English

Feynman-Kac Kernels in Markovian Representations of the Schroedinger Interpolating Dynamics

Quantum Physics 2009-10-28 v2 adap-org chao-dyn chem-ph High Energy Physics - Theory Probability Adaptation and Self-Organizing Systems Chaotic Dynamics

Abstract

Probabilistic solutions of the so called Schr\"{o}dinger boundary data problem provide for a unique Markovian interpolation between any two strictly positive probability densities designed to form the input-output statistics data for the process taking place in a finite-time interval. The key issue is to select the jointly continuous in all variables positive Feynman-Kac kernel, appropriate for the phenomenological (physical) situation. We extend the existing formulations of the problem to cases when the kernel is \it not \rm a fundamental solution of a parabolic equation, and prove the existence of a continuous Markov interpolation in this case. Next, we analyze the compatibility of this stochastic evolution with the original parabolic dynamics, while assumed to be governed by the temporally adjoint pair of (parabolic) partial differential equations, and prove that the pertinent random motion is a diffusion process. In particular, in conjunction with Born's statistical interpretation postulate in quantum theory, we consider stochastic processes which are compatible with the Schr\"{o}dinger picture quantum evolution.

Keywords

Cite

@article{arxiv.quant-ph/9505012,
  title  = {Feynman-Kac Kernels in Markovian Representations of the Schroedinger Interpolating Dynamics},
  author = {Piotr Garbaczewski and Robert Olkiewicz},
  journal= {arXiv preprint arXiv:quant-ph/9505012},
  year   = {2009}
}

Comments

Latex file, J. Math. Phys., accepted for publication

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