Before revision:  We introduce a " Markov chains of Markov chains " model such that with probably (1-\omega) \in[0,1]  random walkers remain in the same layer and follow (layer-specific) intralayer Markov chains , whereas with probability \omega they move to different layers following (node-specific) interlayer Markov chains . By coupling "Markov-chain layers" versus "network layers", we identify novel multiplexity-induced phenomena includingmultiplex imbalance (whereby the multiplex coupling of reversible Markov chains yields an irreversible one) andmultiplex convection ( whereby a stationary distribution exhibits circulating flows that involve multiple layers ).
After revision:  We introduce a " Markov chains of Markov chains " model such that with probably (1-\omega) \in[0,1] random walkers remain in the same layer and follow (layer-specific) intralayer Markov chains , whereas with probability \omega they move to different layers following (node-specific) interlayer Markov chains multiplex imbalance (whereby the multiplex coupling of reversible Markov chains yields an irreversible one) andmultiplex convection ( whereby a stationary distribution exhibits circulating flows that involve multiple layers ).