Well-posed Bayesian inverse problem in Hellinger distance

A Bayesian inverse problem is well posed in Hellinger distance when every datum determines a unique posterior and the posterior depends continuously on the data in Hellinger distance. Since posterior measures are dominated by the prior and squared Hellinger distance is at most twice total variation distance, total-variation well-posedness implies Hellinger well-posedness.