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We describe a path-integral ground-state quantum Monte Carlo method for light nuclei in continuous space. We show how to efficiently update and sample the paths with spin-isospin dependent and spin-orbit interactions. We apply the method to…

Nuclear Theory · Physics 2022-10-28 Rong Chen , Kevin E. Schmidt

We describe a novel simulation method that eliminates the slowing-down problem in the Monte Carlo simulations of imaginary-time path integrals near the continuum limit. This method combines a stochastic blocking procedure with the multigrid…

Statistical Mechanics · Physics 2007-05-23 C. H. Mak , Sergei Zakharov

We present a new, biased Monte Carlo scheme for simulating complex, cyclic peptides. Backbone atoms are equilibrated with a biased rebridging scheme, and side-chain atoms are equilibrated with a look-ahead configurational bias Monte Carlo.…

Biological Physics · Physics 2009-10-31 Minghong G. Wu , Michael W. Deem

Computer simulation with Monte Carlo is an important tool to investigate the function and equilibrium properties of many systems with biological and soft matter materials solvable in solvents. The appropriate treatment of long-range…

Computational Physics · Physics 2015-06-15 Zecheng Gan , Zhenli Xu

Monte Carlo techniques have played an important role in understanding strongly-correlated systems across many areas of physics, covering a wide range of energy and length scales. Among the many Monte Carlo methods applicable to quantum…

Quantum Gases · Physics 2017-11-22 Yangqian Yan , D. Blume

Accurate quantum Monte Carlo calculations of ground and low-lying excited states of light p-shell nuclei are now possible for realistic nuclear Hamiltonians that fit nucleon-nucleon scattering data. At present, results for more than 30…

Nuclear Theory · Physics 2008-11-26 Steven C. Pieper , R. B. Wiringa

Estimating the eigenvalue or energy gap of a Hamiltonian H is vital for studying quantum many-body systems. Particularly, many of the problems in quantum chemistry, condensed matter physics, and nuclear physics investigate the energy gap…

Quantum Physics · Physics 2023-05-22 Yongdan Yang , Ying Li , Xiaosi Xu , Xiao Yuan

We describe collective-move Monte Carlo algorithms designed to approximate the overdamped dynamics of self-assembling nanoscale components equipped with strong, short-ranged and anisotropic interactions. Conventional Monte Carlo simulations…

Statistical Mechanics · Physics 2012-04-16 Stephen Whitelam

We perform a thorough analysis on the choice of estimators for random series path integral methods. In particular, we show that both the thermodynamic (T-method) and the direct (H-method) energy estimators have finite variances and are…

Statistical Mechanics · Physics 2009-11-10 Cristian Predescu , Dubravko Sabo , J. D. Doll , David L. Freeman

Competing phases or interactions in complex many-particle systems can result in free energy barriers that strongly suppress thermal equilibration. Here we discuss how extended ensemble Monte Carlo simulations can be used to study the…

Statistical Mechanics · Physics 2007-05-23 S. Trebst , D. A. Huse , E. Gull , H. G. Katzgraber , U. H. E. Hansmann , M. Troyer

We carry out highly accurate \emph{ab initio} path integral Monte Carlo (PIMC) simulations to directly estimate the free energy of various warm dense matter systems including the uniform electron gas and hydrogen without any nodal…

Quantum Gases · Physics 2024-07-02 Tobias Dornheim , Zhandos Moldabekov , Sebastian Schwalbe , Jan Vorberger

We consider several multiscale-in-time kinetic Monte Carlo models, in which some variables evolve on a fast time scale, while the others evolve on a slow time scale. In the first two models we consider, a particle evolves in a…

Probability · Mathematics 2015-06-12 Salma Lahbabi , Frederic Legoll

We review quantum Monte Carlo methods for dealing with large shell model problems. These methods reduce the imaginary-time many-body evolution operator to a coherent superposition of one-body evolutions in fluctuating one-body fields; the…

Nuclear Theory · Physics 2009-10-30 S. E. Koonin , D. J. Dean , K. Langanke

Quantum many-body systems are characterized by patterns of correlations that define highly-non trivial manifolds when interpreted as data structures. Physical properties of phases and phase transitions are typically retrieved via simple…

Statistical Mechanics · Physics 2021-09-01 Tiago Mendes-Santos , Adriano Angelone , Alex Rodriguez , Rosario Fazio , Marcello Dalmonte

We calculate the hydrogen Hugoniot using ab initio path integral Monte Carlo. We introduce an efficient finite-temperature fixed-node approximation for handling fermions, which includes an optimized mixture of free particle states and…

Materials Science · Physics 2011-08-09 Saad A. Khairallah , J. Shumway , Erik W. Draeger

The direct integration of the harmonic oscillator path integral obscures the fundamental structure of its discrete, imaginary time propagator (density matrix). This work, by first proving an operator identity for contracting two free…

Computational Physics · Physics 2023-10-31 Siu A. Chin

We present a new Monte Carlo algorithm that produces results of high accuracy with reduced simulational effort. Independent random walks are performed (concurrently or serially) in different, restricted ranges of energy, and the resultant…

Statistical Mechanics · Physics 2009-10-31 Fugao Wang , D. P. Landau

In this paper we discuss the possibility of using multilevel Monte Carlo (MLMC) methods for weak approximation schemes. It turns out that by means of a simple coupling between consecutive time discretisation levels, one can achieve the same…

Computational Finance · Quantitative Finance 2014-10-07 Denis Belomestny , Tigran Nagapetyan

A novel method for simulating the statistical mechanics of molecular systems in which both nuclear and electronic degrees of freedom are treated quantum mechanically is presented. The scheme combines a path integral description of the…

Computational Physics · Physics 2009-10-31 Ruben O. Weht , Jorge Kohanoff , Dario A. Estrin , Charusita Chakravarty

Advanced algorithms are necessary to obtain faster-than-real-time dynamic simulations in a number of different physical problems that are characterized by widely disparate time scales. Recent advanced dynamic Monte Carlo algorithms that…

Materials Science · Physics 2016-11-23 M. A. Novotny
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