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In the context of Bayesian inversion for scientific and engineering modeling, Markov chain Monte Carlo sampling strategies are the benchmark due to their flexibility and robustness in dealing with arbitrary posterior probability density…

Computation · Statistics 2021-12-07 Han Lu , Mohammad Khalil , Thomas Catanach , Jiefu Chen , Xuqing Wu , Xin Fu , Cosmin Safta , Yueqin Huang

Auxiliary Field Quantum Monte Carlo (AFQMC) has emerged as a powerful framework for treating strongly correlated electronic systems, offering a favorable balance between computational cost and accuracy. In this paper, we present a novel…

Chemical Physics · Physics 2026-04-03 Maxine Luo , Victor Chen , Yu Wang , Christian B. Mendl

We develop a Monte Carlo framework to analyze the statistics of quantum work in correlated electron systems. Using the Ising-Kondo model in heavy fermions as a paradigmatic platform, we thoroughly illustrate the process of determining the…

Statistical Mechanics · Physics 2025-05-23 Qian-Xi Zhao , Jian-Jun Dong , Zi-Xiang Hu

The auxiliary-field quantum Monte Carlo (AFQMC) method provides a computational framework for solving the time-independent Schroedinger equation in atoms, molecules, solids, and a variety of model systems. AFQMC has recently witnessed…

Computational Physics · Physics 2018-08-14 Mario Motta , Shiwei Zhang

We extend the recently introduced phaseless auxiliary-field quantum Monte Carlo (QMC) approach to any single-particle basis, and apply it to molecular systems with Gaussian basis sets. QMC methods in general scale favorably with system…

Computational Physics · Physics 2007-05-23 W. A. Al-Saidi , Shiwei Zhang , Henry Krakauer

The recently developed density matrix quantum Monte Carlo (DMQMC) algorithm stochastically samples the N -body thermal density matrix and hence provides access to exact properties of many-particle quantum systems at arbitrary temperatures.…

Strongly Correlated Electrons · Physics 2015-10-15 Fionn D. Malone , N. S. Blunt , James J. Shepherd , D. K. K. Lee , J. S. Spencer , W. M. C. Foulkes

We describe an open-source implementation of the continuous-time hybridization-expansion quantum Monte Carlo method for impurity models with general instantaneous two-body interactions and complex hybridization functions. The code is built…

Strongly Correlated Electrons · Physics 2017-05-02 Hiroshi Shinaoka , Emanuel Gull , Philipp Werner

The density matrix quantum Monte Carlo (DMQMC) set of methods stochastically samples the exact $N$-body density matrix for interacting electrons at finite temperature. We introduce a simple modification to the interaction picture DMQMC…

Chemical Physics · Physics 2022-05-25 William Van Benschoten , James J. Shepherd

The generalized quantum master equation provides a powerful tool to describe the dynamics in quantum impurity models driven away from equilibrium. Two complementary approaches, one based on Nakajima--Zwanzig--Mori time-convolution (TC) and…

Mesoscale and Nanoscale Physics · Physics 2016-01-20 Lyran Kidon , Eli Y. Wilner , Eran Rabani

A novel scheme to solve the quantum eigenvalue problem through the imaginary-time Green function Monte Carlo method is presented. This method is applicable to the excited states as well as to the ground state of a generic system. We…

Nuclear Theory · Physics 2008-11-26 Taksu Cheon

We review recent advances in the capabilities of the open source ab initio Quantum Monte Carlo (QMC) package QMCPACK and the workflow tool Nexus used for greater efficiency and reproducibility. The auxiliary field QMC (AFQMC) implementation…

We develop a diagrammatic Monte Carlo method for the real-time dynamics of dissipative quantum impurity models. These are small open quantum systems with interaction and local Markovian dissipation, coupled to a large quantum bath. Our…

Strongly Correlated Electrons · Physics 2024-03-26 Matthieu Vanhoecke , Marco Schirò

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…

Computational Physics · Physics 2011-01-28 Jindrich Kolorenc , Lubos Mitas

Computer modeling of multicellular systems has been a valuable tool for interpreting and guiding in vitro experiments relevant to embryonic morphogenesis, tumor growth, angiogenesis and, lately, structure formation following the printing of…

Biological Physics · Physics 2015-05-28 Elijah Flenner , Lorant Janosi , Bogdan Barz , Adrian Neagu , Gabor Forgacs , Ioan Kosztin

Computational methods both open the frontiers of economic analysis and serve as a bottleneck in what can be achieved. We are the first to study whether Quantum Monte Carlo (QMC) algorithm can improve the runtime of economic applications and…

Quantum Physics · Physics 2024-09-24 Vladimir Skavysh , Sofia Priazhkina , Diego Guala , Thomas R. Bromley

Because of their robustness, efficiency and non-intrusiveness, Monte Carlo methods are probably the most popular approach in uncertainty quantification to computing expected values of quantities of interest (QoIs). Multilevel Monte Carlo…

Numerical Analysis · Mathematics 2022-04-12 Marcus J. Grote , Simon Michel , Fabio Nobile

Variational Monte Carlo and Green's function Monte Carlo are powerful tools for calculations of properties of light nuclei using realistic two-nucleon and three-nucleon potentials. Recently the GFMC method has been extended to multiple…

Nuclear Theory · Physics 2009-11-10 Steven C. Pieper

We generalize the recently developed diagrammatic Monte Carlo techniques for quantum impurity models from an imaginary time to a Keldysh formalism suitable for real-time and nonequilibrium calculations. Both weak-coupling and…

Mesoscale and Nanoscale Physics · Physics 2009-11-13 Philipp Werner , Takashi Oka , Andrew J. Millis

On the base of Diffusion Monte-Carlo method it is developed a new Complex Diffusion Monte-Carlo (CDMC) method allowing to simulate the quantum systems with complex wave function. There are no approximations on the calculation of modulus and…

Condensed Matter · Physics 2007-05-23 B. Abdullaev , M. Musakhanov , A. Nakamura

We present a Metropolis-Hastings Markov chain Monte Carlo (MCMC) algorithm for detecting hidden variables in a continuous time Bayesian network (CTBN), which uses reversible jumps in the sense defined by (Green 1995). In common with several…

Methodology · Statistics 2014-03-18 Blazej Miasojedow , Wojciech Niemiro , John Noble , Krzysztof Opalski
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