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Quantum Monte Carlo methods are powerful techniques for studying strongly interacting Fermi systems. However, implementing these methods on computers with finite-precision arithmetic requires careful attention to numerical stability. In the…

Computational Physics · Physics 2015-05-20 C. N. Gilbreth , Y. Alhassid

We propose using the wave function generated by the quantum selected configuration interaction (QSCI) method as the trial wave function in phaseless auxiliary-field quantum Monte Carlo (ph-AFQMC). In the QSCI framework, electronic…

We employ constrained path Auxiliary Field Quantum Monte Carlo (AFQMC) in the pursuit of studying physical nuclear systems using a lattice formalism. Since AFQMC has been widely used in the study of condensed-matter systems such as the…

Nuclear Theory · Physics 2024-07-16 Ryan Curry , Jayani Dissanayake , Stefano Gandolfi , Alexandros Gezerlis

Monte Carlo (MC) simulations are essential computational approaches with widespread use throughout all areas of science. We present a method for accelerating lattice MC simulations using fully connected and convolutional artificial neural…

Strongly Correlated Electrons · Physics 2019-07-31 Shaozhi Li , Philip M. Dee , Ehsan Khatami , Steven Johnston

We outline how auxiliary-field quantum Monte Carlo (AFQMC) can leverage graphical processing units (GPUs) to accelerate the simulation of solid state sytems. By exploiting conservation of crystal momentum in the one- and two-electron…

Computational Physics · Physics 2020-08-21 Fionn D. Malone , Shuai Zhang , Miguel A. Morales

Quantum Monte Carlo (QMC) methods are some of the most accurate methods for simulating correlated electronic systems. We investigate the compatibility, strengths and weaknesses of two such methods, namely, diffusion Monte Carlo (DMC) and…

Computational Physics · Physics 2020-10-14 Fionn D. Malone , Anouar Benali , Miguel A. Morales , Michel Caffarel , P. R. C. Kent , Luke Shulenburger

We propose an algorithm for accurate, systematic and scalable computation of interatomic forces within the auxiliary-field Quantum Monte Carlo (AFQMC) method. The algorithm relies on the Hellman-Fenyman theorem, and incorporates Pulay…

Computational Physics · Physics 2018-05-30 Mario Motta , Shiwei Zhang

Quantum Monte Carlo (QMC) is an advanced simulation methodology for studies of manybody quantum systems. In this review, we focus on the electronic structure QMC, i.e., methods relevant for systems described by the electron-ion…

Other Condensed Matter · Physics 2010-08-16 Michal Bajdich , Lubos Mitas

We present a framework of an auxiliary field quantum Monte Carlo (QMC) method for multi-orbital Hubbard models. Our formulation can be applied to a Hamiltonian which includes terms for on-site Coulomb interaction for both intra- and…

Strongly Correlated Electrons · Physics 2009-10-30 Yukitoshi Motome , Masatoshi Imada

Local constraint is closely related to the gauge field, so constrained models are usually effective low energy descriptions and important in condensed matter physics. On the other hand, local restriction hinders the application of numerical…

Statistical Mechanics · Physics 2022-10-11 Zheng Yan

We describe an algorithm to reduce the cost of auxiliary-field quantum Monte Carlo (AFQMC) calculations for the electronic structure problem. The technique uses a nested low-rank factorization of the electron repulsion integral (ERI). While…

Computational Physics · Physics 2019-07-02 Mario Motta , James Shee , Shiwei Zhang , Garnet Kin-Lic Chan

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

We introduce a black-box auxiliary field quantum Monte Carlo (AFQMC) approach to perform highly accurate electronic structure calculations using configuration interaction singles and doubles (CISD) trial states. This method consistently…

We extend correlated sampling from classical auxiliary-field quantum Monte Carlo to the quantum-classical (QC-AFQMC) framework, enabling accurate nuclear force computations crucial for geometry optimization and reaction dynamics. Stochastic…

It has become increasingly feasible to use quantum Monte Carlo (QMC) methods to study correlated fermion systems for realistic Hamiltonians. We give a summary of these techniques targeted at researchers in the field of correlated electrons,…

Strongly Correlated Electrons · Physics 2016-08-24 Lucas K. Wagner , David M. Ceperley

We consider the computational efficiency of Monte Carlo (MC) and Multilevel Monte Carlo (MLMC) methods applied to partial differential equations with random coefficients. These arise, for example, in groundwater flow modelling, where a…

Numerical Analysis · Mathematics 2024-12-12 Anastasia Istratuca , Aretha Teckentrup

We discuss the Auxiliary Field Quantum Monte Carlo (AFQMC) method applied to dilute neutron matter at finite temperatures. We formulate the discrete Hubbard-Stratonovich transformation for the interaction with finite effective range which…

Nuclear Theory · Physics 2009-05-29 G. Wlazlowski , P. Magierski

We present an implementation of phaseless Auxiliary-Field Quantum Monte Carlo (ph-AFQMC) utilizing graphical processing units (GPUs). The AFQMC method is recast in terms of matrix operations which are spread across thousands of processing…

Computational Physics · Physics 2018-09-07 James Shee , Evan J. Arthur , Shiwei Zhang , David R. Reichman , Richard A. Friesner

We present a reduced-scaling auxiliary-field quantum Monte Carlo (AFQMC) framework designed for large molecular systems and ensembles, with or without coupling to optical cavities. Our approach leverages the natural block sparsity of…

Chemical Physics · Physics 2026-02-03 Yu Zhang

We develop a static quantum embedding scheme that utilizes different levels of approximations to coupled cluster (CC) theory for an active fragment region and its environment. To reduce the computational cost, we solve the local fragment…

Chemical Physics · Physics 2024-11-13 Avijit Shee , Fabian M. Faulstich , Birgitta Whaley , Lin Lin , Martin Head-Gordon