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Neural Network-based Quantum Monte Carlo (NNQMC), an emerging method for solving many-body quantum systems with high accuracy, has been limitedly applied to small systems due to demanding computation requirements. In this work, we introduce…

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

We propose a new scheme to implement the self-consistent optimization of the trial wave-function in constrained path auxiliary field Quantum Monte Carlo (CP-AFQMC) in the framewok of natural orbitals. In this scheme, a new trial…

Strongly Correlated Electrons · Physics 2023-08-15 Mingpu Qin

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 explore different ways of incorporating accurate trial wave functions into free projection auxiliary field quantum Monte Carlo (fp-AFQMC). Trial states employed include coupled cluster singles and doubles, multi-Slater, and symmetry…

Chemical Physics · Physics 2021-04-15 Ankit Mahajan , Sandeep Sharma

The auxiliary-field quantum Monte Carlo (AFQMC) method provides a computational framework for solving the time-independent Schroedinger equation in atoms, molecules, solids, and a variety of model systems by stochastic sampling. We…

Strongly Correlated Electrons · Physics 2018-07-19 Shiwei Zhang

A series of calculations for the first- and second-row post-d elements (Ga-Br and In-I) are presented using the phaseless auxiliary-field quantum Monte Carlo (AF QMC) method. This method is formulated in a Hilbert space defined by any…

Computational Physics · Physics 2007-05-23 W. A. Al-Saidi , Henry Krakauer , Shiwei Zhang

The use of an approximate reference state wave function |Phi_r> in electronic many-body methods can break the spin symmetry of Born-Oppenheimer spin-independent Hamiltonians. This can result in significant errors, especially when bonds are…

Computational Physics · Physics 2008-03-19 Wirawan Purwanto , W. A. Al-Saidi , Henry Krakauer , Shiwei Zhang

In this work, we develop a size extensive Auxiliary-Field Quantum Monte Carlo (AFQMC) approach that scales as $O(N^5)$ for local energy evaluation by treating the Coupled Cluster Singles and Doubles (CCSD) trial wavefunctions…

Chemical Physics · Physics 2026-05-13 Yichi Zhang , Ankit Mahajan , Yann Damour , Sandeep Sharma

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 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

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 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 present phaseless auxiliary-field (AF) quantum Monte Carlo (QMC) calculations of the ground states of some hydrogen-bonded systems. These systems were selected to test and benchmark different aspects of the new phaseless AF QMC method.…

Computational Physics · Physics 2007-05-23 W. A. Al-Saidi , Henry Krakauer , Shiwei Zhang

We introduce an efficient approach to implement neural network quantum states (NNQS) as trial wavefunctions in auxiliary-field quantum Monte Carlo (AFQMC). NNQS are a recently developed class of variational ans\"atze capable of flexibly…

Chemical Physics · Physics 2025-10-07 Zhi-Yu Xiao , Bowen Kan , Huan Ma , Bowen Zhao , Honghui Shang

The auxiliary field quantum Monte Carlo (AFQMC) method has been a workhorse in the field of strongly correlated electrons for a long time and has found its most recent implementation in the ALF package (https://alf.physik.uni-wuerzburg.de).…

Strongly Correlated Electrons · Physics 2020-09-11 Florian Goth

In this work, we present an overview of the phaseless auxiliary-field quantum Monte Carlo (ph- AFQMC) approach from a computational quantum chemistry perspective, and present a numerical assessment of its performance on main group chemistry…

Chemical Physics · Physics 2022-09-28 Joonho Lee , Hung Q. Pham , David R. Reichman

Quantum Monte Carlo (QMC) algorithms have long relied on Jastrow factors to incorporate dynamic correlation into trial wave functions. While Jastrow-type wave functions have been widely employed in real-space algorithms, they have seen…

Strongly Correlated Electrons · Physics 2016-12-28 Chia-Chen Chang , Brenda M. Rubenstein , Miguel A. Morales

In this work, we test a recently developed method to enhance classical auxiliary-field quantum Monte Carlo (AFQMC) calculations with quantum computers against examples from chemistry and material science, representatives of classes of…

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