Maximizing total variation distance for the Ising model
Consider Glauber dynamics for the Ising model on a finite graph. Which pair of initial states maximizes the total variation distance at time ?
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Consider Glauber dynamics for the Ising model on a finite graph. Which pair of initial states maximizes the total variation distance at time ?
Does Swendsen-Wang dynamics for the Ising model on an -vertex graph always mix in time
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Consider a Markov chain on the set of n by n invertible matrices mod 2, where in each step, two distinct rows are chosen uniformly at random, and the first row is added to the second mod 2. How does the mixing time grow with n? And how does it change if only test functions that are computable in polynomial time are allowed?
Consider random transpositions on sequences of 1, -1, with non-negative partial sums (transpositions that violate this condition are rejected.) How does the mixing time of this chain grow as a function of n ?