English
Related papers

Related papers: Mitigating Green's function Monte Carlo signal-to-…

200 papers

The uniform electron gas (UEG) at finite temperature is of key relevance for many applications in the warm dense matter regime, e.g. dense plasmas and laser excited solids. Also, the quality of density functional theory calculations…

Strongly Correlated Electrons · Physics 2016-02-10 S. Groth , T. Schoof , T. Dornheim , M. Bonitz

Self-learning Monte Carlo method [arXiv:1610.03137, 1611.09364] is a powerful general-purpose numerical method recently introduced to simulate many-body systems. In this work, we implement this method in the framework of determinantal…

Strongly Correlated Electrons · Physics 2018-07-12 Xiao Yan Xu , Yang Qi , Junwei Liu , Liang Fu , Zi Yang Meng

In semi-classical transport, it has become common practice over the past few decades to use ensemble Monte Carlo (EMC) methods for the simulation of transport in semiconductor devices. This method utilizes particles while still addressing…

Mesoscale and Nanoscale Physics · Physics 2023-05-31 David K. Ferry

This paper studies a new and highly efficient Markov chain Monte Carlo (MCMC) methodology to perform Bayesian inference in low-photon imaging problems, with particular attention to situations involving observation noise processes that…

Fixed node diffusion quantum Monte Carlo (FN-DMC) is an increasingly used computational approach for investigating the electronic structure of molecules, solids, and surfaces with controllable accuracy. It stands out among equally accurate…

Computational Physics · Physics 2019-10-03 Andrea Zen , Jan Gerit Brandenburg , Angelos Michaelides , Dario Alfè

Determinant quantum Monte Carlo (DQMC), formulated in complex-fermion representation, has played a key role in studying strongly-correlated fermion systems. However, its applicability is limited due to the requirement of particle-number…

Strongly Correlated Electrons · Physics 2024-08-21 Ze-Yao Han , Zhou-Quan Wan , Hong Yao

Wavefunction correction scheme, which was developed as a variance reduction tool for the pure and fixed-node diffusion Monte Carlo (DMC) computations by Anderson and Freihaut, is applied to the DMC computations of fermions without using the…

Computational Physics · Physics 2010-03-29 Nazim Dugan , Inanc Kanik , Sakir Erkoc

In this manuscript, we study quantum criticality of Dirac fermions via large-scale numerical simulations, focusing on the Gross-Neveu-Yukawa(GNY) chiral-Ising quantum critical point with critical bosonic modes coupled with Dirac fermions.…

Statistical Mechanics · Physics 2020-03-04 Yuzhi Liu , Wei Wang , Kai Sun , Zi Yang Meng

We describe an application of the Monte Carlo method to the Janus deformation of the black brane background. We present numerical results for three and five dimensional black Janus geometries with planar and spherical interfaces. In…

High Energy Physics - Theory · Physics 2017-04-05 Dongsu Bak , Chanju Kim , Kyung Kiu Kim , Hyunsoo Min , Jeong-Pil Song

Due to the intrinsic complexity of the quantum many-body problem, quantum Monte Carlo algorithms and their corresponding Monte Carlo configurations can be defined in various ways. Configurations corresponding to few Feynman diagrams often…

Strongly Correlated Electrons · Physics 2019-04-30 Alexander Kowalski , Andreas Hausoel , Markus Wallerberger , Patrik Gunacker , Giorgio Sangiovanni

Lattice gauge theories coupled to fermionic matter account for many interesting phenomena in both high energy physics and condensed matter physics. Certain regimes, e.g. at finite fermion density, are difficult to simulate with traditional…

High Energy Physics - Lattice · Physics 2023-11-16 Julian Bender , Patrick Emonts , J. Ignacio Cirac

We propose a novel algorithm for calculating the ground-state energy of quantum many-body systems by combining auxiliary-field quantum Monte Carlo (AFQMC) with tensor-train sketching. In AFQMC, a good trial wavefunction to guide the random…

Numerical Analysis · Mathematics 2026-02-17 Ziang Yu , Shiwei Zhang , Yuehaw Khoo

Quantum simulations are a powerful tool for exploring strongly correlated many-body phenomena. Yet, their reach is limited by the fermion sign problem, which causes configuration weights to become negative, compromising statistical…

Strongly Correlated Electrons · Physics 2025-12-04 Ryan Larson , Rubem Mondaini , Richard T. Scalettar

Nuclear many-body systems, ranging from nuclei to neutron stars, are some of the most interesting physical phenomena in our universe, and Quantum Monte Carlo (QMC) approaches are among the most accurate many-body methods currently available…

Nuclear Theory · Physics 2025-01-03 Ryan Curry , Rahul Somasundaram , Stefano Gandolfi , Alexandros Gezerlis , Ingo Tews

Fixed-node diffusion Monte Carlo (DMC) is a stochastic algorithm for finding the lowest energy many-fermion wave function with the same nodal surface as a chosen trial function. It has proved itself among the most accurate methods available…

Condensed Matter · Physics 2009-10-31 W. M. C. Foulkes , Randolph Q. Hood , R. J. Needs

We present a systematic downfolding many-body approach for extended systems. Many-body calculations operate on a simpler Hamiltonian which retains material-specific properties. The Hamiltonian is systematically improvable and allows one to…

Materials Science · Physics 2015-06-02 Fengjie Ma , Wirawan Purwanto , Shiwei Zhang , Henry Krakauer

Although quantum Monte Carlo is, in principal, an exact method for solving the Schroedinger equation, it is well-known that systems of Fermions still pose a challenge. Thus far all solutions to the "sign problem" remain inefficient (or…

Quantum Physics · Physics 2007-05-23 D. Bressanini , D. M. Ceperley , P. J. Reynolds

Fermi gases in strongly coupled regimes, such as the unitary limit, are inherently challenging for many-body methods. Although much progress has been made with purely analytic methods, quantitative results require ab initio numerical…

Statistical Mechanics · Physics 2015-06-16 Dietrich Roscher , Jens Braun , Jiunn-Wei Chen , Joaquín E. Drut

Variational Monte Carlo (VMC) is an approach for computing ground-state wavefunctions that has recently become more powerful due to the introduction of neural network-based wavefunction parametrizations. However, efficiently training neural…

Machine Learning · Statistics 2023-10-03 Robert J. Webber , Michael Lindsey

We present a finite-temperature canonical-ensemble determinant quantum Monte Carlo algorithm that enforces an exact fermion number and enables stable simulations of correlated lattice fermions. We propose a stabilized QR update that reduces…

Strongly Correlated Electrons · Physics 2026-01-21 Tu Hong , Kun Chen , Xiao Yan Xu