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Quantum Monte Carlo (QMC) is a stochastic method which has been particularly successful for ground-state electronic structure calculations but mostly unexplored for the computation of excited-state energies. Here, we show that, within a…

Chemical Physics · Physics 2018-08-09 Anthony Scemama , Anouar Benali , Denis Jacquemin , Michel Caffarel , Pierre-François Loos

We computed the Compton profile of solid and liquid lithium using quantum Monte Carlo (QMC) and compared with recent experimental measurements obtaining good agreement. Importantly, we find it crucial to account for proper core-valence…

Materials Science · Physics 2020-04-24 Yubo Yang , Nozomu Hiraoka , Kazuhiro Matsuda , Markus Holzmann , David M. Ceperley

We present a systematic and comprehensive study of finite-size effects in diffusion quantum Monte Carlo calculations of metals. Several previously introduced schemes for correcting finite-size errors are compared for accuracy and efficiency…

Materials Science · Physics 2016-08-23 Sam Azadi , Matthew Foulkes

In regimes of low signal strengths and therefore a small signal-to-noise ratio, standard data analysis methods often fail to accurately estimate system properties. We present a method based on Monte Carlo simulations to effectively restore…

We study a resonant Bose-Fermi mixture at zero temperature by using the fixed-node diffusion Monte Carlo method. We explore the system from weak to strong boson-fermion interaction, for different concentrations of the bosons relative to the…

Quantum Gases · Physics 2013-03-19 G. Bertaina , E. Fratini , S. Giorgini , P. Pieri

In recent years Quantum Monte Carlo techniques provided to be a valuable tool to study strongly interacting Fermi gases at zero temperature. We have used QMC methods to investigate several properties of the two-components Fermi gas at…

Quantum Gases · Physics 2015-06-18 Stefano Gandolfi

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

We extend the scope of full configuration interaction quantum Monte Carlo (FCIQMC) to be applied to coupled fermion-boson hamiltonians, alleviating the a priori truncation in boson occupation which is necessary for many other wave function…

Strongly Correlated Electrons · Physics 2022-11-09 Robert J. Anderson , Charles C. J. Scott , George H. Booth

We have employed the steepest descent method to optimise the variational ground state quantum Monte Carlo wave function for He, Li, Be, B and C atoms. We have used both the direct energy minimisation and the variance minimisation…

Computational Physics · Physics 2015-05-19 M. Ebrahim Foulaadvand , Mohammad Zarenia

In recent years, the combination of precise quantum Monte Carlo (QMC) methods with realistic nuclear interactions and consistent electroweak currents, in particular those constructed within effective field theories (EFTs), has lead to new…

Nuclear Theory · Physics 2019-09-04 J. E. Lynn , I. Tews , S. Gandolfi , A. Lovato

Monte Carlo methods are widely used for approximating complicated, multidimensional integrals for Bayesian inference. Population Monte Carlo (PMC) is an important class of Monte Carlo methods, which utilizes a population of proposals to…

Methodology · Statistics 2022-08-30 Chaofan Huang , V. Roshan Joseph , Simon Mak

We present a systematic downfolding many-body approach for extended systems. Many-body calculations operate on a simpler Hamiltonian which retains material-specific properties. The Hamiltonian is systematically improvable and allows one to…

Materials Science · Physics 2015-06-02 Fengjie Ma , Wirawan Purwanto , Shiwei Zhang , Henry Krakauer

We consider the problem of improving the efficiency of randomized Fourier feature maps to accelerate training and testing speed of kernel methods on large datasets. These approximate feature maps arise as Monte Carlo approximations to…

Machine Learning · Statistics 2015-08-11 Haim Avron , Vikas Sindhwani , Jiyan Yang , Michael Mahoney

The optimization of neural wave functions in variational Monte Carlo crucially relies on a robust convergence criterion. While the energy variance is theoretically a definitive measure, its practical application as a primary convergence…

Quantum Physics · Physics 2025-11-03 Huan-Chen Shi , Er-Liang Cui , Dan Zhou

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

The yardstick of new first-principles approaches to key points on reaction paths at metal surfaces is chemical accuracy compared to reliable experiment. By this we mean that such values as the activation barrier are required to within 1…

Chemical Physics · Physics 2018-06-14 Philip E. Hoggan

Variational Monte Carlo (VMC) is a powerful and fast-growing method for optimizing and evolving parameterized many-body wave functions, especially with modern neural-network quantum states. In practice, however, the stochastic estimators…

Strongly Correlated Electrons · Physics 2026-03-20 Zhou-Quan Wan , Roeland Wiersema , Shiwei Zhang

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

An accurate and consistent theory of phonons in metals requires that all long-range Coulomb interactions between charged particles (electrons and ions) be treated on equal footing. So far, all attempts to deal with this non-perturbative…

Strongly Correlated Electrons · Physics 2016-11-02 Igor S. Tupitsyn , Andrey S. Mishchenko , Naoto Nagaosa , Nikolay Prokof'ev

We revisit the accuracy of the variational Monte Carlo (VMC) method by taking an example of ground state properties for the one-dimensional Hubbard model. We start from the variational wave functions with the Gutzwiller and long-range…

Strongly Correlated Electrons · Physics 2013-08-13 Ryui Kaneko , Satoshi Morita , Masatoshi Imada
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