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Present quantum Monte Carlo codes use statistical techniques adapted to find the amplitude of a quantum system or the associated eigenvalues. Thus, they do not use a true physical random source. It is demonstrated that, in fact, quantum…

Quantum Physics · Physics 2007-05-23 J. M. A. Figueiredo

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

The accurate computation of forces and other energy derivatives has been a long-standing challenge for quantum Monte Carlo methods. A number of technical obstacles contribute to this challenge. We discuss how these obstacles can be removed…

Materials Science · Physics 2023-05-29 Siyuan Chen , Shiwei Zhang

This chapter is devoted to the computation of equilibrium (thermodynamic) properties of quantum systems. In particular, we will be interested in the situation where the interaction between particles is so strong that it cannot be treated as…

Mesoscale and Nanoscale Physics · Physics 2016-02-03 Alexei Filinov , Jens Böning , Michael Bonitz

The diffusion Monte Carlo method with symmetry-based state selection is used to calculate the quantum energy states of H$_2^+$ confined into potential barriers of atomic dimensions (a model for these ions in solids). Special solutions are…

Chemical Physics · Physics 2019-04-03 Gaia Micca Longo , Savino Longo , Domenico Giordano

Monte Carlo simulations are widely used in many areas including particle accelerators. In this lecture, after a short introduction and reviewing of some statistical backgrounds, we will discuss methods such as direct inversion, rejection…

Computational Physics · Physics 2020-06-19 Ji Qiang

Direct sampling of multi-dimensional systems with quantum Monte Carlo methods allows exact account of many-body effects or particle correlations. The most straightforward approach to solve the Schr\"odinger equation, Diffusion Monte Carlo,…

Quantum Physics · Physics 2017-09-07 Ilkka Ruokosenmäki , Tapio T. Rantala

Closed-form stochastic filtering equations can be derived in a general setting where probability distributions are replaced by some specific outer measures. In this article, we study how the principles of the sequential Monte Carlo method…

Methodology · Statistics 2018-05-07 Jeremie Houssineau , Branko Ristic

A self-contained and tutorial presentation of the diffusion Monte Carlo method for determining the ground state energy and wave function of quantum systems is provided. First, the theoretical basis of the method is derived and then a…

Computational Physics · Physics 2009-10-30 Ioan Kosztin , Byron Faber , Klaus Schulten

We present a set of new numerical methods that are relevant to calculating radiation pressure terms in hydrodynamics calculations, with a particular focus on massive star formation. The radiation force is determined from a Monte Carlo…

Solar and Stellar Astrophysics · Physics 2015-06-23 Tim J. Harries

In this review we discuss, from a unified point of view, a variety of Monte Carlo methods used to solve eigenvalue problems in statistical mechanics and quantum mechanics. Although the applications of these methods differ widely, the…

Condensed Matter · Physics 2011-05-21 M. P. Nightingale , C. J. Umrigar

Quantum Monte Carlo methods are first-principle approaches that approximately solve the Schr\"odinger equation stochastically. As compared to traditional quantum chemistry methods, they offer important advantages such as the ability to…

Chemical Physics · Physics 2020-02-11 Jonas Feldt , Claudia Filippi

Here the recently proposed time-dependent quantum Monte Carlo method is applied to three dimensional para- and ortho-helium atoms subjected to an external electromagnetic field with amplitude sufficient to cause significant ionization. By…

Atomic Physics · Physics 2025-02-05 Ivan P. Christov

Quantum impurity models describe an atom or molecule embedded in a host material with which it can exchange electrons. They are basic to nanoscience as representations of quantum dots and molecular conductors and play an increasingly…

Strongly Correlated Electrons · Physics 2011-05-09 Emanuel Gull , Andrew J. Millis , Alexander I. Lichtenstein , Alexey N. Rubtsov , Matthias Troyer , Philipp Werner

We introduce a novel computational approach for the investigation of complex correlated electron materials which makes it possible to evaluate interatomic forces and thereby determine atomic displacements and structural transformations…

Strongly Correlated Electrons · Physics 2014-04-24 I. Leonov , V. I. Anisimov , D. Vollhardt

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

The concept of molecular similarity appears in many machine-learning algorithms based on the assumption that molecules with similar representations will also share similar properties. In this work, we propose a new way to study similarity…

Chemical Physics · Physics 2025-02-07 Jan Weinreich , Konstantin Karandashev , Guido Falk von Rudorff

Contemporary scientific studies often rely on the understanding of complex quantum systems via computer simulation. This paper initiates the statistical study of quantum simulation and proposes a Monte Carlo method for estimating…

Applications · Statistics 2011-08-04 Yazhen Wang

Techniques for simulating molecules whose conformations satisfy constraints are presented. A method for selecting appropriate moves in Monte Carlo simulations is given. The resulting moves not only obey the constraints but also maintain…

Computational Physics · Physics 2007-05-23 Charles F. F. Karney , Jason E. Ferrara

Fixed-node diffusion Monte Carlo (DMC) is a stochastic algorithm for finding the lowest energy many-fermion wave function with the same nodal surface as a chosen trial function. It has proved itself among the most accurate methods available…

Condensed Matter · Physics 2009-10-31 W. M. C. Foulkes , Randolph Q. Hood , R. J. Needs