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Related papers: Non-orthogonal determinants in multi-Slater-Jastro…

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We propose a general framework for finding the ground state of many-body fermionic systems by using feed-forward neural networks. The anticommutation relation for fermions is usually implemented to a variational wave function by the Slater…

Strongly Correlated Electrons · Physics 2021-12-21 Koji Inui , Yasuyuki Kato , Yukitoshi Motome

By combining density-functional theory (DFT) and wave function theory (WFT) via the range separation (RS) of the interelectronic Coulomb operator, we obtain accurate fixed-node diffusion Monte Carlo (FN-DMC) energies with compact…

Chemical Physics · Physics 2020-11-04 Anthony Scemama , Emmanuel Giner , Anouar Benali , Pierre-François Loos

Quantum Monte Carlo (QMC) is an advanced simulation methodology for studies of manybody quantum systems. In this review, we focus on the electronic structure QMC, i.e., methods relevant for systems described by the electron-ion…

Other Condensed Matter · Physics 2010-08-16 Michal Bajdich , Lubos Mitas

Diffusion Monte Carlo (DMC) is an exact technique to project out the ground state (GS) of a Hamiltonian. Since the GS is always bosonic, in fermionic systems the projection needs to be carried out while imposing anti-symmetric constraints,…

Computational Physics · Physics 2025-01-08 Kousuke Nakano , Sandro Sorella , Dario Alfè , Andrea Zen

An inhomogeneous backflow transformation for many-particle wave functions is presented and applied to electrons in atoms, molecules, and solids. We report variational and diffusion quantum Monte Carlo VMC and DMC energies for various…

Computational Physics · Physics 2008-01-04 P. Lopez-Rios , A. Ma , N. D. Drummond , M. D. Towler , R. J. Needs

We present a recently developed projector quantum Monte Carlo method for calculations of electronic structure in systems with spin-orbit interactions. The method solves for many-body eigenstates in the presence of spin-orbit using the…

Chemical Physics · Physics 2017-08-09 Cody A. Melton , M. Chandler Bennett , Lubos Mitas

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

We have reformulated the quantum Monte Carlo (QMC) technique so that a large part of the calculation scales linearly with the number of atoms. The reformulation is related to a recent alternative proposal for achieving linear-scaling QMC,…

Other Condensed Matter · Physics 2016-08-31 D. Alfe` , M. J. Gillan

In this study we present an optimization method based on the quantum Monte Carlo diagonalization for many-fermion systems. Using the Hubbard-Stratonovich transformation, employed to decompose the interactions in terms of auxiliary fields,…

Strongly Correlated Electrons · Physics 2009-11-13 Takashi Yanagisawa

We present a new method for the optimization of large configuration interaction (CI) expansions in the quantum Monte Carlo (QMC) framework. The central idea here is to replace the non-orthogonal variational optimization of CI coefficients…

Chemical Physics · Physics 2022-05-26 Abdallah Ammar , Emmanuel Giner , Anthony Scemama

We study lithium systems over a range of number of atoms, e.g., atomic anion, dimer, metallic cluster, and body-centered cubic crystal by the diffusion Monte Carlo method. The calculations include both core and valence electrons in order to…

Computational Physics · Physics 2015-07-29 Kevin Rasch , Lubos Mitas

We explore the application of an extrapolative method that yields very accurate total and relative energies from variational and diffusion quantum Monte Carlo (VMC and DMC) results. For a trial wave function consisting of a small…

Computational Physics · Physics 2024-04-25 Seyed Mohammadreza Hosseini , Ali Alavi , Pablo Lopez Rios

The conventional tensor-network states employ real-space product states as reference wave functions. Here, we propose a many-variable variational Monte Carlo (mVMC) method combined with tensor networks by taking advantages of both to study…

Strongly Correlated Electrons · Physics 2017-08-09 Hui-Hai Zhao , Kota Ido , Satoshi Morita , Masatoshi Imada

We present a method for optimizing the location of the fermion ground-state nodes using a combination of diffusion Monte Carlo (DMC) and projected gradient descent (PGD). A PGD iteration shifts the parameters of an arbitrary node-fixing…

Computational Physics · Physics 2022-04-06 John McFarland , Efstratios Manousakis

Diffusion Monte Carlo (DMC) calculations typically yield highly accurate results in solid-state and quantum-chemical calculations. However, operators that do not commute with the Hamiltonian are at best sampled correctly up to second order…

Other Condensed Matter · Physics 2009-11-13 R. Gaudoin , J. M. Pitarke

We apply diffusion quantum Monte Carlo (DMC) to a broad set of solids, benchmarking the method by comparing bulk structural properties (equilibrium volume and bulk modulus) to experiment and DFT based theories. The test set includes…

Materials Science · Physics 2015-06-17 Luke Shulenburger , Thomas R. Mattsson

We introduce a method for accurate quantum chemical calculations based on a simple variational wave function, defined by a single geminal that couples all the electrons into singlet pairs, combined with a real space correlation factor. The…

Materials Science · Physics 2009-10-22 M. Marchi , S. Azadi , M. Casula , S. Sorella

Understanding the real-time evolution of many-electron quantum systems is essential for studying dynamical properties in condensed matter, quantum chemistry, and complex materials, yet it poses a significant theoretical and computational…

Strongly Correlated Electrons · Physics 2024-11-07 Jannes Nys , Gabriel Pescia , Alessandro Sinibaldi , Giuseppe Carleo

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…

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