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Simplification of irreversible Markov chains by removal of states with fast leaving rates
1Beijing Computational Science Research Center, Beijing 100094, PR China; Department of Mathematical Sciences, The University of Texas at Dallas, Richardson, TX 75080, USA.
Abstract:
In the recent work of Ullah et al. (2012a), the authors developed an effective method to simplify reversible Markov chains by removal of states with low equilibrium occupancies. In this paper, we extend this result to irreversible Markov chains. We show that an irreversible chain can be simplified by removal of states with fast leaving rates. Moreover, we reveal that the irreversibility of the chain will always decrease after model simplification. This suggests that although model simplification can retain almost all the dynamic information of the chain, it will lose some thermodynamic information as a trade-off. Examples from biology are also given to illustrate the main results of this paper.
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