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In order to find the equilibrium geometries of molecules and solids and to perform ab initio molecular dynamics, it is necessary to calculate the forces on the nuclei. We present a correlated sampling method to efficiently calculate…

Condensed Matter · Physics 2009-10-31 Claudia Filippi , C. J. Umrigar

We describe a simple scheme to perform phonon calculations with quantum Monte Carlo (QMC) methods, and demonstrate it on metallic hydrogen. Because of the energy and length scales of metallic hydrogen, and the statistical noise inherent to…

Materials Science · Physics 2022-01-25 Kevin Ly , David Ceperley

Quantum Monte Carlo (QMC) methods are some of the most accurate methods for simulating correlated electronic systems. We investigate the compatibility, strengths and weaknesses of two such methods, namely, diffusion Monte Carlo (DMC) and…

Computational Physics · Physics 2020-10-14 Fionn D. Malone , Anouar Benali , Miguel A. Morales , Michel Caffarel , P. R. C. Kent , Luke Shulenburger

We present a study of mono(benzene)TM and bis(benzene)TM systems, where TM={Mo,W}. We calculate the binding energies by quantum Monte Carlo (QMC) approaches and compare the results with other methods and available experiments. The orbitals…

Chemical Physics · Physics 2017-12-01 M. Chandler Bennett , Adem H. Kulahlioglu , Lubos Mitas

Quantum Monte Carlo (QMC) forces have been studied extensively in recent decades because of their importance with spectroscopic observables and geometry optimization. Here we benchmark the accuracy and statistical cost of QMC forces. The…

Computational Physics · Physics 2021-06-16 Juha Tiihonen , Raymond C. Clay , Jaron T. Krogel

Employing a classical density-functional description of liquid environments, we introduce a rigorous method for the diffusion quantum Monte Carlo calculation of free energies and thermodynamic averages of solvated systems that requires…

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

Accurately predicting the formation energy of a compound, which describes its thermodynamic stability, is a key challenge in materials physics. Here, we employ many-body quantum Monte Carlo (QMC) with single-reference trial functions to…

Computational methods both open the frontiers of economic analysis and serve as a bottleneck in what can be achieved. We are the first to study whether Quantum Monte Carlo (QMC) algorithm can improve the runtime of economic applications and…

Quantum Physics · Physics 2024-09-24 Vladimir Skavysh , Sofia Priazhkina , Diego Guala , Thomas R. Bromley

Computer simulation plays a central role in modern day materials science. The utility of a given computational approach depends largely on the balance it provides between accuracy and computational cost. Molecular crystals are a class of…

In the past decade, quantum diffusion Monte Carlo (DMC) has been demonstrated to successfully predict the energetics and properties of a wide range of molecules and solids by numerically solving the electronic many-body Schr\"odinger…

Chemical Physics · Physics 2023-03-10 Bing Huang , O. Anatole von Lilienfeld , Jaron T. Krogel , Anouar Benali

Nuclear physics seeks to describe both bound and unbound states within a unified predictive framework. While coordinate-space Quantum Monte Carlo (QMC) methods have successfully computed bound states for systems with $A \leq 12$, their…

Nuclear Theory · Physics 2025-02-27 Abraham R. Flores , Kenneth M. Nollett , Maria Piarulli

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

Although liquid water is ubiquitous in chemical reactions at roots of life and climate on the earth, the prediction of its properties by high-level ab initio molecular dynamics simulations still represents a formidable task for quantum…

Chemical Physics · Physics 2015-04-22 Andrea Zen , Ye Luo , Guglielmo Mazzola , Leonardo Guidoni , Sandro Sorella

Quantum Monte Carlo (QMC) methods have received considerable attention over the last decades due to their great promise for providing a direct solution to the many-body Schrodinger equation in electronic systems. Thanks to their low scaling…

Chemical Physics · Physics 2013-03-28 M. A. Morales , J. McMinis , B. K. Clark , J. Kim , G. Scuseria

Deep learning has deeply changed the paradigms of many research fields. At the heart of chemical and physical sciences is the accurate ab initio calculation of many-body wavefunction, which has become one of the most notable examples to…

Chemical Physics · Physics 2025-04-01 Yubing Qian , Xiang Li , Zhe Li , Weiluo Ren , Ji Chen

Quantum Monte Carlo (QMC) is a family of powerful tools for addressing quantum many-body problems. However, its applications are often plagued by the fermionic sign problem. A promising strategy is to simulate an interaction without sign…

Nuclear Theory · Physics 2025-05-01 Jun Liu , Teng Wang , Bing-Nan Lu

We present high-accuracy correlated calculations of small Si$_x$H$_y$ molecular systems both in the ground and excited states. We employ quantum Monte Carlo (QMC) together with a variety of many-body wave function approaches based on basis…

Chemical Physics · Physics 2020-10-21 Guangming Wang , Abdulgani Annaberdiyev , Lubos Mitas

A quantum Monte Carlo study of the atomization energies for the G2 set of molecules is presented. Basis size dependence of diffusion Monte Carlo atomization energies is studied with a single determinant Slater-Jastrow trial wavefunction…

Chemical Physics · Physics 2015-06-04 F. R. Petruzielo , Julien Toulouse , C. J. Umrigar

In this work, we test a recently developed method to enhance classical auxiliary-field quantum Monte Carlo (AFQMC) calculations with quantum computers against examples from chemistry and material science, representatives of classes of…