Markov chains are mathematical models that describe systems transitioning between states in a way that depends only on the current state and not on the sequence of events that preceded it. This memoryless property is crucial in analyzing various stochastic processes, allowing connections to important concepts such as return times, ergodicity, and mixing properties in dynamical systems.
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