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Monte Carlo methods are widely used to estimate observables in many-body quantum systems. However, conventional sampling schemes often require a large number of samples to achieve sufficient accuracy. In this work we propose the…

Quantum Physics · Physics 2026-01-29 Wenxuan Zhang , Dingzu Wang , Dario Poletti

We design an enhanced Event-Chain Monte Carlo algorithm to study 1D quantum dissipative systems, using their bosonized representation. Expressing the bosonized Hamiltonian as a path integral over a scalar field enables the application of…

Strongly Correlated Electrons · Physics 2025-08-21 Oscar Bouverot-Dupuis , Alberto Rosso , Manon Michel

On the base of a Feynman-Kac--type formula involving Poisson stochastic processes, recently a Monte Carlo algorithm has been introduced, which describes exactly the real- or imaginary-time evolution of many-body lattice quantum systems. We…

Other Condensed Matter · Physics 2011-07-19 Massimo Ostilli , Carlo Presilla

Approximate inference in probabilistic graphical models (PGMs) can be grouped into deterministic methods and Monte-Carlo-based methods. The former can often provide accurate and rapid inferences, but are typically associated with biases…

Machine Learning · Statistics 2019-01-09 Fredrik Lindsten , Jouni Helske , Matti Vihola

We present an algorithmic solution to the problem of incremental belief updating in the context of Monte Carlo inference in Bayesian statistical models represented by probabilistic programs. Given a model and a sample-approximated…

Machine Learning · Statistics 2024-02-13 David Tolpin

Monte Carlo simulations are powerful tools for understanding the effects of radiation interactions within detector devices allowing not only to evaluate typical estimates for experimental measurements and to serve as means for designing…

Instrumentation and Detectors · Physics 2016-02-09 F. Marinho , K. Akiba

We incorporate explicit, non-perturbative treatment of spin-orbit coupling into ab initio auxiliary-field quantum Monte Carlo (AFQMC) calculations. The approach allows a general computational framework for molecular and bulk systems in…

Strongly Correlated Electrons · Physics 2023-02-16 Brandon Eskridge , Henry Krakauer , Hao Shi , Shiwei Zhang

This work describes methodologies to successfully implement the Implicit Monte Carlo (IMC) scheme for thermal radiative transfer in reduced-precision floating-point arithmetic. The methods used can be broadly categorized into scaling…

Computational Physics · Physics 2025-10-27 Simon Butson , Mathew Cleveland , Alex Long , Todd Palmer

In the absence of a fermion sign problem, auxiliary field (or determinantal) quantum Monte Carlo (DQMC) approaches have long been the numerical method of choice for unbiased, large-scale simulations of interacting many-fermion systems. More…

Strongly Correlated Electrons · Physics 2016-12-22 Peter Broecker , Simon Trebst

The entanglement entropy probing novel phases and phase transitions numerically via quantum Monte Carlo has made great achievements in large-scale interacting spin/boson systems. In contrast, the numerical exploration in interacting fermion…

Statistical Mechanics · Physics 2025-05-15 Weilun Jiang , Gaopei Pan , Zhe Wang , Bin-Bin Mao , Heng Shen , Zheng Yan

We present SpM, a sparse modeling tool for the analytic continuation of imaginary-time Green's function, licensed under GNU General Public License version 3. In quantum Monte Carlo simulation, dynamic physical quantities such as…

Strongly Correlated Electrons · Physics 2019-10-02 Kazuyoshi Yoshimi , Junya Otsuki , Yuichi Motoyama , Masayuki Ohzeki , Hiroshi Shinaoka

We provide a deepened study of autocorrelations in Neural Markov Chain Monte Carlo (NMCMC) simulations, a version of the traditional Metropolis algorithm which employs neural networks to provide independent proposals. We illustrate our…

Statistical Mechanics · Physics 2023-01-18 Piotr Białas , Piotr Korcyl , Tomasz Stebel

In this paper we introduce an approximate method to solve the quantum cavity equations for transverse field Ising models. The method relies on a projective approximation of the exact cavity distributions of imaginary time trajectories…

Disordered Systems and Neural Networks · Physics 2023-03-29 E. Domínguez , H. J. Kappen

Ising machines (IMs) are specialized devices designed to efficiently solve combinatorial optimization problems (COPs). They consist of artificial spins that evolve towards a low-energy configuration representing a problem's solution. Most…

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

With the advent of generalized unitarity and parametric integration techniques, the construction of a generic Next-to-Leading Order Monte Carlo becomes feasible. Such a generator will entail the treatment of QCD color in the amplitudes. We…

High Energy Physics - Phenomenology · Physics 2014-11-20 Walter Giele , Zoltan Kunszt , Jan Winter

Ising annealer is a promising quantum-inspired computing architecture for combinatorial optimization problems. In this paper, we introduce an Ising annealer based on the Hamiltonian Monte Carlo, which updates the variables of all dimensions…

Quantum Physics · Physics 2025-01-15 Hao Wang , Zixuan Liu , Zhixin Xie , Langyu Li , Zibo Miao , Wei Cui , Yu Pan

In this paper, we solve quantum many-body problem by propagating ensembles of trajectories and guiding waves in physical space. We introduce the 'effective potential' correction within the recently proposed time-dependent quantum Monte…

Quantum Physics · Physics 2025-02-05 Ivan P. Christov

In Monte Carlo integration an accurate and reliable determination of the numerical intregration error is essential. We point out the need for an independent estimate of the error on this error, for which we present an unbiased estimator. In…

Numerical Analysis · Mathematics 2016-10-12 R. Bakx , R. H. P. Kleiss , F. Versteegen

Graphics Processing Units (GPUs) are employed for a numerical determination of the analytic structure of two-point correlation functions of Quantum Field Theories. These functions are represented through integrals in d-dimensional Euclidean…

High Energy Physics - Phenomenology · Physics 2013-01-16 Andreas Windisch , Reinhard Alkofer , Gundolf Haase , Manfred Liebmann