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Stochastic Simulations of Clusters

Stochastic Simulations of Clusters

Stochastic Simulations of Clusters
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Stochastic Simulations of Clusters Papeback -

by Emanuele Curotto

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pp. 696 . Papeback. New.
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Details

  • Title Stochastic Simulations of Clusters
  • Author Emanuele Curotto
  • Binding Papeback
  • Condition New
  • Pages 696
  • Volumes 1
  • Language ENG
  • Publisher CRC Press
  • Publication date pp. 696
  • Illustrated Yes
  • Features Bibliography, Illustrated
  • Bookseller's Inventory # 6378268490
  • ISBN 9781138112414 / 1138112410
  • Weight 2.12 lbs (0.96 kg)
  • Dimensions 9.21 x 6.14 x 1.4 in (23.39 x 15.60 x 3.56 cm)
  • Themes
    • Aspects (Academic): Science/Technology Aspects
  • Category Science
  • Dewey Decimal Code 539.601
  • Quantity available 4

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Reader reviews for Stochastic Simulations of Clusters

From the publisher

Unravels Complex Problems through Quantum Monte Carlo Methods

Clusters hold the key to our understanding of intermolecular forces and how these affect the physical properties of bulk condensed matter. They can be found in a multitude of important applications, including novel fuel materials, atmospheric chemistry, semiconductors, nanotechnology, and computational biology. Focusing on the class of weakly bound substances known as van derWaals clusters or complexes, Stochastic Simulations of Clusters: Quantum Methods in Flat and Curved Spaces presents advanced quantum simulation techniques for condensed matter.

The book develops finite temperature statistical simulation tools and real-time algorithms for the exact solution of the Schrdinger equation. It draws on potential energy models to gain insight into the behavior of minima and transition states. Using Monte Carlo methods as well as ground state variational and diffusion Monte Carlo (DMC) simulations, the author explains how to obtain temperature and quantum effects. He also shows how the path integral approach enables the study of quantum effects at finite temperatures.

To overcome timescale problems, this book supplies efficient and accurate methods, such as diagonalization techniques, differential geometry, the path integral method in statistical mechanics, and the DMC approach. Gleaning valuable information from recent research in this area, it presents special techniques for accelerating the convergence of quantum Monte Carlo methods.

About the author

Emanuele Curotto is a professor of chemistry at Arcadia University in Glenside, Pennsylvania.

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