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.
Key Features * 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
Daniel T. Gillespie
Most Helpful Customer Reviews
I have read and worked through much of Gillespie's book. It was exactly what I needed in the way of a meaty but clear and accessible introduction to the subject. I know of no other book like it. There are good books that are more mathematically oriented (Okesendahl), that outline rather than narrate (Gardiner), and that introduce a more limited content (my own), but there is nothing like Gillespie's book: introductory yet wide-ranging content. It was perfect for this physicist who wanted to be introduced to the details of the subject.
This is the most readable introduction to Markov processes I have found.
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