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We investigate the performance of a class of compact and systematically improvable Jastrow-Slater wave functions for the efficient and accurate computation of structural properties, where the determinantal component is expanded with a…

Chemical Physics · Physics 2019-01-17 Monika Dash , Saverio Moroni , Anthony Scemama , Claudia Filippi

Ab initio quantum Monte Carlo (QMC) is a state-of-the-art numerical approach for evaluating accurate expectation values of many-body wavefunctions. However, one of the major drawbacks that still hinders widespread QMC applications is the…

Materials Science · Physics 2024-07-17 Kousuke Nakano , Michele Casula , Giacomo Tenti

We present a simple and general formalism to compute efficiently the derivatives of a multi-determinant Jastrow-Slater wave function, the local energy, the interatomic forces, and similar quantities needed in quantum Monte Carlo. Through a…

Materials Science · Physics 2016-06-22 Claudia Filippi , Roland Assaraf , Saverio Moroni

Computation of ionic forces using quantum Monte Carlo methods has long been a challenge. We introduce a simple procedure, based on known properties of physical electronic densities, to make the variance of the Hellmann-Feynman estimator…

Computational Physics · Physics 2007-05-23 Simone Chiesa , David Ceperley , Shiwei Zhang

Second order stochastic optimization methods, such as the linear method, couple the updates of different parameters and, in so doing, allow statistical uncertainty in one parameter to affect the update of other parameters. In simple tests,…

Chemical Physics · Physics 2025-08-26 Trine Kay Quady , Eric Neuscamman

Classical optimization is a cornerstone of the success of variational quantum algorithms, which often require determining the derivatives of the cost function relative to variational parameters. The computation of the cost function and its…

Quantum Physics · Physics 2025-07-15 Muhammad Umer , Eleftherios Mastorakis , Dimitris G. Angelakis

We examine applicability of the valence bond basis correlator product state ansatz, equivalent to the restricted Boltzmann machine quantum artificial neural network ansatz, and variational Monte Carlo method for direct optimization of…

Strongly Correlated Electrons · Physics 2020-08-12 Tanja Duric , Tomislav Seva

The numerical solution of problems in nonlinear magnetostatics is typically based on a variational formulation in terms of magnetic potentials, the discretization by finite elements, and iterative solvers like the Newton method. The vector…

Numerical Analysis · Mathematics 2024-05-03 Herbert Egger , Felix Engertsberger , Bogdan Radu

Atomic forces are calculated for first-row monohydrides and carbon monoxide within electronic quantum Monte Carlo (QMC). Accurate and efficient forces are achieved by using an improved method for moving variational parameters in variational…

Chemical Physics · Physics 2009-11-10 Myung Won Lee , Massimo Mella , Andrew M. Rappe

A quantum Monte Carlo method is introduced to optimize excited state trial wavefunctions. The method is applied in a correlation function Monte Carlo calculation to compute ground and excited state energies of bosonic van der Waals clusters…

Computational Physics · Physics 2009-11-06 M. P. Nightingale , Vilen Melik-Alaverdian

We present a new form of explicitly correlated wave function whose parameters are mainly linear, to circumvent the problem of the optimization of a large number of non-linear parameters usually encountered with basis sets of explicitly…

Atomic Physics · Physics 2009-11-06 Luca Bertini , Dario Bressanini , Massimo Mella , Gabriele Morosi

This study systematically benchmarks classical optimization strategies for the Quantum Approximate Optimization Algorithm when applied to Generalized Mean-Variance Problems under near-term Noisy Intermediate-Scale Quantum conditions. We…

Quantum Physics · Physics 2025-11-13 Tomáš Bezděk , Haomu Yuan , Vojtěch Novák , Silvie Illésová , Martin Beseda

We develop a formalism and present an algorithm for optimization of the trial wave-function used in fixed-node diffusion quantum Monte Carlo (DMC) methods. We take advantage of a basic property of the walker configuration distribution…

Strongly Correlated Electrons · Physics 2015-05-13 Fernando A. Reboredo , Randolph Q. Hood , Paul R. C. Kent

We consider symmetry-projected Hartree--Fock trial wave functions in constrained-path Monte Carlo (CPMC) calculations. Previous CPMC calculations have mostly employed Hartree--Fock (HF) trial wave functions, restricted or unrestricted. The…

Strongly Correlated Electrons · Physics 2015-03-19 Hao Shi , Carlos A. Jiménez-Hoyos , R. Rodríguez-Guzmán , Gustavo E. Scuseria , Shiwei Zhang

We made a comparative analysis of numerical methods for multidimensional optimization. The main parameter is a number of computations of the test function to reach necessary accuracy, as it is computationally "slow". For complex functions,…

Instrumentation and Methods for Astrophysics · Physics 2013-10-09 Ivan L. Andronov , Maria G. Tkachenko

The precise theoretical determination of the geometrical parameters of molecules at the minima of their potential energy surface and of the corresponding vibrational properties are of fundamental importance for the interpretation of…

Strongly Correlated Electrons · Physics 2013-06-19 Andrea Zen , Delyan Zhelyazov , Leonardo Guidoni

We propose a new Monte Carlo algorithm for the numerical study of general lattice models in Hamiltonian form. The algorithm is based on an initial Ansatz for the ground state wave function depending on a set of free parameters which are…

Statistical Mechanics · Physics 2009-10-31 Matteo Beccaria

We study several aspects of the recently introduced fixed-phase spin-orbit diffusion Monte Carlo (FPSODMC) method, in particular, its relation to the fixed-node method and its potential use as a general approach for electronic structure…

Computational Physics · Physics 2017-10-18 Cody A. Melton , Lubos Mitas

We propose to compute physical properties by Monte Carlo calculations using conditional expectation values. The latter are obtained on top of the usual Monte Carlo sampling by partitioning the physical space in several subspaces or…

Chemical Physics · Physics 2022-08-17 Antoine Bienvenu , Jonas Feldt , Julien Toulouse , Roland Assaraf

The VB-QMC method is presented in this chapter. It consists of using in quantum Monte Carlo (QMC) approaches with a wave function expressed as a usually short expansion of classical Valence-Bond (VB) structures supplemented by a Jastrow…

Chemical Physics · Physics 2022-08-01 Slavko Radenković , Dominik Domin , Julien Toulouse , Benoît Braïda