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A recent preprint by Mazzola and Carleo numerically investigates exponential challenges that can arise for the QC-QMC algorithm introduced in our work, "Unbiasing fermionic quantum Monte Carlo with a quantum computer." As discussed in our…

Quantum mechanics for many-body systems may be reduced to the evaluation of integrals in 3N dimensions using Monte-Carlo, providing the Quantum Monte Carlo ab initio methods. Here we limit ourselves to expectation values for trial…

Computational Physics · Physics 2010-11-22 John Robert Trail , Ryo Maezono

An algorithm is proposed to optimize quantum Monte Carlo (QMC) wave functions based on New ton's method and analytical computation of the first and second derivatives of the variati onal energy. This direct application of the variational…

Chemical Physics · Physics 2016-09-08 Xi Lin , Hongkai Zhang , Andrew M. Rappe

In this note, variational Monte Carlo method based on neural quantum states for spin systems is reviewed. Using a neural network as the wave function allows for a more generalized expression of various types of interactions, including…

Strongly Correlated Electrons · Physics 2024-06-04 Yuntai Song

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

Certain point defects in solids can efficiently be used as qubits for applications in quantum technology. They have spin states that are initializable, readable, robust, and can be manipulated optically. New theoretical methods are needed…

Computational Physics · Physics 2023-09-20 Kristoffer Simula , Ilja Makkonen

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

We propose and analyze a quasi-Monte Carlo (QMC) algorithm for efficient simulation of wave propagation modeled by the Helmholtz equation in a bounded region in which the refractive index is random and spatially heterogenous. Our focus is…

Numerical Analysis · Mathematics 2021-01-27 M. Ganesh , Frances Y. Kuo , Ian H. Sloan

Quantum Monte Carlo (QMC) methods such as Variational Monte Carlo, Diffusion Monte Carlo or Path Integral Monte Carlo are the most accurate and general methods for computing total electronic energies. We will review methods we have…

Computational Physics · Physics 2007-05-23 David Ceperley , Mark Dewing , Carlo Pierleoni

Monte Carlo methods play a central role in particle physics, where they are indispensable for simulating scattering processes, modeling detector responses, and performing multi-dimensional integrals. However, traditional Monte Carlo methods…

Quantum Physics · Physics 2025-10-14 Heechan Yi , Kayoung Ban , Myeonghun Park , Kyoungchul Kong

We review the use of continuum quantum Monte Carlo (QMC) methods for the calculation of energy gaps from first principles, and present a broad set of excited-state calculations carried out with the variational and fixed-node diffusion QMC…

Materials Science · Physics 2018-08-22 Ryan J. Hunt , Marcin Szyniszewski , Genki I. Prayogo , Ryo Maezono , Neil D. Drummond

We elucidate the origin of large differences (two-fold or more) in the fixed-node errors between the first- vs second-row systems for single-configuration trial wave functions in quantum Monte Carlo calculations. This significant difference…

Computational Physics · Physics 2015-06-17 Kevin M. Rasch , Shuming Hu , Lubos Mitas

We investigate Monte Carlo energy and variance minimization techniques for optimizing many-body wave functions. Several variants of the basic techniques are studied, including limiting the variations in the weighting factors which arise in…

Condensed Matter · Physics 2009-10-31 P. R. C. Kent , R. J. Needs , G. Rajagopal

We consider the one-dimensional quantum-statistical problem of interacting spin-less particles in an infinite deep potential valley and on a ring. Several limits for the applicability of the Quantum Monte Carlo (QMC) methods were revealed…

Statistical Mechanics · Physics 2007-05-23 Z. Neda , Z. Dezso

Recently developed neural network-based \emph{ab-initio} solutions (Pfau et. al arxiv:1909.02487v2) for finding ground states of fermionic systems can generate state-of-the-art results on a broad class of systems. In this work, we improve…

Chemical Physics · Physics 2021-03-26 Max Wilson , Nicholas Gao , Filip Wudarski , Eleanor Rieffel , Norm M. Tubman

Quantum Monte Carlo (QMC) methods such as variational Monte Carlo and fixed node diffusion Monte Carlo depend heavily on the quality of the trial wave function. Although Slater-Jastrow wave functions are the most commonly used variational…

Materials Science · Physics 2015-05-28 Bryan K. Clark , Miguel A. Morales , Jeremy McMinis , Jeongnim Kim , Gustavo E. Scuseria

This paper studies the rate of convergence for conditional quasi-Monte Carlo (QMC), which is a counterpart of conditional Monte Carlo. We focus on discontinuous integrands defined on the whole of $R^d$, which can be unbounded. Under…

Numerical Analysis · Mathematics 2018-06-07 Zhijian He

Accurate numerical solution of the five-body Schrodinger equation is effected via variational Monte Carlo in a correlated quark model. The spectrum is assumed to exhibit a narrow resonance with strangeness S=+1. A fully antisymmetrized and…

Nuclear Theory · Physics 2014-11-18 Mark W. Paris

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…

Variational Monte Carlo is a many-body numerical method that scales well with system size. It has been extended to study the Green function only recently by Charlebois and Imada (2020). Here we generalize the approach to systems with open…

Strongly Correlated Electrons · Physics 2022-12-20 P. Rosenberg , D. Sénéchal , A. -M. S. Tremblay , M. Charlebois
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