 Product stationarity under single-coordinate Markov updates

Suppose each coordinate has stationary distribution $\pi$ for the same Markov kernel. Updating one coordinate using independent new randomness while leaving the others fixed preserves the product distribution ${\pi }^{\otimes m}$. For a two-state update with $P(1\to 1)=a$ and $P(0\to 1)=b$, its stationary occupied probability is $p=b/(1-a+b)$. Independent occupied-state indicators then have total mean $mp$ and variance $mp(1-p)$. The conclusion requires the update selection and transition randomness not to introduce dependence on the other coordinates' states.