R2 Reversible coarse dynamics
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Let \(Q\) be a finite Markov generator acting on column probability vectors, let \((B_a)\) be a partition into nonempty blocks, and let \(C_{ai}={{\boldsymbol{1}}}_{i\in B_a}\). Strong lumpability means \(CQ=\overline Q C\) for a coarse Markov generator. For observables, the backward generator is \(Q^T\); weighted \(L^2\) inner products use the stated stationary probability.
Theorem R2.1: Reversibility descends
Assume \(Q\) is strongly lumpable and reversible with respect to a positive stationary distribution \(\pi\), so
Define
Then \(\overline\pi\) is stationary for \(\overline Q\), and
Thus the coarse chain is reversible.
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Proof of Theorem R2.1
Stationarity follows from
For reversibility, use the aggregate rate formula:
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Corollary R2.2: Coarse Dirichlet form
Under the hypotheses of Theorem R2.1, let \(Jg\) be the fine function that is constant with value \(g_a\) on \(B_a\). Then
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Proof of Corollary R2.2
Expand the left side and group the fine indices by their coarse blocks. The aggregate rate criterion converts the resulting sums into the coarse generator entries.
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