Dayar TuğrulOrhan, M. C.2019-02-212019-02-21201897833197494640302-9743http://hdl.handle.net/11693/50139Conference name: 19th International GI/ITG Conference, MMB 2018Date of Conference: February 26-28, 2018The problem of computing the transient probability distribution of countably infinite multidimensional continuous-time Markov chains (CTMCs) arising in systems of stochastic chemical kinetics is addressed by a software tool. Starting from an initial probability distribution, time evolution of the probability distribution associated with the CTMC is described by a system of linear first-order ordinary differential equations, known as the chemical master equation (CME). The solver for the CME uses the time stepping implicit backward differentiation formulae (BDF). Solution vectors in BDF can be stored compactly during transient analysis in one of the Hierarchical Tucker Decomposition, Quantized Tensor Train, or Transposed Quantized Tensor Train formats.EnglishBackward differentiationChemical master equationCompact vectorContinuous-time Markov chainKronecker decompositionConference Paper10.1007/978-3-319-74947-1_2410.1007/978-3-319-74947-11611-3349