the binary oxides CaO, SrO, BaO, Sc2O3, Y2O3, and La2O3. The aim of our calculations is to systematically quantify the accuracy of the DMC method to study this type of metal oxides. The DMC results were compared with local, semi-local, and hybrid Density Functional Theory (DFT) approximations as well as with experimental measurements. The DMC method yields cohesive energies for these oxides with a mean absolute deviation from experimental measurements of 0.18(2) eV, while with local, semi-local, and hybrid DFT approximations, the deviation is 3.06, 0.94, and 1.23 eV, respectively. For lattice constants, the mean absolute deviations in DMC, local, semi-local, and hybrid DFT approximations are 0.017(1), 0.07, 0.05, and 0.04 Å, respectively. DMC is a highly accurate method, outperforming the DFT approximations in describing the cohesive energies and structural parameters of these binary oxides.
Monte Carlo Simulation Study of Diffuse Scattering in PZT, Pb(Zr,Ti)O3
Welberry, T. R.; Goossens, D. J.; Withers, R. L.; Baba-Kishi, K. Z.
2010-05-01
Transverse polarized diffuse streaks have been observed in diffraction patterns of Pb(Zr1- x Ti x )O3 (PZT) ceramics for compositions ranging from x = 0.3 (rhombohedral phase) to x = 0.7 (tetragonal phase) including the important morphotropic phase boundary (MPB) region ( x = 0.48). The streaks correspond to diffuse planes of scattering in three dimensions, and these are oriented normal to the (cubic) piezo-electric properties of the material, but its presence requires the currently accepted models for the average structure to be reassessed.
Tucker, O. J.; Tenishev, V.; Combi, M. R.; Nagy, A. F.; Johnson, R. E.
2013-12-01
15). Snowden D., 2013a. The thermal structure of Titan's upper atmosphere, I: Temperature profiles from Cassini INMS observations. Icarus 226 552-582. Snowden D., 2013b. The Thermal Structure of Titan's Upper Atmosphere, II: Energetics. JGR DOI: :10.1029/. Tucker, O.J., et al., 2013. Diffusion and thermal escape of H2 from Titan's atmosphere: Monte Carlo simulations. Icarus 222, 149-158. Westlake, J.H. et al., 2011. Titan's thermospheric response to various plasma environments. J. Geophys. Res. 116, A03318.
Multilevel sequential Monte Carlo samplers
Beskos, Alexandros
2016-08-29
In this article we consider 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 which depend on 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 discretization levels . âˆž>h0>h1â‹¯>hL. In many practical problems of interest, one cannot achieve an i.i.d. sampling of the associated sequence and a sequential Monte Carlo (SMC) version of the MLMC method is introduced to deal with this problem. 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. That is, relative to exact sampling and Monte Carlo for the distribution at the finest level . hL. The approach is numerically illustrated on a Bayesian inverse problem. Â© 2016 Elsevier B.V.
Lu, Shih-I
2005-05-15
Ab initio calculations of transition state structure and reaction enthalpy of the F + H2-->HF + H reaction has been carried out by the fixed-node diffusion quantum Monte Carlo method in this study. The Monte Carlo sampling is based on the Ornstein-Uhlenbeck random walks guided by a trial wave function constructed from the floating spherical Gaussian orbitals and spherical Gaussian geminals. The Monte Carlo calculated barrier height of 1.09(16) kcal/mol is consistent with the experimental values, 0.86(10)/1.18(10) kcal/mol, and the calculated value from the multireference-type coupled-cluster (MRCC) calculation with the aug-cc-pVQZ(F)/cc-pVQZ(H) basis set, 1.11 kcal/mol. The Monte Carlo-based calculation also gives a similar value of the reaction enthalpy, -32.00(4) kcal/mol, compared with the experimental value, -32.06(17) kcal/mol, and the calculated value from a MRCC/aug-cc-pVQZ(F)/cc-pVQZ(H) calculation, -31.94 kcal/mol. This study clearly indicates a further application of the random-walk-based approach in the field of quantum chemical calculation.
Equilibrium Statistics: Monte Carlo Methods
Kröger, Martin
Monte Carlo methods use random numbers, or ‘random’ sequences, to sample from a known shape of a distribution, or to extract distribution by other means. and, in the context of this book, to (i) generate representative equilibrated samples prior being subjected to external fields, or (ii) evaluate high-dimensional integrals. Recipes for both topics, and some more general methods, are summarized in this chapter. It is important to realize, that Monte Carlo should be as artificial as possible to be efficient and elegant. Advanced Monte Carlo ‘moves’, required to optimize the speed of algorithms for a particular problem at hand, are outside the scope of this brief introduction. One particular modern example is the wavelet-accelerated MC sampling of polymer chains [406].
Monte Carlo Hamiltonian: Linear Potentials
LUO Xiang-Qian; LIU Jin-Jiang; HUANG Chun-Qing; JIANG Jun-Qin; Helmut KROGER
2002-01-01
We further study the validity of the Monte Carlo Hamiltonian method. The advantage of the method,in comparison with the standard Monte Carlo Lagrangian approach, is its capability to study the excited states. Weconsider two quantum mechanical models: a symmetric one V(x) = |x|/2; and an asymmetric one V(x) = ∞, forx ＜ 0 and V(x) = x, for x ≥ 0. The results for the spectrum, wave functions and thermodynamical observables are inagreement with the analytical or Runge-Kutta calculations.
Proton Upset Monte Carlo Simulation
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.
Recent Developments in Quantum Monte Carlo: Methods and Applications
Aspuru-Guzik, Alan; Austin, Brian; Domin, Dominik; Galek, Peter T. A.; Handy, Nicholas; Prasad, Rajendra; Salomon-Ferrer, Romelia; Umezawa, Naoto; Lester, William A.
2007-12-01
The quantum Monte Carlo method in the diffusion Monte Carlo form has become recognized for its capability of describing the electronic structure of atomic, molecular and condensed matter systems to high accuracy. This talk will briefly outline the method with emphasis on recent developments connected with trial function construction, linear scaling, and applications to selected systems.
Practical schemes for accurate forces in quantum Monte Carlo
Moroni, S.; Saccani, S.; Filippi, Claudia
2014-01-01
While the computation of interatomic forces has become a well-established practice within variational Monte Carlo (VMC), the use of the more accurate Fixed-Node Diffusion Monte Carlo (DMC) method is still largely limited to the computation of total energies on structures obtained at a lower level of
Practical schemes for accurate forces in quantum Monte Carlo
Moroni, S.; Saccani, S.; Filippi, C.
2014-01-01
While the computation of interatomic forces has become a well-established practice within variational Monte Carlo (VMC), the use of the more accurate Fixed-Node Diffusion Monte Carlo (DMC) method is still largely limited to the computation of total energies on structures obtained at a lower level of
Diffusion Monte Carlo Study of Bond Dissociation Energies for BH2,B(OH)2, BCl2, and BCl
Hui-ran Li; Xin-lu Cheng; Hong Zhang
2012-01-01
On basis of bond dissociation energies (BDEs) for BH2,B(OH)2,BCl2,and BCl,the diffusion Monte Carlo (DMC) method is applied to explore the BDEs of HB-H,HOB-OH,ClB-Cl,and B-Cl.The effect of the choice of orbitals,as well as the backflow transformation,is studied.The Slater-Jastrow DMC algorithm gives BDEs of 359.1±0.12 kJ/mol for HB-H,410.5±0.50 kJ/mol for HOB-OH,357.8±1.46 kJ/mol for ClB-Cl,and 504.5±0.96 kJ/mol for B-Cl using B3PW91 orbitals and similar BDEs when B3LYP orbitals are used.DMC with backflow corrections (BF-DMC) gives a HB-H BDE of 369.9±0.12 kJ/mol which isclose to one of the available experimental value (375.8 kJ/mol).In the case of HOB-OH BDE,the BF-DMC calculation is 446.0±1.84 kJ/mol that is closer to the experimental BDE.The BF-DMC BDE for ClB-Cl is 343.2±2.34 kJ/mol and the BF-DMC B-Cl BDE is 523.3±0.33 kJ/mol,which are close to the experimental BDEs,341.9 and 530.0 kJ/mol,respectively.
Naglič, Peter; Pernuš, Franjo; Likar, Boštjan; Bürmen, Miran
2015-10-01
Light propagation models often simplify the interface between the optical fiber probe tip and tissue to a laterally uniform boundary with mismatched refractive indices. Such simplification neglects the precise optical properties of the commonly used probe tip materials, e.g. stainless steel or black epoxy. In this paper, we investigate the limitations of the laterally uniform probe-tissue interface in Monte Carlo simulations of diffuse reflectance. In comparison to a realistic probe-tissue interface that accounts for the layout and properties of the probe tip materials, the simplified laterally uniform interface is shown to introduce significant errors into the simulated diffuse reflectance.
Monte Carlo Particle Lists: MCPL
Kittelmann, Thomas; Knudsen, Erik B; Willendrup, Peter; Cai, Xiao Xiao; Kanaki, Kalliopi
2016-01-01
A binary format with lists of particle state information, for interchanging particles between various Monte Carlo simulation applications, is presented. Portable C code for file manipulation is made available to the scientific community, along with converters and plugins for several popular simulation packages.
Applications of Monte Carlo Methods in Calculus.
Gordon, Sheldon P.; Gordon, Florence S.
1990-01-01
Discusses the application of probabilistic ideas, especially Monte Carlo simulation, to calculus. Describes some applications using the Monte Carlo method: Riemann sums; maximizing and minimizing a function; mean value theorems; and testing conjectures. (YP)
Inhomogeneous Monte Carlo simulations of dermoscopic spectroscopy
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.
Curotto, E; Mella, Massimo
2015-03-21
We test the second order Milstein method adapted to simulate diffusion in general compact Riemann manifolds on a number of systems characterized by nonconfining potential energy surfaces of increasing complexity. For the 2-sphere and more complex spaces derived from it, we compare the Milstein method with a number of other first and second order approaches. In each case tested, we find evidence that demonstrate the versatility and relative ease of implementation of the Milstein method derived in Part I.
(U) Introduction to Monte Carlo Methods
Hungerford, Aimee L. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-03-20
Monte Carlo methods are very valuable for representing solutions to particle transport problems. Here we describe a “cook book” approach to handling the terms in a transport equation using Monte Carlo methods. Focus is on the mechanics of a numerical Monte Carlo code, rather than the mathematical foundations of the method.
Monte Carlo Simulation of Methanol Diffusion in Critical Media%甲醇在临界介质中扩散的蒙特卡罗模拟
贾玉香; 郭向云
2006-01-01
The diffusion behavior of methanol in different critical media (n-pentane, n-hexane, n-heptane and acetone) was investigated by the Monte Carlo (MC) method. From the simulation results, the diffusion constant of methanol molecule in the critical n-hexane is much larger than those in n-pentane, n-heptane and acetone. By analyzing the microscopic configurations of the critical mixtures, it is found that the diffusion constant of methanol is related to the local solvent clustering around methanol, but it does not exhibit strong dependence on the size of solvent cluster around methanol. Moreover, the survival time of the solvent cluster plays an important role in determining the diffusion constant.
刘丽娜; 谢树森; 李步洪
2015-01-01
本文采用 Monte Carlo 模拟人体肠道组织的非接触式漫反射光谱，并分别研究了聚焦光束的聚焦深度、组织表面入射光斑与出射光斑（Source-Detector，S-D）之间的距离、探测面积和探测深度对光谱测量的影响，为设计非接触式光谱检测系统提供理论依据。结果表明在利用光谱技术对肠道疾病如早期肠癌进行诊断时，非接触式光谱检测系统的聚焦深度应小于0．1 cm；在漫反射光谱检测时，应根据探测信号的强弱以及探测器的灵敏度选择 S-D 距离；0．06 cm 的探测面积半径能有效地反映组织中氧合血红蛋白和脱氧合血红蛋白含量的变化情况；为反映不同深度组织光学特性，在改变探测深度时，应保持探测光锥顶角不变。%Monte Carlo simulation was applied to analyze the light distribution of the converging light beam in the ho-mogenous intestinal tissue model.The influence of the depth of focus,detection area and source-detector distance on the diffuse reflectance spectroscopy measurement were quantitatively investigated.The results show that the optimal focus depth of the non-contact spectrum system for the diagnosis of the intestinal lesions in situ is 0.1 cm.For the diffuse re-flectance spectroscopy measurement,the source-detector distance can be determined by the intensity of emission light and the response sensitivity of detector.0.06 cm is the optimal detection radius for correctly reflecting the change of the content of oxyhemoglobin and deoxygenated hemoglobin using diffuse reflectance spectroscopy.In order to reduce the influence on the spectrum caused by the change of detection depth,the apex angle of detection light cone should be constant.
Density matrix quantum Monte Carlo
Blunt, N S; Spencer, J S; Foulkes, W M C
2013-01-01
This paper describes a quantum Monte Carlo method capable of sampling the full density matrix of a many-particle system, thus granting access to arbitrary reduced density matrices and allowing expectation values of complicated non-local operators to be evaluated easily. The direct sampling of the density matrix also raises the possibility of calculating previously inaccessible entanglement measures. The algorithm closely resembles the recently introduced full configuration interaction quantum Monte Carlo method, but works all the way from infinite to zero temperature. We explain the theory underlying the method, describe the algorithm, and introduce an importance-sampling procedure to improve the stochastic efficiency. To demonstrate the potential of our approach, the energy and staggered magnetization of the isotropic antiferromagnetic Heisenberg model on small lattices and the concurrence of one-dimensional spin rings are compared to exact or well-established results. Finally, the nature of the sign problem...
Efficient kinetic Monte Carlo simulation
Schulze, Tim P.
2008-02-01
This paper concerns kinetic Monte Carlo (KMC) algorithms that have a single-event execution time independent of the system size. Two methods are presented—one that combines the use of inverted-list data structures with rejection Monte Carlo and a second that combines inverted lists with the Marsaglia-Norman-Cannon algorithm. The resulting algorithms apply to models with rates that are determined by the local environment but are otherwise arbitrary, time-dependent and spatially heterogeneous. While especially useful for crystal growth simulation, the algorithms are presented from the point of view that KMC is the numerical task of simulating a single realization of a Markov process, allowing application to a broad range of areas where heterogeneous random walks are the dominate simulation cost.
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.
张小岗; 韩布兴; 李永旺; 钟炳; 彭少逸
2001-01-01
Monte Carlo method was used to study the effect of diffusion of adsorbed hydrogen atoms on the methanol synthesis reaction behavior under a supercritical condition.The lattice model was employed to describe the surface processes,which included adsorption of reactants,surface reaction,surface diffusion of adsorbed species and re-adsorption of the product.The model converted Monte Carlo steps to the real time according to Botzzman equation.The results indicated that when the adsorbed hydrogen atoms diffused slowly,the active sites reached saturation and the turnover frequency (TOF) declined quickly.The magnitude of TOF was not influenced by the diffusion rate of adsorbed hydrogen atoms when it reached an enough high value.%用Monte Carlo方法研究了非均相催化剂表面吸附态氢原子的迁移对催化反应活性的影响，模拟结果表明，吸附态氢原子扩散很慢时，表面活性位很快被氢原子饱和，转换频率TOF增大到一定程度时很快下降；而当表面吸附态氢原子的扩散速率达到足够大的程度时，TOF将不再受氢原子扩散的影响.
Quantum Monte Carlo using a Stochastic Poisson Solver
Das, D; Martin, R M; Kalos, M H
2005-05-06
Quantum Monte Carlo (QMC) is an extremely powerful method to treat many-body systems. Usually quantum Monte Carlo has been applied in cases where the interaction potential has a simple analytic form, like the 1/r Coulomb potential. However, in a complicated environment as in a semiconductor heterostructure, the evaluation of the interaction itself becomes a non-trivial problem. Obtaining the potential from any grid-based finite-difference method, for every walker and every step is unfeasible. We demonstrate an alternative approach of solving the Poisson equation by a classical Monte Carlo within the overall quantum Monte Carlo scheme. We have developed a modified ''Walk On Spheres'' algorithm using Green's function techniques, which can efficiently account for the interaction energy of walker configurations, typical of quantum Monte Carlo algorithms. This stochastically obtained potential can be easily incorporated within popular quantum Monte Carlo techniques like variational Monte Carlo (VMC) or diffusion Monte Carlo (DMC). We demonstrate the validity of this method by studying a simple problem, the polarization of a helium atom in the electric field of an infinite capacitor.
Monte Carlo approach to turbulence
Dueben, P.; Homeier, D.; Muenster, G. [Muenster Univ. (Germany). Inst. fuer Theoretische Physik; Jansen, K. [DESY, Zeuthen (Germany). John von Neumann-Inst. fuer Computing NIC; Mesterhazy, D. [Humboldt Univ., Berlin (Germany). Inst. fuer Physik
2009-11-15
The behavior of the one-dimensional random-force-driven Burgers equation is investigated in the path integral formalism on a discrete space-time lattice. We show that by means of Monte Carlo methods one may evaluate observables, such as structure functions, as ensemble averages over different field realizations. The regularization of shock solutions to the zero-viscosity limit (Hopf-equation) eventually leads to constraints on lattice parameters required for the stability of the simulations. Insight into the formation of localized structures (shocks) and their dynamics is obtained. (orig.)
Monte Carlo techniques in radiation therapy
Verhaegen, Frank
2013-01-01
Modern cancer treatment relies on Monte Carlo simulations to help radiotherapists and clinical physicists better understand and compute radiation dose from imaging devices as well as exploit four-dimensional imaging data. With Monte Carlo-based treatment planning tools now available from commercial vendors, a complete transition to Monte Carlo-based dose calculation methods in radiotherapy could likely take place in the next decade. Monte Carlo Techniques in Radiation Therapy explores the use of Monte Carlo methods for modeling various features of internal and external radiation sources, including light ion beams. The book-the first of its kind-addresses applications of the Monte Carlo particle transport simulation technique in radiation therapy, mainly focusing on external beam radiotherapy and brachytherapy. It presents the mathematical and technical aspects of the methods in particle transport simulations. The book also discusses the modeling of medical linacs and other irradiation devices; issues specific...
Chemical accuracy from quantum Monte Carlo for the Benzene Dimer
Azadi, Sam; Cohen, R. E
2015-01-01
We report an accurate study of interactions between Benzene molecules using variational quantum Monte Carlo (VMC) and diffusion quantum Monte Carlo (DMC) methods. We compare these results with density functional theory (DFT) using different van der Waals (vdW) functionals. In our QMC calculations, we use accurate correlated trial wave functions including three-body Jastrow factors, and backflow transformations. We consider two benzene molecules in the parallel displaced (PD) geometry, and fin...
Confidence and efficiency scaling in Variational Quantum Monte Carlo calculations
Delyon, François; Holzmann, Markus
2016-01-01
Based on the central limit theorem, we discuss the problem of evaluation of the statistical error of Monte Carlo calculations using a time discretized diffusion process. We present a robust and practical method to determine the effective variance of general observables and show how to verify the equilibrium hypothesis by the Kolmogorov-Smirnov test. We then derive scaling laws of the efficiency illustrated by Variational Monte Carlo calculations on the two dimensional electron gas.
Confidence and efficiency scaling in variational quantum Monte Carlo calculations
Delyon, F.; Bernu, B.; Holzmann, Markus
2017-02-01
Based on the central limit theorem, we discuss the problem of evaluation of the statistical error of Monte Carlo calculations using a time-discretized diffusion process. We present a robust and practical method to determine the effective variance of general observables and show how to verify the equilibrium hypothesis by the Kolmogorov-Smirnov test. We then derive scaling laws of the efficiency illustrated by variational Monte Carlo calculations on the two-dimensional electron gas.
Monte Carlo Treatment Planning for Advanced Radiotherapy
Cronholm, Rickard
and validation of a Monte Carlo model of a medical linear accelerator (i), converting a CT scan of a patient to a Monte Carlo compliant phantom (ii) and translating the treatment plan parameters (including beam energy, angles of incidence, collimator settings etc) to a Monte Carlo input file (iii). A protocol...... previous algorithms since it uses delineations of structures in order to include and/or exclude certain media in various anatomical regions. This method has the potential to reduce anatomically irrelevant media assignment. In house MATLAB scripts translating the treatment plan parameters to Monte Carlo...
Error in Monte Carlo, quasi-error in Quasi-Monte Carlo
Kleiss, R. H. P.; Lazopoulos, A.
2006-01-01
While the Quasi-Monte Carlo method of numerical integration achieves smaller integration error than standard Monte Carlo, its use in particle physics phenomenology has been hindered by the abscence of a reliable way to estimate that error. The standard Monte Carlo error estimator relies on the assumption that the points are generated independently of each other and, therefore, fails to account for the error improvement advertised by the Quasi-Monte Carlo method. We advocate the construction o...
Yu, Jaehyung [Department of Mechanical Science and Engineering, 1206 W Green Street, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801 (United States); Wagner, Lucas K. [Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801 (United States); Ertekin, Elif, E-mail: ertekin@illinois.edu [Department of Mechanical Science and Engineering, 1206 W Green Street, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801 (United States); International Institute for Carbon Neutral Energy Research - WPI-I" 2CNER, Kyushu University, 744 Moto-oka, Nishi-ku, Fukuoka 819-0395 (Japan)
2015-12-14
The fixed node diffusion Monte Carlo (DMC) method has attracted interest in recent years as a way to calculate properties of solid materials with high accuracy. However, the framework for the calculation of properties such as total energies, atomization energies, and excited state energies is not yet fully established. Several outstanding questions remain as to the effect of pseudopotentials, the magnitude of the fixed node error, and the size of supercell finite size effects. Here, we consider in detail the semiconductors ZnSe and ZnO and carry out systematic studies to assess the magnitude of the energy differences arising from controlled and uncontrolled approximations in DMC. The former include time step errors and supercell finite size effects for ground and optically excited states, and the latter include pseudopotentials, the pseudopotential localization approximation, and the fixed node approximation. We find that for these compounds, the errors can be controlled to good precision using modern computational resources and that quantum Monte Carlo calculations using Dirac-Fock pseudopotentials can offer good estimates of both cohesive energy and the gap of these systems. We do however observe differences in calculated optical gaps that arise when different pseudopotentials are used.
Langevin Monte Carlo filtering for target tracking
Iglesias Garcia, Fernando; Bocquel, Melanie; Driessen, Hans
2015-01-01
This paper introduces the Langevin Monte Carlo Filter (LMCF), a particle filter with a Markov chain Monte Carlo algorithm which draws proposals by simulating Hamiltonian dynamics. This approach is well suited to non-linear filtering problems in high dimensional state spaces where the bootstrap filte
An introduction to Monte Carlo methods
Walter, J. -C.; Barkema, G. T.
2015-01-01
Monte Carlo simulations are methods for simulating statistical systems. The aim is to generate a representative ensemble of configurations to access thermodynamical quantities without the need to solve the system analytically or to perform an exact enumeration. The main principles of Monte Carlo sim
An introduction to Monte Carlo methods
Walter, J. -C.; Barkema, G. T.
2015-01-01
Monte Carlo simulations are methods for simulating statistical systems. The aim is to generate a representative ensemble of configurations to access thermodynamical quantities without the need to solve the system analytically or to perform an exact enumeration. The main principles of Monte Carlo sim
Challenges of Monte Carlo Transport
Long, Alex Roberts [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2016-06-10
These are slides from a presentation for Parallel Summer School at Los Alamos National Laboratory. Solving discretized partial differential equations (PDEs) of interest can require a large number of computations. We can identify concurrency to allow parallel solution of discrete PDEs. Simulated particles histories can be used to solve the Boltzmann transport equation. Particle histories are independent in neutral particle transport, making them amenable to parallel computation. Physical parameters and method type determine the data dependencies of particle histories. Data requirements shape parallel algorithms for Monte Carlo. Then, Parallel Computational Physics and Parallel Monte Carlo are discussed and, finally, the results are given. The mesh passing method greatly simplifies the IMC implementation and allows simple load-balancing. Using MPI windows and passive, one-sided RMA further simplifies the implementation by removing target synchronization. The author is very interested in implementations of PGAS that may allow further optimization for one-sided, read-only memory access (e.g. Open SHMEM). The MPICH_RMA_OVER_DMAPP option and library is required to make one-sided messaging scale on Trinitite - Moonlight scales poorly. Interconnect specific libraries or functions are likely necessary to ensure performance. BRANSON has been used to directly compare the current standard method to a proposed method on idealized problems. The mesh passing algorithm performs well on problems that are designed to show the scalability of the particle passing method. BRANSON can now run load-imbalanced, dynamic problems. Potential avenues of improvement in the mesh passing algorithm will be implemented and explored. A suite of test problems that stress DD methods will elucidate a possible path forward for production codes.
The MC21 Monte Carlo Transport Code
Sutton TM, Donovan TJ, Trumbull TH, Dobreff PS, Caro E, Griesheimer DP, Tyburski LJ, Carpenter DC, Joo H
2007-01-09
MC21 is a new Monte Carlo neutron and photon transport code currently under joint development at the Knolls Atomic Power Laboratory and the Bettis Atomic Power Laboratory. MC21 is the Monte Carlo transport kernel of the broader Common Monte Carlo Design Tool (CMCDT), which is also currently under development. The vision for CMCDT is to provide an automated, computer-aided modeling and post-processing environment integrated with a Monte Carlo solver that is optimized for reactor analysis. CMCDT represents a strategy to push the Monte Carlo method beyond its traditional role as a benchmarking tool or ''tool of last resort'' and into a dominant design role. This paper describes various aspects of the code, including the neutron physics and nuclear data treatments, the geometry representation, and the tally and depletion capabilities.
JIN Jing; TANG Yi
2007-01-01
The diffusion Monte Carlo method is applied to study the ground-state properties of charged bosons in one dimension confined in a harmonic double-well trap. The particles interact repulsively through a Coulombic 1/r potential. Numerical results show that the well separation has significant influence on the ground-state properties of the system. When the interaction of the system is weak, ground-state energy decreases with the increasing well separation and has a minimal value. If the well separation increases continually, the ground-state energy increases and approaches to a constant gradually. This effect will be abatable in the strong interacting system. In addition,by calculating the density of the systems for different interaction strengths with various well separations, we find that the density increases abnormally when the well separation is large at the centre of the system.
Mallory, Joel
2015-01-01
The Diffusion Monte Carlo (DMC) method is applied to compute the ground state energies of the water monomer and dimer and their D 2 O isotopomers using MB-pol; the most recent and most accurate ab inito- based potential energy surface (PES). MB-pol has already demonstrated excellent agreement with high level electronic structure data, as well as agreement with some experimental, spectroscopic, and thermodynamic data. Here, the DMC binding energies of (H 2 O) 2 and (D 2 O) 2 agree with the corresponding values obtained from velocity map imaging within, respectively, 0.01 and 0.02 kcal/mol. This work adds two more valuable data points that highlight the accuracy of the MB-pol PES.
Mueller-Bierl, Bernd Michael; Uludag, Kamil; Pereira, Philippe L.; Schick, Fritz
2007-01-01
Extravascular signal decay rate R2 or R2∗ as a function of blood oxygenation, geometry, and field strength was calculated using a Monte Carlo (MC) algorithm for a wider parameter range than hitherto by others. The relaxation rates of gradient-recalled-echo (GRE) and Hahn-spin-echo (HSE) imaging in the presence of blood vessels (ranging from capillaries to veins) have been computed for a wide range of field strengths up to 9.4T and 50% blood deoxygenation. The maximum HSE decay was found to be shifted to lower radii in higher compared to lower field strengths. For GRE, however, the relaxation rate was greatest for large vessels at any field strength. In addition, assessments of computational reliability have been carried out by investigating the influence of the time step, the Monte Carlo step procedure, boundary conditions, the number of angles between the vessel and the exterior field B0, the influence of neighboring vessels having the same orientation as the central vessel, and the number of proton spins. The results were compared with those obtained from a field distribution of the vessel computed by an analytic formula describing the field distribution of an ideal object (an infinitely long cylinder). It was found that the time step is not critical for values equal to or lower than 200 microseconds. The choice of the MC step procedure (three-dimensional Gaussian diffusion, constant one- or three-dimensional diffusion step) also failed to influence the results significantly; in contrast, the free boundary conditions, as well as taking too few angles into account, did introduce errors. Next neighbor vessels with the same orientation as the main vessel did not contribute significantly to signal decay. The total number of particles simulated was also found to play a minor role in computing R2/ R2∗. PMID:18273394
Bernd Michael Mueller-Bierl
2007-01-01
Full Text Available Extravascular signal decay rate R2 or R2∗ as a function of blood oxygenation, geometry, and field strength was calculated using a Monte Carlo (MC algorithm for a wider parameter range than hitherto by others. The relaxation rates of gradient-recalled-echo (GRE and Hahn-spin-echo (HSE imaging in the presence of blood vessels (ranging from capillaries to veins have been computed for a wide range of field strengths up to 9.4 T and 50% blood deoxygenation. The maximum HSE decay was found to be shifted to lower radii in higher compared to lower field strengths. For GRE, however, the relaxation rate was greatest for large vessels at any field strength. In addition, assessments of computational reliability have been carried out by investigating the influence of the time step, the Monte Carlo step procedure, boundary conditions, the number of angles between the vessel and the exterior field B0, the influence of neighboring vessels having the same orientation as the central vessel, and the number of proton spins. The results were compared with those obtained from a field distribution of the vessel computed by an analytic formula describing the field distribution of an ideal object (an infinitely long cylinder. It was found that the time step is not critical for values equal to or lower than 200 microseconds. The choice of the MC step procedure (three-dimensional Gaussian diffusion, constant one- or three-dimensional diffusion step also failed to influence the results significantly; in contrast, the free boundary conditions, as well as taking too few angles into account, did introduce errors. Next neighbor vessels with the same orientation as the main vessel did not contribute significantly to signal decay. The total number of particles simulated was also found to play a minor role in computing R2/ R2∗.
Quantum Monte Carlo for vibrating molecules
Brown, W.R. [Univ. of California, Berkeley, CA (United States). Chemistry Dept.]|[Lawrence Berkeley National Lab., CA (United States). Chemical Sciences Div.
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.
Spike Inference from Calcium Imaging using Sequential Monte Carlo Methods
NeuroData; Paninski, L
2015-01-01
Vogelstein JT, Paninski L. Spike Inference from Calcium Imaging using Sequential Monte Carlo Methods. Statistical and Applied Mathematical Sciences Institute (SAMSI) Program on Sequential Monte Carlo Methods, 2008
Welberry, T R; Heerdegen, A P
2003-12-01
A recently developed method for fitting a Monte Carlo computer-simulation model to observed single-crystal diffuse X-ray scattering has been used to study the diffuse scattering in 4,4'-dimethoxybenzil, C16H14O4. A model involving only nine parameters, consisting of seven intermolecular force constants and two intramolecular torsional force constants, was refined to give an agreement factor, omegaR = [sigma omega(deltaI)2/sigma omegaI2(obs)](1/2), of 18.1% for 118 918 data points in two sections of data. The model was purely thermal in nature. The analysis has shown that the most prominent features of the diffraction patterns, viz. diffuse streaks that occur normal to the [101] direction, are due to longitudinal displacement correlations along chains of molecules extending in this direction. These displacements are transmitted from molecule to molecule via contacts involving pairs of hydrogen bonds between adjacent methoxy groups. In contrast to an earlier study of benzil itself, it was not found to be possible to determine, with any degree of certainty, the torsional force constants for rotations about the single bonds in the molecule. It is supposed that this result may be due to the limited data available in the present study.
Monte Carlo approaches to light nuclei
Carlson, J.
1990-01-01
Significant progress has been made recently in the application of Monte Carlo methods to the study of light nuclei. We review new Green's function Monte Carlo results for the alpha particle, Variational Monte Carlo studies of {sup 16}O, and methods for low-energy scattering and transitions. Through these calculations, a coherent picture of the structure and electromagnetic properties of light nuclei has arisen. In particular, we examine the effect of the three-nucleon interaction and the importance of exchange currents in a variety of experimentally measured properties, including form factors and capture cross sections. 29 refs., 7 figs.
Monte carlo simulation for soot dynamics
Zhou, Kun
2012-01-01
A new Monte Carlo method termed Comb-like frame Monte Carlo is developed to simulate the soot dynamics. Detailed stochastic error analysis is provided. Comb-like frame Monte Carlo is coupled with the gas phase solver Chemkin II to simulate soot formation in a 1-D premixed burner stabilized flame. The simulated soot number density, volume fraction, and particle size distribution all agree well with the measurement available in literature. The origin of the bimodal distribution of particle size distribution is revealed with quantitative proof.
Lattice gauge theories and Monte Carlo simulations
Rebbi, Claudio
1983-01-01
This volume is the most up-to-date review on Lattice Gauge Theories and Monte Carlo Simulations. It consists of two parts. Part one is an introductory lecture on the lattice gauge theories in general, Monte Carlo techniques and on the results to date. Part two consists of important original papers in this field. These selected reprints involve the following: Lattice Gauge Theories, General Formalism and Expansion Techniques, Monte Carlo Simulations. Phase Structures, Observables in Pure Gauge Theories, Systems with Bosonic Matter Fields, Simulation of Systems with Fermions.
Quantum Monte Carlo for minimum energy structures
Wagner, Lucas K
2010-01-01
We present an efficient method to find minimum energy structures using energy estimates from accurate quantum Monte Carlo calculations. This method involves a stochastic process formed from the stochastic energy estimates from Monte Carlo that can be averaged to find precise structural minima while using inexpensive calculations with moderate statistical uncertainty. We demonstrate the applicability of the algorithm by minimizing the energy of the H2O-OH- complex and showing that the structural minima from quantum Monte Carlo calculations affect the qualitative behavior of the potential energy surface substantially.
Fast quantum Monte Carlo on a GPU
Lutsyshyn, Y
2013-01-01
We present a scheme for the parallelization of quantum Monte Carlo on graphical processing units, focusing on bosonic systems and variational Monte Carlo. We use asynchronous execution schemes with shared memory persistence, and obtain an excellent acceleration. Comparing with single core execution, GPU-accelerated code runs over x100 faster. The CUDA code is provided along with the package that is necessary to execute variational Monte Carlo for a system representing liquid helium-4. The program was benchmarked on several models of Nvidia GPU, including Fermi GTX560 and M2090, and the latest Kepler architecture K20 GPU. Kepler-specific optimization is discussed.
11th International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing
Nuyens, Dirk
2016-01-01
This book presents the refereed proceedings of the Eleventh International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held at the University of Leuven (Belgium) in April 2014. These biennial conferences are major events for Monte Carlo and quasi-Monte Carlo researchers. The proceedings include articles based on invited lectures as well as carefully selected contributed papers on all theoretical aspects and applications of Monte Carlo and quasi-Monte Carlo methods. Offering information on the latest developments in these very active areas, this book is an excellent reference resource for theoreticians and practitioners interested in solving high-dimensional computational problems, arising, in particular, in finance, statistics and computer graphics.
Simulation and the Monte Carlo method
Rubinstein, Reuven Y
2016-01-01
Simulation and the Monte Carlo Method, Third Edition reflects the latest developments in the field and presents a fully updated and comprehensive account of the major topics that have emerged in Monte Carlo simulation since the publication of the classic First Edition over more than a quarter of a century ago. While maintaining its accessible and intuitive approach, this revised edition features a wealth of up-to-date information that facilitates a deeper understanding of problem solving across a wide array of subject areas, such as engineering, statistics, computer science, mathematics, and the physical and life sciences. The book begins with a modernized introduction that addresses the basic concepts of probability, Markov processes, and convex optimization. Subsequent chapters discuss the dramatic changes that have occurred in the field of the Monte Carlo method, with coverage of many modern topics including: Markov Chain Monte Carlo, variance reduction techniques such as the transform likelihood ratio...
Monte Carlo simulations for plasma physics
Okamoto, M.; Murakami, S.; Nakajima, N.; Wang, W.X. [National Inst. for Fusion Science, Toki, Gifu (Japan)
2000-07-01
Plasma behaviours are very complicated and the analyses are generally difficult. However, when the collisional processes play an important role in the plasma behaviour, the Monte Carlo method is often employed as a useful tool. For examples, in neutral particle injection heating (NBI heating), electron or ion cyclotron heating, and alpha heating, Coulomb collisions slow down high energetic particles and pitch angle scatter them. These processes are often studied by the Monte Carlo technique and good agreements can be obtained with the experimental results. Recently, Monte Carlo Method has been developed to study fast particle transports associated with heating and generating the radial electric field. Further it is applied to investigating the neoclassical transport in the plasma with steep gradients of density and temperatures which is beyong the conventional neoclassical theory. In this report, we briefly summarize the researches done by the present authors utilizing the Monte Carlo method. (author)
Quantum Monte Carlo Calculations of Light Nuclei
Pieper, Steven C
2007-01-01
During the last 15 years, there has been much progress in defining the nuclear Hamiltonian and applying quantum Monte Carlo methods to the calculation of light nuclei. I describe both aspects of this work and some recent results.
Improved Monte Carlo Renormalization Group Method
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 methods for particle transport
Haghighat, Alireza
2015-01-01
The Monte Carlo method has become the de facto standard in radiation transport. Although powerful, if not understood and used appropriately, the method can give misleading results. Monte Carlo Methods for Particle Transport teaches appropriate use of the Monte Carlo method, explaining the method's fundamental concepts as well as its limitations. Concise yet comprehensive, this well-organized text: * Introduces the particle importance equation and its use for variance reduction * Describes general and particle-transport-specific variance reduction techniques * Presents particle transport eigenvalue issues and methodologies to address these issues * Explores advanced formulations based on the author's research activities * Discusses parallel processing concepts and factors affecting parallel performance Featuring illustrative examples, mathematical derivations, computer algorithms, and homework problems, Monte Carlo Methods for Particle Transport provides nuclear engineers and scientists with a practical guide ...
Smart detectors for Monte Carlo radiative transfer
Baes, Maarten
2008-01-01
Many optimization techniques have been invented to reduce the noise that is inherent in Monte Carlo radiative transfer simulations. As the typical detectors used in Monte Carlo simulations do not take into account all the information contained in the impacting photon packages, there is still room to optimize this detection process and the corresponding estimate of the surface brightness distributions. We want to investigate how all the information contained in the distribution of impacting photon packages can be optimally used to decrease the noise in the surface brightness distributions and hence to increase the efficiency of Monte Carlo radiative transfer simulations. We demonstrate that the estimate of the surface brightness distribution in a Monte Carlo radiative transfer simulation is similar to the estimate of the density distribution in an SPH simulation. Based on this similarity, a recipe is constructed for smart detectors that take full advantage of the exact location of the impact of the photon pack...
Quantum Monte Carlo approaches for correlated systems
Becca, Federico
2017-01-01
Over the past several decades, computational approaches to studying strongly-interacting systems have become increasingly varied and sophisticated. This book provides a comprehensive introduction to state-of-the-art quantum Monte Carlo techniques relevant for applications in correlated systems. Providing a clear overview of variational wave functions, and featuring a detailed presentation of stochastic samplings including Markov chains and Langevin dynamics, which are developed into a discussion of Monte Carlo methods. The variational technique is described, from foundations to a detailed description of its algorithms. Further topics discussed include optimisation techniques, real-time dynamics and projection methods, including Green's function, reptation and auxiliary-field Monte Carlo, from basic definitions to advanced algorithms for efficient codes, and the book concludes with recent developments on the continuum space. Quantum Monte Carlo Approaches for Correlated Systems provides an extensive reference ...
SUN Xiao-yan; JIAO Wei; XIANG Shu-guang; LI Jian-wei
2011-01-01
The diffusion and adsorption behaviors of benzene and propylene in zeolites MFI, MWW and BEA have been studied by molecular dynamics(MD) and grand canonical Monte Carlo(GCMC) simulations. The diffusion coefficients of benzene and propylene in MFI, MWW and BEA zeolites were calculated by simulating the mean-square displacements(MSD) at 298 and 600 K. Benzene and propylene showed the different adsorption rules in the channels of the three zeolites. For propylene, the molecular loadings decreased in the order: BEA(linear channel)〉BEA (tortuous channel)〉MFI(linear channel)〉MWW(l2-membered rings, 12MR channel)〉MFI(tortuous channel)〉MWW (10-membered rings, 10MR channel); for benzene, the molecular loadings decreased in the order: BEA(linear channel)〉BEA(tortuous channel)〉MWW(l2MR channel)〉MFI(linear channel)〉MFl(tortuous channel)〉MWW(10MR channel). Besides, the adsorption isotherms of benzene and propylene in the three zeolites at 298 and 443 K were simulated. The results show that the different factors influenced the molecular adsorption at various temperatures and pressures, leading to the different rules for the adsorption of benzene and propylene molecules in the zeolites. At a low pressure, the unfavorable energy would make the loadings of propylene lower than those of benzene. When pressure was higher than 0.25 kPa, the adsorption of benzene in MFI would nearly reach saturation.
Bartalini, P.; Kryukov, A.; Selyuzhenkov, Ilya V.; Sherstnev, A.; Vologdin, A.
2004-01-01
We present the Monte-Carlo events Data Base (MCDB) project and its development plans. MCDB facilitates communication between authors of Monte-Carlo generators and experimental users. It also provides a convenient book-keeping and an easy access to generator level samples. The first release of MCDB is now operational for the CMS collaboration. In this paper we review the main ideas behind MCDB and discuss future plans to develop this Data Base further within the CERN LCG framework.
Monte Carlo Algorithms for Linear Problems
DIMOV, Ivan
2000-01-01
MSC Subject Classification: 65C05, 65U05. Monte Carlo methods are a powerful tool in many fields of mathematics, physics and engineering. It is known, that these methods give statistical estimates for the functional of the solution by performing random sampling of a certain chance variable whose mathematical expectation is the desired functional. Monte Carlo methods are methods for solving problems using random variables. In the book [16] edited by Yu. A. Shreider one can find the followin...
The Feynman Path Goes Monte Carlo
Sauer, Tilman
2001-01-01
Path integral Monte Carlo (PIMC) simulations have become an important tool for the investigation of the statistical mechanics of quantum systems. I discuss some of the history of applying the Monte Carlo method to non-relativistic quantum systems in path-integral representation. The principle feasibility of the method was well established by the early eighties, a number of algorithmic improvements have been introduced in the last two decades.
Monte Carlo Hamiltonian:Inverse Potential
LUO Xiang-Qian; CHENG Xiao-Ni; Helmut KR(O)GER
2004-01-01
The Monte Carlo Hamiltonian method developed recently allows to investigate the ground state and low-lying excited states of a quantum system,using Monte Carlo(MC)algorithm with importance sampling.However,conventional MC algorithm has some difficulties when applied to inverse potentials.We propose to use effective potential and extrapolation method to solve the problem.We present examples from the hydrogen system.
Error in Monte Carlo, quasi-error in Quasi-Monte Carlo
Kleiss, R H
2006-01-01
While the Quasi-Monte Carlo method of numerical integration achieves smaller integration error than standard Monte Carlo, its use in particle physics phenomenology has been hindered by the abscence of a reliable way to estimate that error. The standard Monte Carlo error estimator relies on the assumption that the points are generated independently of each other and, therefore, fails to account for the error improvement advertised by the Quasi-Monte Carlo method. We advocate the construction of an estimator of stochastic nature, based on the ensemble of pointsets with a particular discrepancy value. We investigate the consequences of this choice and give some first empirical results on the suggested estimators.
Quantum Monte Carlo Endstation for Petascale Computing
Lubos Mitas
2011-01-26
published papers, 15 invited talks and lectures nationally and internationally. My former graduate student and postdoc Dr. Michal Bajdich, who was supported byt this grant, is currently a postdoc with ORNL in the group of Dr. F. Reboredo and Dr. P. Kent and is using the developed tools in a number of DOE projects. The QWalk package has become a truly important research tool used by the electronic structure community and has attracted several new developers in other research groups. Our tools use several types of correlated wavefunction approaches, variational, diffusion and reptation methods, large-scale optimization methods for wavefunctions and enables to calculate energy differences such as cohesion, electronic gaps, but also densities and other properties, using multiple runs one can obtain equations of state for given structures and beyond. Our codes use efficient numerical and Monte Carlo strategies (high accuracy numerical orbitals, multi-reference wave functions, highly accurate correlation factors, pairing orbitals, force biased and correlated sampling Monte Carlo), are robustly parallelized and enable to run on tens of thousands cores very efficiently. Our demonstration applications were focused on the challenging research problems in several fields of materials science such as transition metal solids. We note that our study of FeO solid was the first QMC calculation of transition metal oxides at high pressures.
Applications of quantum Monte Carlo methods in condensed systems
Kolorenc, Jindrich
2010-01-01
The quantum Monte Carlo methods represent a powerful and broadly applicable computational tool for finding very accurate solutions of the stationary Schroedinger equation for atoms, molecules, solids and a variety of model systems. The algorithms are intrinsically parallel and are able to take full advantage of the present-day high-performance computing systems. This review article concentrates on the fixed-node/fixed-phase diffusion Monte Carlo method with emphasis on its applications to electronic structure of solids and other extended many-particle systems.
Monte Carlo scatter correction for SPECT
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.
Favard, Cyril; Wenger, Jérôme; Lenne, Pierre-François; Rigneault, Hervé
2011-03-02
Many efforts have been undertaken over the last few decades to characterize the diffusion process in model and cellular lipid membranes. One of the techniques developed for this purpose, fluorescence correlation spectroscopy (FCS), has proved to be a very efficient approach, especially if the analysis is extended to measurements on different spatial scales (referred to as FCS diffusion laws). In this work, we examine the relevance of FCS diffusion laws for probing the behavior of a pure lipid and a lipid mixture at temperatures below, within and above the phase transitions, both experimentally and numerically. The accuracy of the microscopic description of the lipid mixtures found here extends previous work to a more complex model in which the geometry is unknown and the molecular motion is driven only by the thermodynamic parameters of the system itself. For multilamellar vesicles of both pure lipid and lipid mixtures, the FCS diffusion laws recorded at different temperatures exhibit large deviations from pure Brownian motion and reveal the existence of nanodomains. The variation of the mean size of these domains with temperature is in perfect correlation with the enthalpy fluctuation. This study highlights the advantages of using FCS diffusion laws in complex lipid systems to describe their temporal and spatial structure.
Zhang, Rong; Verkruysse, Wim; Aguilar, Guillermo; Nelson, J Stuart
2005-09-07
Both diffusion approximation (DA) and Monte Carlo (MC) models have been used to simulate light distribution in multilayered human skin with or without discrete blood vessels. However, no detailed comparison of the light distribution, heat generation and induced thermal damage between these two models has been done for discrete vessels. Three models were constructed: (1) MC-based finite element method (FEM) model, referred to as MC-FEM; (2) DA-based FEM with simple scaling factors according to chromophore concentrations (SFCC) in the epidermis and vessels, referred to as DA-FEM-SFCC; and (3) DA-FEM with improved scaling factors (ISF) obtained by equalizing the total light energy depositions that are solved from the DA and MC models in the epidermis and vessels, respectively, referred to as DA-FEM-ISF. The results show that DA-FEM-SFCC underestimates the light energy deposition in the epidermis and vessels when compared to MC-FEM. The difference is nonlinearly dependent on wavelength, dermal blood volume fraction, vessel size and depth, etc. Thus, the temperature and damage profiles are also dramatically different. DA-FEM-ISF achieves much better results in calculating heat generation and induced thermal damage when compared to MC-FEM, and has the advantages of both calculation speed and accuracy. The disadvantage is that a multidimensional ISF table is needed for DA-FEM-ISF to be a practical modelling tool.
Lee, Chu-Yu; Bennett, Kevin M; Debbins, Josef P
2013-05-01
The aim of this study was to investigate the microstructural sensitivity of the statistical distribution and diffusion kurtosis (DKI) models of non-monoexponential signal attenuation in the brain using diffusion-weighted MRI (DWI). We first developed a simulation of 2-D water diffusion inside simulated tissue consisting of semi-permeable cells and a variable cell size. We simulated a DWI acquisition of the signal in a volume using a pulsed gradient spin echo (PGSE) pulse sequence, and fitted the models to the simulated DWI signals using b-values up to 2500 s/mm(2). For comparison, we calculated the apparent diffusion coefficient (ADC) of the monoexponential model (b-value=1000 s/mm(2)). In separate experiments, we varied the cell size (5-10-15 μm), cell volume fraction (0.50-0.65-0.80), and membrane permeability (0.001-0.01-0.1mm/s) to study how the fitted parameters tracked simulated microstructural changes. The ADC was sensitive to all the simulated microstructural changes except the decrease in membrane permeability. The ADC increased with larger cell size, smaller cell volume fraction, and larger membrane permeability. The σstat of the statistical distribution model increased exclusively with a decrease in cell volume fraction. The Kapp of the DKI model was exclusively increased with decreased cell size and decreased with increasing membrane permeability. These results suggest that the non-monoexponential models of water diffusion have different, specific microstructural sensitivity, and a combination of the models may give insights into the microstructural underpinning of tissue pathology.
Monte Carlo EM加速算法%Acceleration of Monte Carlo EM Algorithm
罗季
2008-01-01
EM算法是近年来常用的求后验众数的估计的一种数据增广算法,但由于求出其E步中积分的显示表达式有时很困难,甚至不可能,限制了其应用的广泛性.而Monte Carlo EM算法很好地解决了这个问题,将EM算法中E步的积分用Monte Carlo模拟来有效实现,使其适用性大大增强.但无论是EM算法,还是Monte Carlo EM算法,其收敛速度都是线性的,被缺损信息的倒数所控制,当缺损数据的比例很高时,收敛速度就非常缓慢.而Newton-Raphson算法在后验众数的附近具有二次收敛速率.本文提出Monte Carlo EM加速算法,将Monte Carlo EM算法与Newton-Raphson算法结合,既使得EM算法中的E步用Monte Carlo模拟得以实现,又证明了该算法在后验众数附近具有二次收敛速度.从而使其保留了Monte Carlo EM算法的优点,并改进了Monte Carlo EM算法的收敛速度.本文通过数值例子,将Monte Carlo EM加速算法的结果与EM算法、Monte Carlo EM算法的结果进行比较,进一步说明了Monte Carlo EM加速算法的优良性.
Biagi, S F
1999-01-01
A fast and accurate computer simulation program for electron drift and diffusion in gases under the influence of electric and magnetic fields is described and some calculated results are compared to precise experimental results in carbon tetraflouride and methane mixtures. The calculated Lorentz angles are shown to be typically within 1 deg. of the measured experimental values. The program allows the electric and magnetic fields to be at any angle to each other.
Random Numbers and Monte Carlo Methods
Scherer, Philipp O. J.
Many-body problems often involve the calculation of integrals of very high dimension which cannot be treated by standard methods. For the calculation of thermodynamic averages Monte Carlo methods are very useful which sample the integration volume at randomly chosen points. After summarizing some basic statistics, we discuss algorithms for the generation of pseudo-random numbers with given probability distribution which are essential for all Monte Carlo methods. We show how the efficiency of Monte Carlo integration can be improved by sampling preferentially the important configurations. Finally the famous Metropolis algorithm is applied to classical many-particle systems. Computer experiments visualize the central limit theorem and apply the Metropolis method to the traveling salesman problem.
SMCTC: Sequential Monte Carlo in C++
Adam M. Johansen
2009-04-01
Full Text Available Sequential Monte Carlo methods are a very general class of Monte Carlo methodsfor sampling from sequences of distributions. Simple examples of these algorithms areused very widely in the tracking and signal processing literature. Recent developmentsillustrate that these techniques have much more general applicability, and can be appliedvery eectively to statistical inference problems. Unfortunately, these methods are oftenperceived as being computationally expensive and dicult to implement. This articleseeks to address both of these problems.A C++ template class library for the ecient and convenient implementation of verygeneral Sequential Monte Carlo algorithms is presented. Two example applications areprovided: a simple particle lter for illustrative purposes and a state-of-the-art algorithmfor rare event estimation.
Shell model the Monte Carlo way
Ormand, W.E.
1995-03-01
The formalism for the auxiliary-field Monte Carlo approach to the nuclear shell model is presented. The method is based on a linearization of the two-body part of the Hamiltonian in an imaginary-time propagator using the Hubbard-Stratonovich transformation. The foundation of the method, as applied to the nuclear many-body problem, is discussed. Topics presented in detail include: (1) the density-density formulation of the method, (2) computation of the overlaps, (3) the sign of the Monte Carlo weight function, (4) techniques for performing Monte Carlo sampling, and (5) the reconstruction of response functions from an imaginary-time auto-correlation function using MaxEnt techniques. Results obtained using schematic interactions, which have no sign problem, are presented to demonstrate the feasibility of the method, while an extrapolation method for realistic Hamiltonians is presented. In addition, applications at finite temperature are outlined.
A brief introduction to Monte Carlo simulation.
Bonate, P L
2001-01-01
Simulation affects our life every day through our interactions with the automobile, airline and entertainment industries, just to name a few. The use of simulation in drug development is relatively new, but its use is increasing in relation to the speed at which modern computers run. One well known example of simulation in drug development is molecular modelling. Another use of simulation that is being seen recently in drug development is Monte Carlo simulation of clinical trials. Monte Carlo simulation differs from traditional simulation in that the model parameters are treated as stochastic or random variables, rather than as fixed values. The purpose of this paper is to provide a brief introduction to Monte Carlo simulation methods.
CosmoPMC: Cosmology Population Monte Carlo
Kilbinger, Martin; Cappe, Olivier; Cardoso, Jean-Francois; Fort, Gersende; Prunet, Simon; Robert, Christian P; Wraith, Darren
2011-01-01
We present the public release of the Bayesian sampling algorithm for cosmology, CosmoPMC (Cosmology Population Monte Carlo). CosmoPMC explores the parameter space of various cosmological probes, and also provides a robust estimate of the Bayesian evidence. CosmoPMC is based on an adaptive importance sampling method called Population Monte Carlo (PMC). Various cosmology likelihood modules are implemented, and new modules can be added easily. The importance-sampling algorithm is written in C, and fully parallelised using the Message Passing Interface (MPI). Due to very little overhead, the wall-clock time required for sampling scales approximately with the number of CPUs. The CosmoPMC package contains post-processing and plotting programs, and in addition a Monte-Carlo Markov chain (MCMC) algorithm. The sampling engine is implemented in the library pmclib, and can be used independently. The software is available for download at http://www.cosmopmc.info.
Quantum speedup of Monte Carlo methods.
Montanaro, Ashley
2015-09-08
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.
Self-learning Monte Carlo method
Liu, Junwei; Qi, Yang; Meng, Zi Yang; Fu, Liang
2017-01-01
Monte Carlo simulation is an unbiased numerical tool for studying classical and quantum many-body systems. One of its bottlenecks is the lack of a general and efficient update algorithm for large size systems close to the phase transition, for which local updates perform badly. In this Rapid Communication, we propose a general-purpose Monte Carlo method, dubbed self-learning Monte Carlo (SLMC), in which an efficient update algorithm is first learned from the training data generated in trial simulations and then used to speed up the actual simulation. We demonstrate the efficiency of SLMC in a spin model at the phase transition point, achieving a 10-20 times speedup.
Monte Carlo strategies in scientific computing
Liu, Jun S
2008-01-01
This paperback edition is a reprint of the 2001 Springer edition This book provides a self-contained and up-to-date treatment of the Monte Carlo method and develops a common framework under which various Monte Carlo techniques can be "standardized" and compared Given the interdisciplinary nature of the topics and a moderate prerequisite for the reader, this book should be of interest to a broad audience of quantitative researchers such as computational biologists, computer scientists, econometricians, engineers, probabilists, and statisticians It can also be used as the textbook for a graduate-level course on Monte Carlo methods Many problems discussed in the alter chapters can be potential thesis topics for masters’ or PhD students in statistics or computer science departments Jun Liu is Professor of Statistics at Harvard University, with a courtesy Professor appointment at Harvard Biostatistics Department Professor Liu was the recipient of the 2002 COPSS Presidents' Award, the most prestigious one for sta...
Parallel Markov chain Monte Carlo simulations.
Ren, Ruichao; Orkoulas, G
2007-06-07
With strict detailed balance, parallel Monte Carlo simulation through domain decomposition cannot be validated with conventional Markov chain theory, which describes an intrinsically serial stochastic process. In this work, the parallel version of Markov chain theory and its role in accelerating Monte Carlo simulations via cluster computing is explored. It is shown that sequential updating is the key to improving efficiency in parallel simulations through domain decomposition. A parallel scheme is proposed to reduce interprocessor communication or synchronization, which slows down parallel simulation with increasing number of processors. Parallel simulation results for the two-dimensional lattice gas model show substantial reduction of simulation time for systems of moderate and large size.
Monte Carlo Hamiltonian：Linear Potentials
LUOXiang－Qian; HelmutKROEGER; 等
2002-01-01
We further study the validity of the Monte Carlo Hamiltonian method .The advantage of the method,in comparison with the standard Monte Carlo Lagrangian approach,is its capability to study the excited states.We consider two quantum mechanical models:a symmetric one V(x)=/x/2;and an asymmetric one V(x)==∞,for x<0 and V(x)=2,for x≥0.The results for the spectrum,wave functions and thermodynamical observables are in agreement with the analytical or Runge-Kutta calculations.
Monte Carlo dose distributions for radiosurgery
Perucha, M.; Leal, A.; Rincon, M.; Carrasco, E. [Sevilla Univ. (Spain). Dept. Fisiologia Medica y Biofisica; Sanchez-Doblado, F. [Sevilla Univ. (Spain). Dept. Fisiologia Medica y Biofisica]|[Hospital Univ. Virgen Macarena, Sevilla (Spain). Servicio de Oncologia Radioterapica; Nunez, L. [Clinica Puerta de Hierro, Madrid (Spain). Servicio de Radiofisica; Arrans, R.; Sanchez-Calzado, J.A.; Errazquin, L. [Hospital Univ. Virgen Macarena, Sevilla (Spain). Servicio de Oncologia Radioterapica; Sanchez-Nieto, B. [Royal Marsden NHS Trust (United Kingdom). Joint Dept. of Physics]|[Inst. of Cancer Research, Sutton, Surrey (United Kingdom)
2001-07-01
The precision of Radiosurgery Treatment planning systems is limited by the approximations of their algorithms and by their dosimetrical input data. This fact is especially important in small fields. However, the Monte Carlo methods is an accurate alternative as it considers every aspect of particle transport. In this work an acoustic neurinoma is studied by comparing the dose distribution of both a planning system and Monte Carlo. Relative shifts have been measured and furthermore, Dose-Volume Histograms have been calculated for target and adjacent organs at risk. (orig.)
Monte carlo simulations of organic photovoltaics.
Groves, Chris; Greenham, Neil C
2014-01-01
Monte Carlo simulations are a valuable tool to model the generation, separation, and collection of charges in organic photovoltaics where charges move by hopping in a complex nanostructure and Coulomb interactions between charge carriers are important. We review the Monte Carlo techniques that have been applied to this problem, and describe the results of simulations of the various recombination processes that limit device performance. We show how these processes are influenced by the local physical and energetic structure of the material, providing information that is useful for design of efficient photovoltaic systems.
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.
The Rational Hybrid Monte Carlo Algorithm
Clark, M A
2006-01-01
The past few years have seen considerable progress in algorithmic development for the generation of gauge fields including the effects of dynamical fermions. The Rational Hybrid Monte Carlo (RHMC) algorithm, where Hybrid Monte Carlo is performed using a rational approximation in place the usual inverse quark matrix kernel is one of these developments. This algorithm has been found to be extremely beneficial in many areas of lattice QCD (chiral fermions, finite temperature, Wilson fermions etc.). We review the algorithm and some of these benefits, and we compare against other recent algorithm developements. We conclude with an update of the Berlin wall plot comparing costs of all popular fermion formulations.
The Rational Hybrid Monte Carlo algorithm
Clark, Michael
2006-12-01
The past few years have seen considerable progress in algorithmic development for the generation of gauge fields including the effects of dynamical fermions. The Rational Hybrid Monte Carlo (RHMC) algorithm, where Hybrid Monte Carlo is performed using a rational approximation in place the usual inverse quark matrix kernel is one of these developments. This algorithm has been found to be extremely beneficial in many areas of lattice QCD (chiral fermions, finite temperature, Wilson fermions etc.). We review the algorithm and some of these benefits, and we compare against other recent algorithm developements. We conclude with an update of the Berlin wall plot comparing costs of all popular fermion formulations.
林凌; 张林娜; 李晓霞; 李刚; 王为; 刘瑞安
2014-01-01
The present paper brings the parameters of the detection fiber into Monte Carlo model ,and we studied the influence of fiber optic parameters and the distance of fiber from the detector on the detected optic signal ,.The simulation results show that signals are obviously different when the NA (numerical aperture) and diameter of the fiber are different respectively .With the increase in NA and diameter of the fiber ,the diffuse reflectance and diffuse transmission increase gradually .However ,the dis-tance from the sample surface ,to some extent ,brings little influence when we control it within 1 mm .By further study of the simulation result ,we found that the collection efficient of the fiber is the same in different spatial positions .And the collection efficient of strong scattering material is a constant ,in spite of absorption coefficient and scattering coefficient .We can normalize the diffuse signals collected by fibers with different angular aperture βby the collection efficient .Meanwhile ,this paper provided the fitting curve of the collection efficient in a certain range .For fibers with different diameters ,we can get a good consistence by area normalization .Therefore ,the research on the effects of the difference of the detection fiber on diffuse hyper-spectrum has great significance for practical measurement .And the detection results can be transplanted by collection efficient and area nor-malization when we change the actual detecting fiber .%从漫射高光谱中可以获得被测物体成分、结构及其分布等信息。采用光纤光谱仪获取漫射高光谱是一种常用的方法。Monte Carlo 方法在研究光在浑浊介质的传播方面得到了广泛的应用。然而，使用Monte Carlo方法研究漫射高光谱时，必须考虑实际的检测条件对信号采集的影响。将光纤参数引入到Monte Carlo模型中，研究了光纤参数对被检测光学信号的影响。仿真结果表明，孔径角和半径增大，
Fast sequential Monte Carlo methods for counting and optimization
Rubinstein, Reuven Y; Vaisman, Radislav
2013-01-01
A comprehensive account of the theory and application of Monte Carlo methods Based on years of research in efficient Monte Carlo methods for estimation of rare-event probabilities, counting problems, and combinatorial optimization, Fast Sequential Monte Carlo Methods for Counting and Optimization is a complete illustration of fast sequential Monte Carlo techniques. The book provides an accessible overview of current work in the field of Monte Carlo methods, specifically sequential Monte Carlo techniques, for solving abstract counting and optimization problems. Written by authorities in the
Use of Monte Carlo Methods in brachytherapy; Uso del metodo de Monte Carlo en braquiterapia
Granero Cabanero, D.
2015-07-01
The Monte Carlo method has become a fundamental tool for brachytherapy dosimetry mainly because no difficulties associated with experimental dosimetry. In brachytherapy the main handicap of experimental dosimetry is the high dose gradient near the present sources making small uncertainties in the positioning of the detectors lead to large uncertainties in the dose. This presentation will review mainly the procedure for calculating dose distributions around a fountain using the Monte Carlo method showing the difficulties inherent in these calculations. In addition we will briefly review other applications of the method of Monte Carlo in brachytherapy dosimetry, as its use in advanced calculation algorithms, calculating barriers or obtaining dose applicators around. (Author)
On the use of stochastic approximation Monte Carlo for Monte Carlo integration
Liang, Faming
2009-03-01
The stochastic approximation Monte Carlo (SAMC) algorithm has recently been proposed as a dynamic optimization algorithm in the literature. In this paper, we show in theory that the samples generated by SAMC can be used for Monte Carlo integration via a dynamically weighted estimator by calling some results from the literature of nonhomogeneous Markov chains. Our numerical results indicate that SAMC can yield significant savings over conventional Monte Carlo algorithms, such as the Metropolis-Hastings algorithm, for the problems for which the energy landscape is rugged. © 2008 Elsevier B.V. All rights reserved.
Ramilowski, Jordan A; Farrelly, David
2012-06-14
The diffusion Monte Carlo (DMC) method is a widely used algorithm for computing both ground and excited states of many-particle systems; for states without nodes the algorithm is numerically exact. In the presence of nodes approximations must be introduced, for example, the fixed-node approximation. Recently we have developed a genetic algorithm (GA) based approach which allows the computation of nodal surfaces on-the-fly [Ramilowski and Farrelly, Phys. Chem. Chem. Phys., 2010, 12, 12450]. Here GA-DMC is applied to the computation of rovibrational states of CO-(4)He(N) complexes with N≤ 10. These complexes have been the subject of recent high resolution microwave and millimeter-wave studies which traced the onset of microscopic superfluidity in a doped (4)He droplet, one atom at a time, up to N = 10 [Surin et al., Phys. Rev. Lett., 2008, 101, 233401; Raston et al., Phys. Chem. Chem. Phys., 2010, 12, 8260]. The frequencies of the a-type (microwave) series, which correlate with end-over-end rotation in the CO-(4)He dimer, decrease from N = 1 to 3 and then smoothly increase. This signifies the transition from a molecular complex to a quantum solvated system. The frequencies of the b-type (millimeter-wave) series, which evolves from free rotation of the rigid CO molecule, initially increase from N = 0 to N∼ 6 before starting to decrease with increasing N. An interesting feature of the b-type series, originally observed in the high resolution infra-red (IR) experiments of Tang and McKellar [J. Chem. Phys., 2003, 119, 754] is that, for N = 7, two lines are observed. The GA-DMC algorithm is found to be in good agreement with experimental results and possibly detects the small (∼0.7 cm(-1)) splitting in the b-series line at N = 7. Advantages and disadvantages of GA-DMC are discussed.
Mancini, John S; Bowman, Joel M
2013-03-28
We report a global, full-dimensional, ab initio potential energy surface describing the HCl-H2O dimer. The potential is constructed from a permutationally invariant fit, using Morse-like variables, to over 44,000 CCSD(T)-F12b∕aug-cc-pVTZ energies. The surface describes the complex and dissociated monomers with a total RMS fitting error of 24 cm(-1). The normal modes of the minima, low-energy saddle point and separated monomers, the double minimum isomerization pathway and electronic dissociation energy are accurately described by the surface. Rigorous quantum mechanical diffusion Monte Carlo (DMC) calculations are performed to determine the zero-point energy and wavefunction of the complex and the separated fragments. The calculated zero-point energies together with a De value calculated from CCSD(T) with a complete basis set extrapolation gives a D0 value of 1348 ± 3 cm(-1), in good agreement with the recent experimentally reported value of 1334 ± 10 cm(-1) [B. E. Casterline, A. K. Mollner, L. C. Ch'ng, and H. Reisler, J. Phys. Chem. A 114, 9774 (2010)]. Examination of the DMC wavefunction allows for confident characterization of the zero-point geometry to be dominant at the C(2v) double-well saddle point and not the C(s) global minimum. Additional support for the delocalized zero-point geometry is given by numerical solutions to the 1D Schrödinger equation along the imaginary-frequency out-of-plane bending mode, where the zero-point energy is calculated to be 52 cm(-1) above the isomerization barrier. The D0 of the fully deuterated isotopologue is calculated to be 1476 ± 3 cm(-1), which we hope will stand as a benchmark for future experimental work.
2007-01-01
Extravascular signal decay rate R2 or R2∗ as a function of blood oxygenation, geometry, and field strength was calculated using a Monte Carlo (MC) algorithm for a wider parameter range than hitherto by others. The relaxation rates of gradient-recalled-echo (GRE) and Hahn-spin-echo (HSE) imaging in the presence of blood vessels (ranging from capillaries to veins) have been computed for a wide range of ...
A comparison of Monte Carlo generators
Golan, Tomasz
2014-01-01
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 $\\pi^+$ two-dimensional energy vs cosine distribution.
Monte Carlo Tools for Jet Quenching
Zapp, Korinna
2011-01-01
A thorough understanding of jet quenching on the basis of multi-particle final states and jet observables requires new theoretical tools. This talk summarises the status and propects of the theoretical description of jet quenching in terms of Monte Carlo generators.
An Introduction to Monte Carlo Methods
Raeside, D. E.
1974-01-01
Reviews the principles of Monte Carlo calculation and random number generation in an attempt to introduce the direct and the rejection method of sampling techniques as well as the variance-reduction procedures. Indicates that the increasing availability of computers makes it possible for a wider audience to learn about these powerful methods. (CC)
Variance Reduction Techniques in Monte Carlo Methods
Kleijnen, Jack P.C.; Ridder, A.A.N.; Rubinstein, R.Y.
2010-01-01
Monte Carlo methods are simulation algorithms to estimate a numerical quantity in a statistical model of a real system. These algorithms are executed by computer programs. Variance reduction techniques (VRT) are needed, even though computer speed has been increasing dramatically, ever since the intr
Scalable Domain Decomposed Monte Carlo Particle Transport
O' Brien, Matthew Joseph [Univ. of California, Davis, CA (United States)
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.
Monte Carlo methods beyond detailed balance
Schram, Raoul D.; Barkema, Gerard T.
2015-01-01
Monte Carlo algorithms are nearly always based on the concept of detailed balance and ergodicity. In this paper we focus on algorithms that do not satisfy detailed balance. We introduce a general method for designing non-detailed balance algorithms, starting from a conventional algorithm satisfying
Variance Reduction Techniques in Monte Carlo Methods
Kleijnen, Jack P.C.; Ridder, A.A.N.; Rubinstein, R.Y.
2010-01-01
Monte Carlo methods are simulation algorithms to estimate a numerical quantity in a statistical model of a real system. These algorithms are executed by computer programs. Variance reduction techniques (VRT) are needed, even though computer speed has been increasing dramatically, ever since the intr
An analysis of Monte Carlo tree search
James, S
2017-02-01
Full Text Available Monte Carlo Tree Search (MCTS) is a family of directed search algorithms that has gained widespread attention in recent years. Despite the vast amount of research into MCTS, the effect of modifications on the algorithm, as well as the manner...
Monte Carlo Simulation of Counting Experiments.
Ogden, Philip M.
A computer program to perform a Monte Carlo simulation of counting experiments was written. The program was based on a mathematical derivation which started with counts in a time interval. The time interval was subdivided to form a binomial distribution with no two counts in the same subinterval. Then the number of subintervals was extended to…
A Monte Carlo Model of Light Propagation in Nontransparent Tissue
姚建铨; 朱水泉; 胡海峰; 王瑞康
2004-01-01
To sharpen the imaging of structures, it is vital to develop a convenient and efficient quantitative algorithm of the optical coherence tomography (OCT) sampling. In this paper a new Monte Carlo model is set up and how light propagates in bio-tissue is analyzed in virtue of mathematics and physics equations. The relations,in which light intensity of Class 1 and Class 2 light with different wavelengths changes with their permeation depth,and in which Class 1 light intensity (signal light intensity) changes with the probing depth, and in which angularly resolved diffuse reflectance and diffuse transmittance change with the exiting angle, are studied. The results show that Monte Carlo simulation results are consistent with the theory data.
Monte Carlo radiation transport in external beam radiotherapy
Çeçen, Yiğit
2013-01-01
The use of Monte Carlo in radiation transport is an effective way to predict absorbed dose distributions. Monte Carlo modeling has contributed to a better understanding of photon and electron transport by radiotherapy physicists. The aim of this review is to introduce Monte Carlo as a powerful radiation transport tool. In this review, photon and electron transport algorithms for Monte Carlo techniques are investigated and a clinical linear accelerator model is studied for external beam radiot...
Reboredo, F A; Hood, R Q; Kent, P C
2009-01-06
We develop a formalism and present an algorithm for optimization of the trial wave-function used in fixed-node diffusion quantum Monte Carlo (DMC) methods. The formalism is based on the DMC mixed estimator of the ground state probability density. We take advantage of a basic property of the walker configuration distribution generated in a DMC calculation, to (i) project-out a multi-determinant expansion of the fixed node ground state wave function and (ii) to define a cost function that relates the interacting-ground-state-fixed-node and the non-interacting trial wave functions. We show that (a) locally smoothing out the kink of the fixed-node ground-state wave function at the node generates a new trial wave function with better nodal structure and (b) we argue that the noise in the fixed-node wave function resulting from finite sampling plays a beneficial role, allowing the nodes to adjust towards the ones of the exact many-body ground state in a simulated annealing-like process. Based on these principles, we propose a method to improve both single determinant and multi-determinant expansions of the trial wave function. The method can be generalized to other wave function forms such as pfaffians. We test the method in a model system where benchmark configuration interaction calculations can be performed and most components of the Hamiltonian are evaluated analytically. Comparing the DMC calculations with the exact solutions, we find that the trial wave function is systematically improved. The overlap of the optimized trial wave function and the exact ground state converges to 100% even starting from wave functions orthogonal to the exact ground state. Similarly, the DMC total energy and density converges to the exact solutions for the model. In the optimization process we find an optimal non-interacting nodal potential of density-functional-like form whose existence was predicted in a previous publication [Phys. Rev. B 77 245110 (2008)]. Tests of the method are
Cooper, M A
2000-01-01
We present various approximations for the angular distribution of particles emerging from an optically thick, purely isotropically scattering region into a vacuum. Our motivation is to use such a distribution for the Fleck-Canfield random walk method [1] for implicit Monte Carlo (IMC) [2] radiation transport problems. We demonstrate that the cosine distribution recommended in the original random walk paper [1] is a poor approximation to the angular distribution predicted by transport theory. Then we examine other approximations that more closely match the transport angular distribution.
Hybrid Monte Carlo with Chaotic Mixing
Kadakia, Nirag
2016-01-01
We propose a hybrid Monte Carlo (HMC) technique applicable to high-dimensional multivariate normal distributions that effectively samples along chaotic trajectories. The method is predicated on the freedom of choice of the HMC momentum distribution, and due to its mixing properties, exhibits sample-to-sample autocorrelations that decay far faster than those in the traditional hybrid Monte Carlo algorithm. We test the methods on distributions of varying correlation structure, finding that the proposed technique produces superior covariance estimates, is less reliant on step-size tuning, and can even function with sparse or no momentum re-sampling. The method presented here is promising for more general distributions, such as those that arise in Bayesian learning of artificial neural networks and in the state and parameter estimation of dynamical systems.
Monte Carlo study of real time dynamics
Alexandru, Andrei; Bedaque, Paulo F; Vartak, Sohan; Warrington, Neill C
2016-01-01
Monte Carlo studies involving real time dynamics are severely restricted by the sign problem that emerges from highly oscillatory phase of the path integral. In this letter, we present a new method to compute real time quantities on the lattice using the Schwinger-Keldysh formalism via Monte Carlo simulations. The key idea is to deform the path integration domain to a complex manifold where the phase oscillations are mild and the sign problem is manageable. We use the previously introduced "contraction algorithm" to create a Markov chain on this alternative manifold. We substantiate our approach by analyzing the quantum mechanical anharmonic oscillator. Our results are in agreement with the exact ones obtained by diagonalization of the Hamiltonian. The method we introduce is generic and in principle applicable to quantum field theory albeit very slow. We discuss some possible improvements that should speed up the algorithm.
Multilevel sequential Monte-Carlo samplers
Jasra, Ajay
2016-01-05
Multilevel Monte-Carlo methods provide a powerful computational technique for reducing the computational cost of estimating expectations for a given computational effort. They are particularly relevant for computational problems when approximate distributions are determined via a resolution parameter h, with h=0 giving the theoretical exact distribution (e.g. SDEs or inverse problems with PDEs). The method provides a benefit by coupling samples from successive resolutions, and estimating differences of successive expectations. We develop a methodology that brings Sequential Monte-Carlo (SMC) algorithms within the framework of the Multilevel idea, as SMC provides a natural set-up for coupling samples over different resolutions. We prove that the new algorithm indeed preserves the benefits of the multilevel principle, even if samples at all resolutions are now correlated.
Monte Carlo Simulation for Particle Detectors
Pia, Maria Grazia
2012-01-01
Monte Carlo simulation is an essential component of experimental particle physics in all the phases of its life-cycle: the investigation of the physics reach of detector concepts, the design of facilities and detectors, the development and optimization of data reconstruction software, the data analysis for the production of physics results. This note briefly outlines some research topics related to Monte Carlo simulation, that are relevant to future experimental perspectives in particle physics. The focus is on physics aspects: conceptual progress beyond current particle transport schemes, the incorporation of materials science knowledge relevant to novel detection technologies, functionality to model radiation damage, the capability for multi-scale simulation, quantitative validation and uncertainty quantification to determine the predictive power of simulation. The R&D on simulation for future detectors would profit from cooperation within various components of the particle physics community, and synerg...
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.
Composite biasing in Monte Carlo radiative transfer
Baes, Maarten; Lunttila, Tuomas; Bianchi, Simone; Camps, Peter; Juvela, Mika; Kuiper, Rolf
2016-01-01
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 spe...
Multilevel Monte Carlo Approaches for Numerical Homogenization
Efendiev, Yalchin R.
2015-10-01
In this article, we study the application of multilevel Monte Carlo (MLMC) approaches to numerical random homogenization. Our objective is to compute the expectation of some functionals of the homogenized coefficients, or of the homogenized solutions. This is accomplished within MLMC by considering different sizes of representative volumes (RVEs). Many inexpensive computations with the smallest RVE size are combined with fewer expensive computations performed on larger RVEs. Likewise, when it comes to homogenized solutions, different levels of coarse-grid meshes are used to solve the homogenized equation. We show that, by carefully selecting the number of realizations at each level, we can achieve a speed-up in the computations in comparison to a standard Monte Carlo method. Numerical results are presented for both one-dimensional and two-dimensional test-cases that illustrate the efficiency of the approach.
Monte Carlo simulations on SIMD computer architectures
Burmester, C.P.; Gronsky, R. [Lawrence Berkeley Lab., CA (United States); Wille, L.T. [Florida Atlantic Univ., Boca Raton, FL (United States). Dept. of Physics
1992-03-01
Algorithmic considerations regarding the implementation of various materials science applications of the Monte Carlo technique to single instruction multiple data (SMM) computer architectures are presented. In particular, implementation of the Ising model with nearest, next nearest, and long range screened Coulomb interactions on the SIMD architecture MasPar MP-1 (DEC mpp-12000) series of massively parallel computers is demonstrated. Methods of code development which optimize processor array use and minimize inter-processor communication are presented including lattice partitioning and the use of processor array spanning tree structures for data reduction. Both geometric and algorithmic parallel approaches are utilized. Benchmarks in terms of Monte Carlo updates per second for the MasPar architecture are presented and compared to values reported in the literature from comparable studies on other architectures.
Handbook of Markov chain Monte Carlo
Brooks, Steve
2011-01-01
""Handbook of Markov Chain Monte Carlo"" brings together the major advances that have occurred in recent years while incorporating enough introductory material for new users of MCMC. Along with thorough coverage of the theoretical foundations and algorithmic and computational methodology, this comprehensive handbook includes substantial realistic case studies from a variety of disciplines. These case studies demonstrate the application of MCMC methods and serve as a series of templates for the construction, implementation, and choice of MCMC methodology.
Accelerated Monte Carlo by Embedded Cluster Dynamics
Brower, R. C.; Gross, N. A.; Moriarty, K. J. M.
1991-07-01
We present an overview of the new methods for embedding Ising spins in continuous fields to achieve accelerated cluster Monte Carlo algorithms. The methods of Brower and Tamayo and Wolff are summarized and variations are suggested for the O( N) models based on multiple embedded Z2 spin components and/or correlated projections. Topological features are discussed for the XY model and numerical simulations presented for d=2, d=3 and mean field theory lattices.
An introduction to Monte Carlo methods
Walter, J.-C.; Barkema, G. T.
2015-01-01
Monte Carlo simulations are methods for simulating statistical systems. The aim is to generate a representative ensemble of configurations to access thermodynamical quantities without the need to solve the system analytically or to perform an exact enumeration. The main principles of Monte Carlo simulations are ergodicity and detailed balance. The Ising model is a lattice spin system with nearest neighbor interactions that is appropriate to illustrate different examples of Monte Carlo simulations. It displays a second order phase transition between disordered (high temperature) and ordered (low temperature) phases, leading to different strategies of simulations. The Metropolis algorithm and the Glauber dynamics are efficient at high temperature. Close to the critical temperature, where the spins display long range correlations, cluster algorithms are more efficient. We introduce the rejection free (or continuous time) algorithm and describe in details an interesting alternative representation of the Ising model using graphs instead of spins with the so-called Worm algorithm. We conclude with an important discussion of the dynamical effects such as thermalization and correlation time.
Kinetic Monte Carlo Studies of Hydrogen Abstraction from Graphite
Cuppen, H M
2008-01-01
We present Monte Carlo simulations on Eley-Rideal abstraction reactions of atomic hydrogen chemisorbed on graphite. The results are obtained via a hybrid approach where energy barriers derived from density functional theory calculations are used as input to Monte Carlo simulations. By comparing with experimental data, we discriminate between contributions from different Eley-Rideal mechanisms. A combination of two different mechanisms yields good quantitative and qualitative agreement between the experimentally derived and the simulated Eley-Rideal abstraction cross sections and surface configurations. These two mechanisms include a direct Eley-Rideal reaction with fast diffusing H atoms and a dimer mediated Eley-Rideal mechanism with increased cross section at low coverage. Such a dimer mediated Eley-Rideal mechanism has not previously been proposed and serves as an alternative explanation to the steering behavior often given as the cause of the coverage dependence observed in Eley-Rideal reaction cross sect...
Minimising biases in full configuration interaction quantum Monte Carlo
Vigor, W. A.; Spencer, J. S.; Bearpark, M. J.; Thom, A. J. W.
2015-03-01
We show that Full Configuration Interaction Quantum Monte Carlo (FCIQMC) is a Markov chain in its present form. We construct the Markov matrix of FCIQMC for a two determinant system and hence compute the stationary distribution. These solutions are used to quantify the dependence of the population dynamics on the parameters defining the Markov chain. Despite the simplicity of a system with only two determinants, it still reveals a population control bias inherent to the FCIQMC algorithm. We investigate the effect of simulation parameters on the population control bias for the neon atom and suggest simulation setups to, in general, minimise the bias. We show a reweight ing scheme to remove the bias caused by population control commonly used in diffusion Monte Carlo [Umrigar et al., J. Chem. Phys. 99, 2865 (1993)] is effective and recommend its use as a post processing step.
Minimising biases in full configuration interaction quantum Monte Carlo.
Vigor, W A; Spencer, J S; Bearpark, M J; Thom, A J W
2015-03-14
We show that Full Configuration Interaction Quantum Monte Carlo (FCIQMC) is a Markov chain in its present form. We construct the Markov matrix of FCIQMC for a two determinant system and hence compute the stationary distribution. These solutions are used to quantify the dependence of the population dynamics on the parameters defining the Markov chain. Despite the simplicity of a system with only two determinants, it still reveals a population control bias inherent to the FCIQMC algorithm. We investigate the effect of simulation parameters on the population control bias for the neon atom and suggest simulation setups to, in general, minimise the bias. We show a reweight ing scheme to remove the bias caused by population control commonly used in diffusion Monte Carlo [Umrigar et al., J. Chem. Phys. 99, 2865 (1993)] is effective and recommend its use as a post processing step.
Quantum Monte Carlo calculations with chiral effective field theory interactions.
Gezerlis, A; Tews, I; Epelbaum, E; Gandolfi, S; Hebeler, K; Nogga, A; Schwenk, A
2013-07-19
We present the first quantum Monte Carlo (QMC) calculations with chiral effective field theory (EFT) interactions. To achieve this, we remove all sources of nonlocality, which hamper the inclusion in QMC calculations, in nuclear forces to next-to-next-to-leading order. We perform auxiliary-field diffusion Monte Carlo (AFDMC) calculations for the neutron matter energy up to saturation density based on local leading-order, next-to-leading order, and next-to-next-to-leading order nucleon-nucleon interactions. Our results exhibit a systematic order-by-order convergence in chiral EFT and provide nonperturbative benchmarks with theoretical uncertainties. For the softer interactions, perturbative calculations are in excellent agreement with the AFDMC results. This work paves the way for QMC calculations with systematic chiral EFT interactions for nuclei and nuclear matter, for testing the perturbativeness of different orders, and allows for matching to lattice QCD results by varying the pion mass.
Guideline of Monte Carlo calculation. Neutron/gamma ray transport simulation by Monte Carlo method
2002-01-01
This report condenses basic theories and advanced applications of neutron/gamma ray transport calculations in many fields of nuclear energy research. Chapters 1 through 5 treat historical progress of Monte Carlo methods, general issues of variance reduction technique, cross section libraries used in continuous energy Monte Carlo codes. In chapter 6, the following issues are discussed: fusion benchmark experiments, design of ITER, experiment analyses of fast critical assembly, core analyses of JMTR, simulation of pulsed neutron experiment, core analyses of HTTR, duct streaming calculations, bulk shielding calculations, neutron/gamma ray transport calculations of the Hiroshima atomic bomb. Chapters 8 and 9 treat function enhancements of MCNP and MVP codes, and a parallel processing of Monte Carlo calculation, respectively. An important references are attached at the end of this report.
Díez, A; Largo, J; Solana, J R
2006-08-21
Computer simulations have been performed for fluids with van der Waals potential, that is, hard spheres with attractive inverse power tails, to determine the equation of state and the excess energy. On the other hand, the first- and second-order perturbative contributions to the energy and the zero- and first-order perturbative contributions to the compressibility factor have been determined too from Monte Carlo simulations performed on the reference hard-sphere system. The aim was to test the reliability of this "exact" perturbation theory. It has been found that the results obtained from the Monte Carlo perturbation theory for these two thermodynamic properties agree well with the direct Monte Carlo simulations. Moreover, it has been found that results from the Barker-Henderson [J. Chem. Phys. 47, 2856 (1967)] perturbation theory are in good agreement with those from the exact perturbation theory.
Nourdine Massoum
2014-04-01
Full Text Available The field of microelectronics has made surprising advances in the last decade, mainly pushed by the enormous progress in semiconductor technology. Such a reduction of dimensions allows the fabrication of chips with more than one million components. In addition, it opens the way to new physical phenomena, which were not present in traditional structures. In this context, the Monte Carlo simulation has particular significance. This approach allowed conceiving applicable model for GaInP MESFET operating in the turn-one or pinch-off region, and valid for the short-channel and the long-channel GaInP MESFET, in which the two-dimensional potential distribution contributed by the depletion layer under the gate is obtained by conventional 1D approximation
Chemical accuracy from quantum Monte Carlo for the benzene dimer
Azadi, Sam, E-mail: s.azadi@ucl.ac.uk [Department of Earth Science and Thomas Young Centre, University College London, London WC1E 6BT (United Kingdom); Cohen, R. E. [London Centre for Nanotechnology, University College London, London WC1E 6BT, United Kingdom and Extreme Materials Initiative, Geophysical Laboratory, Carnegie Institution of Washington, Washington, D.C. 20015 (United States)
2015-09-14
We report an accurate study of interactions between benzene molecules using variational quantum Monte Carlo (VMC) and diffusion quantum Monte Carlo (DMC) methods. We compare these results with density functional theory using different van der Waals functionals. In our quantum Monte Carlo (QMC) calculations, we use accurate correlated trial wave functions including three-body Jastrow factors and backflow transformations. We consider two benzene molecules in the parallel displaced geometry, and find that by highly optimizing the wave function and introducing more dynamical correlation into the wave function, we compute the weak chemical binding energy between aromatic rings accurately. We find optimal VMC and DMC binding energies of −2.3(4) and −2.7(3) kcal/mol, respectively. The best estimate of the coupled-cluster theory through perturbative triplets/complete basis set limit is −2.65(2) kcal/mol [Miliordos et al., J. Phys. Chem. A 118, 7568 (2014)]. Our results indicate that QMC methods give chemical accuracy for weakly bound van der Waals molecular interactions, comparable to results from the best quantum chemistry methods.
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.
A Monte Carlo algorithm for degenerate plasmas
Turrell, A.E., E-mail: a.turrell09@imperial.ac.uk; 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.
A note on simultaneous Monte Carlo tests
Hahn, Ute
In this short note, Monte Carlo tests of goodness of fit for data of the form X(t), t ∈ I are considered, that reject the null hypothesis if X(t) leaves an acceptance region bounded by an upper and lower curve for some t in I. A construction of the acceptance region is proposed that complies to a...... to a given target level of rejection, and yields exact p-values. The construction is based on pointwise quantiles, estimated from simulated realizations of X(t) under the null hypothesis....
Archimedes, the Free Monte Carlo simulator
Sellier, Jean Michel D
2012-01-01
Archimedes is the GNU package for Monte Carlo simulations of electron transport in semiconductor devices. The first release appeared in 2004 and since then it has been improved with many new features like quantum corrections, magnetic fields, new materials, GUI, etc. This document represents the first attempt to have a complete manual. Many of the Physics models implemented are described and a detailed description is presented to make the user able to write his/her own input deck. Please, feel free to contact the author if you want to contribute to the project.
Cluster hybrid Monte Carlo simulation algorithms
Plascak, J. A.; Ferrenberg, Alan M.; Landau, D. P.
2002-06-01
We show that addition of Metropolis single spin flips to the Wolff cluster-flipping Monte Carlo procedure leads to a dramatic increase in performance for the spin-1/2 Ising model. We also show that adding Wolff cluster flipping to the Metropolis or heat bath algorithms in systems where just cluster flipping is not immediately obvious (such as the spin-3/2 Ising model) can substantially reduce the statistical errors of the simulations. A further advantage of these methods is that systematic errors introduced by the use of imperfect random-number generation may be largely healed by hybridizing single spin flips with cluster flipping.
Introduction to Cluster Monte Carlo Algorithms
Luijten, E.
This chapter provides an introduction to cluster Monte Carlo algorithms for classical statistical-mechanical systems. A brief review of the conventional Metropolis algorithm is given, followed by a detailed discussion of the lattice cluster algorithm developed by Swendsen and Wang and the single-cluster variant introduced by Wolff. For continuum systems, the geometric cluster algorithm of Dress and Krauth is described. It is shown how their geometric approach can be generalized to incorporate particle interactions beyond hardcore repulsions, thus forging a connection between the lattice and continuum approaches. Several illustrative examples are discussed.
Monte Carlo simulation for the transport beamline
Romano, F.; Cuttone, G.; Jia, S. B.; Varisano, A. [INFN, Laboratori Nazionali del Sud, Via Santa Sofia 62, Catania (Italy); Attili, A.; Marchetto, F.; Russo, G. [INFN, Sezione di Torino, Via P.Giuria, 1 10125 Torino (Italy); Cirrone, G. A. P.; Schillaci, F.; Scuderi, V. [INFN, Laboratori Nazionali del Sud, Via Santa Sofia 62, Catania, Italy and Institute of Physics Czech Academy of Science, ELI-Beamlines project, Na Slovance 2, Prague (Czech Republic); Carpinelli, M. [INFN Sezione di Cagliari, c/o Dipartimento di Fisica, Università di Cagliari, Cagliari (Italy); Tramontana, A. [INFN, Laboratori Nazionali del Sud, Via Santa Sofia 62, Catania, Italy and Università di Catania, Dipartimento di Fisica e Astronomia, Via S. Sofia 64, Catania (Italy)
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.
Mosaic crystal algorithm for Monte Carlo simulations
Seeger, P A
2002-01-01
An algorithm is presented for calculating reflectivity, absorption, and scattering of mosaic crystals in Monte Carlo simulations of neutron instruments. The algorithm uses multi-step transport through the crystal with an exact solution of the Darwin equations at each step. It relies on the kinematical model for Bragg reflection (with parameters adjusted to reproduce experimental data). For computation of thermal effects (the Debye-Waller factor and coherent inelastic scattering), an expansion of the Debye integral as a rapidly converging series of exponential terms is also presented. Any crystal geometry and plane orientation may be treated. The algorithm has been incorporated into the neutron instrument simulation package NISP. (orig.)
Marcus, Ryan C. [Los Alamos National Laboratory
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.
Quantum Monte Carlo study of the first-row atoms and ions
Seth, P; Needs, R J
2010-01-01
Quantum Monte Carlo calculations of the first-row atoms Li-Ne and their singly-positively-charged ions are reported. Multi-determinant-Jastrow-backflow trial wave functions are used which recover more than 98% of the correlation energy at the Variational Monte Carlo (VMC) level and more than 99% of the correlation energy at the Diffusion Monte Carlo (DMC) level for both the atoms and ions. We obtain the first ionization potentials to chemical accuracy. We also report scalar relativistic corrections to the energies, mass-polarization terms, and one- and two-electron expectation values.
Development of a Monte-Carlo based method for calculating the effect of stationary fluctuations
Pettersen, E. E.; Demazire, C.; Jareteg, K.
2015-01-01
that corresponds to the real part of the neutron balance, and one that corresponds to the imaginary part. The two equivalent problems are in nature similar to two subcritical systems driven by external neutron sources, and can thus be treated as such in a Monte Carlo framework. The definition of these two...... of light water reactor conditions in an infinite lattice of fuel pins surrounded by water. The test case highlights flux gradients that are steeper in the Monte Carlo-based transport solution than in the diffusion-based solution. Compared to other Monte Carlo-based methods earlier proposed for carrying out...
State-of-the-art Monte Carlo 1988
Soran, P.D.
1988-06-28
Particle transport calculations in highly dimensional and physically complex geometries, such as detector calibration, radiation shielding, space reactors, and oil-well logging, generally require Monte Carlo transport techniques. Monte Carlo particle transport can be performed on a variety of computers ranging from APOLLOs to VAXs. Some of the hardware and software developments, which now permit Monte Carlo methods to be routinely used, are reviewed in this paper. The development of inexpensive, large, fast computer memory, coupled with fast central processing units, permits Monte Carlo calculations to be performed on workstations, minicomputers, and supercomputers. The Monte Carlo renaissance is further aided by innovations in computer architecture and software development. Advances in vectorization and parallelization architecture have resulted in the development of new algorithms which have greatly reduced processing times. Finally, the renewed interest in Monte Carlo has spawned new variance reduction techniques which are being implemented in large computer codes. 45 refs.
Monte Carlo Numerical Models for Nuclear Logging Applications
Fusheng Li
2012-06-01
Full Text Available Nuclear logging is one of most important logging services provided by many oil service companies. The main parameters of interest are formation porosity, bulk density, and natural radiation. Other services are also provided from using complex nuclear logging tools, such as formation lithology/mineralogy, etc. Some parameters can be measured by using neutron logging tools and some can only be measured by using a gamma ray tool. To understand the response of nuclear logging tools, the neutron transport/diffusion theory and photon diffusion theory are needed. Unfortunately, for most cases there are no analytical answers if complex tool geometry is involved. For many years, Monte Carlo numerical models have been used by nuclear scientists in the well logging industry to address these challenges. The models have been widely employed in the optimization of nuclear logging tool design, and the development of interpretation methods for nuclear logs. They have also been used to predict the response of nuclear logging systems for forward simulation problems. In this case, the system parameters including geometry, materials and nuclear sources, etc., are pre-defined and the transportation and interactions of nuclear particles (such as neutrons, photons and/or electrons in the regions of interest are simulated according to detailed nuclear physics theory and their nuclear cross-section data (probability of interacting. Then the deposited energies of particles entering the detectors are recorded and tallied and the tool responses to such a scenario are generated. A general-purpose code named Monte Carlo N– Particle (MCNP has been the industry-standard for some time. In this paper, we briefly introduce the fundamental principles of Monte Carlo numerical modeling and review the physics of MCNP. Some of the latest developments of Monte Carlo Models are also reviewed. A variety of examples are presented to illustrate the uses of Monte Carlo numerical models
Monte Carlo Simulations: Number of Iterations and Accuracy
2015-07-01
Jessica Schultheis for her editorial review. vi INTENTIONALLY LEFT BLANK. 1 1. Introduction Monte Carlo (MC) methods1 are often used...ARL-TN-0684 ● JULY 2015 US Army Research Laboratory Monte Carlo Simulations: Number of Iterations and Accuracy by William...needed. Do not return it to the originator. ARL-TN-0684 ● JULY 2015 US Army Research Laboratory Monte Carlo Simulations: Number
Alternative Monte Carlo Approach for General Global Illumination
徐庆; 李朋; 徐源; 孙济洲
2004-01-01
An alternative Monte Carlo strategy for the computation of global illumination problem was presented.The proposed approach provided a new and optimal way for solving Monte Carlo global illumination based on the zero variance importance sampling procedure. A new importance driven Monte Carlo global illumination algorithm in the framework of the new computing scheme was developed and implemented. Results, which were obtained by rendering test scenes, show that this new framework and the newly derived algorithm are effective and promising.
Validation of Compton Scattering Monte Carlo Simulation Models
Weidenspointner, Georg; Hauf, Steffen; Hoff, Gabriela; Kuster, Markus; Pia, Maria Grazia; Saracco, Paolo
2014-01-01
Several models for the Monte Carlo simulation of Compton scattering on electrons are quantitatively evaluated with respect to a large collection of experimental data retrieved from the literature. Some of these models are currently implemented in general purpose Monte Carlo systems; some have been implemented and evaluated for possible use in Monte Carlo particle transport for the first time in this study. Here we present first and preliminary results concerning total and differential Compton scattering cross sections.
Multiple Monte Carlo Testing with Applications in Spatial Point Processes
Mrkvička, Tomáš; Myllymäki, Mari; Hahn, Ute
with a function as the test statistic, 3) several Monte Carlo tests with functions as test statistics. The rank test has correct (global) type I error in each case and it is accompanied with a p-value and with a graphical interpretation which shows which subtest or which distances of the used test function......The rank envelope test (Myllym\\"aki et al., Global envelope tests for spatial processes, arXiv:1307.0239 [stat.ME]) is proposed as a solution to multiple testing problem for Monte Carlo tests. Three different situations are recognized: 1) a few univariate Monte Carlo tests, 2) a Monte Carlo test...
THE MCNPX MONTE CARLO RADIATION TRANSPORT CODE
WATERS, LAURIE S. [Los Alamos National Laboratory; MCKINNEY, GREGG W. [Los Alamos National Laboratory; DURKEE, JOE W. [Los Alamos National Laboratory; FENSIN, MICHAEL L. [Los Alamos National Laboratory; JAMES, MICHAEL R. [Los Alamos National Laboratory; JOHNS, RUSSELL C. [Los Alamos National Laboratory; PELOWITZ, DENISE B. [Los Alamos National Laboratory
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.
Multi-Index Monte Carlo (MIMC)
Haji Ali, Abdul Lateef
2015-01-07
We propose and analyze a novel Multi-Index Monte Carlo (MIMC) method for weak approximation of stochastic models that are described in terms of differential equations either driven by random measures or with random coefficients. The MIMC method is both a stochastic version of the combination technique introduced by Zenger, Griebel and collaborators and an extension of the Multilevel Monte Carlo (MLMC) method first described by Heinrich and Giles. Inspired by Giles’s seminal work, instead of using first-order differences as in MLMC, we use in MIMC high-order mixed differences to reduce the variance of the hierarchical differences dramatically. Under standard assumptions on the convergence rates of the weak error, variance and work per sample, the optimal index set turns out to be of Total Degree (TD) type. When using such sets, MIMC yields new and improved complexity results, which are natural generalizations of Giles’s MLMC analysis, and which increase the domain of problem parameters for which we achieve the optimal convergence.
Multi-Index Monte Carlo (MIMC)
Haji Ali, Abdul Lateef
2016-01-06
We propose and analyze a novel Multi-Index Monte Carlo (MIMC) method for weak approximation of stochastic models that are described in terms of differential equations either driven by random measures or with random coefficients. The MIMC method is both a stochastic version of the combination technique introduced by Zenger, Griebel and collaborators and an extension of the Multilevel Monte Carlo (MLMC) method first described by Heinrich and Giles. Inspired by Giles s seminal work, instead of using first-order differences as in MLMC, we use in MIMC high-order mixed differences to reduce the variance of the hierarchical differences dramatically. Under standard assumptions on the convergence rates of the weak error, variance and work per sample, the optimal index set turns out to be of Total Degree (TD) type. When using such sets, MIMC yields new and improved complexity results, which are natural generalizations of Giles s MLMC analysis, and which increase the domain of problem parameters for which we achieve the optimal convergence, O(TOL-2).
Discrete range clustering using Monte Carlo methods
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.
Quantum Monte Carlo Calculations of Neutron Matter
Carlson, J; Ravenhall, D G
2003-01-01
Uniform neutron matter is approximated by a cubic box containing a finite number of neutrons, with periodic boundary conditions. We report variational and Green's function Monte Carlo calculations of the ground state of fourteen neutrons in a periodic box using the Argonne $\\vep $ two-nucleon interaction at densities up to one and half times the nuclear matter density. The effects of the finite box size are estimated using variational wave functions together with cluster expansion and chain summation techniques. They are small at subnuclear densities. We discuss the expansion of the energy of low-density neutron gas in powers of its Fermi momentum. This expansion is strongly modified by the large nn scattering length, and does not begin with the Fermi-gas kinetic energy as assumed in both Skyrme and relativistic mean field theories. The leading term of neutron gas energy is ~ half the Fermi-gas kinetic energy. The quantum Monte Carlo results are also used to calibrate the accuracy of variational calculations ...
Information Geometry and Sequential Monte Carlo
Sim, Aaron; Stumpf, Michael P H
2012-01-01
This paper explores the application of methods from information geometry to the sequential Monte Carlo (SMC) sampler. In particular the Riemannian manifold Metropolis-adjusted Langevin algorithm (mMALA) is adapted for the transition kernels in SMC. Similar to its function in Markov chain Monte Carlo methods, the mMALA is a fully adaptable kernel which allows for efficient sampling of high-dimensional and highly correlated parameter spaces. We set up the theoretical framework for its use in SMC with a focus on the application to the problem of sequential Bayesian inference for dynamical systems as modelled by sets of ordinary differential equations. In addition, we argue that defining the sequence of distributions on geodesics optimises the effective sample sizes in the SMC run. We illustrate the application of the methodology by inferring the parameters of simulated Lotka-Volterra and Fitzhugh-Nagumo models. In particular we demonstrate that compared to employing a standard adaptive random walk kernel, the SM...
Particle acceleration at shocks - A Monte Carlo method
Kirk, J. G.; Schneider, P.
1987-01-01
A Monte Carlo method is presented for the problem of acceleration of test particles at relativistic shocks. The particles are assumed to diffuse in pitch angle as a result of scattering off magnetic irregularities frozen into the fluid. Several tests are performed using the analytic results available for both relativistic and nonrelativistic shock speeds. The acceleration at relativistic shocks under the influence of radiation losses is investigated, including the effects of a momentum dependence in the diffusion coefficient. The results demonstrate the usefulness of the technique in those situations in which the diffusion approximation cannot be employed, such as when relativistic bulk motion is considered, when particles are permitted to escape at the boundaries, and when the effects of the finite length of the particle mean free path are important.
Monte Carlo study of electron transport in monolayer silicene
Borowik, Piotr; Thobel, Jean-Luc; Adamowicz, Leszek
2016-11-01
Electron mobility and diffusion coefficients in monolayer silicene are calculated by Monte Carlo simulations using simplified band structure with linear energy bands. Results demonstrate reasonable agreement with the full-band Monte Carlo method in low applied electric field conditions. Negative differential resistivity is observed and an explanation of the origin of this effect is proposed. Electron mobility and diffusion coefficients are studied in low applied electric field conditions. We demonstrate that a comparison of these parameter values can provide a good check that the calculation is correct. Low-field mobility in silicene exhibits {T}-3 temperature dependence for nondegenerate electron gas conditions and {T}-1 for higher electron concentrations, when degenerate conditions are imposed. It is demonstrated that to explain the relation between mobility and temperature in nondegenerate electron gas the linearity of the band structure has to be taken into account. It is also found that electron-electron scattering only slightly modifies low-field electron mobility in degenerate electron gas conditions.
Morse Monte Carlo Radiation Transport Code System
Emmett, M.B.
1975-02-01
The report contains sections containing descriptions of the MORSE and PICTURE codes, input descriptions, sample problems, deviations of the physical equations and explanations of the various error messages. The MORSE code is a multipurpose neutron and gamma-ray transport Monte Carlo code. Time dependence for both shielding and criticality problems is provided. General three-dimensional geometry may be used with an albedo option available at any material surface. The PICTURE code provide aid in preparing correct input data for the combinatorial geometry package CG. It provides a printed view of arbitrary two-dimensional slices through the geometry. By inspecting these pictures one may determine if the geometry specified by the input cards is indeed the desired geometry. 23 refs. (WRF)
Variational Monte Carlo study of pentaquark states
Mark W. Paris
2005-07-01
Accurate numerical solution of the five-body Schrodinger equation is effected via variational Monte Carlo. The spectrum is assumed to exhibit a narrow resonance with strangeness S=+1. A fully antisymmetrized and pair-correlated five-quark wave function is obtained for the assumed non-relativistic Hamiltonian which has spin, isospin, and color dependent pair interactions and many-body confining terms which are fixed by the non-exotic spectra. Gauge field dynamics are modeled via flux tube exchange factors. The energy determined for the ground states with J=1/2 and negative (positive) parity is 2.22 GeV (2.50 GeV). A lower energy negative parity state is consistent with recent lattice results. The short-range structure of the state is analyzed via its diquark content.
Monte Carlo simulation of neutron scattering instruments
Seeger, P.A.; Daemen, L.L.; Hjelm, R.P. Jr.
1998-12-01
A code package consisting of the Monte Carlo Library MCLIB, the executing code MC{_}RUN, the web application MC{_}Web, and various ancillary codes is proposed as an open standard for simulation of neutron scattering instruments. The architecture of the package includes structures to define surfaces, regions, and optical elements contained in regions. A particle is defined by its vector position and velocity, its time of flight, its mass and charge, and a polarization vector. The MC{_}RUN code handles neutron transport and bookkeeping, while the action on the neutron within any region is computed using algorithms that may be deterministic, probabilistic, or a combination. Complete versatility is possible because the existing library may be supplemented by any procedures a user is able to code. Some examples are shown.
Atomistic Monte Carlo simulation of lipid membranes
Wüstner, Daniel; Sklenar, Heinz
2014-01-01
, 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......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...
Experimental Monte Carlo Quantum Process Certification
Steffen, L; Fedorov, A; Baur, M; Wallraff, A
2012-01-01
Experimental implementations of quantum information processing have now reached a level of sophistication where quantum process tomography is impractical. The number of experimental settings as well as the computational cost of the data post-processing now translates to days of effort to characterize even experiments with as few as 8 qubits. Recently a more practical approach to determine the fidelity of an experimental quantum process has been proposed, where the experimental data is compared directly to an ideal process using Monte Carlo sampling. Here we present an experimental implementation of this scheme in a circuit quantum electrodynamics setup to determine the fidelity of two qubit gates, such as the cphase and the cnot gate, and three qubit gates, such as the Toffoli gate and two sequential cphase gates.
Gas discharges modeling by Monte Carlo technique
Savić Marija
2010-01-01
Full Text Available The basic assumption of the Townsend theory - that ions produce secondary electrons - is valid only in a very narrow range of the reduced electric field E/N. In accordance with the revised Townsend theory that was suggested by Phelps and Petrović, secondary electrons are produced in collisions of ions, fast neutrals, metastable atoms or photons with the cathode, or in gas phase ionizations by fast neutrals. In this paper we tried to build up a Monte Carlo code that can be used to calculate secondary electron yields for different types of particles. The obtained results are in good agreement with the analytical results of Phelps and. Petrović [Plasma Sourc. Sci. Technol. 8 (1999 R1].
On nonlinear Markov chain Monte Carlo
Andrieu, Christophe; Doucet, Arnaud; Del Moral, Pierre; 10.3150/10-BEJ307
2011-01-01
Let $\\mathscr{P}(E)$ be the space of probability measures on a measurable space $(E,\\mathcal{E})$. In this paper we introduce a class of nonlinear Markov chain Monte Carlo (MCMC) methods for simulating from a probability measure $\\pi\\in\\mathscr{P}(E)$. Nonlinear Markov kernels (see [Feynman--Kac Formulae: Genealogical and Interacting Particle Systems with Applications (2004) Springer]) $K:\\mathscr{P}(E)\\times E\\rightarrow\\mathscr{P}(E)$ can be constructed to, in some sense, improve over MCMC methods. However, such nonlinear kernels cannot be simulated exactly, so approximations of the nonlinear kernels are constructed using auxiliary or potentially self-interacting chains. Several nonlinear kernels are presented and it is demonstrated that, under some conditions, the associated approximations exhibit a strong law of large numbers; our proof technique is via the Poisson equation and Foster--Lyapunov conditions. We investigate the performance of our approximations with some simulations.
Monte Carlo exploration of warped Higgsless models
Hewett, JoAnne L.; Lillie, Benjamin; Rizzo, Thomas Gerard [Stanford Linear Accelerator Center, 2575 Sand Hill Rd., Menlo Park, CA, 94025 (United States)]. E-mail: rizzo@slac.stanford.edu
2004-10-01
We have performed a detailed Monte Carlo exploration of the parameter space for a warped Higgsless model of electroweak symmetry breaking in 5 dimensions. This model is based on the SU(2){sub L} x SU(2){sub R} x U(1){sub B-L} gauge group in an AdS{sub 5} bulk with arbitrary gauge kinetic terms on both the Planck and TeV branes. Constraints arising from precision electroweak measurements and collider data are found to be relatively easy to satisfy. We show, however, that the additional requirement of perturbative unitarity up to the cut-off, {approx_equal} 10 TeV, in W{sub L}{sup +}W{sub L}{sup -} elastic scattering in the absence of dangerous tachyons eliminates all models. If successful models of this class exist, they must be highly fine-tuned. (author)
Monte Carlo Exploration of Warped Higgsless Models
Hewett, J L; Rizzo, T G
2004-01-01
We have performed a detailed Monte Carlo exploration of the parameter space for a warped Higgsless model of electroweak symmetry breaking in 5 dimensions. This model is based on the $SU(2)_L\\times SU(2)_R\\times U(1)_{B-L}$ gauge group in an AdS$_5$ bulk with arbitrary gauge kinetic terms on both the Planck and TeV branes. Constraints arising from precision electroweak measurements and collider data are found to be relatively easy to satisfy. We show, however, that the additional requirement of perturbative unitarity up to the cut-off, $\\simeq 10$ TeV, in $W_L^+W_L^-$ elastic scattering in the absence of dangerous tachyons eliminates all models. If successful models of this class exist, they must be highly fine-tuned.
Monte Carlo Implementation of Polarized Hadronization
Matevosyan, Hrayr H; Thomas, Anthony W
2016-01-01
We study the polarized quark hadronization in a Monte Carlo (MC) framework based on the recent extension of the quark-jet framework, where a self-consistent treatment of the quark polarization transfer in a sequential hadronization picture has been presented. Here, we first adopt this approach for MC simulations of hadronization process with finite number of produced hadrons, expressing the relevant probabilities in terms of the eight leading twist quark-to-quark transverse momentum dependent (TMD) splitting functions (SFs) for elementary $q \\to q'+h$ transition. We present explicit expressions for the unpolarized and Collins fragmentation functions (FFs) of unpolarized hadrons emitted at rank two. Further, we demonstrate that all the current spectator-type model calculations of the leading twist quark-to-quark TMD SFs violate the positivity constraints, and propose quark model based ansatz for these input functions that circumvents the problem. We validate our MC framework by explicitly proving the absence o...
Commensurabilities between ETNOs: a Monte Carlo survey
Marcos, C de la Fuente
2016-01-01
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 Nin...
Variable length trajectory compressible hybrid Monte Carlo
Nishimura, Akihiko
2016-01-01
Hybrid Monte Carlo (HMC) generates samples from a prescribed probability distribution in a configuration space by simulating Hamiltonian dynamics, followed by the Metropolis (-Hastings) acceptance/rejection step. Compressible HMC (CHMC) generalizes HMC to a situation in which the dynamics is reversible but not necessarily Hamiltonian. This article presents a framework to further extend the algorithm. Within the existing framework, each trajectory of the dynamics must be integrated for the same amount of (random) time to generate a valid Metropolis proposal. Our generalized acceptance/rejection mechanism allows a more deliberate choice of the integration time for each trajectory. The proposed algorithm in particular enables an effective application of variable step size integrators to HMC-type sampling algorithms based on reversible dynamics. The potential of our framework is further demonstrated by another extension of HMC which reduces the wasted computations due to unstable numerical approximations and corr...
Lunar Regolith Albedos Using Monte Carlos
Wilson, T. L.; Andersen, V.; Pinsky, L. S.
2003-01-01
The analysis of planetary regoliths for their backscatter albedos produced by cosmic rays (CRs) is important for space exploration and its potential contributions to science investigations in fundamental physics and astrophysics. Albedos affect all such experiments and the personnel that operate them. Groups have analyzed the production rates of various particles and elemental species by planetary surfaces when bombarded with Galactic CR fluxes, both theoretically and by means of various transport codes, some of which have emphasized neutrons. Here we report on the preliminary results of our current Monte Carlo investigation into the production of charged particles, neutrons, and neutrinos by the lunar surface using FLUKA. In contrast to previous work, the effects of charm are now included.
Nuclear reactions in Monte Carlo codes.
Ferrari, A; Sala, P R
2002-01-01
The physics foundations of hadronic interactions as implemented in most Monte Carlo codes are presented together with a few practical examples. The description of the relevant physics is presented schematically split into the major steps in order to stress the different approaches required for the full understanding of nuclear reactions at intermediate and high energies. Due to the complexity of the problem, only a few semi-qualitative arguments are developed in this paper. The description will be necessarily schematic and somewhat incomplete, but hopefully it will be useful for a first introduction into this topic. Examples are shown mostly for the high energy regime, where all mechanisms mentioned in the paper are at work and to which perhaps most of the readers are less accustomed. Examples for lower energies can be found in the references.
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......, 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....
Geometric Monte Carlo and Black Janus Geometries
Bak, Dongsu; Kim, Kyung Kiu; Min, Hyunsoo; Song, Jeong-Pil
2016-01-01
We describe an application of the Monte Carlo method to the Janus deformation of the black brane background. We present numerical results for three and five dimensional black Janus geometries with planar and spherical interfaces. In particular, we argue that the 5D geometry with a spherical interface has an application in understanding the finite temperature bag-like QCD model via the AdS/CFT correspondence. The accuracy and convergence of the algorithm are evaluated with respect to the grid spacing. The systematic errors of the method are determined using an exact solution of 3D black Janus. This numerical approach for solving linear problems is unaffected initial guess of a trial solution and can handle an arbitrary geometry under various boundary conditions in the presence of source fields.
Modeling neutron guides using Monte Carlo simulations
Wang, D Q; Crow, M L; Wang, X L; Lee, W T; Hubbard, C R
2002-01-01
Four neutron guide geometries, straight, converging, diverging and curved, were characterized using Monte Carlo ray-tracing simulations. The main areas of interest are the transmission of the guides at various neutron energies and the intrinsic time-of-flight (TOF) peak broadening. Use of a delta-function time pulse from a uniform Lambert neutron source allows one to quantitatively simulate the effect of guides' geometry on the TOF peak broadening. With a converging guide, the intensity and the beam divergence increases while the TOF peak width decreases compared with that of a straight guide. By contrast, use of a diverging guide decreases the intensity and the beam divergence, and broadens the width (in TOF) of the transmitted neutron pulse.
QUANTUM MONTE-CARLO SIMULATIONS - ALGORITHMS, LIMITATIONS AND APPLICATIONS
DERAEDT, H
1992-01-01
A survey is given of Quantum Monte Carlo methods currently used to simulate quantum lattice models. The formalisms employed to construct the simulation algorithms are sketched. The origin of fundamental (minus sign) problems which limit the applicability of the Quantum Monte Carlo approach is shown
QWalk: A Quantum Monte Carlo Program for Electronic Structure
Wagner, Lucas K; Mitas, Lubos
2007-01-01
We describe QWalk, a new computational package capable of performing Quantum Monte Carlo electronic structure calculations for molecules and solids with many electrons. We describe the structure of the program and its implementation of Quantum Monte Carlo methods. It is open-source, licensed under the GPL, and available at the web site http://www.qwalk.org
Quantum Monte Carlo Simulations : Algorithms, Limitations and Applications
Raedt, H. De
1992-01-01
A survey is given of Quantum Monte Carlo methods currently used to simulate quantum lattice models. The formalisms employed to construct the simulation algorithms are sketched. The origin of fundamental (minus sign) problems which limit the applicability of the Quantum Monte Carlo approach is shown
Reporting Monte Carlo Studies in Structural Equation Modeling
Boomsma, Anne
2013-01-01
In structural equation modeling, Monte Carlo simulations have been used increasingly over the last two decades, as an inventory from the journal Structural Equation Modeling illustrates. Reaching out to a broad audience, this article provides guidelines for reporting Monte Carlo studies in that fiel
Efficiency and accuracy of Monte Carlo (importance) sampling
Waarts, P.H.
2003-01-01
Monte Carlo Analysis is often regarded as the most simple and accurate reliability method. Be-sides it is the most transparent method. The only problem is the accuracy in correlation with the efficiency. Monte Carlo gets less efficient or less accurate when very low probabilities are to be computed
The Monte Carlo Method. Popular Lectures in Mathematics.
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…
Forest canopy BRDF simulation using Monte Carlo method
Huang, J.; Wu, B.; Zeng, Y.; Tian, Y.
2006-01-01
Monte Carlo method is a random statistic method, which has been widely used to simulate the Bidirectional Reflectance Distribution Function (BRDF) of vegetation canopy in the field of visible remote sensing. The random process between photons and forest canopy was designed using Monte Carlo method.
Sensitivity of Monte Carlo simulations to input distributions
RamoRao, B. S.; Srikanta Mishra, S.; McNeish, J.; Andrews, R. W.
2001-07-01
The sensitivity of the results of a Monte Carlo simulation to the shapes and moments of the probability distributions of the input variables is studied. An economical computational scheme is presented as an alternative to the replicate Monte Carlo simulations and is explained with an illustrative example. (Author) 4 refs.
Further experience in Bayesian analysis using Monte Carlo Integration
H.K. van Dijk (Herman); T. Kloek (Teun)
1980-01-01
textabstractAn earlier paper [Kloek and Van Dijk (1978)] is extended in three ways. First, Monte Carlo integration is performed in a nine-dimensional parameter space of Klein's model I [Klein (1950)]. Second, Monte Carlo is used as a tool for the elicitation of a uniform prior on a finite region by
New Approaches and Applications for Monte Carlo Perturbation Theory
Aufiero, Manuele; Bidaud, Adrien; Kotlyar, Dan; Leppänen, Jaakko; Palmiotti, Giuseppe; Salvatores, Massimo; Sen, Sonat; Shwageraus, Eugene; Fratoni, Massimiliano
2017-02-01
This paper presents some of the recent and new advancements in the extension of Monte Carlo Perturbation Theory methodologies and application. In particular, the discussed problems involve Brunup calculation, perturbation calculation based on continuous energy functions, and Monte Carlo Perturbation Theory in loosely coupled systems.
Forest canopy BRDF simulation using Monte Carlo method
Huang, J.; Wu, B.; Zeng, Y.; Tian, Y.
2006-01-01
Monte Carlo method is a random statistic method, which has been widely used to simulate the Bidirectional Reflectance Distribution Function (BRDF) of vegetation canopy in the field of visible remote sensing. The random process between photons and forest canopy was designed using Monte Carlo method.
CERN Summer Student Report 2016 Monte Carlo Data Base Improvement
Caciulescu, Alexandru Razvan
2016-01-01
During my Summer Student project I worked on improving the Monte Carlo Data Base and MonALISA services for the ALICE Collaboration. The project included learning the infrastructure for tracking and monitoring of the Monte Carlo productions as well as developing a new RESTful API for seamless integration with the JIRA issue tracking framework.
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, 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
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
2016-06-07
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
Fission Matrix Capability for MCNP Monte Carlo
Carney, Sean E. [Los Alamos National Laboratory; Brown, Forrest B. [Los Alamos National Laboratory; Kiedrowski, Brian C. [Los Alamos National Laboratory; Martin, William R. [Los Alamos National Laboratory
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
Vectorized Monte Carlo methods for reactor lattice analysis
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.
Quantum Monte Carlo methods algorithms for lattice models
Gubernatis, James; Werner, Philipp
2016-01-01
Featuring detailed explanations of the major algorithms used in quantum Monte Carlo simulations, this is the first textbook of its kind to provide a pedagogical overview of the field and its applications. The book provides a comprehensive introduction to the Monte Carlo method, its use, and its foundations, and examines algorithms for the simulation of quantum many-body lattice problems at finite and zero temperature. These algorithms include continuous-time loop and cluster algorithms for quantum spins, determinant methods for simulating fermions, power methods for computing ground and excited states, and the variational Monte Carlo method. Also discussed are continuous-time algorithms for quantum impurity models and their use within dynamical mean-field theory, along with algorithms for analytically continuing imaginary-time quantum Monte Carlo data. The parallelization of Monte Carlo simulations is also addressed. This is an essential resource for graduate students, teachers, and researchers interested in ...
Baräo, Fernando; Nakagawa, Masayuki; Távora, Luis; Vaz, Pedro
2001-01-01
This book focusses on the state of the art of Monte Carlo methods in radiation physics and particle transport simulation and applications, the latter involving in particular, the use and development of electron--gamma, neutron--gamma and hadronic codes. Besides the basic theory and the methods employed, special attention is paid to algorithm development for modeling, and the analysis of experiments and measurements in a variety of fields ranging from particle to medical physics.
Last-passage Monte Carlo algorithm for mutual capacitance.
Hwang, Chi-Ok; Given, James A
2006-08-01
We develop and test the last-passage diffusion algorithm, a charge-based Monte Carlo algorithm, for the mutual capacitance of a system of conductors. The first-passage algorithm is highly efficient because it is charge based and incorporates importance sampling; it averages over the properties of Brownian paths that initiate outside the conductor and terminate on its surface. However, this algorithm does not seem to generalize to mutual capacitance problems. The last-passage algorithm, in a sense, is the time reversal of the first-passage algorithm; it involves averages over particles that initiate on an absorbing surface, leave that surface, and diffuse away to infinity. To validate this algorithm, we calculate the mutual capacitance matrix of the circular-disk parallel-plate capacitor and compare with the known numerical results. Good agreement is obtained.
Lopez-Duran, D; Perez de Tudela, R; Rodriguez-Cantano, R; Gonzalez-Lezana, T; De Lara-Castells, M P; Delgado-Barrio, G; Villarreal, P, E-mail: davidl@iff.csic.es [Instituto de Fisica Fundamental, C.S.I.C., Serrano 123, 28006 Madrid (Spain)
2011-08-01
In this paper, we study the energy and geometric properties of Cs{sub 2}({sup 3}{Sigma}{sub u})-({sup 4}He){sub N} clusters, 2{<=}N{<=}20, N even, through a diffusion Monte Carlo methodology. Considering the results for doped clusters in which the He-impurity interaction dominates over the He-He one, our aim is to investigate the case when this assumption is not fulfilled anymore and the helium-helium potential becomes dominant. We find a scenario where a pure helium subcomplex is formed, leaving out the alkaline dimer, with the largest species gathering the helium atoms in a two-shell-like structure, the first of which is filled with ten particles. Our results are in agreement with previous theoretical and experimental findings.
Hu, Shuming; Mitas, Lubos
2012-02-01
Thorium dioxide solid is a unique optical and heat-resistant actinide material with large gap and cohesion. It is a diamagnet, unlike a number of other similar actinide oxides. We investigate the electronic structure of ThO2 using Density Functional Theory (DFT) and quantum Monte Carlo (QMC) methods. We adopt Stuttgart RLC and RSC effective core potentials (pseudopotentials) for the Th atom. In the DFT calculations, some of the properties are verified in all-electron calculations using the FLAPW techniques. Using the fixed-node diffusion Monte Carlo we calculate the ground state and several excited states from which we estimate the cohesion and the band gap. Simulation cells of several sizes are used to estimate/reduce the finite size effects. We compare the QMC results with recent DFT calculations with several types of functionals which include hybrids such as PBE0 and HSE. Insights from QMC calculations give us understanding of the correlations beyond the DFT approaches and pave the way for accurate electronic structure calculations of other actinide materials.
Chemical accuracy from quantum Monte Carlo for the Benzene Dimer
Azadi, Sam
2015-01-01
We report an accurate study of interactions between Benzene molecules using variational quantum Monte Carlo (VMC) and diffusion quantum Monte Carlo (DMC) methods. We compare these results with density functional theory (DFT) using different van der Waals (vdW) functionals. In our QMC calculations, we use accurate correlated trial wave functions including three-body Jastrow factors, and backflow transformations. We consider two benzene molecules in the parallel displaced (PD) geometry, and find that by highly optimizing the wave function and introducing more dynamical correlation into the wave function, we compute the weak chemical binding energy between aromatic rings accurately. We find optimal VMC and DMC binding energies of -2.3(4) and -2.7(3) kcal/mol, respectively. The best estimate of the CCSD(T)/CBS limit is -2.65(2) kcal/mol [E. Miliordos et al, J. Phys. Chem. A 118, 7568 (2014)]. Our results indicate that QMC methods give chemical accuracy for weakly bound van der Waals molecular interactions, compar...
Flow in Random Microstructures: a Multilevel Monte Carlo Approach
Icardi, Matteo
2016-01-06
In this work we are interested in the fast estimation of effective parameters of random heterogeneous materials using Multilevel Monte Carlo (MLMC). MLMC is an efficient and flexible solution for the propagation of uncertainties in complex models, where an explicit parametrisation of the input randomness is not available or too expensive. We propose a general-purpose algorithm and computational code for the solution of Partial Differential Equations (PDEs) on random heterogeneous materials. We make use of the key idea of MLMC, based on different discretization levels, extending it in a more general context, making use of a hierarchy of physical resolution scales, solvers, models and other numerical/geometrical discretisation parameters. Modifications of the classical MLMC estimators are proposed to further reduce variance in cases where analytical convergence rates and asymptotic regimes are not available. Spheres, ellipsoids and general convex-shaped grains are placed randomly in the domain with different placing/packing algorithms and the effective properties of the heterogeneous medium are computed. These are, for example, effective diffusivities, conductivities, and reaction rates. The implementation of the Monte-Carlo estimators, the statistical samples and each single solver is done efficiently in parallel. The method is tested and applied for pore-scale simulations of random sphere packings.
The Monte Carlo method the method of statistical trials
Shreider, YuA
1966-01-01
The Monte Carlo Method: The Method of Statistical Trials is a systematic account of the fundamental concepts and techniques of the Monte Carlo method, together with its range of applications. Some of these applications include the computation of definite integrals, neutron physics, and in the investigation of servicing processes. This volume is comprised of seven chapters and begins with an overview of the basic features of the Monte Carlo method and typical examples of its application to simple problems in computational mathematics. The next chapter examines the computation of multi-dimensio
Monte Carlo simulations for heavy ion dosimetry
Geithner, O.
2006-07-26
Water-to-air stopping power ratio (s{sub w,air}) calculations for the ionization chamber dosimetry of clinically relevant ion beams with initial energies from 50 to 450 MeV/u have been performed using the Monte Carlo technique. To simulate the transport of a particle in water the computer code SHIELD-HIT v2 was used which is a substantially modified version of its predecessor SHIELD-HIT v1. The code was partially rewritten, replacing formerly used single precision variables with double precision variables. The lowest particle transport specific energy was decreased from 1 MeV/u down to 10 keV/u by modifying the Bethe- Bloch formula, thus widening its range for medical dosimetry applications. Optional MSTAR and ICRU-73 stopping power data were included. The fragmentation model was verified using all available experimental data and some parameters were adjusted. The present code version shows excellent agreement with experimental data. Additional to the calculations of stopping power ratios, s{sub w,air}, the influence of fragments and I-values on s{sub w,air} for carbon ion beams was investigated. The value of s{sub w,air} deviates as much as 2.3% at the Bragg peak from the recommended by TRS-398 constant value of 1.130 for an energy of 50 MeV/u. (orig.)
Rare event simulation using Monte Carlo methods
Rubino, Gerardo
2009-01-01
In a probabilistic model, a rare event is an event with a very small probability of occurrence. The forecasting of rare events is a formidable task but is important in many areas. For instance a catastrophic failure in a transport system or in a nuclear power plant, the failure of an information processing system in a bank, or in the communication network of a group of banks, leading to financial losses. Being able to evaluate the probability of rare events is therefore a critical issue. Monte Carlo Methods, the simulation of corresponding models, are used to analyze rare events. This book sets out to present the mathematical tools available for the efficient simulation of rare events. Importance sampling and splitting are presented along with an exposition of how to apply these tools to a variety of fields ranging from performance and dependability evaluation of complex systems, typically in computer science or in telecommunications, to chemical reaction analysis in biology or particle transport in physics. ...
A continuation multilevel Monte Carlo algorithm
Collier, Nathan
2014-09-05
We propose a novel Continuation Multi Level Monte Carlo (CMLMC) algorithm for weak approximation of stochastic models. The CMLMC algorithm solves the given approximation problem for a sequence of decreasing tolerances, ending when the required error tolerance is satisfied. CMLMC assumes discretization hierarchies that are defined a priori for each level and are geometrically refined across levels. The actual choice of computational work across levels is based on parametric models for the average cost per sample and the corresponding variance and weak error. These parameters are calibrated using Bayesian estimation, taking particular notice of the deepest levels of the discretization hierarchy, where only few realizations are available to produce the estimates. The resulting CMLMC estimator exhibits a non-trivial splitting between bias and statistical contributions. We also show the asymptotic normality of the statistical error in the MLMC estimator and justify in this way our error estimate that allows prescribing both required accuracy and confidence in the final result. Numerical results substantiate the above results and illustrate the corresponding computational savings in examples that are described in terms of differential equations either driven by random measures or with random coefficients. © 2014, Springer Science+Business Media Dordrecht.
Monte Carlo Simulations of the Photospheric Process
Santana, Rodolfo; Hernandez, Roberto A; Kumar, Pawan
2015-01-01
We present a Monte Carlo (MC) code we wrote to simulate the photospheric process and to study the photospheric spectrum above the peak energy. Our simulations were performed with a photon to electron ratio $N_{\\gamma}/N_{e} = 10^{5}$, as determined by observations of the GRB prompt emission. We searched an exhaustive parameter space to determine if the photospheric process can match the observed high-energy spectrum of the prompt emission. If we do not consider electron re-heating, we determined that the best conditions to produce the observed high-energy spectrum are low photon temperatures and high optical depths. However, for these simulations, the spectrum peaks at an energy below 300 keV by a factor $\\sim 10$. For the cases we consider with higher photon temperatures and lower optical depths, we demonstrate that additional energy in the electrons is required to produce a power-law spectrum above the peak-energy. By considering electron re-heating near the photosphere, the spectrum for these simulations h...
Finding Planet Nine: a Monte Carlo approach
Marcos, C de la Fuente
2016-01-01
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 degrees, and an argument of perihelion of 150 degrees. 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 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 antialignment scenario. In addition and after studying the current statistic...
Atomistic Monte Carlo simulation of lipid membranes.
Wüstner, Daniel; Sklenar, Heinz
2014-01-24
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.
Parallel Monte Carlo Simulation of Aerosol Dynamics
Kun Zhou
2014-02-01
Full Text Available A highly efficient Monte Carlo (MC algorithm is developed for the numerical simulation of aerosol dynamics, that is, nucleation, surface growth, and coagulation. Nucleation and surface growth are handled with deterministic means, while coagulation is simulated with a stochastic method (Marcus-Lushnikov stochastic process. Operator splitting techniques are used to synthesize the deterministic and stochastic parts in the algorithm. The algorithm is parallelized using the Message Passing Interface (MPI. The parallel computing efficiency is investigated through numerical examples. Near 60% parallel efficiency is achieved for the maximum testing case with 3.7 million MC particles running on 93 parallel computing nodes. The algorithm is verified through simulating various testing cases and comparing the simulation results with available analytical and/or other numerical solutions. Generally, it is found that only small number (hundreds or thousands of MC particles is necessary to accurately predict the aerosol particle number density, volume fraction, and so forth, that is, low order moments of the Particle Size Distribution (PSD function. Accurately predicting the high order moments of the PSD needs to dramatically increase the number of MC particles.
Monte Carlo simulations of Protein Adsorption
Sharma, Sumit; Kumar, Sanat K.; Belfort, Georges
2008-03-01
Amyloidogenic diseases, such as, Alzheimer's are caused by adsorption and aggregation of partially unfolded proteins. Adsorption of proteins is a concern in design of biomedical devices, such as dialysis membranes. Protein adsorption is often accompanied by conformational rearrangements in protein molecules. Such conformational rearrangements are thought to affect many properties of adsorbed protein molecules such as their adhesion strength to the surface, biological activity, and aggregation tendency. It has been experimentally shown that many naturally occurring proteins, upon adsorption to hydrophobic surfaces, undergo a helix to sheet or random coil secondary structural rearrangement. However, to better understand the equilibrium structural complexities of this phenomenon, we have performed Monte Carlo (MC) simulations of adsorption of a four helix bundle, modeled as a lattice protein, and studied the adsorption behavior and equilibrium protein conformations at different temperatures and degrees of surface hydrophobicity. To study the free energy and entropic effects on adsorption, Canonical ensemble MC simulations have been combined with Weighted Histogram Analysis Method(WHAM). Conformational transitions of proteins on surfaces will be discussed as a function of surface hydrophobicity and compared to analogous bulk transitions.
Monte Carlo simulations of the NIMROD diffractometer
Botti, A. [University of Roma TRE, Rome (Italy)]. E-mail: botti@fis.uniroma3.it; Ricci, M.A. [University of Roma TRE, Rome (Italy); Bowron, D.T. [ISIS-Rutherford Appleton Laboratory, Chilton (United Kingdom); Soper, A.K. [ISIS-Rutherford Appleton Laboratory, Chilton (United Kingdom)
2006-11-15
The near and intermediate range order diffractometer (NIMROD) has been selected as a day one instrument on the second target station at ISIS. Uniquely, NIMROD will provide continuous access to particle separations ranging from the interatomic (<1A) to the mesoscopic (<300A). This instrument is mainly designed for structural investigations, although the possibility of putting a Fermi chopper (and corresponding NIMONIC chopper) in the incident beam line, will potentially allow the performance of low resolution inelastic scattering measurements. The performance characteristics of the TOF diffractometer have been simulated by means of a series of Monte Carlo calculations. In particular, the flux as a function of the transferred momentum Q as well as the resolution in Q and transferred energy have been estimated. Moreover, the possibility of including a honeycomb collimator in order to achieve better resolution has been tested. Here, we want to present the design of this diffractometer that will bridge the gap between wide- and small-angle neutron scattering experiments.
Monte Carlo Simulation of River Meander Modelling
Posner, A. J.; Duan, J. G.
2010-12-01
This study first compares the first order analytical solutions for flow field by Ikeda et. al. (1981) and Johanesson and Parker (1989b). Ikeda et. al.’s (1981) linear bank erosion model was implemented to predict the rate of bank erosion in which the bank erosion coefficient is treated as a stochastic variable that varies with physical properties of the bank (e.g. cohesiveness, stratigraphy, vegetation density). The developed model was used to predict the evolution of meandering planforms. Then, the modeling results were analyzed and compared to the observed data. Since the migration of meandering channel consists of downstream translation, lateral expansion, and downstream or upstream rotations. Several measures are formulated in order to determine which of the resulting planform is closest to the experimental measured one. Results from the deterministic model highly depend on the calibrated erosion coefficient. Since field measurements are always limited, the stochastic model yielded more realistic predictions of meandering planform evolutions. Due to the random nature of bank erosion coefficient, the meandering planform evolution is a stochastic process that can only be accurately predicted by a stochastic model. Quasi-2D Ikeda (1989) flow solution with Monte Carlo Simulation of Bank Erosion Coefficient.
Commensurabilities between ETNOs: a Monte Carlo survey
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 simulations for focusing elliptical guides
Valicu, Roxana [FRM2 Garching, Muenchen (Germany); Boeni, Peter [E20, TU Muenchen (Germany)
2009-07-01
The aim of the Monte Carlo simulations using McStas Programme was to improve the focusing of the neutron beam existing at PGAA (FRM II) by prolongation of the existing elliptic guide (coated now with supermirrors with m=3) with a new part. First we have tried with an initial length of the additional guide of 7,5cm and coatings for the neutron guide of supermirrors with m=4,5 and 6. The gain (calculated by dividing the intensity in the focal point after adding the guide by the intensity at the focal point with the initial guide) obtained for this coatings indicated that a coating with m=5 would be appropriate for a first trial. The next step was to vary the length of the additional guide for this m value and therefore choosing the appropriate length for the maximal gain. With the m value and the length of the guide fixed we have introduced an aperture 1 cm before the focal point and we have varied the radius of this aperture in order to obtain a focused beam. We have observed a dramatic decrease in the size of the beam in the focal point after introducing this aperture. The simulation results, the gains obtained and the evolution of the beam size will be presented.
Monte Carlo Production Management at CMS
Boudoul, G.; Pol, A; Srimanobhas, P; Vlimant, J R; Franzoni, Giovanni
2015-01-01
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 (2010-2012), 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 toaggregate the information needed for the configuration and prioritization of the events production,assure the book-keeping and 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 2012.McM is based on recent server infrastructure technology (CherryPy + java) and relies on a CouchDB database back-end.This contribution will coverthe one and half year of operational experience managing samples of simulated events for CMS,the evolution of its functionalitiesand the extension of its capabi...
Monte Carlo models of dust coagulation
Zsom, Andras
2010-01-01
The thesis deals with the first stage of planet formation, namely dust coagulation from micron to millimeter sizes in circumstellar disks. For the first time, we collect and compile the recent laboratory experiments on dust aggregates into a collision model that can be implemented into dust coagulation models. We put this model into a Monte Carlo code that uses representative particles to simulate dust evolution. Simulations are performed using three different disk models in a local box (0D) located at 1 AU distance from the central star. We find that the dust evolution does not follow the previously assumed growth-fragmentation cycle, but growth is halted by bouncing before the fragmentation regime is reached. We call this the bouncing barrier which is an additional obstacle during the already complex formation process of planetesimals. The absence of the growth-fragmentation cycle and the halted growth has two important consequences for planet formation. 1) It is observed that disk atmospheres are dusty thr...
Atomistic Monte Carlo Simulation of Lipid Membranes
Daniel Wüstner
2014-01-01
Full Text Available 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.
Parallel Monte Carlo simulation of aerosol dynamics
Zhou, K.
2014-01-01
A highly efficient Monte Carlo (MC) algorithm is developed for the numerical simulation of aerosol dynamics, that is, nucleation, surface growth, and coagulation. Nucleation and surface growth are handled with deterministic means, while coagulation is simulated with a stochastic method (Marcus-Lushnikov stochastic process). Operator splitting techniques are used to synthesize the deterministic and stochastic parts in the algorithm. The algorithm is parallelized using the Message Passing Interface (MPI). The parallel computing efficiency is investigated through numerical examples. Near 60% parallel efficiency is achieved for the maximum testing case with 3.7 million MC particles running on 93 parallel computing nodes. The algorithm is verified through simulating various testing cases and comparing the simulation results with available analytical and/or other numerical solutions. Generally, it is found that only small number (hundreds or thousands) of MC particles is necessary to accurately predict the aerosol particle number density, volume fraction, and so forth, that is, low order moments of the Particle Size Distribution (PSD) function. Accurately predicting the high order moments of the PSD needs to dramatically increase the number of MC particles. 2014 Kun Zhou et al.
Measuring Berry curvature with quantum Monte Carlo
Kolodrubetz, Michael
2014-01-01
The Berry curvature and its descendant, the Berry phase, play an important role in quantum mechanics. They can be used to understand the Aharonov-Bohm effect, define topological Chern numbers, and generally to investigate the geometric properties of a quantum ground state manifold. While Berry curvature has been well-studied in the regimes of few-body physics and non-interacting particles, its use in the regime of strong interactions is hindered by the lack of numerical methods to solve it. In this paper we fill this gap by implementing a quantum Monte Carlo method to solve for the Berry curvature, based on interpreting Berry curvature as a leading correction to imaginary time ramps. We demonstrate our algorithm using the transverse-field Ising model in one and two dimensions, the latter of which is non-integrable. Despite the fact that the Berry curvature gives information about the phase of the wave function, we show that our algorithm has no sign or phase problem for standard sign-problem-free Hamiltonians...
Radiation Transport for Explosive Outflows: A Multigroup Hybrid Monte Carlo Method
Wollaeger, Ryan T; Graziani, Carlo; Couch, Sean M; Jordan, George C; Lamb, Donald Q; Moses, Gregory A
2013-01-01
We explore the application of Implicit Monte Carlo (IMC) and Discrete Diffusion Monte Carlo (DDMC) to radiation transport in strong fluid outflows with structured opacity. The IMC method of Fleck & Cummings is a stochastic computational technique for nonlinear radiation transport. IMC is partially implicit in time and may suffer in efficiency when tracking Monte Carlo particles through optically thick materials. The DDMC method of Densmore accelerates an IMC computation where the domain is diffusive. Recently, Abdikamalov extended IMC and DDMC to multigroup, velocity-dependent neutrino transport with the intent of modeling neutrino dynamics in core-collapse supernovae. Densmore has also formulated a multifrequency extension to the originally grey DDMC method. In this article we rigorously formulate IMC and DDMC over a high-velocity Lagrangian grid for possible application to photon transport in the post-explosion phase of Type Ia supernovae. The method described is suitable for a large variety of non-mono...
Evidence for Stable Square Ice from Quantum Monte Carlo
Chen, Ji; Brandenburg, Jan Gerit; Alfè, Dario; Michaelides, Angelos
2016-01-01
Recent experiments on ice formed by water under nanoconfinement provide evidence for a two-dimensional (2D) `square ice' phase. However, the interpretation of the experiments has been questioned and the stability of square ice has become a matter of debate. Partially this is because the simulation approaches employed so far (force fields and density functional theory) struggle to accurately describe the very small energy differences between the relevant phases. Here we report a study of 2D ice using an accurate wave-function based electronic structure approach, namely Diffusion Monte Carlo (DMC). We find that at relatively high pressure square ice is indeed the lowest enthalpy phase examined, supporting the initial experimental claim. Moreover, at lower pressures a `pentagonal ice' phase (not yet observed experimentally) has the lowest enthalpy, and at ambient pressure the `pentagonal ice' phase is degenerate with a `hexagonal ice' phase. Our DMC results also allow us to evaluate the accuracy of various densi...
SPAMCART: a code for smoothed particle Monte Carlo radiative transfer
Lomax, O.; Whitworth, A. P.
2016-10-01
We present a code for generating synthetic spectral energy distributions and intensity maps from smoothed particle hydrodynamics simulation snapshots. The code is based on the Lucy Monte Carlo radiative transfer method, i.e. it follows discrete luminosity packets as they propagate through a density field, and then uses their trajectories to compute the radiative equilibrium temperature of the ambient dust. The sources can be extended and/or embedded, and discrete and/or diffuse. The density is not mapped on to a grid, and therefore the calculation is performed at exactly the same resolution as the hydrodynamics. We present two example calculations using this method. First, we demonstrate that the code strictly adheres to Kirchhoff's law of radiation. Secondly, we present synthetic intensity maps and spectra of an embedded protostellar multiple system. The algorithm uses data structures that are already constructed for other purposes in modern particle codes. It is therefore relatively simple to implement.
Quantum Monte Carlo calculations of two neutrons in finite volume
Klos, P; Tews, I; Gandolfi, S; Gezerlis, A; Hammer, H -W; Hoferichter, M; Schwenk, A
2016-01-01
Ab initio calculations provide direct access to the properties of pure neutron systems that are challenging to study experimentally. In addition to their importance for fundamental physics, their properties are required as input for effective field theories of the strong interaction. In this work, we perform auxiliary-field diffusion Monte Carlo calculations of the ground and first excited state of two neutrons in a finite box, considering a simple contact potential as well as chiral effective field theory interactions. We compare the results against exact diagonalizations and present a detailed analysis of the finite-volume effects, whose understanding is crucial for determining observables from the calculated energies. Using the L\\"uscher formula, we extract the low-energy S-wave scattering parameters from ground- and excited-state energies for different box sizes.
Random number generators tested on quantum Monte Carlo simulations.
Hongo, Kenta; Maezono, Ryo; Miura, Kenichi
2010-08-01
We have tested and compared several (pseudo) random number generators (RNGs) applied to a practical application, ground state energy calculations of molecules using variational and diffusion Monte Carlo metheds. A new multiple recursive generator with 8th-order recursion (MRG8) and the Mersenne twister generator (MT19937) are tested and compared with the RANLUX generator with five luxury levels (RANLUX-[0-4]). Both MRG8 and MT19937 are proven to give the same total energy as that evaluated with RANLUX-4 (highest luxury level) within the statistical error bars with less computational cost to generate the sequence. We also tested the notorious implementation of linear congruential generator (LCG), RANDU, for comparison.
Kinetic Monte Carlo modelling of neutron irradiation damage in iron
Gamez, L. [Instituto de Fusion Nuclear, UPM, Madrid (Spain); Departamento de Fisica Aplicada, ETSII, UPM, Madrid (Spain)], E-mail: linarejos.gamez@upm.es; Martinez, E. [Instituto de Fusion Nuclear, UPM, Madrid (Spain); Lawrence Livermore National Laboratory, LLNL, CA 94550 (United States); Perlado, J.M.; Cepas, P. [Instituto de Fusion Nuclear, UPM, Madrid (Spain); Caturla, M.J. [Departamento de Fisica Aplicada, Universidad de Alicante, Alicante (Spain); Victoria, M. [Instituto de Fusion Nuclear, UPM, Madrid (Spain); Marian, J. [Lawrence Livermore National Laboratory, LLNL, CA 94550 (United States); Arevalo, C. [Instituto de Fusion Nuclear, UPM, Madrid (Spain); Hernandez, M.; Gomez, D. [CIEMAT, Madrid (Spain)
2007-10-15
Ferritic steels (FeCr based alloys) are key materials needed to fulfill the requirements expected in future nuclear fusion facilities, both for magnetic and inertial confinement, and advanced fission reactors (GIV) and transmutation systems. Research in such field is actually a critical aspect in the European research program and abroad. Experimental and multiscale simulation methodologies are going hand by hand in increasing the knowledge of materials performance. At DENIM, it is progressing in some specific part of the well-linked simulation methodology both for defects energetics and diffusion, and for dislocation dynamics. In this study, results obtained from kinetic Monte Carlo simulations of neutron irradiated Fe under different conditions are presented, using modified ad hoc parameters. A significant agreement with experimental measurements has been found for some of the parameterization and mechanisms considered. The results of these simulations are discussed and compared with previous calculations.
Monte-Carlo simulation-based statistical modeling
Chen, John
2017-01-01
This book brings together expert researchers engaged in Monte-Carlo simulation-based statistical modeling, offering them a forum to present and discuss recent issues in methodological development as well as public health applications. It is divided into three parts, with the first providing an overview of Monte-Carlo techniques, the second focusing on missing data Monte-Carlo methods, and the third addressing Bayesian and general statistical modeling using Monte-Carlo simulations. The data and computer programs used here will also be made publicly available, allowing readers to replicate the model development and data analysis presented in each chapter, and to readily apply them in their own research. Featuring highly topical content, the book has the potential to impact model development and data analyses across a wide spectrum of fields, and to spark further research in this direction.
EXTENDED MONTE CARLO LOCALIZATION ALGORITHM FOR MOBILE SENSOR NETWORKS
无
2008-01-01
A real-world localization system for wireless sensor networks that adapts for mobility and irregular radio propagation model is considered.The traditional range-based techniques and recent range-free localization schemes are not welt competent for localization in mobile sensor networks,while the probabilistic approach of Bayesian filtering with particle-based density representations provides a comprehensive solution to such localization problem.Monte Carlo localization is a Bayesian filtering method that approximates the mobile node’S location by a set of weighted particles.In this paper,an enhanced Monte Carlo localization algorithm-Extended Monte Carlo Localization (Ext-MCL) is suitable for the practical wireless network environment where the radio propagation model is irregular.Simulation results show the proposal gets better localization accuracy and higher localizable node number than previously proposed Monte Carlo localization schemes not only for ideal radio model,but also for irregular one.
On the Markov Chain Monte Carlo (MCMC) method
Rajeeva L Karandikar
2006-04-01
Markov Chain Monte Carlo (MCMC) is a popular method used to generate samples from arbitrary distributions, which may be speciﬁed indirectly. In this article, we give an introduction to this method along with some examples.
Bayesian phylogeny analysis via stochastic approximation Monte Carlo
Cheon, Sooyoung
2009-11-01
Monte Carlo methods have received much attention in the recent literature of phylogeny analysis. However, the conventional Markov chain Monte Carlo algorithms, such as the Metropolis-Hastings algorithm, tend to get trapped in a local mode in simulating from the posterior distribution of phylogenetic trees, rendering the inference ineffective. In this paper, we apply an advanced Monte Carlo algorithm, the stochastic approximation Monte Carlo algorithm, to Bayesian phylogeny analysis. Our method is compared with two popular Bayesian phylogeny software, BAMBE and MrBayes, on simulated and real datasets. The numerical results indicate that our method outperforms BAMBE and MrBayes. Among the three methods, SAMC produces the consensus trees which have the highest similarity to the true trees, and the model parameter estimates which have the smallest mean square errors, but costs the least CPU time. © 2009 Elsevier Inc. All rights reserved.
Bayesian phylogeny analysis via stochastic approximation Monte Carlo.
Cheon, Sooyoung; Liang, Faming
2009-11-01
Monte Carlo methods have received much attention in the recent literature of phylogeny analysis. However, the conventional Markov chain Monte Carlo algorithms, such as the Metropolis-Hastings algorithm, tend to get trapped in a local mode in simulating from the posterior distribution of phylogenetic trees, rendering the inference ineffective. In this paper, we apply an advanced Monte Carlo algorithm, the stochastic approximation Monte Carlo algorithm, to Bayesian phylogeny analysis. Our method is compared with two popular Bayesian phylogeny software, BAMBE and MrBayes, on simulated and real datasets. The numerical results indicate that our method outperforms BAMBE and MrBayes. Among the three methods, SAMC produces the consensus trees which have the highest similarity to the true trees, and the model parameter estimates which have the smallest mean square errors, but costs the least CPU time.
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.
Monte Carlo simulations: Hidden errors from ``good'' random number generators
Ferrenberg, Alan M.; Landau, D. P.; Wong, Y. Joanna
1992-12-01
The Wolff algorithm is now accepted as the best cluster-flipping Monte Carlo algorithm for beating ``critical slowing down.'' We show how this method can yield incorrect answers due to subtle correlations in ``high quality'' random number generators.
An Introduction to Multilevel Monte Carlo for Option Valuation
Higham, Desmond J
2015-01-01
Monte Carlo is a simple and flexible tool that is widely used in computational finance. In this context, it is common for the quantity of interest to be the expected value of a random variable defined via a stochastic differential equation. In 2008, Giles proposed a remarkable improvement to the approach of discretizing with a numerical method and applying standard Monte Carlo. His multilevel Monte Carlo method offers an order of speed up given by the inverse of epsilon, where epsilon is the required accuracy. So computations can run 100 times more quickly when two digits of accuracy are required. The multilevel philosophy has since been adopted by a range of researchers and a wealth of practically significant results has arisen, most of which have yet to make their way into the expository literature. In this work, we give a brief, accessible, introduction to multilevel Monte Carlo and summarize recent results applicable to the task of option evaluation.
MODELING LEACHING OF VIRUSES BY THE MONTE CARLO METHOD
A predictive screening model was developed for fate and transport of viruses in the unsaturated zone. A database of input parameters allowed Monte Carlo analysis with the model. The resulting kernel densities of predicted attenuation during percolation indicated very ...
A MONTE-CARLO METHOD FOR ESTIMATING THE CORRELATION EXPONENT
MIKOSCH, T; WANG, QA
1995-01-01
We propose a Monte Carlo method for estimating the correlation exponent of a stationary ergodic sequence. The estimator can be considered as a bootstrap version of the classical Hill estimator. A simulation study shows that the method yields reasonable estimates.
Using Supervised Learning to Improve Monte Carlo Integral Estimation
Tracey, Brendan; Alonso, Juan J
2011-01-01
Monte Carlo (MC) techniques are often used to estimate integrals of a multivariate function using randomly generated samples of the function. In light of the increasing interest in uncertainty quantification and robust design applications in aerospace engineering, the calculation of expected values of such functions (e.g. performance measures) becomes important. However, MC techniques often suffer from high variance and slow convergence as the number of samples increases. In this paper we present Stacked Monte Carlo (StackMC), a new method for post-processing an existing set of MC samples to improve the associated integral estimate. StackMC is based on the supervised learning techniques of fitting functions and cross validation. It should reduce the variance of any type of Monte Carlo integral estimate (simple sampling, importance sampling, quasi-Monte Carlo, MCMC, etc.) without adding bias. We report on an extensive set of experiments confirming that the StackMC estimate of an integral is more accurate than ...
A MONTE-CARLO METHOD FOR ESTIMATING THE CORRELATION EXPONENT
MIKOSCH, T; WANG, QA
We propose a Monte Carlo method for estimating the correlation exponent of a stationary ergodic sequence. The estimator can be considered as a bootstrap version of the classical Hill estimator. A simulation study shows that the method yields reasonable estimates.
Accelerating Monte Carlo Renderers by Ray Histogram Fusion
Mauricio Delbracio
2015-03-01
Full Text Available This paper details the recently introduced Ray Histogram Fusion (RHF filter for accelerating Monte Carlo renderers [M. Delbracio et al., Boosting Monte Carlo Rendering by Ray Histogram Fusion, ACM Transactions on Graphics, 33 (2014]. In this filter, each pixel in the image is characterized by the colors of the rays that reach its surface. Pixels are compared using a statistical distance on the associated ray color distributions. Based on this distance, it decides whether two pixels can share their rays or not. The RHF filter is consistent: as the number of samples increases, more evidence is required to average two pixels. The algorithm provides a significant gain in PSNR, or equivalently accelerates the rendering process by using many fewer Monte Carlo samples without observable bias. Since the RHF filter depends only on the Monte Carlo samples color values, it can be naturally combined with all rendering effects.
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.
Public Infrastructure for Monte Carlo Simulation: publicMC@BATAN
Waskita, A A; Akbar, Z; Handoko, L T; 10.1063/1.3462759
2010-01-01
The first cluster-based public computing for Monte Carlo simulation in Indonesia is introduced. The system has been developed to enable public to perform Monte Carlo simulation on a parallel computer through an integrated and user friendly dynamic web interface. The beta version, so called publicMC@BATAN, has been released and implemented for internal users at the National Nuclear Energy Agency (BATAN). In this paper the concept and architecture of publicMC@BATAN are presented.
Radiative Equilibrium and Temperature Correction in Monte Carlo Radiation Transfer
Bjorkman, J. E.; Wood, Kenneth
2001-01-01
We describe a general radiative equilibrium and temperature correction procedure for use in Monte Carlo radiation transfer codes with sources of temperature-independent opacity, such as astrophysical dust. The technique utilizes the fact that Monte Carlo simulations track individual photon packets, so we may easily determine where their energy is absorbed. When a packet is absorbed, it heats a particular cell within the envelope, raising its temperature. To enforce radiative equilibrium, the ...
de Finetti Priors using Markov chain Monte Carlo computations.
Bacallado, Sergio; Diaconis, Persi; Holmes, Susan
2015-07-01
Recent advances in Monte Carlo methods allow us to revisit work by de Finetti who suggested the use of approximate exchangeability in the analyses of contingency tables. This paper gives examples of computational implementations using Metropolis Hastings, Langevin and Hamiltonian Monte Carlo to compute posterior distributions for test statistics relevant for testing independence, reversible or three way models for discrete exponential families using polynomial priors and Gröbner bases.
Event-chain Monte Carlo for classical continuous spin models
Michel, Manon; Mayer, Johannes; Krauth, Werner
2015-10-01
We apply the event-chain Monte Carlo algorithm to classical continuum spin models on a lattice and clarify the condition for its validity. In the two-dimensional XY model, it outperforms the local Monte Carlo algorithm by two orders of magnitude, although it remains slower than the Wolff cluster algorithm. In the three-dimensional XY spin glass model at low temperature, the event-chain algorithm is far superior to the other algorithms.
Study of the Transition Flow Regime using Monte Carlo Methods
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.
Monte Carlo Simulation of Optical Properties of Wake Bubbles
CAO Jing; WANG Jiang-An; JIANG Xing-Zhou; SHI Sheng-Wei
2007-01-01
Based on Mie scattering theory and the theory of multiple light scattering, the light scattering properties of air bubbles in a wake are analysed by Monte Carlo simulation. The results show that backscattering is enhanced obviously due to the existence of bubbles, especially with the increase of bubble density, and that it is feasible to use the Monte Carlo method to study the properties of light scattering by air bubbles.
Successful combination of the stochastic linearization and Monte Carlo methods
Elishakoff, I.; Colombi, P.
1993-01-01
A combination of a stochastic linearization and Monte Carlo techniques is presented for the first time in literature. A system with separable nonlinear damping and nonlinear restoring force is considered. The proposed combination of the energy-wise linearization with the Monte Carlo method yields an error under 5 percent, which corresponds to the error reduction associated with the conventional stochastic linearization by a factor of 4.6.
Monte Carlo methods for light propagation in biological tissues
Vinckenbosch, Laura; Lacaux, Céline; Tindel, Samy; Thomassin, Magalie; Obara, Tiphaine
2016-01-01
Light propagation in turbid media is driven by the equation of radiative transfer. We give a formal probabilistic representation of its solution in the framework of biological tissues and we implement algorithms based on Monte Carlo methods in order to estimate the quantity of light that is received by a homogeneous tissue when emitted by an optic fiber. A variance reduction method is studied and implemented, as well as a Markov chain Monte Carlo method based on the Metropolis–Hastings algori...
Multiscale Monte Carlo equilibration: pure Yang-Mills theory
Endres, Michael G; Detmold, William; Orginos, Kostas; Pochinsky, Andrew V
2015-01-01
We present a multiscale thermalization algorithm for lattice gauge theory, which enables efficient parallel generation of uncorrelated gauge field configurations. The algorithm combines standard Monte Carlo techniques with ideas drawn from real space renormalization group and multigrid methods. We demonstrate the viability of the algorithm for pure Yang-Mills gauge theory for both heat bath and hybrid Monte Carlo evolution, and show that it ameliorates the problem of topological freezing up to controllable lattice spacing artifacts.
Geometrical and Monte Carlo projectors in 3D PET reconstruction
Aguiar, Pablo; Rafecas López, Magdalena; Ortuno, Juan Enrique; Kontaxakis, George; Santos, Andrés; Pavía, Javier; Ros, Domènec
2010-01-01
Purpose: In the present work, the authors compare geometrical and Monte Carlo projectors in detail. The geometrical projectors considered were the conventional geometrical Siddon ray-tracer (S-RT) and the orthogonal distance-based ray-tracer (OD-RT), based on computing the orthogonal distance from the center of image voxel to the line-of-response. A comparison of these geometrical projectors was performed using different point spread function (PSF) models. The Monte Carlo-based method under c...
Monte Carlo method for solving a parabolic problem
Tian Yi
2016-01-01
Full Text Available In this paper, we present a numerical method based on random sampling for a parabolic problem. This method combines use of the Crank-Nicolson method and Monte Carlo method. In the numerical algorithm, we first discretize governing equations by Crank-Nicolson method, and obtain a large sparse system of linear algebraic equations, then use Monte Carlo method to solve the linear algebraic equations. To illustrate the usefulness of this technique, we apply it to some test problems.
MONTE CARLO SIMULATION OF CHARGED PARTICLE IN AN ELECTRONEGATIVE PLASMA
L SETTAOUTI
2003-12-01
Full Text Available Interest in radio frequency (rf discharges has grown tremendously in recent years due to their importance in microelectronic technologies. Especially interesting are the properties of discharges in electronegative gases which are most frequently used for technological applications. Monte Carlo simulation have become increasingly important as a simulation tool particularly in the area of plasma physics. In this work, we present some detailed properties of rf plasmas obtained by Monte Carlo simulation code, in SF6
Monte Carlo Volcano Seismic Moment Tensors
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.
Quantum Monte Carlo with directed loops.
Syljuåsen, Olav F; Sandvik, Anders W
2002-10-01
We introduce the concept of directed loops in stochastic series expansion and path-integral quantum Monte Carlo methods. Using the detailed balance rules for directed loops, we show that it is possible to smoothly connect generally applicable simulation schemes (in which it is necessary to include backtracking processes in the loop construction) to more restricted loop algorithms that can be constructed only for a limited range of Hamiltonians (where backtracking can be avoided). The "algorithmic discontinuities" between general and special points (or regions) in parameter space can hence be eliminated. As a specific example, we consider the anisotropic S=1/2 Heisenberg antiferromagnet in an external magnetic field. We show that directed-loop simulations are very efficient for the full range of magnetic fields (zero to the saturation point) and anisotropies. In particular, for weak fields and anisotropies, the autocorrelations are significantly reduced relative to those of previous approaches. The back-tracking probability vanishes continuously as the isotropic Heisenberg point is approached. For the XY model, we show that back tracking can be avoided for all fields extending up to the saturation field. The method is hence particularly efficient in this case. We use directed-loop simulations to study the magnetization process in the two-dimensional Heisenberg model at very low temperatures. For LxL lattices with L up to 64, we utilize the step structure in the magnetization curve to extract gaps between different spin sectors. Finite-size scaling of the gaps gives an accurate estimate of the transverse susceptibility in the thermodynamic limit: chi( perpendicular )=0.0659+/-0.0002.
Monte Carlo simulation of large electron fields
Faddegon, Bruce A.; Perl, Joseph; Asai, Makoto
2008-03-01
Two Monte Carlo systems, EGSnrc and Geant4, the latter with two different 'physics lists,' were used to calculate dose distributions in large electron fields used in radiotherapy. Source and geometry parameters were adjusted to match calculated results to measurement. Both codes were capable of accurately reproducing the measured dose distributions of the six electron beams available on the accelerator. Depth penetration matched the average measured with a diode and parallel-plate chamber to 0.04 cm or better. Calculated depth dose curves agreed to 2% with diode measurements in the build-up region, although for the lower beam energies there was a discrepancy of up to 5% in this region when calculated results are compared to parallel-plate measurements. Dose profiles at the depth of maximum dose matched to 2-3% in the central 25 cm of the field, corresponding to the field size of the largest applicator. A 4% match was obtained outside the central region. The discrepancy observed in the bremsstrahlung tail in published results that used EGS4 is no longer evident. Simulations with the different codes and physics lists used different source energies, incident beam angles, thicknesses of the primary foils, and distance between the primary and secondary foil. The true source and geometry parameters were not known with sufficient accuracy to determine which parameter set, including the energy of the source, was closest to the truth. These results underscore the requirement for experimental benchmarks of depth penetration and electron scatter for beam energies and foils relevant to radiotherapy.
Dosimetry applications in GATE Monte Carlo toolkit.
Papadimitroulas, Panagiotis
2017-02-21
Monte Carlo (MC) simulations are a well-established method for studying physical processes in medical physics. The purpose of this review is to present GATE dosimetry applications on diagnostic and therapeutic simulated protocols. There is a significant need for accurate quantification of the absorbed dose in several specific applications such as preclinical and pediatric studies. GATE is an open-source MC toolkit for simulating imaging, radiotherapy (RT) and dosimetry applications in a user-friendly environment, which is well validated and widely accepted by the scientific community. In RT applications, during treatment planning, it is essential to accurately assess the deposited energy and the absorbed dose per tissue/organ of interest, as well as the local statistical uncertainty. Several types of realistic dosimetric applications are described including: molecular imaging, radio-immunotherapy, radiotherapy and brachytherapy. GATE has been efficiently used in several applications, such as Dose Point Kernels, S-values, Brachytherapy parameters, and has been compared against various MC codes which are considered as standard tools for decades. Furthermore, the presented studies show reliable modeling of particle beams when comparing experimental with simulated data. Examples of different dosimetric protocols are reported for individualized dosimetry and simulations combining imaging and therapy dose monitoring, with the use of modern computational phantoms. Personalization of medical protocols can be achieved by combining GATE MC simulations with anthropomorphic computational models and clinical anatomical data. This is a review study, covering several dosimetric applications of GATE, and the different tools used for modeling realistic clinical acquisitions with accurate dose assessment. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.
Monte Carlo implementation of polarized hadronization
Matevosyan, Hrayr H.; Kotzinian, Aram; Thomas, Anthony W.
2017-01-01
We study the polarized quark hadronization in a Monte Carlo (MC) framework based on the recent extension of the quark-jet framework, where a self-consistent treatment of the quark polarization transfer in a sequential hadronization picture has been presented. Here, we first adopt this approach for MC simulations of the hadronization process with a finite number of produced hadrons, expressing the relevant probabilities in terms of the eight leading twist quark-to-quark transverse-momentum-dependent (TMD) splitting functions (SFs) for elementary q →q'+h transition. We present explicit expressions for the unpolarized and Collins fragmentation functions (FFs) of unpolarized hadrons emitted at rank 2. Further, we demonstrate that all the current spectator-type model calculations of the leading twist quark-to-quark TMD SFs violate the positivity constraints, and we propose a quark model based ansatz for these input functions that circumvents the problem. We validate our MC framework by explicitly proving the absence of unphysical azimuthal modulations of the computed polarized FFs, and by precisely reproducing the earlier derived explicit results for rank-2 pions. Finally, we present the full results for pion unpolarized and Collins FFs, as well as the corresponding analyzing powers from high statistics MC simulations with a large number of produced hadrons for two different model input elementary SFs. The results for both sets of input functions exhibit the same general features of an opposite signed Collins function for favored and unfavored channels at large z and, at the same time, demonstrate the flexibility of the quark-jet framework by producing significantly different dependences of the results at mid to low z for the two model inputs.
kmos: A lattice kinetic Monte Carlo framework
Hoffmann, Max J.; Matera, Sebastian; Reuter, Karsten
2014-07-01
Kinetic Monte Carlo (kMC) simulations have emerged as a key tool for microkinetic modeling in heterogeneous catalysis and other materials applications. Systems, where site-specificity of all elementary reactions allows a mapping onto a lattice of discrete active sites, can be addressed within the particularly efficient lattice kMC approach. To this end we describe the versatile kmos software package, which offers a most user-friendly implementation, execution, and evaluation of lattice kMC models of arbitrary complexity in one- to three-dimensional lattice systems, involving multiple active sites in periodic or aperiodic arrangements, as well as site-resolved pairwise and higher-order lateral interactions. Conceptually, kmos achieves a maximum runtime performance which is essentially independent of lattice size by generating code for the efficiency-determining local update of available events that is optimized for a defined kMC model. For this model definition and the control of all runtime and evaluation aspects kmos offers a high-level application programming interface. Usage proceeds interactively, via scripts, or a graphical user interface, which visualizes the model geometry, the lattice occupations and rates of selected elementary reactions, while allowing on-the-fly changes of simulation parameters. We demonstrate the performance and scaling of kmos with the application to kMC models for surface catalytic processes, where for given operation conditions (temperature and partial pressures of all reactants) central simulation outcomes are catalytic activity and selectivities, surface composition, and mechanistic insight into the occurrence of individual elementary processes in the reaction network.
Perturbation Monte Carlo methods for tissue structure alterations.
Nguyen, Jennifer; Hayakawa, Carole K; Mourant, Judith R; Spanier, Jerome
2013-01-01
This paper describes an extension of the perturbation Monte Carlo method to model light transport when the phase function is arbitrarily perturbed. Current perturbation Monte Carlo methods allow perturbation of both the scattering and absorption coefficients, however, the phase function can not be varied. The more complex method we develop and test here is not limited in this way. We derive a rigorous perturbation Monte Carlo extension that can be applied to a large family of important biomedical light transport problems and demonstrate its greater computational efficiency compared with using conventional Monte Carlo simulations to produce forward transport problem solutions. The gains of the perturbation method occur because only a single baseline Monte Carlo simulation is needed to obtain forward solutions to other closely related problems whose input is described by perturbing one or more parameters from the input of the baseline problem. The new perturbation Monte Carlo methods are tested using tissue light scattering parameters relevant to epithelia where many tumors originate. The tissue model has parameters for the number density and average size of three classes of scatterers; whole nuclei, organelles such as lysosomes and mitochondria, and small particles such as ribosomes or large protein complexes. When these parameters or the wavelength is varied the scattering coefficient and the phase function vary. Perturbation calculations give accurate results over variations of ∼15-25% of the scattering parameters.
A Survey on Multilevel Monte Carlo for European Options
Masoud Moharamnejad
2016-03-01
Full Text Available One of the most applicable and common methods for pricing options is the Monte Carlo simulation. Among the advantages of this method we can name ease of use, being suitable for different types of options including vanilla options and exotic options. On one hand, convergence rate of Monte Carlo's variance is , which has a slow convergence in responding problems, such that for achieving accuracy of ε for a d dimensional problem, computation complexity would be . Thus, various methods have been proposed in Monte Carlo framework to increase the convergence rate of variance as variance reduction methods. One of the recent methods was proposed by Gills in 2006, is the multilevel Monte Carlo method. This method besides reducing the computationcomplexity to while being used in Euler discretizing and to while being used in Milsteindiscretizing method, has the capacity to be combined with other variance reduction methods. In this article, multilevel Monte Carlo using Euler and Milsteindiscretizing methods is adopted for comparing computation complexity with standard Monte Carlo method in pricing European call options.
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.
Bayesian Optimal Experimental Design Using Multilevel Monte Carlo
Issaid, Chaouki Ben
2015-01-07
Experimental design is very important since experiments are often resource-exhaustive and time-consuming. We carry out experimental design in the Bayesian framework. To measure the amount of information, which can be extracted from the data in an experiment, we use the expected information gain as the utility function, which specifically is the expected logarithmic ratio between the posterior and prior distributions. Optimizing this utility function enables us to design experiments that yield the most informative data for our purpose. One of the major difficulties in evaluating the expected information gain is that the integral is nested and can be high dimensional. We propose using Multilevel Monte Carlo techniques to accelerate the computation of the nested high dimensional integral. The advantages are twofold. First, the Multilevel Monte Carlo can significantly reduce the cost of the nested integral for a given tolerance, by using an optimal sample distribution among different sample averages of the inner integrals. Second, the Multilevel Monte Carlo method imposes less assumptions, such as the concentration of measures, required by Laplace method. We test our Multilevel Monte Carlo technique using a numerical example on the design of sensor deployment for a Darcy flow problem governed by one dimensional Laplace equation. We also compare the performance of the Multilevel Monte Carlo, Laplace approximation and direct double loop Monte Carlo.
Measure of Bias Cancellation in Fixed-Node Quantum Monte Carlo
Dubecký, Matúš
2016-01-01
We introduce a measure of fixed-node (FN) bias cancellation useful for a priori assessment of FN diffusion Monte Carlo (FN-DMC) energy differences, based on post-Hartree-Fock natural orbital occupation numbers. The proposed quantity reflects the non-equivalency of static correlations in trial wave functions and uncovers the nature of biases observed in some small noncovalent complexes.
Kinetic Monte Carlo simulation of thin film growth
ZHANG; Peifeng(张佩峰); ZHENG; Xiaoping(郑小平); HE; Deyan(贺德衍)
2003-01-01
A three-dimensional kinetic Monte Carlo technique has been developed for simulating growth of thin Cu films. The model involves incident atom attachment, diffusion of the atoms on the growing surface, and detachment of the atoms from the growing surface. The related effect by surface atom diffusion was taken into account. A great improvement was made on calculation of the activation energy for atom diffusion based on a reasonable assumption of interaction potential between atoms. The surface roughness and the relative density of the films were simulated as the functions of growth substrate temperature and film thickness. The results showed that there exists an optimum growth temperature Topt at a given deposition rate. When the substrate temperature approaches to Topt, the growing surface becomes smoothing and the relative density of the films increases. The surface roughness minimizes and the relative density saturates at Topt. The surface roughness increases with an increment of substrate temperature when the temperature is higher than Topt. Topt iS a function of the deposition rate and the influence of the deposition rate on the surface roughness depends on the substrate temperatures. The simulation results also showed that the relative density decreases with the increasing of the deposition rate and the average thickness of the film.
Monte Carlo systems used for treatment planning and dose verification
Brualla, Lorenzo [Universitaetsklinikum Essen, NCTeam, Strahlenklinik, Essen (Germany); Rodriguez, Miguel [Centro Medico Paitilla, Balboa (Panama); Lallena, Antonio M. [Universidad de Granada, Departamento de Fisica Atomica, Molecular y Nuclear, Granada (Spain)
2017-04-15
General-purpose radiation transport Monte Carlo codes have been used for estimation of the absorbed dose distribution in external photon and electron beam radiotherapy patients since several decades. Results obtained with these codes are usually more accurate than those provided by treatment planning systems based on non-stochastic methods. Traditionally, absorbed dose computations based on general-purpose Monte Carlo codes have been used only for research, owing to the difficulties associated with setting up a simulation and the long computation time required. To take advantage of radiation transport Monte Carlo codes applied to routine clinical practice, researchers and private companies have developed treatment planning and dose verification systems that are partly or fully based on fast Monte Carlo algorithms. This review presents a comprehensive list of the currently existing Monte Carlo systems that can be used to calculate or verify an external photon and electron beam radiotherapy treatment plan. Particular attention is given to those systems that are distributed, either freely or commercially, and that do not require programming tasks from the end user. These systems are compared in terms of features and the simulation time required to compute a set of benchmark calculations. (orig.) [German] Seit mehreren Jahrzehnten werden allgemein anwendbare Monte-Carlo-Codes zur Simulation des Strahlungstransports benutzt, um die Verteilung der absorbierten Dosis in der perkutanen Strahlentherapie mit Photonen und Elektronen zu evaluieren. Die damit erzielten Ergebnisse sind meist akkurater als solche, die mit nichtstochastischen Methoden herkoemmlicher Bestrahlungsplanungssysteme erzielt werden koennen. Wegen des damit verbundenen Arbeitsaufwands und der langen Dauer der Berechnungen wurden Monte-Carlo-Simulationen von Dosisverteilungen in der konventionellen Strahlentherapie in der Vergangenheit im Wesentlichen in der Forschung eingesetzt. Im Bemuehen, Monte-Carlo
Monte Carlo Techniques for Nuclear Systems - Theory Lectures
Brown, Forrest B. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Monte Carlo Methods, Codes, and Applications Group; Univ. of New Mexico, Albuquerque, NM (United States). Nuclear Engineering Dept.
2016-11-29
These are lecture notes for a Monte Carlo class given at the University of New Mexico. The following topics are covered: course information; nuclear eng. review & MC; random numbers and sampling; computational geometry; collision physics; tallies and statistics; eigenvalue calculations I; eigenvalue calculations II; eigenvalue calculations III; variance reduction; parallel Monte Carlo; parameter studies; fission matrix and higher eigenmodes; doppler broadening; Monte Carlo depletion; HTGR modeling; coupled MC and T/H calculations; fission energy deposition. Solving particle transport problems with the Monte Carlo method is simple - just simulate the particle behavior. The devil is in the details, however. These lectures provide a balanced approach to the theory and practice of Monte Carlo simulation codes. The first lectures provide an overview of Monte Carlo simulation methods, covering the transport equation, random sampling, computational geometry, collision physics, and statistics. The next lectures focus on the state-of-the-art in Monte Carlo criticality simulations, covering the theory of eigenvalue calculations, convergence analysis, dominance ratio calculations, bias in Keff and tallies, bias in uncertainties, a case study of a realistic calculation, and Wielandt acceleration techniques. The remaining lectures cover advanced topics, including HTGR modeling and stochastic geometry, temperature dependence, fission energy deposition, depletion calculations, parallel calculations, and parameter studies. This portion of the class focuses on using MCNP to perform criticality calculations for reactor physics and criticality safety applications. It is an intermediate level class, intended for those with at least some familiarity with MCNP. Class examples provide hands-on experience at running the code, plotting both geometry and results, and understanding the code output. The class includes lectures & hands-on computer use for a variety of Monte Carlo calculations
Reducing quasi-ergodicity in a double well potential by Tsallis Monte Carlo simulation
Iwamatsu, Masao; Okabe, Yutaka
2000-01-01
A new Monte Carlo scheme based on the system of Tsallis's generalized statistical mechanics is applied to a simple double well potential to calculate the canonical thermal average of potential energy. Although we observed serious quasi-ergodicity when using the standard Metropolis Monte Carlo algorithm, this problem is largely reduced by the use of the new Monte Carlo algorithm. Therefore the ergodicity is guaranteed even for short Monte Carlo steps if we use this new canonical Monte Carlo sc...
Finding organic vapors - a Monte Carlo approach
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.
Coherent Scattering Imaging Monte Carlo Simulation
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
NRMC - A GPU code for N-Reverse Monte Carlo modeling of fluids in confined media
Sánchez-Gil, Vicente; Noya, Eva G.; Lomba, Enrique
2017-08-01
NRMC is a parallel code for performing N-Reverse Monte Carlo modeling of fluids in confined media [V. Sánchez-Gil, E.G. Noya, E. Lomba, J. Chem. Phys. 140 (2014) 024504]. This method is an extension of the usual Reverse Monte Carlo method to obtain structural models of confined fluids compatible with experimental diffraction patterns, specifically designed to overcome the problem of slow diffusion that can appear under conditions of tight confinement. Most of the computational time in N-Reverse Monte Carlo modeling is spent in the evaluation of the structure factor for each trial configuration, a calculation that can be easily parallelized. Implementation of the structure factor evaluation in NVIDIA® CUDA so that the code can be run on GPUs leads to a speed up of up to two orders of magnitude.
Giner, Emmanuel; Toulouse, Julien
2016-01-01
We explore the use in quantum Monte Carlo (QMC) of trial wave functions consisting of a Jastrow factor multiplied by a truncated configuration-interaction (CI) expansion in Slater determinants obtained from a CI perturbatively selected iteratively (CIPSI) calculation. In the CIPSI algorithm, the CI expansion is iteratively enlarged by selecting the best determinants using perturbation theory, which provides an optimal and automatic way of constructing truncated CI expansions approaching the full CI limit. We perform a systematic study of variational Monte Carlo (VMC) and fixed-node diffusion Monte Carlo (DMC) total energies of first-row atoms from B to Ne with different levels of optimization of the parameters (Jastrow parameters, coefficients of the determinants, and orbital parameters) in these trial wave functions. The results show that the reoptimization of the coefficients of the determinants in VMC (together with the Jastrow factor) leads to an important lowering of both VMC and DMC total energies, and ...
Crossing the mesoscale no-mans land via parallel kinetic Monte Carlo.
Garcia Cardona, Cristina (San Diego State University); Webb, Edmund Blackburn, III; Wagner, Gregory John; Tikare, Veena; Holm, Elizabeth Ann; Plimpton, Steven James; Thompson, Aidan Patrick; Slepoy, Alexander (U. S. Department of Energy, NNSA); Zhou, Xiao Wang; Battaile, Corbett Chandler; Chandross, Michael Evan
2009-10-01
The kinetic Monte Carlo method and its variants are powerful tools for modeling materials at the mesoscale, meaning at length and time scales in between the atomic and continuum. We have completed a 3 year LDRD project with the goal of developing a parallel kinetic Monte Carlo capability and applying it to materials modeling problems of interest to Sandia. In this report we give an overview of the methods and algorithms developed, and describe our new open-source code called SPPARKS, for Stochastic Parallel PARticle Kinetic Simulator. We also highlight the development of several Monte Carlo models in SPPARKS for specific materials modeling applications, including grain growth, bubble formation, diffusion in nanoporous materials, defect formation in erbium hydrides, and surface growth and evolution.
An unbiased Hessian representation for Monte Carlo PDFs
Carrazza, Stefano; Forte, Stefano [Universita di Milano, TIF Lab, Dipartimento di Fisica, Milan (Italy); INFN, Sezione di Milano (Italy); Kassabov, Zahari [Universita di Milano, TIF Lab, Dipartimento di Fisica, Milan (Italy); Universita di Torino, Dipartimento di Fisica, Turin (Italy); INFN, Sezione di Torino (Italy); Latorre, Jose Ignacio [Universitat de Barcelona, Departament d' Estructura i Constituents de la Materia, Barcelona (Spain); Rojo, Juan [University of Oxford, Rudolf Peierls Centre for Theoretical Physics, Oxford (United Kingdom)
2015-08-15
We develop a methodology for the construction of a Hessian representation of Monte Carlo sets of parton distributions, based on the use of a subset of the Monte Carlo PDF replicas as an unbiased linear basis, and of a genetic algorithm for the determination of the optimal basis. We validate the methodology by first showing that it faithfully reproduces a native Monte Carlo PDF set (NNPDF3.0), and then, that if applied to Hessian PDF set (MMHT14) which was transformed into a Monte Carlo set, it gives back the starting PDFs with minimal information loss. We then show that, when applied to a large Monte Carlo PDF set obtained as combination of several underlying sets, the methodology leads to a Hessian representation in terms of a rather smaller set of parameters (MC-H PDFs), thereby providing an alternative implementation of the recently suggested Meta-PDF idea and a Hessian version of the recently suggested PDF compression algorithm (CMC-PDFs). The mc2hessian conversion code is made publicly available together with (through LHAPDF6) a Hessian representations of the NNPDF3.0 set, and the MC-H PDF set. (orig.)
An Unbiased Hessian Representation for Monte Carlo PDFs
Carrazza, Stefano; Kassabov, Zahari; Latorre, Jose Ignacio; Rojo, Juan
2015-01-01
We develop a methodology for the construction of a Hessian representation of Monte Carlo sets of parton distributions, based on the use of a subset of the Monte Carlo PDF replicas as an unbiased linear basis, and of a genetic algorithm for the determination of the optimal basis. We validate the methodology by first showing that it faithfully reproduces a native Monte Carlo PDF set (NNPDF3.0), and then, that if applied to Hessian PDF set (MMHT14) which was transformed into a Monte Carlo set, it gives back the starting PDFs with minimal information loss. We then show that, when applied to a large Monte Carlo PDF set obtained as combination of several underlying sets, the methodology leads to a Hessian representation in terms of a rather smaller set of parameters (CMC-H PDFs), thereby providing an alternative implementation of the recently suggested Meta-PDF idea and a Hessian version of the recently suggested PDF compression algorithm (CMC-PDFs). The mc2hessian conversion code is made publicly available togethe...
Monte Carlo evaluation of kerma in an HDR brachytherapy bunker
Perez-Calatayud, J [Department of Atomic, Molecular and Nuclear Physics, and IFIC, CSIC-University of Valencia, Burjassot (Spain); Granero, D [Department of Atomic, Molecular and Nuclear Physics, and IFIC, CSIC-University of Valencia, Burjassot (Spain); Ballester, F [Department of Atomic, Molecular and Nuclear Physics, and IFIC, CSIC-University of Valencia, Burjassot (Spain); Casal, E [Department of Atomic, Molecular and Nuclear Physics, and IFIC, CSIC-University of Valencia, Burjassot (Spain); Crispin, V [FIVO, Fundacion Instituto Valenciano De OncologIa, Valencia (Spain); Puchades, V [Grupo IMO-SFA, Madrid (Spain); Leon, A [Department of Chemistry and Nuclear Engineering, Polytechnic University of Valencia, Valencia (Spain); Verdu, G [Department of Chemistry and Nuclear Engineering, Polytechnic University of Valencia, Valencia (Spain)
2004-12-21
In recent years, the use of high dose rate (HDR) after-loader machines has greatly increased due to the shift from traditional Cs-137/Ir-192 low dose rate (LDR) to HDR brachytherapy. The method used to calculate the required concrete and, where appropriate, lead shielding in the door is based on analytical methods provided by documents published by the ICRP, the IAEA and the NCRP. The purpose of this study is to perform a more realistic kerma evaluation at the entrance maze door of an HDR bunker using the Monte Carlo code GEANT4. The Monte Carlo results were validated experimentally. The spectrum at the maze entrance door, obtained with Monte Carlo, has an average energy of about 110 keV, maintaining a similar value along the length of the maze. The comparison of results from the aforementioned values with the Monte Carlo ones shows that results obtained using the albedo coefficient from the ICRP document more closely match those given by the Monte Carlo method, although the maximum value given by MC calculations is 30% greater. (note)
The Monte Carlo code MCSHAPE: Main features and recent developments
Scot, Viviana, E-mail: viviana.scot@unibo.it; Fernandez, Jorge E.
2015-06-01
MCSHAPE is a general purpose Monte Carlo code developed at the University of Bologna to simulate the diffusion of X- and gamma-ray photons with the special feature of describing the full evolution of the photon polarization state along the interactions with the target. The prevailing photon–matter interactions in the energy range 1–1000 keV, Compton and Rayleigh scattering and photoelectric effect, are considered. All the parameters that characterize the photon transport can be suitably defined: (i) the source intensity, (ii) its full polarization state as a function of energy, (iii) the number of collisions, and (iv) the energy interval and resolution of the simulation. It is possible to visualize the results for selected groups of interactions. MCSHAPE simulates the propagation in heterogeneous media of polarized photons (from synchrotron sources) or of partially polarized sources (from X-ray tubes). In this paper, the main features of MCSHAPE are illustrated with some examples and a comparison with experimental data. - Highlights: • MCSHAPE is an MC code for the simulation of the diffusion of photons in the matter. • It includes the proper description of the evolution of the photon polarization state. • The polarization state is described by means of the Stokes vector, I, Q, U, V. • MCSHAPE includes the computation of the detector influence in the measured spectrum. • MCSHAPE features are illustrated with examples and comparison with experiments.
Monte Carlo studies of model Langmuir monolayers.
Opps, S B; Yang, B; Gray, C G; Sullivan, D E
2001-04-01
This paper examines some of the basic properties of a model Langmuir monolayer, consisting of surfactant molecules deposited onto a water subphase. The surfactants are modeled as rigid rods composed of a head and tail segment of diameters sigma(hh) and sigma(tt), respectively. The tails consist of n(t) approximately 4-7 effective monomers representing methylene groups. These rigid rods interact via site-site Lennard-Jones potentials with different interaction parameters for the tail-tail, head-tail, and head-head interactions. In a previous paper, we studied the ground-state properties of this system using a Landau approach. In the present paper, Monte Carlo simulations were performed in the canonical ensemble to elucidate the finite-temperature behavior of this system. Simulation techniques, incorporating a system of dynamic filters, allow us to decrease CPU time with negligible statistical error. This paper focuses on several of the key parameters, such as density, head-tail diameter mismatch, and chain length, responsible for driving transitions from uniformly tilted to untilted phases and between different tilt-ordered phases. Upon varying the density of the system, with sigma(hh)=sigma(tt), we observe a transition from a tilted (NNN)-condensed phase to an untilted-liquid phase and, upon comparison with recent experiments with fatty acid-alcohol and fatty acid-ester mixtures [M. C. Shih, M. K. Durbin, A. Malik, P. Zschack, and P. Dutta, J. Chem. Phys. 101, 9132 (1994); E. Teer, C. M. Knobler, C. Lautz, S. Wurlitzer, J. Kildae, and T. M. Fischer, J. Chem. Phys. 106, 1913 (1997)], we identify this as the L'(2)/Ov-L1 phase boundary. By varying the head-tail diameter ratio, we observe a decrease in T(c) with increasing mismatch. However, as the chain length was increased we observed that the transition temperatures increased and differences in T(c) due to head-tail diameter mismatch were diminished. In most of the present research, the water was treated as a hard
Monte Carlo analysis of radiative transport in oceanographic lidar measurements
Cupini, E.; Ferro, G. [ENEA, Divisione Fisica Applicata, Centro Ricerche Ezio Clementel, Bologna (Italy); Ferrari, N. [Bologna Univ., Bologna (Italy). Dipt. Ingegneria Energetica, Nucleare e del Controllo Ambientale
2001-07-01
The analysis of oceanographic lidar systems measurements is often carried out with semi-empirical methods, since there is only a rough understanding of the effects of many environmental variables. The development of techniques for interpreting the accuracy of lidar measurements is needed to evaluate the effects of various environmental situations, as well as of different experimental geometric configurations and boundary conditions. A Monte Carlo simulation model represents a tool that is particularly well suited for answering these important questions. The PREMAR-2F Monte Carlo code has been developed taking into account the main molecular and non-molecular components of the marine environment. The laser radiation interaction processes of diffusion, re-emission, refraction and absorption are treated. In particular are considered: the Rayleigh elastic scattering, produced by atoms and molecules with small dimensions with respect to the laser emission wavelength (i.e. water molecules), the Mie elastic scattering, arising from atoms or molecules with dimensions comparable to the laser wavelength (hydrosols), the Raman inelastic scattering, typical of water, the absorption of water, inorganic (sediments) and organic (phytoplankton and CDOM) hydrosols, the fluorescence re-emission of chlorophyll and yellow substances. PREMAR-2F is an extension of a code for the simulation of the radiative transport in atmospheric environments (PREMAR-2). The approach followed in PREMAR-2 was to combine conventional Monte Carlo techniques with analytical estimates of the probability of the receiver to have a contribution from photons coming back after an interaction in the field of view of the lidar fluorosensor collecting apparatus. This offers an effective mean for modelling a lidar system with realistic geometric constraints. The retrieved semianalytic Monte Carlo radiative transfer model has been developed in the frame of the Italian Research Program for Antarctica (PNRA) and it is
Calibration and Monte Carlo modelling of neutron long counters
Tagziria, H
2000-01-01
The Monte Carlo technique has become a very powerful tool in radiation transport as full advantage is taken of enhanced cross-section data, more powerful computers and statistical techniques, together with better characterisation of neutron and photon source spectra. At the National Physical Laboratory, calculations using the Monte Carlo radiation transport code MCNP-4B have been combined with accurate measurements to characterise two long counters routinely used to standardise monoenergetic neutron fields. New and more accurate response function curves have been produced for both long counters. A novel approach using Monte Carlo methods has been developed, validated and used to model the response function of the counters and determine more accurately their effective centres, which have always been difficult to establish experimentally. Calculations and measurements agree well, especially for the De Pangher long counter for which details of the design and constructional material are well known. The sensitivit...
Vectorizing and macrotasking Monte Carlo neutral particle algorithms
Heifetz, D.B.
1987-04-01
Monte Carlo algorithms for computing neutral particle transport in plasmas have been vectorized and macrotasked. The techniques used are directly applicable to Monte Carlo calculations of neutron and photon transport, and Monte Carlo integration schemes in general. A highly vectorized code was achieved by calculating test flight trajectories in loops over arrays of flight data, isolating the conditional branches to as few a number of loops as possible. A number of solutions are discussed to the problem of gaps appearing in the arrays due to completed flights, which impede vectorization. A simple and effective implementation of macrotasking is achieved by dividing the calculation of the test flight profile among several processors. A tree of random numbers is used to ensure reproducible results. The additional memory required for each task may preclude using a larger number of tasks. In future machines, the limit of macrotasking may be possible, with each test flight, and split test flight, being a separate task.
Properties of Reactive Oxygen Species by Quantum Monte Carlo
Zen, Andrea; Guidoni, Leonardo
2014-01-01
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 ...
LCG MCDB - a Knowledgebase of Monte Carlo Simulated Events
Belov, S; Galkin, E; Gusev, A; Pokorski, Witold; Sherstnev, A V
2008-01-01
In this paper we report on LCG Monte Carlo Data Base (MCDB) and software which has been developed to operate MCDB. The main purpose of the LCG MCDB project is to provide a storage and documentation system for sophisticated event samples simulated for the LHC collaborations by experts. In many cases, the modern Monte Carlo simulation of physical processes requires expert knowledge in Monte Carlo generators or significant amount of CPU time to produce the events. MCDB is a knowledgebase mainly to accumulate simulated events of this type. The main motivation behind LCG MCDB is to make the sophisticated MC event samples available for various physical groups. All the data from MCDB is accessible in several convenient ways. LCG MCDB is being developed within the CERN LCG Application Area Simulation project.
The Monte Carlo method in quantum field theory
Morningstar, C
2007-01-01
This series of six lectures is an introduction to using the Monte Carlo method to carry out nonperturbative studies in quantum field theories. Path integrals in quantum field theory are reviewed, and their evaluation by the Monte Carlo method with Markov-chain based importance sampling is presented. Properties of Markov chains are discussed in detail and several proofs are presented, culminating in the fundamental limit theorem for irreducible Markov chains. The example of a real scalar field theory is used to illustrate the Metropolis-Hastings method and to demonstrate the effectiveness of an action-preserving (microcanonical) local updating algorithm in reducing autocorrelations. The goal of these lectures is to provide the beginner with the basic skills needed to start carrying out Monte Carlo studies in quantum field theories, as well as to present the underlying theoretical foundations of the method.
TAKING THE NEXT STEP WITH INTELLIGENT MONTE CARLO
Booth, T.E.; Carlson, J.A. [and others
2000-10-01
For many scientific calculations, Monte Carlo is the only practical method available. Unfortunately, standard Monte Carlo methods converge slowly as the square root of the computer time. We have shown, both numerically and theoretically, that the convergence rate can be increased dramatically if the Monte Carlo algorithm is allowed to adapt based on what it has learned from previous samples. As the learning continues, computational efficiency increases, often geometrically fast. The particle transport work achieved geometric convergence for a two-region problem as well as for problems with rapidly changing nuclear data. The statistics work provided theoretical proof of geometic convergence for continuous transport problems and promising initial results for airborne migration of particles. The statistical physics work applied adaptive methods to a variety of physical problems including the three-dimensional Ising glass, quantum scattering, and eigenvalue problems.
Optimised Iteration in Coupled Monte Carlo - Thermal-Hydraulics Calculations
Hoogenboom, J. Eduard; Dufek, Jan
2014-06-01
This paper describes an optimised iteration scheme for the number of neutron histories and the relaxation factor in successive iterations of coupled Monte Carlo and thermal-hydraulic reactor calculations based on the stochastic iteration method. The scheme results in an increasing number of neutron histories for the Monte Carlo calculation in successive iteration steps and a decreasing relaxation factor for the spatial power distribution to be used as input to the thermal-hydraulics calculation. The theoretical basis is discussed in detail and practical consequences of the scheme are shown, among which a nearly linear increase per iteration of the number of cycles in the Monte Carlo calculation. The scheme is demonstrated for a full PWR type fuel assembly. Results are shown for the axial power distribution during several iteration steps. A few alternative iteration method are also tested and it is concluded that the presented iteration method is near optimal.
Monte Carlo tests of the ELIPGRID-PC algorithm
Davidson, J.R.
1995-04-01
The standard tool for calculating the probability of detecting pockets of contamination called hot spots has been the ELIPGRID computer code of Singer and Wickman. The ELIPGRID-PC program has recently made this algorithm available for an IBM{reg_sign} PC. However, no known independent validation of the ELIPGRID algorithm exists. This document describes a Monte Carlo simulation-based validation of a modified version of the ELIPGRID-PC code. The modified ELIPGRID-PC code is shown to match Monte Carlo-calculated hot-spot detection probabilities to within {plus_minus}0.5% for 319 out of 320 test cases. The one exception, a very thin elliptical hot spot located within a rectangular sampling grid, differed from the Monte Carlo-calculated probability by about 1%. These results provide confidence in the ability of the modified ELIPGRID-PC code to accurately predict hot-spot detection probabilities within an acceptable range of error.
Efficiency of Monte Carlo sampling in chaotic systems.
Leitão, Jorge C; Lopes, J M Viana Parente; Altmann, Eduardo G
2014-11-01
In this paper we investigate how the complexity of chaotic phase spaces affect the efficiency of importance sampling Monte Carlo simulations. We focus on flat-histogram simulations of the distribution of finite-time Lyapunov exponent in a simple chaotic system and obtain analytically that the computational effort: (i) scales polynomially with the finite time, a tremendous improvement over the exponential scaling obtained in uniform sampling simulations; and (ii) the polynomial scaling is suboptimal, a phenomenon known as critical slowing down. We show that critical slowing down appears because of the limited possibilities to issue a local proposal in the Monte Carlo procedure when it is applied to chaotic systems. These results show how generic properties of chaotic systems limit the efficiency of Monte Carlo simulations.
Sequential Monte Carlo on large binary sampling spaces
Schäfer, Christian
2011-01-01
A Monte Carlo algorithm is said to be adaptive if it automatically calibrates its current proposal distribution using past simulations. The choice of the parametric family that defines the set of proposal distributions is critical for a good performance. In this paper, we present such a parametric family for adaptive sampling on high-dimensional binary spaces. A practical motivation for this problem is variable selection in a linear regression context. We want to sample from a Bayesian posterior distribution on the model space using an appropriate version of Sequential Monte Carlo. Raw versions of Sequential Monte Carlo are easily implemented using binary vectors with independent components. For high-dimensional problems, however, these simple proposals do not yield satisfactory results. The key to an efficient adaptive algorithm are binary parametric families which take correlations into account, analogously to the multivariate normal distribution on continuous spaces. We provide a review of models for binar...
Monte Carlo simulation of laser attenuation characteristics in fog
Wang, Hong-Xia; Sun, Chao; Zhu, You-zhang; Sun, Hong-hui; Li, Pan-shi
2011-06-01
Based on the Mie scattering theory and the gamma size distribution model, the scattering extinction parameter of spherical fog-drop is calculated. For the transmission attenuation of the laser in the fog, a Monte Carlo simulation model is established, and the impact of attenuation ratio on visibility and field angle is computed and analysed using the program developed by MATLAB language. The results of the Monte Carlo method in this paper are compared with the results of single scattering method. The results show that the influence of multiple scattering need to be considered when the visibility is low, and single scattering calculations have larger errors. The phenomenon of multiple scattering can be interpreted more better when the Monte Carlo is used to calculate the attenuation ratio of the laser transmitting in the fog.
VARIATIONAL MONTE-CARLO APPROACH FOR ARTICULATED OBJECT TRACKING
Kartik Dwivedi
2013-12-01
Full Text Available In this paper, we describe a novel variational Monte Carlo approach for modeling and tracking body parts of articulated objects. An articulated object (human target is represented as a dynamic Markov network of the different constituent parts. The proposed approach combines local information of individual body parts and other spatial constraints influenced by neighboring parts. The movement of the relative parts of the articulated body is modeled with local information of displacements from the Markov network and the global information from other neighboring parts. We explore the effect of certain model parameters (including the number of parts tracked; number of Monte-Carlo cycles, etc. on system accuracy and show that ourvariational Monte Carlo approach achieves better efficiency and effectiveness compared to other methods on a number of real-time video datasets containing single targets.
Meaningful timescales from Monte Carlo simulations of molecular systems
Costa, Liborio I
2016-01-01
A new Markov Chain Monte Carlo method for simulating the dynamics of molecular systems with atomistic detail is introduced. In contrast to traditional Kinetic Monte Carlo approaches, where the state of the system is associated with minima in the energy landscape, in the proposed method, the state of the system is associated with the set of paths traveled by the atoms and the transition probabilities for an atom to be displaced are proportional to the corresponding velocities. In this way, the number of possible state-to-state transitions is reduced to a discrete set, and a direct link between the Monte Carlo time step and true physical time is naturally established. The resulting rejection-free algorithm is validated against event-driven molecular dynamics: the equilibrium and non-equilibrium dynamics of hard disks converge to the exact results with decreasing displacement size.
Monte Carlo Methods for Tempo Tracking and Rhythm Quantization
Cemgil, A T; 10.1613/jair.1121
2011-01-01
We present a probabilistic generative model for timing deviations in expressive music performance. The structure of the proposed model is equivalent to a switching state space model. The switch variables correspond to discrete note locations as in a musical score. The continuous hidden variables denote the tempo. We formulate two well known music recognition problems, namely tempo tracking and automatic transcription (rhythm quantization) as filtering and maximum a posteriori (MAP) state estimation tasks. Exact computation of posterior features such as the MAP state is intractable in this model class, so we introduce Monte Carlo methods for integration and optimization. We compare Markov Chain Monte Carlo (MCMC) methods (such as Gibbs sampling, simulated annealing and iterative improvement) and sequential Monte Carlo methods (particle filters). Our simulation results suggest better results with sequential methods. The methods can be applied in both online and batch scenarios such as tempo tracking and transcr...
Monte Carlo Simulation in Statistical Physics An Introduction
Binder, Kurt
2010-01-01
Monte Carlo Simulation in Statistical Physics deals with the computer simulation of many-body systems in condensed-matter physics and related fields of physics, chemistry and beyond, to traffic flows, stock market fluctuations, etc.). Using random numbers generated by a computer, probability distributions are calculated, allowing the estimation of the thermodynamic properties of various systems. This book describes the theoretical background to several variants of these Monte Carlo methods and gives a systematic presentation from which newcomers can learn to perform such simulations and to analyze their results. The fifth edition covers Classical as well as Quantum Monte Carlo methods. Furthermore a new chapter on the sampling of free-energy landscapes has been added. To help students in their work a special web server has been installed to host programs and discussion groups (http://wwwcp.tphys.uni-heidelberg.de). Prof. Binder was awarded the Berni J. Alder CECAM Award for Computational Physics 2001 as well ...
Applicability of Quasi-Monte Carlo for lattice systems
Ammon, Andreas; Jansen, Karl; Leovey, Hernan; Griewank, Andreas; Müller-Preussker, Micheal
2013-01-01
This project investigates the applicability of quasi-Monte Carlo methods to Euclidean lattice systems in order to improve the asymptotic error scaling of observables for such theories. The error of an observable calculated by averaging over random observations generated from ordinary Monte Carlo simulations scales like $N^{-1/2}$, where $N$ is the number of observations. By means of quasi-Monte Carlo methods it is possible to improve this scaling for certain problems to $N^{-1}$, or even further if the problems are regular enough. We adapted and applied this approach to simple systems like the quantum harmonic and anharmonic oscillator and verified an improved error scaling of all investigated observables in both cases.
Failure Probability Estimation of Wind Turbines by Enhanced Monte Carlo
Sichani, Mahdi Teimouri; Nielsen, Søren R.K.; Naess, Arvid
2012-01-01
This paper discusses the estimation of the failure probability of wind turbines required by codes of practice for designing them. The Standard Monte Carlo (SMC) simulations may be used for this reason conceptually as an alternative to the popular Peaks-Over-Threshold (POT) method. However......, estimation of very low failure probabilities with SMC simulations leads to unacceptably high computational costs. In this study, an Enhanced Monte Carlo (EMC) method is proposed that overcomes this obstacle. The method has advantages over both POT and SMC in terms of its low computational cost and accuracy...... is controlled by the pitch controller. This provides a fair framework for comparison of the behavior and failure event of the wind turbine with emphasis on the effect of the pitch controller. The Enhanced Monte Carlo method is then applied to the model and the failure probabilities of the model are estimated...
Implementation of Monte Carlo Simulations for the Gamma Knife System
Xiong, W [Memorial Sloan-Kettering Cancer Center/Mercy Medical Center, 1000 N Village Ave., Rockville Centre, NY 11570 (United States); Huang, D [Memorial Sloan-Kettering Cancer Center/Mercy Medical Center, 1000 N Village Ave., Rockville Centre, NY 11570 (United States); Lee, L [Memorial Sloan-Kettering Cancer Center/Mercy Medical Center, 1000 N Village Ave., Rockville Centre, NY 11570 (United States); Feng, J [Memorial Sloan-Kettering Cancer Center/Mercy Medical Center, 1000 N Village Ave., Rockville Centre, NY 11570 (United States); Morris, K [Memorial Sloan-Kettering Cancer Center/Mercy Medical Center, 1000 N Village Ave., Rockville Centre, NY 11570 (United States); Calugaru, E [Memorial Sloan-Kettering Cancer Center/Mercy Medical Center, 1000 N Village Ave., Rockville Centre, NY 11570 (United States); Burman, C [Memorial Sloan-Kettering Cancer Center/Mercy Medical Center, 1000 N Village Ave., Rockville Centre, NY 11570 (United States); Li, J [Fox Chase Cancer Center, 333 Cottman Ave., Philadelphia, PA 17111 (United States); Ma, C-M [Fox Chase Cancer Center, 333 Cottman Ave., Philadelphia, PA 17111 (United States)
2007-06-15
Currently the Gamma Knife system is accompanied with a treatment planning system, Leksell GammaPlan (LGP) which is a standard, computer-based treatment planning system for Gamma Knife radiosurgery. In LGP, the dose calculation algorithm does not consider the scatter dose contributions and the inhomogeneity effect due to the skull and air cavities. To improve the dose calculation accuracy, Monte Carlo simulations have been implemented for the Gamma Knife planning system. In this work, the 201 Cobalt-60 sources in the Gamma Knife unit are considered to have the same activity. Each Cobalt-60 source is contained in a cylindric stainless steel capsule. The particle phase space information is stored in four beam data files, which are collected in the inner sides of the 4 treatment helmets, after the Cobalt beam passes through the stationary and helmet collimators. Patient geometries are rebuilt from patient CT data. Twenty two Patients are included in the Monte Carlo simulation for this study. The dose is calculated using Monte Carlo in both homogenous and inhomogeneous geometries with identical beam parameters. To investigate the attenuation effect of the skull bone the dose in a 16cm diameter spherical QA phantom is measured with and without a 1.5mm Lead-covering and also simulated using Monte Carlo. The dose ratios with and without the 1.5mm Lead-covering are 89.8% based on measurements and 89.2% according to Monte Carlo for a 18mm-collimator Helmet. For patient geometries, the Monte Carlo results show that although the relative isodose lines remain almost the same with and without inhomogeneity corrections, the difference in the absolute dose is clinically significant. The average inhomogeneity correction is (3.9 {+-} 0.90) % for the 22 patients investigated. These results suggest that the inhomogeneity effect should be considered in the dose calculation for Gamma Knife treatment planning.
Accelerated rescaling of single Monte Carlo simulation runs with the Graphics Processing Unit (GPU).
Yang, Owen; Choi, Bernard
2013-01-01
To interpret fiber-based and camera-based measurements of remitted light from biological tissues, researchers typically use analytical models, such as the diffusion approximation to light transport theory, or stochastic models, such as Monte Carlo modeling. To achieve rapid (ideally real-time) measurement of tissue optical properties, especially in clinical situations, there is a critical need to accelerate Monte Carlo simulation runs. In this manuscript, we report on our approach using the Graphics Processing Unit (GPU) to accelerate rescaling of single Monte Carlo runs to calculate rapidly diffuse reflectance values for different sets of tissue optical properties. We selected MATLAB to enable non-specialists in C and CUDA-based programming to use the generated open-source code. We developed a software package with four abstraction layers. To calculate a set of diffuse reflectance values from a simulated tissue with homogeneous optical properties, our rescaling GPU-based approach achieves a reduction in computation time of several orders of magnitude as compared to other GPU-based approaches. Specifically, our GPU-based approach generated a diffuse reflectance value in 0.08ms. The transfer time from CPU to GPU memory currently is a limiting factor with GPU-based calculations. However, for calculation of multiple diffuse reflectance values, our GPU-based approach still can lead to processing that is ~3400 times faster than other GPU-based approaches.
Quantum Monte Carlo calculations with chiral effective field theory interactions
Tews, Ingo
2015-10-12
The neutron-matter equation of state connects several physical systems over a wide density range, from cold atomic gases in the unitary limit at low densities, to neutron-rich nuclei at intermediate densities, up to neutron stars which reach supranuclear densities in their core. An accurate description of the neutron-matter equation of state is therefore crucial to describe these systems. To calculate the neutron-matter equation of state reliably, precise many-body methods in combination with a systematic theory for nuclear forces are needed. Chiral effective field theory (EFT) is such a theory. It provides a systematic framework for the description of low-energy hadronic interactions and enables calculations with controlled theoretical uncertainties. Chiral EFT makes use of a momentum-space expansion of nuclear forces based on the symmetries of Quantum Chromodynamics, which is the fundamental theory of strong interactions. In chiral EFT, the description of nuclear forces can be systematically improved by going to higher orders in the chiral expansion. On the other hand, continuum Quantum Monte Carlo (QMC) methods are among the most precise many-body methods available to study strongly interacting systems at finite densities. They treat the Schroedinger equation as a diffusion equation in imaginary time and project out the ground-state wave function of the system starting from a trial wave function by propagating the system in imaginary time. To perform this propagation, continuum QMC methods require as input local interactions. However, chiral EFT, which is naturally formulated in momentum space, contains several sources of nonlocality. In this Thesis, we show how to construct local chiral two-nucleon (NN) and three-nucleon (3N) interactions and discuss results of first QMC calculations for pure neutron systems. We have performed systematic auxiliary-field diffusion Monte Carlo (AFDMC) calculations for neutron matter using local chiral NN interactions. By
A standard Event Class for Monte Carlo Generators
L.A.Gerren; M.Fischler
2001-01-01
StdHepC++[1]is a CLHEP[2] Monte Carlo event class library which provides a common interface to Monte Carlo Event Generators,This work is an extensive redesign of the StdHep Fortran interface to use the full power of object oriented design,A generated event maps naturally onto the Directed Acyclic Graph concept and we have used the HepMC classes to implement this.The full implementation allows the user to combine events to simulate beam pileup and access them transparently as though they were a single event.
Parallelization of Monte Carlo codes MVP/GMVP
Nagaya, Yasunobu; Mori, Takamasa; Nakagawa, Masayuki [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment; Sasaki, Makoto
1998-03-01
General-purpose Monte Carlo codes MVP/GMVP are well-vectorized and thus enable us to perform high-speed Monte Carlo calculations. In order to achieve more speedups, we parallelized the codes on the different types of the parallel processing platforms. The platforms reported are a distributed-memory vector-parallel computer Fujitsu VPP500, a distributed-memory massively parallel computer Intel Paragon and a distributed-memory scalar-parallel computer Hitachi SR2201. As mentioned generally, ideal speedup could be obtained for large-scale problems but parallelization efficiency got worse as the batch size per a processing element (PE) was smaller. (author)
Parton distribution functions in Monte Carlo factorisation scheme
Jadach, S.; Płaczek, W.; Sapeta, S.; Siódmok, A.; Skrzypek, M.
2016-12-01
A next step in development of the KrkNLO method of including complete NLO QCD corrections to hard processes in a LO parton-shower Monte Carlo is presented. It consists of a generalisation of the method, previously used for the Drell-Yan process, to Higgs-boson production. This extension is accompanied with the complete description of parton distribution functions in a dedicated, Monte Carlo factorisation scheme, applicable to any process of production of one or more colour-neutral particles in hadron-hadron collisions.
Kinetic Monte Carlo method applied to nucleic acid hairpin folding.
Sauerwine, Ben; Widom, Michael
2011-12-01
Kinetic Monte Carlo on coarse-grained systems, such as nucleic acid secondary structure, is advantageous for being able to access behavior at long time scales, even minutes or hours. Transition rates between coarse-grained states depend upon intermediate barriers, which are not directly simulated. We propose an Arrhenius rate model and an intermediate energy model that incorporates the effects of the barrier between simulated states without enlarging the state space itself. Applying our Arrhenius rate model to DNA hairpin folding, we demonstrate improved agreement with experiment compared to the usual kinetic Monte Carlo model. Further improvement results from including rigidity of single-stranded stacking.
Quasi-Monte Carlo methods for the Heston model
Jan Baldeaux; Dale Roberts
2012-01-01
In this paper, we discuss the application of quasi-Monte Carlo methods to the Heston model. We base our algorithms on the Broadie-Kaya algorithm, an exact simulation scheme for the Heston model. As the joint transition densities are not available in closed-form, the Linear Transformation method due to Imai and Tan, a popular and widely applicable method to improve the effectiveness of quasi-Monte Carlo methods, cannot be employed in the context of path-dependent options when the underlying pr...
Modelling hadronic interactions in cosmic ray Monte Carlo generators
Pierog Tanguy
2015-01-01
Full Text Available Currently the uncertainty in the prediction of shower observables for different primary particles and energies is dominated by differences between hadronic interaction models. The LHC data on minimum bias measurements can be used to test Monte Carlo generators and these new constraints will help to reduce the uncertainties in air shower predictions. In this article, after a short introduction on air showers and Monte Carlo generators, we will show the results of the comparison between the updated version of high energy hadronic interaction models EPOS LHC and QGSJETII-04 with LHC data. Results for air shower simulations and their consequences on comparisons with air shower data will be discussed.
An overview of Monte Carlo treatment planning for radiotherapy.
Spezi, Emiliano; Lewis, Geraint
2008-01-01
The implementation of Monte Carlo dose calculation algorithms in clinical radiotherapy treatment planning systems has been anticipated for many years. Despite a continuous increase of interest in Monte Carlo Treatment Planning (MCTP), its introduction into clinical practice has been delayed by the extent of calculation time required. The development of newer and faster MC codes is behind the commercialisation of the first MC-based treatment planning systems. The intended scope of this article is to provide the reader with a compact 'primer' on different approaches to MCTP with particular attention to the latest developments in the field.
Monte Carlo simulation of electron slowing down in indium
Rouabah, Z.; Hannachi, M. [Materials and Electronic Systems Laboratory (LMSE), University of Bordj Bou Arreridj, Bordj Bou Arreridj (Algeria); Champion, C. [Université de Bordeaux 1, CNRS/IN2P3, Centre d’Etudes Nucléaires de Bordeaux-Gradignan, (CENBG), Gradignan (France); Bouarissa, N., E-mail: n_bouarissa@yahoo.fr [Laboratory of Materials Physics and its Applications, University of M' sila, 28000 M' sila (Algeria)
2015-07-15
Highlights: • Electron scattering in indium targets. • Modeling of elastic cross-sections. • Monte Carlo simulation of low energy electrons. - Abstract: In the current study, we aim at simulating via a detailed Monte Carlo code, the electron penetration in a semi-infinite indium medium for incident energies ranging from 0.5 to 5 keV. Electron range, backscattering coefficients, mean penetration depths as well as stopping profiles are then reported. The results may be seen as the first predictions for low-energy electron penetration in indium target.
Monte Carlo methods and models in finance and insurance
Korn, Ralf
2010-01-01
Offering a unique balance between applications and calculations, this book incorporates the application background of finance and insurance with the theory and applications of Monte Carlo methods. It presents recent methods and algorithms, including the multilevel Monte Carlo method, the statistical Romberg method, and the Heath-Platen estimator, as well as recent financial and actuarial models, such as the Cheyette and dynamic mortality models. The book enables readers to find the right algorithm for a desired application and illustrates complicated methods and algorithms with simple applicat
Utilising Monte Carlo Simulation for the Valuation of Mining Concessions
Rosli Said
2005-12-01
Full Text Available Valuation involves the analyses of various input data to produce an estimated value. Since each input is itself often an estimate, there is an element of uncertainty in the input. This leads to uncertainty in the resultant output value. It is argued that a valuation must also convey information on the uncertainty, so as to be more meaningful and informative to the user. The Monte Carlo simulation technique can generate the information on uncertainty and is therefore potentially useful to valuation. This paper reports on the investigation that has been conducted to apply Monte Carlo simulation technique in mineral valuation, more specifically, in the valuation of a quarry concession.
PEPSI — a Monte Carlo generator for polarized leptoproduction
Mankiewicz, L.; Schäfer, A.; Veltri, M.
1992-09-01
We describe PEPSI (Polarized Electron Proton Scattering Interactions), a Monte Carlo program for polarized deep inelastic leptoproduction mediated by electromagnetic interaction, and explain how to use it. The code is a modification of the LEPTO 4.3 Lund Monte Carlo for unpolarized scattering. The hard virtual gamma-parton scattering is generated according to the polarization-dependent QCD cross-section of the first order in α S. PEPSI requires the standard polarization-independent JETSET routines to simulate the fragmentation into final hadrons.
THE APPLICATION OF MONTE CARLO SIMULATION FOR A DECISION PROBLEM
Çiğdem ALABAŞ
2001-01-01
Full Text Available The ultimate goal of the standard decision tree approach is to calculate the expected value of a selected performance measure. In the real-world situations, the decision problems become very complex as the uncertainty factors increase. In such cases, decision analysis using standard decision tree approach is not useful. One way of overcoming this difficulty is the Monte Carlo simulation. In this study, a Monte Carlo simulation model is developed for a complex problem and statistical analysis is performed to make the best decision.
Accuracy Analysis of Assembly Success Rate with Monte Carlo Simulations
仲昕; 杨汝清; 周兵
2003-01-01
Monte Carlo simulation was applied to Assembly Success Rate (ASR) analyses.ASR of two peg-in-hole robot assemblies was used as an example by taking component parts' sizes,manufacturing tolerances and robot repeatability into account.A statistic arithmetic expression was proposed and deduced in this paper,which offers an alternative method of estimating the accuracy of ASR,without having to repeat the simulations.This statistic method also helps to choose a suitable sample size,if error reduction is desired.Monte Carlo simulation results demonstrated the feasibility of the method.
Novel Quantum Monte Carlo Approaches for Quantum Liquids
Rubenstein, Brenda M.
Quantum Monte Carlo methods are a powerful suite of techniques for solving the quantum many-body problem. By using random numbers to stochastically sample quantum properties, QMC methods are capable of studying low-temperature quantum systems well beyond the reach of conventional deterministic techniques. QMC techniques have likewise been indispensible tools for augmenting our current knowledge of superfluidity and superconductivity. In this thesis, I present two new quantum Monte Carlo techniques, the Monte Carlo Power Method and Bose-Fermi Auxiliary-Field Quantum Monte Carlo, and apply previously developed Path Integral Monte Carlo methods to explore two new phases of quantum hard spheres and hydrogen. I lay the foundation for a subsequent description of my research by first reviewing the physics of quantum liquids in Chapter One and the mathematics behind Quantum Monte Carlo algorithms in Chapter Two. I then discuss the Monte Carlo Power Method, a stochastic way of computing the first several extremal eigenvalues of a matrix too memory-intensive to be stored and therefore diagonalized. As an illustration of the technique, I demonstrate how it can be used to determine the second eigenvalues of the transition matrices of several popular Monte Carlo algorithms. This information may be used to quantify how rapidly a Monte Carlo algorithm is converging to the equilibrium probability distribution it is sampling. I next present the Bose-Fermi Auxiliary-Field Quantum Monte Carlo algorithm. This algorithm generalizes the well-known Auxiliary-Field Quantum Monte Carlo algorithm for fermions to bosons and Bose-Fermi mixtures. Despite some shortcomings, the Bose-Fermi Auxiliary-Field Quantum Monte Carlo algorithm represents the first exact technique capable of studying Bose-Fermi mixtures of any size in any dimension. In Chapter Six, I describe a new Constant Stress Path Integral Monte Carlo algorithm for the study of quantum mechanical systems under high pressures. While
Fission source sampling in coupled Monte Carlo simulations
Olsen, Boerge; Dufek, Jan [KTH Royal Inst. of Technology, Stockholm (Sweden). Div. of Nuclear Research Technology
2017-05-15
We study fission source sampling methods suitable for the iterative way of solving coupled Monte Carlo neutronics problems. Specifically, we address the question as to how the initial Monte Carlo fission source should be optimally sampled at the beginning of each iteration step. We compare numerically two approaches of sampling the initial fission source; the tested techniques are derived from well-known methods for iterating the neutron flux in coupled simulations. The first technique samples the initial fission source using the source from the previous iteration step, while the other technique uses a combination of all previous steps for this purpose. We observe that the previous-step approach performs the best.
Monte Carlo simulation of electrons in dense gases
Tattersall, Wade; Boyle, Greg; Cocks, Daniel; Buckman, Stephen; White, Ron
2014-10-01
We implement a Monte-Carlo simulation modelling the transport of electrons and positrons in dense gases and liquids, by using a dynamic structure factor that allows us to construct structure-modified effective cross sections. These account for the coherent effects caused by interactions with the relatively dense medium. The dynamic structure factor also allows us to model thermal gases in the same manner, without needing to directly sample the velocities of the neutral particles. We present the results of a series of Monte Carlo simulations that verify and apply this new technique, and make comparisons with macroscopic predictions and Boltzmann equation solutions. Financial support of the Australian Research Council.
Green's function monte carlo and the many-fermion problem
Kalos, M. H.
The application of Green's function Monte Carlo to many body problems is outlined. For boson problems, the method is well developed and practical. An "efficiency principle",importance sampling, can be used to reduce variance. Fermion problems are more difficult because spatially antisymmetric functions must be represented as a difference of two density functions. Naively treated, this leads to a rapid growth of Monte Carlo error. Methods for overcoming the difficulty are discussed. Satisfactory algorithms exist for few-body problems; for many-body problems more work is needed, but it is likely that adequate methods will soon be available.
Cosmological Markov Chain Monte Carlo simulation with Cmbeasy
Müller, C M
2004-01-01
We introduce a Markov Chain Monte Carlo simulation and data analysis package for the cosmological computation package Cmbeasy. We have taken special care in implementing an adaptive step algorithm for the Markov Chain Monte Carlo in order to improve convergence. Data analysis routines are provided which allow to test models of the Universe against up-to-date measurements of the Cosmic Microwave Background, Supernovae Ia and Large Scale Structure. The observational data is provided with the software for convenient usage. The package is publicly available as part of the Cmbeasy software at www.cmbeasy.org.
王雪峰; 陈兴稣; 苏金善; 王元庆
2016-01-01
Monte Carlo算法是一种数学统计方法,应用于随机过程的问题.扩散光层析成像重建中的正向问题,就是一个随机概率统计过程,Monte Carlo算法可以较好地模拟光子在组织体中的散射和吸收的过程,与真实情况非常接近.总结分析了Monte Carlo模拟的经典方法和几种改进的方法.给出了Monte Carlo算法在扩散光层析成像重建过程的主要应用及发展.
Stochastic simulation and Monte-Carlo methods; Simulation stochastique et methodes de Monte-Carlo
Graham, C. [Centre National de la Recherche Scientifique (CNRS), 91 - Gif-sur-Yvette (France); Ecole Polytechnique, 91 - Palaiseau (France); Talay, D. [Institut National de Recherche en Informatique et en Automatique (INRIA), 78 - Le Chesnay (France); Ecole Polytechnique, 91 - Palaiseau (France)
2011-07-01
This book presents some numerical probabilistic methods of simulation with their convergence speed. It combines mathematical precision and numerical developments, each proposed method belonging to a precise theoretical context developed in a rigorous and self-sufficient manner. After some recalls about the big numbers law and the basics of probabilistic simulation, the authors introduce the martingales and their main properties. Then, they develop a chapter on non-asymptotic estimations of Monte-Carlo method errors. This chapter gives a recall of the central limit theorem and precises its convergence speed. It introduces the Log-Sobolev and concentration inequalities, about which the study has greatly developed during the last years. This chapter ends with some variance reduction techniques. In order to demonstrate in a rigorous way the simulation results of stochastic processes, the authors introduce the basic notions of probabilities and of stochastic calculus, in particular the essential basics of Ito calculus, adapted to each numerical method proposed. They successively study the construction and important properties of the Poisson process, of the jump and deterministic Markov processes (linked to transport equations), and of the solutions of stochastic differential equations. Numerical methods are then developed and the convergence speed results of algorithms are rigorously demonstrated. In passing, the authors describe the probabilistic interpretation basics of the parabolic partial derivative equations. Non-trivial applications to real applied problems are also developed. (J.S.)
Burkatzki, Mark Thomas
2008-07-01
The author presents scalar-relativistic energy-consistent Hartree-Fock pseudopotentials for the main-group and 3d-transition-metal elements. The pseudopotentials do not exhibit a singularity at the nucleus and are therefore suitable for quantum Monte Carlo (QMC) calculations. The author demonstrates their transferability through extensive benchmark calculations of atomic excitation spectra as well as molecular properties. In particular, the author computes the vibrational frequencies and binding energies of 26 first- and second-row diatomic molecules using post Hartree-Fock methods, finding excellent agreement with the corresponding all-electron values. The author shows that the presented pseudopotentials give superior accuracy than other existing pseudopotentials constructed specifically for QMC. The localization error and the efficiency in QMC are discussed. The author also presents QMC calculations for selected atomic and diatomic 3d-transitionmetal systems. Finally, valence basis sets of different sizes (VnZ with n=D,T,Q,5 for 1st and 2nd row; with n=D,T for 3rd to 5th row; with n=D,T,Q for the 3d transition metals) optimized for the pseudopotentials are presented. (orig.)
A Novel Exact Fixed-node Quantum Monte Carlo Algorithm
Hong Xin HUANG
2004-01-01
In this paper we proposed a novel exact fixed-node quantum Monte Carlo (EFNQMC) algorithm, which is a self-optimizing and self-improving procedure. In contrast to the previous EFNQMC method, the trial function is optimized synchronistically in the diffusion procedure, but not before the beginning of EFNQMC computation. In order to optimize the trial function, the improved steepest descent technique is used, in which the step size is automatically adjustable. The procedure is quasi-Newton and converges super linearly. We also use a novel trial function, which has correct electron-electron and electron-nucleus cusp conditions. The novel EFNQMC algorithm and the novel trial function are employed to calculate the energies of 11A1 state of CH2, 1Ag state of C8 and the ground-states of H2, LiH, Li2, H2O, respectively. The test results show that both the novel algorithm and the trial function proposed in the present paper are very excellent.
Evidence for stable square ice from quantum Monte Carlo
Chen, Ji; Zen, Andrea; Brandenburg, Jan Gerit; Alfè, Dario; Michaelides, Angelos
2016-12-01
Recent experiments on ice formed by water under nanoconfinement provide evidence for a two-dimensional (2D) "square ice" phase. However, the interpretation of the experiments has been questioned and the stability of square ice has become a matter of debate. Partially this is because the simulation approaches employed so far (force fields and density functional theory) struggle to accurately describe the very small energy differences between the relevant phases. Here we report a study of 2D ice using an accurate wave-function based electronic structure approach, namely diffusion Monte Carlo (DMC). We find that at relatively high pressure, square ice is indeed the lowest enthalpy phase examined, supporting the initial experimental claim. Moreover, at lower pressures, a "pentagonal ice" phase (not yet observed experimentally) has the lowest enthalpy, and at ambient pressure, the "pentagonal ice" phase is degenerate with a "hexagonal ice" phase. Our DMC results also allow us to evaluate the accuracy of various density functional theory exchange-correlation functionals and force field models, and in doing so we extend the understanding of how such methodologies perform to challenging 2D structures presenting dangling hydrogen bonds.
Quantum Monte Carlo calculations of the dimerization energy of borane.
Fracchia, Francesco; Bressanini, Dario; Morosi, Gabriele
2011-09-07
Accurate thermodynamic data are required to improve the performance of chemical hydrides that are potential hydrogen storage materials. Boron compounds are among the most interesting candidates. However, different experimental measurements of the borane dimerization energy resulted in a rather wide range (-34.3 to -39.1) ± 2 kcal/mol. Diffusion Monte Carlo (DMC) simulations usually recover more than 95% of the correlation energy, so energy differences rely less on error cancellation than other methods. DMC energies of BH(3), B(2)H(6), BH(3)CO, CO, and BH(2)(+) allowed us to predict the borane dimerization energy, both via the direct process and indirect processes such as the dissociation of BH(3)CO. Our D(e) = -43.12(8) kcal/mol, corrected for the zero point energy evaluated by considering the anharmonic contributions, results in a borane dimerization energy of -36.59(8) kcal/mol. The process via the dissociation of BH(3)CO gives -34.5(2) kcal/mol. Overall, our values suggest a slightly less D(e) than the most recent W4 estimate D(e) = -44.47 kcal/mol [A. Karton and J. M. L. Martin, J. Phys. Chem. A 111, 5936 (2007)]. Our results show that reliable thermochemical data for boranes can be predicted by fixed node (FN)-DMC calculations.
Effective quantum Monte Carlo algorithm for modeling strongly correlated systems
Kashurnikov, V. A.; Krasavin, A. V.
2007-01-01
A new effective Monte Carlo algorithm based on principles of continuous time is presented. It allows calculating, in an arbitrary discrete basis, thermodynamic quantities and linear response of mixed boson-fermion, spin-boson, and other strongly correlated systems which admit no analytic description
Time management for Monte-Carlo tree search in Go
Baier, Hendrik; Winands, Mark H M
2012-01-01
The dominant approach for programs playing the game of Go is nowadays Monte-Carlo Tree Search (MCTS). While MCTS allows for fine-grained time control, little has been published on time management for MCTS programs under tournament conditions. This paper investigates the effects that various time-man
Variational Monte Carlo calculations of few-body nuclei
Wiringa, R.B.
1986-01-01
The variational Monte Carlo method is described. Results for the binding energies, density distributions, momentum distributions, and static longitudinal structure functions of the /sup 3/H, /sup 3/He, and /sup 4/He ground states, and for the energies of the low-lying scattering states in /sup 4/He are presented. 25 refs., 3 figs.
Monte Carlo studies of nuclei and quantum liquid drops
Pandharipande, V.R.; Pieper, S.C.
1989-01-01
The progress in application of variational and Green's function Monte Carlo methods to nuclei is reviewed. The nature of single-particle orbitals in correlated quantum liquid drops is discussed, and it is suggested that the difference between quasi-particle and mean-field orbitals may be of importance in nuclear structure physics. 27 refs., 7 figs., 2 tabs.
Determining MTF of digital detector system with Monte Carlo simulation
Jeong, Eun Seon; Lee, Hyung Won; Nam, Sang Hee
2005-04-01
We have designed a detector based on a-Se(amorphous Selenium) and done simulation the detector with Monte Carlo method. We will apply the cascaded linear system theory to determine the MTF for whole detector system. For direct comparison with experiment, we have simulated 139um pixel pitch and used simulated X-ray tube spectrum.
Data libraries as a collaborative tool across Monte Carlo codes
Augelli, Mauro; Han, Mincheol; Hauf, Steffen; Kim, Chan-Hyeung; Kuster, Markus; Pia, Maria Grazia; Quintieri, Lina; Saracco, Paolo; Seo, Hee; Sudhakar, Manju; Eidenspointner, Georg; Zoglauer, Andreas
2010-01-01
The role of data libraries in Monte Carlo simulation is discussed. A number of data libraries currently in preparation are reviewed; their data are critically examined with respect to the state-of-the-art in the respective fields. Extensive tests with respect to experimental data have been performed for the validation of their content.
A separable shadow Hamiltonian hybrid Monte Carlo method.
Sweet, Christopher R; Hampton, Scott S; Skeel, Robert D; Izaguirre, Jesús A
2009-11-07
Hybrid Monte Carlo (HMC) is a rigorous sampling method that uses molecular dynamics (MD) as a global Monte Carlo move. The acceptance rate of HMC decays exponentially with system size. The shadow hybrid Monte Carlo (SHMC) was previously introduced to reduce this performance degradation by sampling instead from the shadow Hamiltonian defined for MD when using a symplectic integrator. SHMC's performance is limited by the need to generate momenta for the MD step from a nonseparable shadow Hamiltonian. We introduce the separable shadow Hamiltonian hybrid Monte Carlo (S2HMC) method based on a formulation of the leapfrog/Verlet integrator that corresponds to a separable shadow Hamiltonian, which allows efficient generation of momenta. S2HMC gives the acceptance rate of a fourth order integrator at the cost of a second-order integrator. Through numerical experiments we show that S2HMC consistently gives a speedup greater than two over HMC for systems with more than 4000 atoms for the same variance. By comparison, SHMC gave a maximum speedup of only 1.6 over HMC. S2HMC has the additional advantage of not requiring any user parameters beyond those of HMC. S2HMC is available in the program PROTOMOL 2.1. A Python version, adequate for didactic purposes, is also in MDL (http://mdlab.sourceforge.net/s2hmc).
Quantum Monte Carlo diagonalization method as a variational calculation
Mizusaki, Takahiro; Otsuka, Takaharu [Tokyo Univ. (Japan). Dept. of Physics; Honma, Michio
1997-05-01
A stochastic method for performing large-scale shell model calculations is presented, which utilizes the auxiliary field Monte Carlo technique and diagonalization method. This method overcomes the limitation of the conventional shell model diagonalization and can extremely widen the feasibility of shell model calculations with realistic interactions for spectroscopic study of nuclear structure. (author)
Monte Carlo simulation of quantum statistical lattice models
Raedt, Hans De; Lagendijk, Ad
1985-01-01
In this article we review recent developments in computational methods for quantum statistical lattice problems. We begin by giving the necessary mathematical basis, the generalized Trotter formula, and discuss the computational tools, exact summations and Monte Carlo simulation, that will be used t
Distributed and Adaptive Darting Monte Carlo through Regenerations
Ahn, S.; Chen, Y.; Welling, M.
2013-01-01
Darting Monte Carlo (DMC) is a MCMC procedure designed to effectively mix between multiple modes of a probability distribution. We propose an adaptive and distributed version of this method by using regenerations. This allows us to run multiple chains in parallel and adapt the shape of the jump regi
A novel Monte Carlo approach to hybrid local volatility models
A.W. van der Stoep (Anton); L.A. Grzelak (Lech Aleksander); C.W. Oosterlee (Cornelis)
2017-01-01
textabstractWe present in a Monte Carlo simulation framework, a novel approach for the evaluation of hybrid local volatility [Risk, 1994, 7, 18–20], [Int. J. Theor. Appl. Finance, 1998, 1, 61–110] models. In particular, we consider the stochastic local volatility model—see e.g. Lipton et al. [Quant.
SPANDY: a Monte Carlo program for gas target scattering geometry
Jarmie, N.; Jett, J.H.; Niethammer, A.C.
1977-02-01
A Monte Carlo computer program is presented that simulates a two-slit gas target scattering geometry. The program is useful in estimating effects due to finite geometry and multiple scattering in the target foil. Details of the program are presented and experience with a specific example is discussed.
Monte Carlo Simulation of Partially Confined Flexible Polymers
Hermsen, G.F.; de Geeter, B.A.; van der Vegt, N.F.A.; Wessling, Matthias
2002-01-01
We have studied conformational properties of flexible polymers partially confined to narrow pores of different size using configurational biased Monte Carlo simulations under athermal conditions. The asphericity of the chain has been studied as a function of its center of mass position along the por
Tackling the premature convergence problem in Monte-Carlo localization
Kootstra, G.; de Boer, B.
2009-01-01
Monte-Carlo localization uses particle filtering to estimate the position of the robot. The method is known to suffer from the loss of potential positions when there is ambiguity present in the environment. Since many indoor environments are highly symmetric, this problem of premature convergence is
Nonequilibrium Candidate Monte Carlo Simulations with Configurational Freezing Schemes.
Giovannelli, Edoardo; Gellini, Cristina; Pietraperzia, Giangaetano; Cardini, Gianni; Chelli, Riccardo
2014-10-14
Nonequilibrium Candidate Monte Carlo simulation [Nilmeier et al., Proc. Natl. Acad. Sci. U.S.A. 2011, 108, E1009-E1018] is a tool devised to design Monte Carlo moves with high acceptance probabilities that connect uncorrelated configurations. Such moves are generated through nonequilibrium driven dynamics, producing candidate configurations accepted with a Monte Carlo-like criterion that preserves the equilibrium distribution. The probability of accepting a candidate configuration as the next sample in the Markov chain basically depends on the work performed on the system during the nonequilibrium trajectory and increases with decreasing such a work. It is thus strategically relevant to find ways of producing nonequilibrium moves with low work, namely moves where dissipation is as low as possible. This is the goal of our methodology, in which we combine Nonequilibrium Candidate Monte Carlo with Configurational Freezing schemes developed by Nicolini et al. (J. Chem. Theory Comput. 2011, 7, 582-593). The idea is to limit the configurational sampling to particles of a well-established region of the simulation sample, namely the region where dissipation occurs, while leaving fixed the other particles. This allows to make the system relaxation faster around the region perturbed by the finite-time switching move and hence to reduce the dissipated work, eventually enhancing the probability of accepting the generated move. Our combined approach enhances significantly configurational sampling, as shown by the case of a bistable dimer immersed in a dense fluid.
Monte Carlo simulation of magnetic nanostructured thin films
Guan Zhi-Qiang; Yutaka Abe; Jiang Dong-Hua; Lin Hai; Yoshitake Yamazakia; Wu Chen-Xu
2004-01-01
@@ Using Monte Carlo simulation, we have compared the magnetic properties between nanostructured thin films and two-dimensional crystalline solids. The dependence of nanostructured properties on the interaction between particles that constitute the nanostructured thin films is also studied. The result shows that the parameters in the interaction potential have an important effect on the properties of nanostructured thin films at the transition temperatures.
Multi-microcomputer system for Monte-Carlo calculations
Berg, B; Krasemann, H
1981-01-01
The authors propose a microcomputer system that allows parallel processing for Monte Carlo calculations in lattice gauge theories, simulations of high energy physics experiments and many other fields of current interest. The master-n-slave multiprocessor system is based on the Motorola MC 6800 microprocessor. One attraction of this processor is that it allows up to 16 M Byte random access memory.
Criticality benchmarks validation of the Monte Carlo code TRIPOLI-2
Maubert, L. (Commissariat a l' Energie Atomique, Inst. de Protection et de Surete Nucleaire, Service d' Etudes de Criticite, 92 - Fontenay-aux-Roses (France)); Nouri, A. (Commissariat a l' Energie Atomique, Inst. de Protection et de Surete Nucleaire, Service d' Etudes de Criticite, 92 - Fontenay-aux-Roses (France)); Vergnaud, T. (Commissariat a l' Energie Atomique, Direction des Reacteurs Nucleaires, Service d' Etudes des Reacteurs et de Mathematique Appliquees, 91 - Gif-sur-Yvette (France))
1993-04-01
The three-dimensional energy pointwise Monte-Carlo code TRIPOLI-2 includes metallic spheres of uranium and plutonium, nitrate plutonium solutions, square and triangular pitch assemblies of uranium oxide. Results show good agreements between experiments and calculations, and avoid a part of the code and its ENDF-B4 library validation. (orig./DG)
Strain in the mesoscale kinetic Monte Carlo model for sintering
Bjørk, Rasmus; Frandsen, Henrik Lund; Tikare, V.
2014-01-01
Shrinkage strains measured from microstructural simulations using the mesoscale kinetic Monte Carlo (kMC) model for solid state sintering are discussed. This model represents the microstructure using digitized discrete sites that are either grain or pore sites. The algorithm used to simulate...
Monte Carlo estimation of the conditional Rasch model
Akkermans, Wies M.W.
1994-01-01
In order to obtain conditional maximum likelihood estimates, the so-called conditioning estimates have to be calculated. In this paper a method is examined that does not calculate these constants exactly, but approximates them using Monte Carlo Markov Chains. As an example, the method is applied to
Monte Carlo estimation of the conditional Rasch model
Akkermans, W.
1998-01-01
In order to obtain conditional maximum likelihood estimates, the conditioning constants are needed. Geyer and Thompson (1992) proposed a Markov chain Monte Carlo method that can be used to approximate these constants when they are difficult to calculate exactly. In the present paper, their method is
Nanoporous gold formation by dealloying : A Metropolis Monte Carlo study
Zinchenko, O.; De Raedt, H. A.; Detsi, E.; Onck, P. R.; De Hosson, J. T. M.
2013-01-01
A Metropolis Monte Carlo study of the dealloying mechanism leading to the formation of nanoporous gold is presented. A simple lattice-gas model for gold, silver and acid particles, vacancies and products of chemical reactions is adopted. The influence of temperature, concentration and lattice defect
Quantum Monte Carlo simulation of topological phase transitions
Yamamoto, Arata; Kimura, Taro
2016-12-01
We study the electron-electron interaction effects on topological phase transitions by the ab initio quantum Monte Carlo simulation. We analyze two-dimensional class A topological insulators and three-dimensional Weyl semimetals with the long-range Coulomb interaction. The direct computation of the Chern number shows the electron-electron interaction modifies or extinguishes topological phase transitions.
Calculating coherent pair production with Monte Carlo methods
Bottcher, C.; Strayer, M.R.
1989-01-01
We discuss calculations of the coherent electromagnetic pair production in ultra-relativistic hadron collisions. This type of production, in lowest order, is obtained from three diagrams which contain two virtual photons. We discuss simple Monte Carlo methods for evaluating these classes of diagrams without recourse to involved algebraic reduction schemes. 19 refs., 11 figs.
A Monte Carlo Evaluation of Maximum Likelihood Multidimensional Scaling Methods
Bijmolt, T.H.A.; Wedel, M.
1996-01-01
We compare three alternative Maximum Likelihood Multidimensional Scaling methods for pairwise dissimilarity ratings, namely MULTISCALE, MAXSCAL, and PROSCAL in a Monte Carlo study.The three MLMDS methods recover the true con gurations very well.The recovery of the true dimensionality depends on the
Direct determination of liquid phase coexistence by Monte Carlo simulations
Zweistra, H.J.A.; Besseling, N.A.M.
2006-01-01
A formalism to determine coexistence points by means of Monte Carlo simulations is presented. The general idea of the method is to perform a simulation simultaneously in several unconnected boxes which can exchange particles. At equilibrium, most of the boxes will be occupied by a homogeneous phase.
Monte Carlo methods for multidimensional integration for European option pricing
Todorov, V.; Dimov, I. T.
2016-10-01
In this paper, we illustrate examples of highly accurate Monte Carlo and quasi-Monte Carlo methods for multiple integrals related to the evaluation of European style options. The idea is that the value of the option is formulated in terms of the expectation of some random variable; then the average of independent samples of this random variable is used to estimate the value of the option. First we obtain an integral representation for the value of the option using the risk neutral valuation formula. Then with an appropriations change of the constants we obtain a multidimensional integral over the unit hypercube of the corresponding dimensionality. Then we compare a specific type of lattice rules over one of the best low discrepancy sequence of Sobol for numerical integration. Quasi-Monte Carlo methods are compared with Adaptive and Crude Monte Carlo techniques for solving the problem. The four approaches are completely different thus it is a question of interest to know which one of them outperforms the other for evaluation multidimensional integrals in finance. Some of the advantages and disadvantages of the developed algorithms are discussed.
Monte Carlo Simulation Optimizing Design of Grid Ionization Chamber
ZHENG; Yu-lai; WANG; Qiang; YANG; Lu
2013-01-01
The grid ionization chamber detector is often used for measuring charged particles.Based on Monte Carlo simulation method,the energy loss distribution and electron ion pairs of alpha particle with different energy have been calculated to determine suitable filling gas in the ionization chamber filled with
Optimization of sequential decisions by least squares Monte Carlo method
Nishijima, Kazuyoshi; Anders, Annett
change adaptation measures, and evacuation of people and assets in the face of an emerging natural hazard event. Focusing on the last example, an efficient solution scheme is proposed by Anders and Nishijima (2011). The proposed solution scheme takes basis in the least squares Monte Carlo method, which...
Testing Dependent Correlations with Nonoverlapping Variables: A Monte Carlo Simulation
Silver, N. Clayton; Hittner, James B.; May, Kim
2004-01-01
The authors conducted a Monte Carlo simulation of 4 test statistics or comparing dependent correlations with no variables in common. Empirical Type 1 error rates and power estimates were determined for K. Pearson and L. N. G. Filon's (1898) z, O. J. Dunn and V. A. Clark's (1969) z, J. H. Steiger's (1980) original modification of Dunn and Clark's…
Bayesian Monte Carlo Method for Nuclear Data Evaluation
Koning, A.J., E-mail: koning@nrg.eu
2015-01-15
A Bayesian Monte Carlo method is outlined which allows a systematic evaluation of nuclear reactions using TALYS. The result will be either an EXFOR-weighted covariance matrix or a collection of random files, each accompanied by an experiment based weight.
Auxiliary-field quantum Monte Carlo methods in nuclei
Alhassid, Y
2016-01-01
Auxiliary-field quantum Monte Carlo methods enable the calculation of thermal and ground state properties of correlated quantum many-body systems in model spaces that are many orders of magnitude larger than those that can be treated by conventional diagonalization methods. We review recent developments and applications of these methods in nuclei using the framework of the configuration-interaction shell model.
Play It Again: Teaching Statistics with Monte Carlo Simulation
Sigal, Matthew J.; Chalmers, R. Philip
2016-01-01
Monte Carlo simulations (MCSs) provide important information about statistical phenomena that would be impossible to assess otherwise. This article introduces MCS methods and their applications to research and statistical pedagogy using a novel software package for the R Project for Statistical Computing constructed to lessen the often steep…
Exact Dynamics via Poisson Process: a unifying Monte Carlo paradigm
Gubernatis, James
2014-03-01
A common computational task is solving a set of ordinary differential equations (o.d.e.'s). A little known theorem says that the solution of any set of o.d.e.'s is exactly solved by the expectation value over a set of arbitary Poisson processes of a particular function of the elements of the matrix that defines the o.d.e.'s. The theorem thus provides a new starting point to develop real and imaginary-time continous-time solvers for quantum Monte Carlo algorithms, and several simple observations enable various quantum Monte Carlo techniques and variance reduction methods to transfer to a new context. I will state the theorem, note a transformation to a very simple computational scheme, and illustrate the use of some techniques from the directed-loop algorithm in context of the wavefunction Monte Carlo method that is used to solve the Lindblad master equation for the dynamics of open quantum systems. I will end by noting that as the theorem does not depend on the source of the o.d.e.'s coming from quantum mechanics, it also enables the transfer of continuous-time methods from quantum Monte Carlo to the simulation of various classical equations of motion heretofore only solved deterministically.
Monte Carlo method for magnetic impurities in metals
Hirsch, J. E.; Fye, R. M.
1986-01-01
The paper discusses a Monte Carlo algorithm to study properties of dilute magnetic alloys; the method can treat a small number of magnetic impurities interacting wiith the conduction electrons in a metal. Results for the susceptibility of a single Anderson impurity in the symmetric case show the expected universal behavior at low temperatures. Some results for two Anderson impurities are also discussed.
Improved Monte Carlo model for multiple scattering calculations
Weiwei Cai; Lin Ma
2012-01-01
The coupling between the Monte Carlo (MC) method and geometrical optics to improve accuracy is investigated.The results obtained show improved agreement with previous experimental data,demonstrating that the MC method,when coupled with simple geometrical optics,can simulate multiple scattering with enhanced fidelity.
Simulating Strongly Correlated Electron Systems with Hybrid Monte Carlo
LIU Chuan
2000-01-01
Using the path integral representation, the Hubbard and the periodic Anderson model on D-dimensional cubic lattice are transformed into field theories of fermions in D + 1 dimensions. These theories at half-filling possess a positive definite real symmetry fermion matrix and can be simulated using the hybrid Monte Carlo method.
Research of Monte Carlo Simulation in Commercial Bank Risk Management
BeimingXiao
2004-01-01
Simulation method is an important-tool in financial risk management. It can simulate financial variable or economic wriable and deal with non-linear or non-nominal issue. This paper analyzes the usage of "Monte Carlo" approach in commercial bank risk management.
Observations on variational and projector Monte Carlo methods.
Umrigar, C J
2015-10-28
Variational Monte Carlo and various projector Monte Carlo (PMC) methods are presented in a unified manner. Similarities and differences between the methods and choices made in designing the methods are discussed. Both methods where the Monte Carlo walk is performed in a discrete space and methods where it is performed in a continuous space are considered. It is pointed out that the usual prescription for importance sampling may not be advantageous depending on the particular quantum Monte Carlo method used and the observables of interest, so alternate prescriptions are presented. The nature of the sign problem is discussed for various versions of PMC methods. A prescription for an exact PMC method in real space, i.e., a method that does not make a fixed-node or similar approximation and does not have a finite basis error, is presented. This method is likely to be practical for systems with a small number of electrons. Approximate PMC methods that are applicable to larger systems and go beyond the fixed-node approximation are also discussed.
Monte-carlo calculations for some problems of quantum mechanics
Novoselov, A. A., E-mail: novoselov@goa.bog.msu.ru; Pavlovsky, O. V.; Ulybyshev, M. V. [Moscow State University (Russian Federation)
2012-09-15
The Monte-Carlo technique for the calculations of functional integral in two one-dimensional quantum-mechanical problems had been applied. The energies of the bound states in some potential wells were obtained using this method. Also some peculiarities in the calculation of the kinetic energy in the ground state had been studied.
Quantum Monte Carlo simulation of topological phase transitions
Yamamoto, Arata
2016-01-01
We study the electron-electron interaction effects on topological phase transitions by the ab-initio quantum Monte Carlo simulation. We analyze two-dimensional class A topological insulators and three-dimensional Weyl semimetals with the long-range Coulomb interaction. The direct computation of the Chern number shows the electron-electron interaction modifies or extinguishes topological phase transitions.
Exploring Mass Perception with Markov Chain Monte Carlo
Cohen, Andrew L.; Ross, Michael G.
2009-01-01
Several previous studies have examined the ability to judge the relative mass of objects in idealized collisions. With a newly developed technique of psychological Markov chain Monte Carlo sampling (A. N. Sanborn & T. L. Griffiths, 2008), this work explores participants; perceptions of different collision mass ratios. The results reveal…
CMS Monte Carlo production operations in a distributed computing environment
Mohapatra, A; Khomich, A; Lazaridis, C; Hernández, J M; Caballero, J; Hof, C; Kalinin, S; Flossdorf, A; Abbrescia, M; De Filippis, N; Donvito, G; Maggi, G; My, S; Pompili, A; Sarkar, S; Maes, J; Van Mulders, P; Villella, I; De Weirdt, S; Hammad, G; Wakefield, S; Guan, W; Lajas, J A S; Elmer, P; Evans, D; Fanfani, A; Bacchi, W; Codispoti, G; Van Lingen, F; Kavka, C; Eulisse, G
2008-01-01
Monte Carlo production for the CMS experiment is carried out in a distributed computing environment; the goal of producing 30M simulated events per month in the first half of 2007 has been reached. A brief overview of the production operations and statistics is presented.
A Variational Monte Carlo Approach to Atomic Structure
Davis, Stephen L.
2007-01-01
The practicality and usefulness of variational Monte Carlo calculations to atomic structure are demonstrated. It is found to succeed in quantitatively illustrating electron shielding, effective nuclear charge, l-dependence of the orbital energies, and singlet-tripetenergy splitting and ionization energy trends in atomic structure theory.
Monte Carlo Simulation on Glueball Search at BESⅢ
QIN Hu; SHEN Xiao-Yan
2007-01-01
The J/ψ radiative decays are suggested as promising modes for glueball search. A full Monte Carlo simulation of J/ψ→γηη and γηη', based on the design of BESⅢ detector, is performed to study the sensitivity of searching for a possible tensor glueball at BESⅢ.
The Metropolis Monte Carlo Method in Statistical Physics
Landau, David P.
2003-11-01
A brief overview is given of some of the advances in statistical physics that have been made using the Metropolis Monte Carlo method. By complementing theory and experiment, these have increased our understanding of phase transitions and other phenomena in condensed matter systems. A brief description of a new method, commonly known as "Wang-Landau sampling," will also be presented.
Exploring Mass Perception with Markov Chain Monte Carlo
Cohen, Andrew L.; Ross, Michael G.
2009-01-01
Several previous studies have examined the ability to judge the relative mass of objects in idealized collisions. With a newly developed technique of psychological Markov chain Monte Carlo sampling (A. N. Sanborn & T. L. Griffiths, 2008), this work explores participants; perceptions of different collision mass ratios. The results reveal…
An Overview of the Monte Carlo Methods, Codes, & Applications Group
Trahan, Travis John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2016-08-30
This report sketches the work of the Group to deliver first-principle Monte Carlo methods, production quality codes, and radiation transport-based computational and experimental assessments using the codes MCNP and MCATK for such applications as criticality safety, non-proliferation, nuclear energy, nuclear threat reduction and response, radiation detection and measurement, radiation health protection, and stockpile stewardship.
Monte Carlo Simulation of Partially Confined Flexible Polymers
Hermsen, G.F.; de Geeter, B.A.; van der Vegt, N.F.A.; Wessling, Matthias
2002-01-01
We have studied conformational properties of flexible polymers partially confined to narrow pores of different size using configurational biased Monte Carlo simulations under athermal conditions. The asphericity of the chain has been studied as a function of its center of mass position along the
Direct Monte Carlo simulation of nanoscale mixed gas bearings
Kyaw Sett Myo
2015-06-01
Full Text Available The conception of sealed hard drives with helium gas mixture has been recently suggested over the current hard drives for achieving higher reliability and less position error. Therefore, it is important to understand the effects of different helium gas mixtures on the slider bearing characteristics in the head–disk interface. In this article, the helium/air and helium/argon gas mixtures are applied as the working fluids and their effects on the bearing characteristics are studied using the direct simulation Monte Carlo method. Based on direct simulation Monte Carlo simulations, the physical properties of these gas mixtures such as mean free path and dynamic viscosity are achieved and compared with those obtained from theoretical models. It is observed that both results are comparable. Using these gas mixture properties, the bearing pressure distributions are calculated under different fractions of helium with conventional molecular gas lubrication models. The outcomes reveal that the molecular gas lubrication results could have relatively good agreement with those of direct simulation Monte Carlo simulations, especially for pure air, helium, or argon gas cases. For gas mixtures, the bearing pressures predicted by molecular gas lubrication model are slightly larger than those from direct simulation Monte Carlo simulation.
Monte Carlo: in the beginning and some great expectations
Metropolis, N.
1985-01-01
The central theme will be on the historical setting and origins of the Monte Carlo Method. The scene was post-war Los Alamos Scientific Laboratory. There was an inevitability about the Monte Carlo Event: the ENIAC had recently enjoyed its meteoric rise (on a classified Los Alamos problem); Stan Ulam had returned to Los Alamos; John von Neumann was a frequent visitor. Techniques, algorithms, and applications developed rapidly at Los Alamos. Soon, the fascination of the Method reached wider horizons. The first paper was submitted for publication in the spring of 1949. In the summer of 1949, the first open conference was held at the University of California at Los Angeles. Of some interst perhaps is an account of Fermi's earlier, independent application in neutron moderation studies while at the University of Rome. The quantum leap expected with the advent of massively parallel processors will provide stimuli for very ambitious applications of the Monte Carlo Method in disciplines ranging from field theories to cosmology, including more realistic models in the neurosciences. A structure of multi-instruction sets for parallel processing is ideally suited for the Monte Carlo approach. One may even hope for a modest hardening of the soft sciences.
On a full Monte Carlo approach to quantum mechanics
Sellier, J. M.; Dimov, I.
2016-12-01
The Monte Carlo approach to numerical problems has shown to be remarkably efficient in performing very large computational tasks since it is an embarrassingly parallel technique. Additionally, Monte Carlo methods are well known to keep performance and accuracy with the increase of dimensionality of a given problem, a rather counterintuitive peculiarity not shared by any known deterministic method. Motivated by these very peculiar and desirable computational features, in this work we depict a full Monte Carlo approach to the problem of simulating single- and many-body quantum systems by means of signed particles. In particular we introduce a stochastic technique, based on the strategy known as importance sampling, for the computation of the Wigner kernel which, so far, has represented the main bottleneck of this method (it is equivalent to the calculation of a multi-dimensional integral, a problem in which complexity is known to grow exponentially with the dimensions of the problem). The introduction of this stochastic technique for the kernel is twofold: firstly it reduces the complexity of a quantum many-body simulation from non-linear to linear, secondly it introduces an embarassingly parallel approach to this very demanding problem. To conclude, we perform concise but indicative numerical experiments which clearly illustrate how a full Monte Carlo approach to many-body quantum systems is not only possible but also advantageous. This paves the way towards practical time-dependent, first-principle simulations of relatively large quantum systems by means of affordable computational resources.
Dynamic Monte Carlo simulation of chain growth polymerization and its concentration effect
LüWenqi
2005-01-01
Simul., 2000, 9: 188-195.[12]Xu, G., Ding, J., Yang, Y., Monte Carlo simulation of self-avoid- ing lattice chains subject to simple shear flow, 1. Model and simulation algorithm, J. Chem. Phys., 1997, 107(10): 4070-4084.[13]Xu, G., Ding, J., Yang, Y., Anisotropic and enhanced self-diffusion of a macromolecular chain under simple shear flow as revealed by Monte Carlo simulation on lattices, Macromol. Theory Simul., 1998, 7: 129-140.[14]Chen, Y., Zhang, Q., Ding, J., A coarse-grained model and associ- ated lattice Monte Carlo simulation of coil-helix transition of a homopolypeptide, J. Chem. Phys., 2004, 120(7): 3467-3474.[15]Yang, Y., Zhang, H., Monte Carlo Method in Polymer Science (in Chinese), Shanghai: Fudan Univ. Press, 1993, 65-75, 266-269.[16]de Gennes, P. G., Scaling Concepts in Polymer Physics, New York, Ithaca: Cornell Univ. Press, 1979, Chapter 2.[17]Carmesin, I., Kremer, K., The bond fluctuation method: A new effective algorithm for the dynamics of polymers in all spatial dimensions, Macromolecules, 1988, 21: 2819-2823.[18]Paul, W., Binder, K., Heermann, D. et al., Dynamics of polymer solutions and melts, Reptation predictions and scaling of relaxation times, J. Chem. Phys., 1991, 95: 7726-7740.[19]Flory, P. J., Principles of Polymer Chemistry, New York, Ithaca: Cornell Univ. Press, 1953, 317-345.[20]Xu, G., Ding, J., Yang, Y., Static scaling law of two-dimensional macromolecular chains with excluded volume, J. Fudan Univ., Natural Sci. (in Chinese), 1997, 36(4): 361-369.
Quantum Monte Carlo for electronic structure: Recent developments and applications
Rodriquez, Maria Milagos Soto [Lawrence Berkeley Lab. and Univ. of California, Berkeley, CA (United States). Dept. of Chemistry
1995-04-01
Quantum Monte Carlo (QMC) methods have been found to give excellent results when applied to chemical systems. The main goal of the present work is to use QMC to perform electronic structure calculations. In QMC, a Monte Carlo simulation is used to solve the Schroedinger equation, taking advantage of its analogy to a classical diffusion process with branching. In the present work the author focuses on how to extend the usefulness of QMC to more meaningful molecular systems. This study is aimed at questions concerning polyatomic and large atomic number systems. The accuracy of the solution obtained is determined by the accuracy of the trial wave function`s nodal structure. Efforts in the group have given great emphasis to finding optimized wave functions for the QMC calculations. Little work had been done by systematically looking at a family of systems to see how the best wave functions evolve with system size. In this work the author presents a study of trial wave functions for C, CH, C_{2}H and C_{2}H_{2}. The goal is to study how to build wave functions for larger systems by accumulating knowledge from the wave functions of its fragments as well as gaining some knowledge on the usefulness of multi-reference wave functions. In a MC calculation of a heavy atom, for reasonable time steps most moves for core electrons are rejected. For this reason true equilibration is rarely achieved. A method proposed by Batrouni and Reynolds modifies the way the simulation is performed without altering the final steady-state solution. It introduces an acceleration matrix chosen so that all coordinates (i.e., of core and valence electrons) propagate at comparable speeds. A study of the results obtained using their proposed matrix suggests that it may not be the optimum choice. In this work the author has found that the desired mixing of coordinates between core and valence electrons is not achieved when using this matrix. A bibliography of 175 references is
Development of ray tracing visualization program by Monte Carlo method
Higuchi, Kenji; Otani, Takayuki [Japan Atomic Energy Research Inst., Tokyo (Japan); Hasegawa, Yukihiro
1997-09-01
Ray tracing algorithm is a powerful method to synthesize three dimensional computer graphics. In conventional ray tracing algorithms, a view point is used as a starting point of ray tracing, from which the rays are tracked up to the light sources through center points of pixels on the view screen to calculate the intensities of the pixels. This manner, however, makes it difficult to define the configuration of light source as well as to strictly simulate the reflections of the rays. To resolve these problems, we have developed a new ray tracing means which traces rays from a light source, not from a view point, with use of Monte Carlo method which is widely applied in nuclear fields. Moreover, we adopt the variance reduction techniques to the program with use of the specialized machine (Monte-4) for particle transport Monte Carlo so that the computational time could be successfully reduced. (author)
Development of ray tracing visualization program by Monte Carlo method
Higuchi, Kenji; Otani, Takayuki [Japan Atomic Energy Research Inst., Tokyo (Japan); Hasegawa, Yukihiro
1997-09-01
Ray tracing algorithm is a powerful method to synthesize three dimensional computer graphics. In conventional ray tracing algorithms, a view point is used as a starting point of ray tracing, from which the rays are tracked up to the light sources through center points of pixels on the view screen to calculate the intensities of the pixels. This manner, however, makes it difficult to define the configuration of light source as well as to strictly simulate the reflections of the rays. To resolve these problems, we have developed a new ray tracing means which traces rays from a light source, not from a view point, with use of Monte Carlo method which is widely applied in nuclear fields. Moreover, we adopt the variance reduction techniques to the program with use of the specialized machine (Monte-4) for particle transport Monte Carlo so that the computational time could be successfully reduced. (author)
Direct aperture optimization for IMRT using Monte Carlo generated beamlets.
Bergman, Alanah M; Bush, Karl; Milette, Marie-Pierre; Popescu, I Antoniu; Otto, Karl; Duzenli, Cheryl
2006-10-01
This work introduces an EGSnrc-based Monte Carlo (MC) beamlet does distribution matrix into a direct aperture optimization (DAO) algorithm for IMRT inverse planning. The technique is referred to as Monte Carlo-direct aperture optimization (MC-DAO). The goal is to assess if the combination of accurate Monte Carlo tissue inhomogeneity modeling and DAO inverse planning will improve the dose accuracy and treatment efficiency for treatment planning. Several authors have shown that the presence of small fields and/or inhomogeneous materials in IMRT treatment fields can cause dose calculation errors for algorithms that are unable to accurately model electronic disequilibrium. This issue may also affect the IMRT optimization process because the dose calculation algorithm may not properly model difficult geometries such as targets close to low-density regions (lung, air etc.). A clinical linear accelerator head is simulated using BEAMnrc (NRC, Canada). A novel in-house algorithm subdivides the resulting phase space into 2.5 X 5.0 mm2 beamlets. Each beamlet is projected onto a patient-specific phantom. The beamlet dose contribution to each voxel in a structure-of-interest is calculated using DOSXYZnrc. The multileaf collimator (MLC) leaf positions are linked to the location of the beamlet does distributions. The MLC shapes are optimized using direct aperture optimization (DAO). A final Monte Carlo calculation with MLC modeling is used to compute the final dose distribution. Monte Carlo simulation can generate accurate beamlet dose distributions for traditionally difficult-to-calculate geometries, particularly for small fields crossing regions of tissue inhomogeneity. The introduction of DAO results in an additional improvement by increasing the treatment delivery efficiency. For the examples presented in this paper the reduction in the total number of monitor units to deliver is approximately 33% compared to fluence-based optimization methods.
Global Monte Carlo Simulation with High Order Polynomial Expansions
William R. Martin; James Paul Holloway; Kaushik Banerjee; Jesse Cheatham; Jeremy Conlin
2007-12-13
The functional expansion technique (FET) was recently developed for Monte Carlo simulation. The basic idea of the FET is to expand a Monte Carlo tally in terms of a high order expansion, the coefficients of which can be estimated via the usual random walk process in a conventional Monte Carlo code. If the expansion basis is chosen carefully, the lowest order coefficient is simply the conventional histogram tally, corresponding to a flat mode. This research project studied the applicability of using the FET to estimate the fission source, from which fission sites can be sampled for the next generation. The idea is that individual fission sites contribute to expansion modes that may span the geometry being considered, possibly increasing the communication across a loosely coupled system and thereby improving convergence over the conventional fission bank approach used in most production Monte Carlo codes. The project examined a number of basis functions, including global Legendre polynomials as well as “local” piecewise polynomials such as finite element hat functions and higher order versions. The global FET showed an improvement in convergence over the conventional fission bank approach. The local FET methods showed some advantages versus global polynomials in handling geometries with discontinuous material properties. The conventional finite element hat functions had the disadvantage that the expansion coefficients could not be estimated directly but had to be obtained by solving a linear system whose matrix elements were estimated. An alternative fission matrix-based response matrix algorithm was formulated. Studies were made of two alternative applications of the FET, one based on the kernel density estimator and one based on Arnoldi’s method of minimized iterations. Preliminary results for both methods indicate improvements in fission source convergence. These developments indicate that the FET has promise for speeding up Monte Carlo fission source
Multiple-time-stepping generalized hybrid Monte Carlo methods
Escribano, Bruno, E-mail: bescribano@bcamath.org [BCAM—Basque Center for Applied Mathematics, E-48009 Bilbao (Spain); Akhmatskaya, Elena [BCAM—Basque Center for Applied Mathematics, E-48009 Bilbao (Spain); IKERBASQUE, Basque Foundation for Science, E-48013 Bilbao (Spain); Reich, Sebastian [Universität Potsdam, Institut für Mathematik, D-14469 Potsdam (Germany); Azpiroz, Jon M. [Kimika Fakultatea, Euskal Herriko Unibertsitatea (UPV/EHU) and Donostia International Physics Center (DIPC), P.K. 1072, Donostia (Spain)
2015-01-01
Performance of the generalized shadow hybrid Monte Carlo (GSHMC) method [1], which proved to be superior in sampling efficiency over its predecessors [2–4], molecular dynamics and hybrid Monte Carlo, can be further improved by combining it with multi-time-stepping (MTS) and mollification of slow forces. We demonstrate that the comparatively simple modifications of the method not only lead to better performance of GSHMC itself but also allow for beating the best performed methods, which use the similar force splitting schemes. In addition we show that the same ideas can be successfully applied to the conventional generalized hybrid Monte Carlo method (GHMC). The resulting methods, MTS-GHMC and MTS-GSHMC, provide accurate reproduction of thermodynamic and dynamical properties, exact temperature control during simulation and computational robustness and efficiency. MTS-GHMC uses a generalized momentum update to achieve weak stochastic stabilization to the molecular dynamics (MD) integrator. MTS-GSHMC adds the use of a shadow (modified) Hamiltonian to filter the MD trajectories in the HMC scheme. We introduce a new shadow Hamiltonian formulation adapted to force-splitting methods. The use of such Hamiltonians improves the acceptance rate of trajectories and has a strong impact on the sampling efficiency of the method. Both methods were implemented in the open-source MD package ProtoMol and were tested on a water and a protein systems. Results were compared to those obtained using a Langevin Molly (LM) method [5] on the same systems. The test results demonstrate the superiority of the new methods over LM in terms of stability, accuracy and sampling efficiency. This suggests that putting the MTS approach in the framework of hybrid Monte Carlo and using the natural stochasticity offered by the generalized hybrid Monte Carlo lead to improving stability of MTS and allow for achieving larger step sizes in the simulation of complex systems.
Monte Carlo Simulation Program from the World Petroleum Assessment 2000, DDS-60 (Emc2.xls)
U.S. Geological Survey, Department of the Interior — Monte Carlo programs described in chapter MC, Monte Carlo Simulation Method. Emc2.xls was the program used to calculate the estimates of undiscovered resources for...
Mont Carlo Simulation Program from the World Petroleum Assessment 2000, DDS-60 (emcee.xls).xml
U.S. Geological Survey, Department of the Interior — Monte Carlo programs described in chapter MC, Monte Carlo Simulation Method. Emc2.xls was the program used to calculate the estimates of undiscovered resources for...
Monte Carlo Simulation Program from the World Petroleum Assessment 2000, DDS-60 (Emc2.xls).
U.S. Geological Survey, Department of the Interior — Monte Carlo programs described in chapter MC, Monte Carlo Simulation Method. Emc2.xls was the program used to calculate the estimates of undiscovered resources for...
Mont Carlo Simulation Program from the World Petroleum Assessment 2000, DDS-60 (emcee.xls)
U.S. Geological Survey, Department of the Interior — Monte Carlo programs described in chapter MC, Monte Carlo Simulation Method. Emc2.xls was the program used to calculate the estimates of undiscovered resources for...
Monte Carlo simulations of single and coupled synthetic molecular motors.
Chen, C-M; Zuckermann, M
2012-11-01
We use a minimal model to study the processive motion of coupled synthetic molecular motors along a DNA track and we present data from Monte Carlo (MC) computer simulations based on this model. The model was originally proposed by Bromley et al. [HFSP J. 3, 204 (2009)] for studying the properties of a synthetic protein motor, the "Tumbleweed" (TW), and involves rigid Y-shaped motors diffusively rotating along the track while controlled by a series of periodically injected ligand pulses into the solution. The advantage of the model is that it mimics the mechanical properties of the TW motor in detail. Both the average first passage time which measures the diffusive motion of the motors, and the average dwell time on the track which measures their processivity are investigated by varying the parameters of the model. The latter includes ligand concentration and the range and strength of the binding interaction between motors and the track. In particular, it is of experimental interest to study the dependence of these dynamic time scales of the motors on the ligand concentration. Single rigid TW motors were first studied since no previous MC simulations of these motors have been performed. We first studied single motors for which we found a logarithmic decrease of the average first passage time and a logarithmic increase of the average dwell time with increasing ligand concentration. For two coupled motors, the dependence on ligand concentration is still logarithmic for the average first passage time but becomes linear for the average dwell time. This suggests a much greater stability in the processive motion of coupled motors as compared to single motors in the limit of large ligand concentration. By increasing the number of coupled motors, m, it was found that the average first passage time of the coupled motors only increases slowly with m while the average dwell time increases exponentially with m. Thus the stability of coupled motors on the track can be
Deposition at glancing angle, surface roughness, and protein adsorption: Monte Carlo simulations.
Zhdanov, Vladimir P; Rechendorff, Kristian; Hovgaard, Mads B; Besenbacher, Flemming
2008-06-19
To generate rough surfaces in Monte Carlo simulations, we use the 2 + 1 solid-on-solid model of deposition with rapid transient diffusion of newly arrived atoms supplied at glancing angle. The surfaces generated are employed to scrutinize the effect of surface roughness on adsorption of globular and anisotropic rodlike proteins. The obtained results are compared with the available experimental data for Ta deposition at glancing angle and for the bovine serum albumin and fibrinogen uptake on the corresponding Ta films.
Kinetic Monte Carlo simulation of physical vapor deposition of thin Cu film
WANG Jun; CHEN Chang-qi; ZHU Wu
2004-01-01
A two-dimensional Kinetic Monte Carlo method has been developed for simulating the physical vapor deposition of thin Cu films on Cu substrate. An improved embedded atom method was used to calculate the interatomic potential and determine the diffusion barrier energy and residence time. Parameters, including incident angle,deposition rate and substrate temperature, were investigated and discussed in order to find their influences on the thin film morphology.
Goldman, Saul
1983-10-01
A method we call energy-scaled displacement Monte Carlo (ESDMC) whose purpose is to improve sampling efficiency and thereby speed up convergence rates in Monte Carlo calculations is presented. The method involves scaling the maximum displacement a particle may make on a trial move to the particle's configurational energy. The scaling is such that on the average, the most stable particles make the smallest moves and the most energetic particles the largest moves. The method is compared to Metropolis Monte Carlo (MMC) and Force Bias Monte Carlo of (FBMC) by applying all three methods to a dense Lennard-Jones fluid at two temperatures, and to hot ST2 water. The functions monitored as the Markov chains developed were, for the Lennard-Jones case: melting, radial distribution functions, internal energies, and heat capacities. For hot ST2 water, we monitored energies and heat capacities. The results suggest that ESDMC samples configuration space more efficiently than either MMC or FBMC in these systems for the biasing parameters used here. The benefit from using ESDMC seemed greatest for the Lennard-Jones systems.
Both, J.P.; Lee, Y.K.; Mazzolo, A.; Peneliau, Y.; Petit, O.; Roesslinger, B. [CEA Saclay, Dir. de l' Energie Nucleaire (DEN), Service d' Etudes de Reacteurs et de Modelisation Avancee, 91 - Gif sur Yvette (France)
2003-07-01
Tripoli-4 is a three dimensional calculations code using the Monte Carlo method to simulate the transport of neutrons, photons, electrons and positrons. This code is used in four application fields: the protection studies, the criticality studies, the core studies and the instrumentation studies. Geometry, cross sections, description of sources, principle. (N.C.)
Uniform distribution and quasi-Monte Carlo methods discrepancy, integration and applications
Kritzer, Peter; Pillichshammer, Friedrich; Winterhof, Arne
2014-01-01
The survey articles in this book focus on number theoretic point constructions, uniform distribution theory, and quasi-Monte Carlo methods. As deterministic versions of the Monte Carlo method, quasi-Monte Carlo rules enjoy increasing popularity, with many fruitful applications in mathematical practice, as for example in finance, computer graphics, and biology.
The impact of Monte Carlo simulation: a scientometric analysis of scholarly literature
Pia, Maria Grazia; Bell, Zane W; Dressendorfer, Paul V
2010-01-01
A scientometric analysis of Monte Carlo simulation and Monte Carlo codes has been performed over a set of representative scholarly journals related to radiation physics. The results of this study are reported and discussed. They document and quantitatively appraise the role of Monte Carlo methods and codes in scientific research and engineering applications.
Fast orthogonal transforms for multi-level quasi-Monte Carlo integration
Irrgeher, Christian; Leobacher, Gunther
2015-01-01
We combine a generic method for finding fast orthogonal transforms for a given quasi-Monte Carlo integration problem with the multilevel Monte Carlo method. It is shown by example that this combined method can vastly improve the efficiency of quasi-Monte Carlo.
Martin, E.; Gschwind, R.; Henriet, J.; Sauget, M.; Makovicka, L. [IRMA/Enisys/FEMTO-ST, Pole universitaire des Portes du Jura, place Tharradin, BP 71427, 2521 1 - Montbeliard cedex (France)
2010-07-01
In order to reduce the computing time needed by Monte Carlo codes in the field of irradiation physics, notably in dosimetry, the authors report the use of artificial neural networks in combination with preliminary Monte Carlo calculations. During the learning phase, Monte Carlo calculations are performed in homogeneous media to allow the building up of the neural network. Then, dosimetric calculations (in heterogeneous media, unknown by the network) can be performed by the so-learned network. Results with an equivalent precision can be obtained within less than one minute on a simple PC whereas several days are needed with a Monte Carlo calculation
Synchrotron stereotactic radiotherapy: dosimetry by Fricke gel and Monte Carlo simulations.
Boudou, Caroline; Biston, Marie-Claude; Corde, Stéphanie; Adam, Jean-François; Ferrero, Claudio; Estève, François; Elleaume, Hélène
2004-11-21
Synchrotron stereotactic radiotherapy (SSR) consists in loading the tumour with a high atomic number element (Z), and exposing it to monochromatic x-rays from a synchrotron source (50-100 keV), in stereotactic conditions. The dose distribution results from both the stereotactic monochromatic x-ray irradiation and the presence of the high Z element. The purpose of this preliminary study was to evaluate the two-dimensional dose distribution resulting solely from the irradiation geometry, using Monte Carlo simulations and a Fricke gel dosimeter. The verification of a Monte Carlo-based dosimetry was first assessed by depth dose measurements in a water tank. We thereafter used a Fricke dosimeter to compare Monte Carlo simulations with dose measurements. The Fricke dosimeter is a solution containing ferrous ions which are oxidized to ferric ions under ionizing radiation, proportionally to the absorbed dose. A cylindrical phantom filled with Fricke gel was irradiated in stereotactic conditions over several slices with a continuous beam (beam section = 0.1 x 1 cm2). The phantom and calibration vessels were then imaged by nuclear magnetic resonance. The measured doses were fairly consistent with those predicted by Monte Carlo simulations. However, the measured maximum absolute dose was 10% underestimated regarding calculation. The loss of information in the higher region of dose is explained by the diffusion of ferric ions. Monte Carlo simulation is the most accurate tool for dosimetry including complex geometries made of heterogeneous materials. Although the technique requires improvements, gel dosimetry remains an essential tool for the experimental verification of dose distribution in SSR with millimetre precision.
JEWEL - a Monte Carlo Model for Jet Quenching
Zapp, Korinna; Wiedemann, Urs Achim
2009-01-01
The Monte Carlo model JEWEL 1.0 (Jet Evolution With Energy Loss) simulates parton shower evolution in the presence of a dense QCD medium. In its current form medium interactions are modelled as elastic scattering based on perturbative matrix elements and a simple prescription for medium induced gluon radiation. The parton shower is interfaced with a hadronisation model. In the absence of medium effects JEWEL is shown to reproduce jet measurements at LEP. The collisional energy loss is consistent with analytic calculations, but with JEWEL we can go a step further and characterise also jet-induced modifications of the medium. Elastic and inelastic medium interactions are shown to lead to distinctive modifications of the jet fragmentation pattern, which should allow to experimentally distinguish between collisional and radiative energy loss mechanisms. In these proceedings the main JEWEL results are summarised and a Monte Carlo algorithm is outlined that allows to include the Landau-Pomerantschuk-Migdal effect i...
Research on GPU Acceleration for Monte Carlo Criticality Calculation
Xu, Qi; Yu, Ganglin; Wang, Kan
2014-06-01
The Monte Carlo neutron transport method can be naturally parallelized by multi-core architectures due to the dependency between particles during the simulation. The GPU+CPU heterogeneous parallel mode has become an increasingly popular way of parallelism in the field of scientific supercomputing. Thus, this work focuses on the GPU acceleration method for the Monte Carlo criticality simulation, as well as the computational efficiency that GPUs can bring. The "neutron transport step" is introduced to increase the GPU thread occupancy. In order to test the sensitivity of the MC code's complexity, a 1D one-group code and a 3D multi-group general purpose code are respectively transplanted to GPUs, and the acceleration effects are compared. The result of numerical experiments shows considerable acceleration effect of the "neutron transport step" strategy. However, the performance comparison between the 1D code and the 3D code indicates the poor scalability of MC codes on GPUs.
Applying polynomial filtering to mass preconditioned Hybrid Monte Carlo
Haar, Taylor; Zanotti, James; Nakamura, Yoshifumi
2016-01-01
The use of mass preconditioning or Hasenbusch filtering in modern Hybrid Monte Carlo simulations is common. At light quark masses, multiple filters (three or more) are typically used to reduce the cost of generating dynamical gauge fields; however, the task of tuning a large number of Hasenbusch mass terms is non-trivial. The use of short polynomial approximations to the inverse has been shown to provide an effective UV filter for HMC simulations. In this work we investigate the application of polynomial filtering to the mass preconditioned Hybrid Monte Carlo algorithm as a means of introducing many time scales into the molecular dynamics integration with a simplified parameter tuning process. A generalized multi-scale integration scheme that permits arbitrary step- sizes and can be applied to Omelyan-style integrators is also introduced. We find that polynomial-filtered mass-preconditioning (PF-MP) performs as well as or better than standard mass preconditioning, with significantly less fine tuning required.
Monte Carlo uncertainty analyses for integral beryllium experiments
Fischer, U; Tsige-Tamirat, H
2000-01-01
The novel Monte Carlo technique for calculating point detector sensitivities has been applied to two representative beryllium transmission experiments with the objective to investigate the sensitivity of important responses such as the neutron multiplication and to assess the related uncertainties due to the underlying cross-section data uncertainties. As an important result, it has been revealed that the neutron multiplication power of beryllium can be predicted with good accuracy using state-of-the-art nuclear data evaluations. Severe discrepancies do exist for the spectral neutron flux distribution that would transmit into significant uncertainties of the calculated neutron spectra and of the nuclear blanket performance in blanket design calculations. With regard to this, it is suggested to re-analyse the secondary energy and angle distribution data of beryllium by means of Monte Carlo based sensitivity and uncertainty calculations. Related code development work is underway.
A Monte Carlo algorithm for simulating fermions on Lefschetz thimbles
Alexandru, Andrei; Bedaque, Paulo
2016-01-01
A possible solution of the notorious sign problem preventing direct Monte Carlo calculations for systems with non-zero chemical potential is to deform the integration region in the complex plane to a Lefschetz thimble. We investigate this approach for a simple fermionic model. We introduce an easy to implement Monte Carlo algorithm to sample the dominant thimble. Our algorithm relies only on the integration of the gradient flow in the numerically stable direction, which gives it a distinct advantage over the other proposed algorithms. We demonstrate the stability and efficiency of the algorithm by applying it to an exactly solvable fermionic model and compare our results with the analytical ones. We report a very good agreement for a certain region in the parameter space where the dominant contribution comes from a single thimble, including a region where standard methods suffer from a severe sign problem. However, we find that there are also regions in the parameter space where the contribution from multiple...
Monte Carlo Euler approximations of HJM term structure financial models
Björk, Tomas
2012-11-22
We present Monte Carlo-Euler methods for a weak approximation problem related to the Heath-Jarrow-Morton (HJM) term structure model, based on Itô stochastic differential equations in infinite dimensional spaces, and prove strong and weak error convergence estimates. The weak error estimates are based on stochastic flows and discrete dual backward problems, and they can be used to identify different error contributions arising from time and maturity discretization as well as the classical statistical error due to finite sampling. Explicit formulas for efficient computation of sharp error approximation are included. Due to the structure of the HJM models considered here, the computational effort devoted to the error estimates is low compared to the work to compute Monte Carlo solutions to the HJM model. Numerical examples with known exact solution are included in order to show the behavior of the estimates. © 2012 Springer Science+Business Media Dordrecht.