A Probabilistic Approach to Carne’s Bound

Carne’s bound is a sharp inequality controlling the transition probabilities for a discrete reversible Markov chain (Section 1). Its ordinary proof uses spectral techniques which look as efficient as miraculous. Here we present a new proof, comparing a “drift” for ways “out” and “back”, to get the gaussian part of the bound (Section 2), and using a conditioning technique to get the flight factor (Section 4). Moreover we show how our proof is more “supple” than Carne’s one and may generalize (Section 3.2).