Introduction to the Fast Multipole Method : Topics in Computational Biophysics, Theory, and Implementation

Victor Anisimov

ISBN 10: 1032337400 / ISBN 13: 9781032337401

Edité par CRC Press, 2022

A propos de cet article

nach der Bestellung gedruckt Neuware - Printed after ordering - Introduction to the Fast Multipole Method introduces the reader to the theory and computer implementation of the Fast Multipole Method. It covers the topics of Laplace's equation, spherical harmonics, angular momentum, the Wigner matrix, the addition theorem for solid harmonics, and lattice sums for periodic boundary conditions, along with providing a complete, self-contained explanation of the math of the method, so that anyone having an undergraduate grasp of calculus should be able to follow the material presented. The authors derive the Fast Multipole Method from first principles and systematically construct the theory connecting all the parts.Key FeaturesIntroduces each topic from first principlesDerives every equation presented, and explains each step in its derivationBuilds the necessary theory in order to understand, develop, and use the methodDescribes the conversion from theory to computer implementationGuides through code optimization and parallelization.

N° de réf. du vendeur 9781032337401

Détails bibliographiques

• Titre: Introduction to the Fast Multipole Method : Topics in Computational Biophysics, Theory, and Implementation
• Éditeur: CRC Press
• Date de parution: 2022
• Langue: anglais
• ISBN à 10 chiffres: 1032337400
• ISBN à 13 chiffres: 9781032337401
• Reliure: Taschenbuch
• État de l'article: Neu

A propos de ce titre

Synopsis

This book introduces the reader to the theory and methodology of quantum-mechanical modeling of chemical and biological systems. Given the immense complexity of such systems, there is a constant search for new methods.

À propos de l?auteur

Victor Anisimov is an Application Performance Engineer at the Argonne Leadership Computing Facility. He holds a Ph.D. degree in Physical Chemistry from the Institute of Chemical Physics of the Russian Academy of Sciences (1997), which was followed by 5 years of computational chemistry software development with Fujitsu, where his team developed the linear scaling semi-empirical quantum chemistry code LocalSCF that expanded the limits of the approximate electronic structure theory to millions of atoms. He performed postdoctoral work at the University of Maryland at Baltimore (2003-2008), and at the University of Texas at Houston (2008-2011), improving molecular dynamics methods and contributing to the CHARMM code. In the National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign (2011-2019), Dr. Anisimov held the position of Senior Research Scientist, conducted application support for petascale resource allocation teams on the Blue Waters supercomputer, optimized various application codes, and improved the performance and scaling profiles of coupled cluster singles and doubles electronic structure method in NWChem code. Dr. Anisimov works on the faithful representation of long-range electrostatic interactions in large-scale molecular simulations, near-neighbor communication algorithms, and linear-scaling methods. He specializes in performance optimization and fidelity improvements of electronic structure and soft matter simulation application codes on exascale platforms.

James J. P. Stewart pioneered the use of semiempirical quantum chemistry methods in research and teaching. After teaching at the University of Strathclyde in Glasgow, Scotland, he became a researcher at the United States Air Force Academy, then taught as an adjoint professor at the University of Colorado. For the past 30 years, his company, Stewart Computational Chemistry, has been marketing his program, MOPAC, which now has over 30,000 licensed users and groups worldwide. Dr. Stewart has authored over 150 research papers and his works have been cited over 38,000 times.