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Stochastic Processes for Physicists

Stochastic Processes for Physicists

Stochastic Processes for Physicists

Understanding Noisy Systems
Kurt Jacobs, University of Massachusetts, Boston
February 2010
Hardback
9780521765428
AUD$80.86
exc GST
Hardback
USD
eBook

    Stochastic processes are an essential part of numerous branches of physics, as well as in biology, chemistry, and finance. This textbook provides a solid understanding of stochastic processes and stochastic calculus in physics, without the need for measure theory. In avoiding measure theory, this textbook gives readers the tools necessary to use stochastic methods in research with a minimum of mathematical background. Coverage of the more exotic Levy processes is included, as is a concise account of numerical methods for simulating stochastic systems driven by Gaussian noise. The book concludes with a non-technical introduction to the concepts and jargon of measure-theoretic probability theory. With over 70 exercises, this textbook is an easily accessible introduction to stochastic processes and their applications, as well as methods for numerical simulation, for graduate students and researchers in physics.

    • Provides a solid understanding of stochastic processes and stochastic calculus in physics, without the need for measure theory
    • Gives readers the tools necessary to use stochastic methods in research with a minimum of mathematical background
    • Concludes with a non-technical introduction to the concepts and jargon of measure-theoretic probability theory

    Reviews & endorsements

    'Jacobs is an enthusiastic, clear, and concise writer. He presents each theory by means of heuristic arguments and calculations.' Cosma Shalizi, Physics Today

    'I think this book is a very nice introduction to the subject of stochastic processes.' Zentralblatt MATH

    See more reviews

    Product details

    September 2010
    Adobe eBook Reader
    9780511686344
    0 pages
    0kg
    17 b/w illus. 73 exercises
    This ISBN is for an eBook version which is distributed on our behalf by a third party.

    Table of Contents

    • 1. A review of probability theory
    • 2. Differential equations
    • 3. Stochastic equations with Gaussian noise
    • 4. Further properties of stochastic processes
    • 5. Some applications of Gaussian noise
    • 6. Numerical methods for Gaussian noise
    • 7. Fokker–Planck equations and reaction-diffusion systems
    • 8. Jump processes
    • 9. Levy processes
    • 10. Modern probability theory
    • Appendix
    • References
    • Index.