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We introduce an efficient approach to implement correlated many-body trial wave functions in auxiliary-field quantum Monte Carlo (AFQMC). To control the sign/phase problem in AFQMC, a constraint is derived from an exact gauge condition but…

Strongly Correlated Electrons · Physics 2025-10-27 Zhi-Yu Xiao , Zixiang Lu , Yixiao Chen , Tao Xiang , Shiwei Zhang

We extend the use of coupled cluster (CC) trial states in the phaseless auxiliary-field quantum Monte Carlo (AFQMC) method beyond single and double excitations to include both triple and quadruple excitations. With this AFQMC/CC hierarchy,…

Chemical Physics · Physics 2025-10-09 Eirik F. Kjønstad , Yann Damour , Sandeep Sharma , Garnet Kin-Lic Chan

Phaseless auxiliary-field quantum Monte Carlo (ph-AFQMC) has emerged as a promising electronic structure method for correlated electronic systems. However, the quality of its predictions depends critically on the choice of trial…

Chemical Physics · Physics 2026-05-06 Don Danilov , Brad Ganoe , Leon Otis , Zhi Gong , Zixiang Lu , James Shee

We introduce an efficient and numerically stable technique to make use of a BCS trial wave function in the computation of correlation functions of strongly correlated quantum fermion systems. The technique is applicable to any projection…

Strongly Correlated Electrons · Physics 2019-08-28 Ettore Vitali , Peter Rosenberg , Shiwei Zhang

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

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

In this work, we report, for the first time, an implementation of fermionic auxiliary-field quantum Monte Carlo (AFQMC) using matrix product state (MPS) trial wavefunctions, dubbed MPS-AFQMC. Calculating overlaps between an MPS trial and…

Chemical Physics · Physics 2025-01-13 Tong Jiang , Bryan O'Gorman , Ankit Mahajan , Joonho Lee

The accuracy of phaseless auxiliary-field quantum Monte Carlo (ph-AFQMC) can be systematically improved with better trial states. Using multi-Slater determinant trial states, ph-AFQMC has the potential to faithfully treat strongly…

Chemical Physics · Physics 2024-06-13 Yifei Huang , Zhen Guo , Hung Q. Pham , Dingshun Lv

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

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 phaseless auxiliary-field quantum Monte Carlo (ph-AFQMC) method is a stochastic imaginary-time projection technique for computing ground-state properties of strongly correlated quantum systems, with accuracy that depends critically on…

We explore a novel and straightforward solution to the sign problem that has plagued the Auxiliary-field Monte Carlo (AFMC) method applied to many-body systems for more than a decade. We present a solution to the sign problem that has…

Nuclear Theory · Physics 2007-08-23 G. Stoitcheva , W. E. Ormand , D. Neuhauser , D. J. Dean

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

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

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 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…

Here we develop a new scheme of projective quantum Monte-Carlo (QMC) simulation combining unbiased zero-temperature (projective) determinant QMC and variational Monte-Carlo based on Gutzwiller projection wave function, dubbed as…

Strongly Correlated Electrons · Physics 2026-04-08 Wei-Xuan Chang , Zi-Xiang Li

Quantum Monte Carlo (QMC) methods offer exact solutions for quantum many-body systems but face severe limitations in fermionic systems like atomic nuclei due to the sign problem. While sign-problem-free QMC algorithms exist and provide…

Nuclear Theory · Physics 2026-01-06 Zhong-Wang Niu , Bing-Nan Lu

The recently proposed full configuration interaction quantum Monte Carlo method allows access to essentially exact ground-state energies of systems of interacting fermions substantially larger than previously tractable without knowledge of…

Computational Physics · Physics 2012-12-17 J. S. Spencer , N. S. Blunt , W. M. C. Foulkes

For optimal accuracy, auxiliary-field quantum Monte Carlo (AFQMC) requires trial states consisting of multiple Slater determinants. We develop an efficient algorithm to select the determinants from an AFQMC random walk eliminating the need…

Chemical Physics · Physics 2025-07-08 Zoran Sukurma , Martin Schlipf , Georg Kresse
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