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The implementation and reliability of a quadratic diffusion Monte Carlo method for the study of ground-state properties of atoms are discussed. We show in the simple yet non-trivial calculation of the binding energy of the Li atom that the…

Condensed Matter · Physics 2009-11-07 A. Sarsa , J. Boronat , J. Casulleras

Obtaining accurate ground and low-lying excited states of electronic systems is crucial in a multitude of important applications. One ab initio method for solving the Schr\"odinger equation that scales favorably for large systems is…

Chemical Physics · Physics 2023-01-19 Mike Entwistle , Zeno Schätzle , Paolo A. Erdman , Jan Hermann , Frank Noé

A variational Monte Carlo method is used to generate sets of orthogonal trial functions, Psi_T(J^pi,T), for given quantum numbers in various light p-shell nuclei. These Psi_T are then used as input to Green's function Monte Carlo…

Nuclear Theory · Physics 2008-11-26 Steven C. Pieper , R. B. Wiringa , J. Carlson

A family of Variational Quantum Eigensolver (VQE) methods is designed to maximize the resource of existing noisy intermediate-scale quantum (NISQ) devices. However, VQE approaches encounter various difficulties in simulating molecules of…

Chemical Physics · Physics 2022-08-16 M. D. Sapova , A. K. Fedorov

We use a variational Monte Carlo algorithm to solve the electronic structure of two-dimensional semiconductor quantum dots in external magnetic field. We present accurate many-body wave functions for the system in various magnetic field…

Mesoscale and Nanoscale Physics · Physics 2009-11-11 Ari Harju

We introduce several improvements to the penalty-based variational quantum Monte Carlo (VMC) algorithm for computing electronic excited states of Entwistle $\textit{et al.}$ [M. T. Entwistle $\textit{et al.}$, Nat. Commun. $\textbf{14}$,…

Chemical Physics · Physics 2024-09-23 P. Bernát Szabó , Zeno Schätzle , Mike T. Entwistle , Frank Noé

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

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

Quantum Monte Carlo (QMC) methods have proven to be highly accurate for computing excited states, but the choice of optimization strategies for multiple states remains an active topic of investigation. In this work, we revisit the…

Computational Physics · Physics 2025-04-15 Stuart Shepard , Anthony Scemama , Saverio Moroni , Claudia Filippi

We extend Quantum Computing Quantum Monte Carlo (QCQMC) beyond ground-state energy estimation by systematically constructing the quantum circuits used for state preparation. Replacing the original Variational Quantum Eigensolver (VQE)…

In this communication, we propose a method for obtaining isolated excited states within the Full Configuration Interaction Quantum Monte Carlo framework. This method allows for stable sampling with respect to collapse to lower energy states…

Strongly Correlated Electrons · Physics 2014-10-10 George H. Booth , Garnet Kin-Lic Chan

A computational model is presented to calculate the ground state energy of neutral and charged excitons confined in semiconductor quantum dots. The model is based on the variational Quantum Monte Carlo method and effective mass…

Mesoscale and Nanoscale Physics · Physics 2021-02-03 Josep Planelles , Juan I. Climente

We introduce an extension of the time-dependent variational Monte Carlo (tVMC) method that adaptively controls the expressivity of the variational quantum state during the simulation of the dynamics. This adaptive tVMC (atVMC) approach is…

Quantum Physics · Physics 2026-01-09 Raffaele Salioni , Rocco Martinazzo , Davide Emilio Galli , Christian Apostoli

We introduce a variational Monte Carlo algorithm for approximating finite-temperature quantum many-body systems, based on the minimization of a modified free energy. This approach directly approximates the state at a fixed temperature,…

Quantum Physics · Physics 2025-02-18 Sirui Lu , Giacomo Giudice , J. Ignacio Cirac

We present a stable and systematically improvable quantum Monte Carlo (QMC) approach to calculating excited-state energies, which we implement using our fast randomized iteration method for the full configuration interaction problem…

Computational Physics · Physics 2023-10-03 Samuel M. Greene , Robert J. Webber , James E. T. Smith , Jonathan Weare , Timothy C. Berkelbach

It has become increasingly feasible to use quantum Monte Carlo (QMC) methods to study correlated fermion systems for realistic Hamiltonians. We give a summary of these techniques targeted at researchers in the field of correlated electrons,…

Strongly Correlated Electrons · Physics 2016-08-24 Lucas K. Wagner , David M. Ceperley

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

Quantum Monte Carlo methods are used to calculate various ground state properties of charged bosons in two dimensions, throughout the whole density range where the fluid phase is stable. Wigner crystallization is predicted at $r_s\simeq…

Condensed Matter · Physics 2018-05-01 S. De Palo , S. Conti , S. Moroni

We investigate the issue of optimization stability in variance-based state-specific variational Monte Carlo, discussing the roles of the objective function, the complexity of wave function ansatz, the amount of sampling effort, and the…

Chemical Physics · Physics 2022-12-20 Leon Otis , Eric Neuscamman