Markov Chains Approximations of jump-Diffusion Quantum Trajectories

Details Markov Chains Approximations of jump-Diffusion Quantum Trajectories Markov Chains Approximations of jump-Diffusion Quantum Trajectories

2008-03-18

arxiv.org/abs/0803.2593v1

Mathematics

Probability

Scientific paper

"Quantum trajectories" are solutions of stochastic differential equations also called Belavkin or Stochastic Schr\"odinger Equations. They describe random phenomena in quantum measurement theory. Two types of such equations are usually considered, one is driven by a one-dimensional Brownian motion and the other is driven by a counting process. In this article, we present a way to obtain more advanced models which use jump-diffusion stochastic differential equations. Such models come from solutions of martingale problems for infinitesimal generators. These generators are obtained from the limit of generators of classical Markov chains which describe discrete models of quantum trajectories. Furthermore, stochastic models of jump-diffusion equations are physically justified by proving that their solutions can be obtained as the limit of the discrete trajectories.

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