Markov Processes: An Introduction for Physical Scientists by Daniel T. GillespieMarkov Processes: An Introduction for Physical Scientists by Daniel T. Gillespie

Markov Processes: An Introduction for Physical Scientists

byDaniel T. Gillespie, Daniel T. Gillespie

Other | December 2, 1991

Pricing and Purchase Info

$64.79 online 
$81.00 list price save 20%
Earn 324 plum® points

In stock online

Ships free on orders over $25

Not available in stores


Markov process theory is basically an extension of ordinary calculus to accommodate functions whos time evolutions are not entirely deterministic. It is a subject that is becoming increasingly important for many fields of science. This book develops the single-variable theory of both continuous and jump Markov processes in a way that should appeal especially to physicists and chemists at the senior and graduate level.
  • A self-contained, prgamatic exposition of the needed elements of random variable theory
  • Logically integrated derviations of the Chapman-Kolmogorov equation, the Kramers-Moyal equations, the Fokker-Planck equations, the Langevin equation, the master equations, and the moment equations
  • Detailed exposition of Monte Carlo simulation methods, with plots of many numerical examples
  • Clear treatments of first passages, first exits, and stable state fluctuations and transitions
  • Carefully drawn applications to Brownian motion, molecular diffusion, and chemical kinetics
Title:Markov Processes: An Introduction for Physical ScientistsFormat:OtherDimensions:592 pages, 1 × 1 × 1 inPublished:December 2, 1991Publisher:Elsevier ScienceLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0080918379

ISBN - 13:9780080918372


Table of Contents

Random Variable Theory General Features of a Markov Process Continuous Markov Processes Jump Markov Processes with Continuum States Jump Markov Processes with Discrete States Temporally Homogeneous Birth-Death Markov Processes Appendixes: Some Useful Integral Identities Integral Representations of the Delta Functions An Approximate Solution Procedure for "Open" Moment Evolution Equations Estimating the Width and Area of a Function Peak Can the Accuracy of the Continuous Process Simulation Formula Be Improved? Proof of the Birth-Death Stability Theorem Solution of the Matrix Differential Equation