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Ben Leimkuhler, Charles Matthews - Molecular Dynamics- With Deterministic and Stochastic Numerical Methods [RAR->PDF] [ENG]

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  Molecular Dynamics: With Deterministic and Stochastic Numerical Methods
 
Springer | Applied Mathematics Textbook | May 20 2015 | ISBN-10: 3319163744 | 443 pages | pdf | 11.76 mb
  
 

  by Ben Leimkuhler (Author), Charles Matthews (Author)
  From the Back Cover
  This book describes the
mathematical underpinnings of algorithms used for molecular dynamics simulation, including both deterministic and
stochastic numerical methods. Molecular dynamics is one of the most versatile and powerful methods of modern
computational science and engineering and is used widely in chemistry, physics, materials science and biology.
Understanding the foundations of numerical methods means knowing how to select the best one for a given problem (from
the wide range of techniques on offer) and how to create new, efficient methods to address particular challenges as they
arise in complex applications. 
  
  Aimed at a broad audience, this book presents the basic theory of
Hamiltonian mechanics and stochastic differential equations, as well as topics including symplectic numerical methods,
the handling of constraints and rigid bodies, the efficient treatment of Langevin dynamics, thermostats to control the
molecular ensemble, multiple time-stepping, and the dissipative particle dynamics method. 
  
  About the
Author
  Benedict Leimkuhler has worked extensively for more than two decades on the study of molecular dynamics
algorithms. He is the author of research publications on constrained molecular dynamics, temperature controls,
stochastic molecular dynamics methods, quantum methods, and advanced integration strategies (multiple time-stepping,
adaptive methods). He currently holds the Chair of Applied Mathematics at the University of Edinburgh, is a Fellow of
the Royal Society of Edinburgh and a Fellow of the Institute of Mathematics and Its Applications, and is on the
editorial boards of four journals.
  
  Charles Matthews obtained his PhD in applied mathematics from the
University of Edinburgh, working in the area of numerical methods for stochastic differential equations. He has
published research in both chemical physics and mathematics journals on discretization problems in molecular dynamics.
He currently is a research staff member in the Department of Statistics at the University of Chicago, investigating
sampling methodologies for molecular simulation and the modelling of power networks.
  
  Topics
 
Applications of Mathematics
  Mathematical and Computational Biology
   						

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