Markov chain mixing times
Edited by Reza Gheissari and Anna Ben Hamou
In general, we will use the following notation in the problem list. We consider aperiodic irreducible Markov chains on a state space, \Omega with unique invariant (stationary) distribution \pi. In the discrete time setting we allow the matrix (P)_{x,y\in\Omega} with P_{xy}=P(x,y) to denote the transition matrix of the Markov chain.
A chain is reversible if \pi(x)P(x,y)=\pi(y)P(y,x) for all x,y\in\Omega. Q(x,y)=\pi(x)P(x,y) is the edge measure on (x,y). We denote by t_{\mbox{mix}} the total variation mixing time defined as t_{\mbox{mix}}(\epsilon)=\inf\{t:\sup_{\omega_0\in\Omega}\|P^t(\omega_0,\cdot)-\pi(\cdot)\|_{TV}\leq \epsilon\}\,,
A chain is reversible if \pi(x)P(x,y)=\pi(y)P(y,x) for all x,y\in\Omega. Q(x,y)=\pi(x)P(x,y) is the edge measure on (x,y). We denote by t_{\mbox{mix}} the total variation mixing time defined as t_{\mbox{mix}}(\epsilon)=\inf\{t:\sup_{\omega_0\in\Omega}\|P^t(\omega_0,\cdot)-\pi(\cdot)\|_{TV}\leq \epsilon\}\,,
and set t_{\mbox{mix}}=t_{\mbox{mix}}(\epsilon), where the total variation distance
\|\mu-\nu\|_{TV}=\tfrac 12 \|\mu-\nu\|_{\ell^1}\,.
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Cite this as: AimPL: Markov chain mixing times, available at http://aimpl.org/markovmixing.