Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
521164 | Journal of Computational Physics | 2010 | 18 Pages |
Abstract
Solving chemical master equations numerically on a large state space is known to be a difficult problem because the huge number of unknowns is far beyond the capacity of traditional methods. We present an adaptive method which compresses the problem very efficiently by representing the solution in a sparse wavelet basis that is updated in each step. The step-size is chosen adaptively according to estimates of the temporal and spatial approximation errors. Numerical examples demonstrate the reliability of the error estimation and show that the method can solve large problems with bimodal solution profiles.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Tobias Jahnke, Tudor Udrescu,