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Proposition 10.6 -- the commute time identity

Proved
MarkovMixing.commute_time_identity

by Shuze Chen · Aug 21, 2026 · Mathlib 0df444a (Lean v4.33.1)

markov-chainsmixing-timesprobability

Let ccc be a network on a finite vertex set VVV: a symmetric nonnegative conductance function with total vertex conductance c(x)=∑yc(x,y)>0c(x)=\sum_yc(x,y)>0c(x)=∑y​c(x,y)>0 everywhere, carrying the irreducible walk P(x,y)=c(x,y)/c(x)P(x,y)=c(x,y)/c(x)P(x,y)=c(x,y)/c(x). Write cG=∑xc(x)c_G=\sum_xc(x)cG​=∑x​c(x) for the total conductance of the network, Ea(τb)\mathbb E_a(\tau_b)Ea​(τb​) for the expected number of steps for the walk started at aaa to first reach bbb, and R(a↔b)R(a\leftrightarrow b)R(a↔b) for the effective resistance, defined through the voltage W(x)=Px{τa<τb}W(x)=\mathbb P_x\{\tau_a<\tau_b\}W(x)=Px​{τa​<τb​} and current ∥I∥=∑yc(a,y)[W(a)−W(y)]\|I\|=\sum_yc(a,y)[W(a)-W(y)]∥I∥=∑y​c(a,y)[W(a)−W(y)] as R(a↔b)=∥I∥−1R(a\leftrightarrow b)=\|I\|^{-1}R(a↔b)=∥I∥−1.

The theorem (the Commute Time Identity, Proposition 10.6 of Levin–Peres–Wilmer, the capstone of Chapters 9–11) asserts: for any two distinct vertices a≠ba\ne ba=b,

Ea(τb)+Eb(τa)  =  cG  R(a↔b).\mathbb E_a(\tau_b)+\mathbb E_b(\tau_a)\;=\;c_G\;R(a\leftrightarrow b).Ea​(τb​)+Eb​(τa​)=cG​R(a↔b).

The expected round-trip time between two vertices is exactly the total conductance times the effective resistance between them. This single identity converts the entire electrical toolkit — series/parallel reduction, Thomson's principle, Rayleigh monotonicity — into exact computations and bounds for hitting and cover times of reversible chains.

Preamble
import Definitions.Def_mm_network
Formal statement
namespace MarkovMixing

/-- **Proposition 10.6, the Commute Time Identity** (LPW), the capstone of
Chapters 9–11: for the random walk on a network,
`E_a(τ_b) + E_b(τ_a) = c_G · R(a ↔ b)`. -/
theorem commute_time_identity {V : Type*} [Fintype V] [DecidableEq V]
    (c : V → V → ℝ) (hc : IsConductance c)
    (hpos : ∀ x : V, 0 < vertexConductance c x)
    (hirr : Irreducible (networkWalk c)) (a b : V) (hab : a ≠ b) :
    expSetHitTime (networkWalk c) a {b} + expSetHitTime (networkWalk c) b {a} =
      totalConductance c * effectiveResistance c a b := by
  sorry

end MarkovMixing
Source
D. A. Levin, Y. Peres, E. L. Wilmer, Markov Chains and Mixing Times, AMS 2009, https://documents.epfl.ch/groups/i/ip/ipg/www/2013-2014/Random_Walks/markovmixing.pdf, Section 10.3, Proposition 10.6, Eq. (10.8), p. 130

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