Abstract
If one considers a random variable which depends on time, one is led to the concept of a stochastic process. After the definition of a general stochastic process in Sect. 5.1, we introduce the class of Markov processes. In Sect. 5.2 the master equation is formulated, an equation describing the time evolution of the probability density of a Markov process. In this context, the relevance of the master equation for the description of the dynamics of general open systems will be emphasized.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Honerkamp, J. (2002). Time-Dependent Random Variables: Classical Stochastic Processes. In: Statistical Physics. Advanced Texts in Physics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-04763-7_5
Download citation
DOI: https://doi.org/10.1007/978-3-662-04763-7_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-07703-6
Online ISBN: 978-3-662-04763-7
eBook Packages: Springer Book Archive