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We propose a novel Monte-Carlo based ab-initio algorithm for directly computing the statistics for quantities of interest in an immiscible two-phase compressible flow. Our algorithm samples the underlying probability space and evolves these…

Numerical Analysis · Mathematics 2023-03-30 Marco Petrella , Remi Abgrall , Siddhartha Mishra

We present a real-time quantum Monte Carlo algorithm that simulates the dynamics of open quantum systems by stochastically compressing and evolving the density matrix under both Markovian and non-Markovian master equations. Our algorithm…

Quantum Physics · Physics 2025-09-11 Tong Shen , Daniel A. Lidar

In this work we introduce the Dual Boson Diagrammatic Monte Carlo technique for strongly interacting electronic systems. This method combines the strength of dynamical mean-filed theory for non-perturbative description of local correlations…

Strongly Correlated Electrons · Physics 2020-11-06 M. Vandelli , V. Harkov , E. A. Stepanov , J. Gukelberger , E. Kozik , A. Rubio , A. I. Lichtenstein

We derive the exact dual representation of the bosonic Hubbard model which takes the form of conserved current loops. The hardcore limit, which corresponds to the quantum spin-${1\over 2}$ Heisenberg antiferromagnet, is also obtained. In…

Statistical Mechanics · Physics 2009-10-31 G. G. Batrouni , H. Mabilat

Random batch algorithms are constructed for quantum Monte Carlo simulations. The main objective is to alleviate the computational cost associated with the calculations of two-body interactions, including the pairwise interactions in the…

Computational Physics · Physics 2020-09-01 Shi Jin , Xiantao Li

A first-order, Monte Carlo ensemble method has been recently introduced for solving parabolic equations with random coefficients in [26], which is a natural synthesis of the ensemble-based, Monte Carlo sampling algorithm and the…

Numerical Analysis · Mathematics 2018-02-19 Yan Luo , Zhu Wang

We present density response estimators for Monte Carlo simulations that are based on a reweighting procedure, where the samples of an unperturbed system are used to estimate the properties of a system perturbed by an external harmonic…

We present a numerically exact Inchworm Monte Carlo method for equilibrium multiorbital quantum impurity problems with general interactions and hybridizations. We show that the method, originally developed to overcome the dynamical sign…

Strongly Correlated Electrons · Physics 2020-05-25 Eitan Eidelstein , Emanuel Gull , Guy Cohen

Correlated fermions are of high interest in condensed matter (Fermi liquids, Wigner molecules), cold atomic gases and dense plasmas. Here we propose a novel approach to path integral Monte Carlo (PIMC) simulations of strongly degenerate…

Quantum Gases · Physics 2016-01-15 Tobias Dornheim , Simon Groth , Alexey Filinov , Michael Bonitz

High-order virtual excitations play an important role in microscopic models of nuclear reactions at intermediate energies. However, the factorial growth of their complexity has prevented their consistent inclusion in ab initio many-body…

Nuclear Theory · Physics 2025-05-15 Stefano Brolli , Carlo Barbieri , Enrico Vigezzi

Artifacts arise in the simulations of electrolytes using periodic boundary conditions (PBC). We show the origin of these artifacts are the periodic image charges and the constraint of charge neutrality inside the simulation box, both of…

Soft Condensed Matter · Physics 2015-09-30 Yihao Liang , Zhenli Xu , Xiangjun Xing

The development of numerical methods capable of simulating realistic materials with strongly correlated electrons, with controllable errors, is a central challenge in quantum many-body physics. Here we describe how a hybrid between…

Strongly Correlated Electrons · Physics 2015-04-23 Alexei A. Kananenka , Emanuel Gull , Dominika Zgid

New efficient and accurate numerical methods are proposed to compute ground states and dynamics of dipolar Bose-Einstein condensates (BECs) described by a three-dimensional (3D) Gross-Pitaevskii equation (GPE) with a dipolar interaction…

Quantum Gases · Physics 2021-10-26 Weizhua Bao , Yongyong Cai , Hanquan Wang

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

Markov chain Monte Carlo (MCMC) methods are foundational algorithms for Bayesian inference and probabilistic modeling. However, most MCMC algorithms are inherently sequential and their time complexity scales linearly with the sequence…

Computation · Statistics 2025-12-03 David M. Zoltowski , Skyler Wu , Xavier Gonzalez , Leo Kozachkov , Scott W. Linderman

We introduce a numerical algorithm to stochastically sample the dual fermion perturbation series around the dynamical mean field theory, generating all topologies of two-particle interaction vertices. We show results in the weak and strong…

Strongly Correlated Electrons · Physics 2016-07-07 Sergei Iskakov , Andrey E. Antipov , Emanuel Gull

This study addresses the challenge of simulating realistic particle systems by proposing a novel particle decomposition scheme that improves the parallel performance of surface resolved particle simulations. Realistic particle systems often…

Fluid Dynamics · Physics 2024-03-21 J. E. Marquardt , N. Hafen , M. J. Krause

Diagrammatic Monte Carlo approach is applied to a problem of a single spin-down fermion resonantly interacting with the sea of ideal spin-up fermions. On one hand, we develop a generic, sign-problem tolerant, method of exact numerical…

Statistical Mechanics · Physics 2009-11-13 Nikolay Prokof'ev , Boris Svistunov

It is well known that using the conventional non-Hermitian but ${\cal PT}-$symmetric Bose-Hubbard Hamiltonian with real spectrum one can realize the Bose-Einstein condensation (BEC) process in an exceptional-point limit of order $N$. Such…

Quantum Physics · Physics 2021-09-09 Miloslav Znojil

We introduce a novel Multi-Order Monte Carlo approach for uncertainty quantification in the context of multiscale time-dependent partial differential equations. The new framework leverages Implicit-Explicit Runge-Kutta time integrators to…

Numerical Analysis · Mathematics 2026-04-08 Giulia Bertaglia , Walter Boscheri , Lorenzo Pareschi