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We present a quantum Monte-Carlo algorithm for computing the perturbative expansion in power of the coupling constant $U$ of the out-of-equilibrium Green's functions of interacting Hamiltonians of fermions. The algorithm extends the one…

Strongly Correlated Electrons · Physics 2019-09-23 Corentin Bertrand , Olivier Parcollet , Antoine Maillard , Xavier Waintal

Aims. Numerical test-particle simulations are a reliable and frequently used tool to test analytical transport theories and to predict mean-free paths. The comparison between solutions of the diffusion equation and the particle flux is used…

High Energy Astrophysical Phenomena · Physics 2016-02-17 R. C. Tautz , J. Bolte , A. Shalchi

Interconnection studies require solving numerous instances of the AC load or power flow (AC PF) problem to simulate diverse scenarios as power systems navigate the ongoing energy transition. To expedite such studies, this work leverages…

Quantum Physics · Physics 2025-09-18 Thinh Viet Le , Md Obaidur Rahman , Vassilis Kekatos

We introduce two novel quantum Monte Carlo methods and employ them to study the superfluid-insulator transition in a two-dimensional system of hard-core bosons. One of the methods is appropriate for zero temperature and is based upon…

Condensed Matter · Physics 2009-10-22 Shiwei Zhang , N. Kawashima , J. Carlson , J. E. Gubernatis

Quantum-enhanced auxiliary field quantum Monte Carlo (QC-AFQMC) uses output from a quantum computer to increase the accuracy of its classical counterpart. The algorithm requires the estimation of overlaps between walker states and a trial…

We introduce a Diagrammatic Monte Carlo (DiagMC) approach to angular momentum properties of quantum many-particle systems possessing a macroscopic number of degrees of freedom. The treatment is based on a diagrammatic expansion that merges…

Quantum Gases · Physics 2018-10-24 G. Bighin , T. V. Tscherbul , M. Lemeshko

We apply the effective potential analytic continuation (EPAC) method to one-dimensional asymmetric potential systems to obtain the real time quantum correlation functions at various temperatures. Comparing the EPAC results with the exact…

Quantum Physics · Physics 2009-11-10 Atsushi Horikoshi , Kenichi Kinugawa

Applications that require substantial computational resources today cannot avoid the use of heavily parallel machines. Embracing the opportunities of parallel computing and especially the possibilities provided by a new generation of…

Computational Physics · Physics 2017-09-14 Martin Weigel

We present an open source Python 3 library aimed at practitioners of molecular simulation, especially Monte Carlo simulation. The aims of the library are to facilitate the generation of simulation data for a wide range of problems; and to…

Inspired by the universal approximation theorem and widespread adoption of artificial neural network techniques in a diversity of fields, we propose feed-forward neural networks as a general purpose trial wave function for quantum Monte…

Computational Physics · Physics 2021-01-26 Jan Kessler , Francesco Calcavecchia , Thomas D. Kühne

We present a new efficient method for Monte Carlo simulations of diffusion-reaction processes. First introduced by us in [Phys. Rev. Lett., 97:230602, 2006], the new algorithm skips the traditional small diffusion hops and propagates the…

Materials Science · Physics 2013-05-29 T. Oppelstrup , V. V. Bulatov , A. Donev , M. H. Kalos , G. H. Gilmer , B. Sadigh

We present an extension of constrained-path auxiliary-field quantum Monte Carlo (CP-AFQMC) for the treatment of correlated electronic systems coupled to phonons. The algorithm follows the standard CP-AFQMC approach for description of the…

Strongly Correlated Electrons · Physics 2021-03-24 Joonho Lee , Shiwei Zhang , David R. Reichman

Multifractal Detrended Fluctuation Analysis (MFDFA) is a powerful and widely used technique for characterizing the scaling properties and long-range correlations of complex time series. However, its application often involves significant…

Machine learning approaches, enabled by the emergence of comprehensive databases of materials properties, are becoming a fruitful direction for materials analysis. As a result, a plethora of models have been constructed and trained on…

We present a new quantum Monte Carlo algorithm suitable for generically complex problems, such as systems coupled to external magnetic fields or anyons in two spatial dimensions. We find that the choice of gauge plays a nontrivial role, and…

Condensed Matter · Physics 2009-10-22 Lizeng Zhang , Geoff Canright , Ted Barnes

For quantum computing (QC) to emerge as a practically indispensable computational tool, there is a need for quantum protocols with an end-to-end practical applications -- in this instance, fluid dynamics. We debut here a high performance…

Quantum Physics · Physics 2023-12-05 Sachin S. Bharadwaj , Katepalli R. Sreenivasan

This paper introduces the Exascale Grid Optimization (ExaGO) toolkit, a library for solving large-scale alternating current optimal power flow (ACOPF) problems including stochastic effects, security constraints and multi-period constraints.…

Systems and Control · Electrical Eng. & Systems 2022-03-22 Shrirang Abhyankar , Slaven Peles , Tamara Becejac , Jesse Holzer , Asher Mancinelli , Cameron Rutherford

A general synthetic iterative scheme is proposed to solve the Enskog equation within a Monte Carlo framework. The method demonstrates rapid convergence by reducing intermediate Monte Carlo evolution and preserves the asymptotic-preserving…

Fluid Dynamics · Physics 2025-09-26 Bin Hu , Liyan Luo , Lei Wu

The open source ALPS (Algorithms and Libraries for Physics Simulations) project provides a collection of physics libraries and applications, with a focus on simulations of lattice models and strongly correlated electron systems. The…

Analytic continuation (AC) from imaginary-time Green's function to spectral function is essential in the numerical analysis of dynamical properties in quantum many-body systems. However, this process faces a fundamental challenge: it is an…

Strongly Correlated Electrons · Physics 2024-09-04 Yuichi Motoyama , Hiroshi Shinaoka , Junya Otsuki , Kazuyoshi Yoshimi