Metastability of finite state Markov chains: a recursive procedure to identify slow variables for model reduction

preprint2015arXivOpen access

Abstract

Consider a sequence (ηN(t):t≥0)(η^N(t) :t\ge 0) of continuous-time, irreducible Markov chains evolving on a fixed finite set EE, indexed by a parameter NN. Denote by RN(η,ξ)R_N(η,ξ) the jump rates of the Markov chain ηtNη^N_t, and assume that for any pair of bonds (η,ξ)(η,ξ), (η′,ξ′)(η',ξ') arctan⁡{RN(η,ξ)/RN(η′,ξ′)}\arctan \{R_N(η,ξ)/R_N(η',ξ')\} converges as N↑∞N\uparrow\infty. Under a hypothesis slightly more restrictive (cf. \eqref{mhyp} below), we present a recursive procedure which provides a sequence of increasing time-scales $θ^1_N, \dots, θ^{\mf p}_N$, θNj≪θNj+1θ^j_N \ll θ^{j+1}_N, and of coarsening partitions $\{\ms E^j_1, \dots, \ms E^j_{\mf n_j}, Δ^j\}$, $1\le j\le \mf p$, of the set EE. Let $ϕ_j: E \to \{0,1, \dots, \mf n_j\}$ be the projection defined by $ ϕ_j(η) = \sum_{x=1}^{\mf n_j} x \, \mb 1\{η\in \ms E^j_x\}$. For each $1\le j\le \mf p$, we prove that the hidden Markov chain XNj(t)=ϕj(ηN(tθNj))X^j_N(t) = ϕ_j(η^N(tθ^j_N)) converges to a Markov chain on $\{1, \dots, \mf n_j\}$.

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