Markovian optical modes.

We describe the transition of a set of optical modes following a Markov chain process, where the mean value of the amplitude converge to a new type of partially coherent mode, with the property that the coherence features are easily tunable with the parameters of the chain. The amplitude of the resulting mode depends on the probability transition of the chain. As a prototype, we establish an analogy with gambler's chain ruin, using as a basis for the vector space the Bessel modes of integer order. Computer simulations are shown.