Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Approximate Numerical Integration of the Chemical Master Equation for
  Stochastic Reaction Networks   Numerical solution of the chemical master equation for stochastic reaction
networks typically suffers from the state space explosion problem due to the
curse of dimensionality and from stiffness due to multiple time scales. The
dimension of the state space equals the number of molecular species involved in
the reaction network and the size of the system of differential equations
equals the number of states in the corresponding continuous-time Markov chain,
which is usually enormously huge and often even infinite. Thus, efficient
numerical solution approaches must be able to handle huge, possibly infinite
and stiff systems of differential equations efficiently. We present an
approximate numerical integration approach that combines a dynamical state
space truncation procedure with efficient numerical integration schemes for
systems of ordinary differential equations including adaptive step size
selection based on local error estimates. The efficiency and accuracy is
demonstrated by numerical examples.

22
The categories of this paper are: chao-dyn
23
The categories of this paper are: solv-int
3
The categories of this paper are: physics
8
The categories of this paper are: hep-ex
9
The categories of this paper are: nlin
7
The categories of this paper are: hep-th
13
The categories of this paper are: quant-ph
32
The categories of this paper are: atom-ph
33
The categories of this paper are: plasm-ph
16
The categories of this paper are: stat
12
The categories of this paper are: nucl-th
37
The categories of this paper are: supr-con
4
The categories of this paper are: cond-mat
21
The categories of this paper are: adap-org
36
The categories of this paper are: cmp-lg
27
The categories of this paper are: comp-gas