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We introduce the adiabatic quantum Monte Carlo (AQMC) method, where we gradually crank up the interaction strength, as an amelioration of the sign problem. It is motivated by the adiabatic theorem and will approach the true ground-state if…

Strongly Correlated Electrons · Physics 2021-11-18 Mohammad-Sadegh Vaezi , Amir-Reza Negari , Amin Moharramipour , Abolhassan Vaezi

Quantum Monte Carlo (QMC) methods are the gold standard for studying equilibrium properties of quantum many-body systems -- their phase transitions, ground and thermal state properties. However, in many interesting situations QMC methods…

Quantum Physics · Physics 2020-08-19 Dominik Hangleiter , Ingo Roth , Daniel Nagaj , Jens Eisert

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 is a general numerical method for correlated many-electron systems, which is being increasingly applied in lattice models, atoms, molecules, and solids. Here we introduce the theory and…

Computational Physics · Physics 2021-02-24 Hao Shi , Shiwei Zhang

Density matrix quantum Monte Carlo (DMQMC) is a recently-developed method for stochastically sampling the $N$-particle thermal density matrix to obtain exact-on-average energies for model and \emph{ab initio} systems. We report a systematic…

The quantum Monte-Carlo method is applied to two-dimensional electron systems under strong magnetic fields. The negative-sign problem involved by this method can be avoided for certain filling factors by modifying interaction parameters…

Mesoscale and Nanoscale Physics · Physics 2009-11-10 Sei Suzuki , Tatsuya Nakajima

Quantum Monte Carlo (QMC) methods can very accurately compute ground state properties of quantum systems. We applied these methods to a system of boson hard spheres to get exact, infinite system size results for the ground state at several…

Computational Physics · Physics 2016-09-08 Mark Dewing

The density matrix quantum Monte Carlo (DMQMC) set of methods stochastically samples the exact $N$-body density matrix for interacting electrons at finite temperature. We introduce a simple modification to the interaction picture DMQMC…

Chemical Physics · Physics 2022-05-25 William Van Benschoten , James J. Shepherd

We show that the recently developed phaseless auxiliary-field quantum Monte Carlo (AFQMC) method can be used to study excited states, providing an alternative to standard quantum chemistry methods. The phaseless AFQMC approach, whose…

Computational Physics · Physics 2013-07-09 Wirawan Purwanto , Shiwei Zhang , Henry Krakauer

The recently developed auxiliary field diffusion Monte Carlo method is applied to compute the equation of state and the compressibility of neutron matter. By combining diffusion Monte Carlo for the spatial degrees of freedom and auxiliary…

Nuclear Theory · Physics 2009-11-10 A. Sarsa , S. Fantoni , K. E. Schmidt , F. Pederiva

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

Auxiliary Field Quantum Monte Carlo (AFQMC) has emerged as a powerful framework for treating strongly correlated electronic systems, offering a favorable balance between computational cost and accuracy. In this paper, we present a novel…

Chemical Physics · Physics 2026-04-03 Maxine Luo , Victor Chen , Yu Wang , Christian B. Mendl

The Auxiliary-Field Quantum Monte Carlo (AFQMC) algorithm is a powerful quantum many-body method that can be used successfully as an alternative to standard quantum chemistry approaches to compute the ground state of many body systems, such…

Chemical Physics · Physics 2018-07-23 Edgar Josué Landinez Borda , John A. Gomez , Miguel A. Morales

We introduce a method that combines the power of both the lattice Green function Monte Carlo (LGFMC) with the auxiliary field techniques (AFQMC), and allows us to compute exact ground state properties of the Hubbard model for U<~ 4t on…

Strongly Correlated Electrons · Physics 2015-06-03 Sandro Sorella

We extend the recently introduced phaseless auxiliary-field quantum Monte Carlo (QMC) approach to any single-particle basis, and apply it to molecular systems with Gaussian basis sets. QMC methods in general scale favorably with system…

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

Using trial wavefunctions prepared on quantum devices to reduce the bias of auxiliary-field quantum Monte Carlo (QC-AFQMC) has established itself as a promising hybrid approach to the simulation of strongly correlated many body systems.…

Quantum Physics · Physics 2024-09-16 Matthew Kiser , Matthias Beuerle , Fedor Simkovic

Quantum Monte Carlo (QMC) methods are one of the most important tools for studying interacting quantum many-body systems. The vast majority of QMC calculations in interacting fermion systems require a constraint to control the sign problem.…

Strongly Correlated Electrons · Physics 2016-12-08 Mingpu Qin , Hao Shi , Shiwei Zhang

The exact and phaseless variants of Auxiliary-Field Quantum Monte Carlo (AFQMC) have been shown to be capable of producing accurate ground-state energies for a wide variety of systems including those which exhibit substantial electron…

Chemical Physics · Physics 2017-07-25 James Shee , Shiwei Zhang , David R. Reichman , Richard A. Friesner

Ab initio auxiliary-field quantum Monte Carlo (AFQMC) is a systematically improvable many-body method, but its application to extended solids has been severely limited by unfavorable computational scaling and memory requirements that…

Strongly Correlated Electrons · Physics 2026-02-25 Jinghong Zhang , Meng-Fu Chen , Adam Rettig , Tong Jiang , Paul J. Robinson , Hieu Q. Dinh , Anton Z. Ni , Joonho Lee

Sequential Monte Carlo (SMC) methods are not only a popular tool in the analysis of state space models, but offer an alternative to MCMC in situations where Bayesian inference must proceed via simulation. This paper introduces a new SMC…

Computation · Statistics 2010-05-11 Paul Fearnhead , Benjamin M. Taylor
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