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Probability II / Discrete-Time Markov Chains

The Detailed Balance Condition and Time Reversibility

Solving πp=π\pi p = \pi directly, as the previous lesson did, requires setting up and solving a linear system — feasible for three states, tedious for thirty. Detailed balance is a stronger, purely local condition — balance the flow between every pair of states, not just the flow into and out of each state overall — that, when it holds, both guarantees stationarity and often makes π\pi trivial to write down by hand. It also has a striking interpretive payoff: a chain satisfying detailed balance looks statistically identical whether you watch it run forwards or backwards in time.
Learning objectives. By the end of this note you should be able to:
  • state the detailed balance condition and show it implies stationarity;
  • solve for the stationary distribution of a birth-death chain using detailed balance;
  • compute the stationary distribution of a random walk on a graph directly from vertex degrees;
  • state the reversibility theorem and identify when a chain equals its own time-reversal.

In this lesson

  1. Detailed balance implies stationarity
  2. Birth-death chains
  3. Random walks on graphs
  4. Time reversibility

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