TY - JOUR
T1 - Transitions States of Stochastic Chemical Kinetic Systems
AU - Du , Jun
AU - Liu , Di
JO - Communications in Computational Physics
VL - 2
SP - 606
EP - 627
PY - 2020
DA - 2020/12
SN - 29
DO - http://doi.org/10.4208/cicp.OA-2019-0014
UR - https://global-sci.org/intro/article_detail/cicp/18476.html
KW - Transition path theory, Markov chain, reacting network.
AB - <p style="text-align: justify;">Based on Transition Path Theory (TPT) for Markov jump processes [1, 2],
we develop a general approach for identifying and calculating Transition States (TS)
of stochastic chemical reacting networks. We first extend the concept of probability
current, originally defined on edges connecting different nodes in the configuration
space [2], to each sub-network. To locate sub-networks with maximal probability current on the separatrix between reactive and non-reactive events, which will give the
Transition States of the reaction, constraint optimization is conducted. We further introduce an alternative scheme to compute the transition pathways by topological sorting, which is shown to be highly efficient through analysis.</p>