  Stochastic processes under resetting at random times have attracted a lot of
attention in recent years and served as illustrations of nontrivial and
interesting static and dynamic features of stochastic dynamics. In this paper,
we aim to address how the entropy rate is affected by stochastic resetting in
discrete-time Markovian processes, and explore nontrivial effects of the
resetting in the mixing properties of a stochastic process. In particular, we
consider resetting random walks on complex networks and compute the entropy
rate as a function of the resetting probability. Interestingly, we find that
the entropy rate can show a nonmonotonic dependence on the resetting
probability. There exists an optimal resetting probability for which the
entropy rate reaches a maximum. We also show that the maximum entropy rate can
be larger than that of the maximal-entropy random walks on the same topology.
Our study provides a new nontrivial effect of stochastic resetting on
nonequilibrium statistical physics.
