Schroedinger's interpolation problem through Feynman-Kac kernels

We discuss the so-called Schr{\"o}dinger problem of deducing the microscopic (basically stochastic) evolution that is consistent with given positive boundary probability densities for a process covering a finite fixed time interval. The sought for dynamics may preserve the probability measure or induce its evolution, and is known to be uniquely reproducible, if the Markov property is required. Feynman-Kac type kernels are the principal ingredients of the solution and determine the transition probability density of the corresponding stochastic process. The result applies to a large variety of nonequilibrium statistical physics and quantum situations.