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arXiv · 2608.22925

Importance-Reweighted Fock-Space Variational Monte Carlo

Zheng Che
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Abstract

Fock-space variational Monte Carlo (FS-VMC) evaluates variational quantities by sampling discrete many-body configurations. In molecular applications, concentrated Born distributions can hinder Markov-chain mixing, while Monte Carlo estimators can also exhibit large variance. We introduce importance-reweighted FS-VMC (IR-FS-VMC), which combines Metropolis--Hastings sampling, an evaluation kernel, and self-normalized importance sampling to estimate the Born-distribution energy, gradient, and stochastic reconfiguration (SR) matrix. Controlled comparisons on equilibrium H2O and Fe2S2 show that the acceptance rate and local-energy variance can respond differently to the sampling and estimation procedure. A single production protocol yields accurate variational energies for H2O dissociation, 36-site hydrogen lattices, and Fe2S2 and Fe4S4 active spaces without system-specific sampling parameters.

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Zheng Che. 2026-09-16. Importance-Reweighted Fock-Space Variational Monte Carlo. https://arxiv.org/abs/2608.22925

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