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Coupling of Markov Chains

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If you have a question about this talk, please contact Jasper Lee.

We can model random processes such as shuffling cards using Markov chains. For a certain class of them we can find a stationary distribution to which the process will converge.

I will explain how coupling of Markov Chains is used to estimate the time needed to get close to this stationary distribution. For example, how often do you have to shuffle a deck of cards until you are fairly sure that they are distributed uniformly?

In terms of applications, I will describe a polynomial time probabilistic algorithm for graph colouring, and I will explain a magic trick!

This talk is part of the Churchill CompSci Talks series.

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