Quantum Monte Carlo origins, development, applications

Cover of: Quantum Monte Carlo |

Published by Oxford University Press in New York .

Written in English

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Subjects:

  • Monte Carlo method -- Abstracts.,
  • Quantum theory -- Abstracts.

Edition Notes

Includes index.

Book details

Statementby James B. Anderson.
GenreAbstracts.
ContributionsAnderson, James B., 1935-
Classifications
LC ClassificationsQC20.7.M65 Q37 2006
The Physical Object
Paginationp. cm.
ID Numbers
Open LibraryOL17931185M
ISBN 100195310101
ISBN 109780195310108
LC Control Number2006040145

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One of the most challenging problems in the field of quantum Monte Carlo techniques, the negative-sign problem, is also discussed and new methods proposed to partially overcome it. In addition, low-dimensional quantum spin systems are studied. The origins of Quantum Monte Carlo methods are often attributed to Enrico Fermi and Robert Richtmyer who developed in a mean field particle interpretation of neutron-chain reactions, but the first heuristic-like and genetic type particle algorithm (a.k.a.

Resampled or Reconfiguration Monte Carlo methods) for estimating ground state energies of quantum systems (in reduced matrix models) is due. Over the past several decades, computational approaches to studying strongly-interacting systems have become increasingly varied and sophisticated.

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Thijssen. Also, one good package for some Monte Carlo simulations is the ALPS of the codes are written in C++. Quantum Monte Carlo Methods in Equilibrium and Nonequilibrium Systems Proceedings of the Ninth Taniguchi International Symposium, Susono, Japan, November 14–18, This invaluable book consists of 16 chapters written by some of the most notable researchers in the field of quantum Monte Carlo, highlighting the advances made since Lester Jr.'s monograph with the same title.

It may be regarded as the proceedings of the Symposium on Advances in Quantum Monte 2/5(1). ISBN: OCLC Number: Description: ix, pages: illustrations ; 24 cm.

Contents: Fixed-node and fixed-phase approximations and their relationship to variable spins in quantum Monte Carlo / Cody A. Melton and Lubos Mitas --Using CIPSI nodes in diffusion Monte Carlo / Michel Caffarel, Thomas Applencourt, Emmanuel Giner, and Anthony Scemama --Interpolated wave.

Quantum Computing Algorithms for Artificial Intelligence Dr. Amit Ray explains the quantum annealing, Quantum Monte Carlo Tree Search, Quantum algorithms for traveling salesman problems, and Quantum algorithms for gradient descent problems in depth.

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The equations often are applied assuming that quantum exchange does not matter (the particles are assumed to be Boltzmann particles, not the physically realistic fermion and boson particles).

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