Use . The Dirichlet form of a Markov chain is
The equality follows by expanding the square and using row sums one and the stationary distribution identity. For the reversible Markov chain, detailed balance makes a self-adjoint operator, with real orthonormal eigenbasis and ordered eigenvalues .
Adding a constant changes neither the variance nor the Dirichlet form of a Markov chain. Expand the centered function as . Then
For every nonconstant the quotient is at least , and equality is attained at . This proves
Equivalently minimize the Dirichlet form of a Markov chain over centered unit-norm functions. This is the variational characterization underlying the Poincare inequality for a reversible Markov chain, and does not require the transition matrix to have nonnegative eigenvalues. For a one-state chain there is no nonconstant test function; the displayed minimization concerns .

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