When I study Markov chain (or sampling) related papers, most of them emphasize "uniform stationary distribution". But, I can't sure why it is important for Markov chain problems or randomized algorithms. Is this because uniform stationary distribution easily satisfies the reversibility of our Markov chain?
If possible, could you please give me some references or explanations? Thanks for your help.