Stochastic Simulations of Clusters

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A01=Emanuele Curotto
advanced quantum simulation techniques
Atomic Clusters
Author_Emanuele Curotto
Average Potential Energy
Basics of Classical Dynamics
Basin Hopping
call
Canonical Partition Function
Category=PHFC
Category=PHQ
Category=PNR
condensed matter simulation
Cos? Sin
Cosφ Sin
enddo
Enddo Enddo
energy
eq_bestseller
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_science
finite temperature algorithms
FORTRAN Essentials
Ground State Energy
Hamiltonian Matrix
Harmonic Oscillator
Heat Capacity
Holonomic Constraints
integral
intermolecular forces modeling
Laplace Beltrami Operator
Lie Algebra
Matrix Quantum Mechanics
Metropolis Algorithm
nanotechnology applications
Optical Activity
parallel
Parallel Tempering
Partition Function
path
Path Integral Simulations
Pi
pot
potential
Potential Energy Surfaces
quantum Monte Carlo
Quantum Simulations
R0 Rij
Return End
Spherical Top
statistical mechanics methods
Stereographic Projection
surface
tempering
The Basics of Stochastic Computations
Trial Wavefunction

Product details

  • ISBN 9781138112414
  • Weight: 1290g
  • Dimensions: 156 x 234mm
  • Publication Date: 13 Jun 2017
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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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 Schrödinger 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.

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

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