A Bayesian Approach to Inverse Quantum Statistics
classification
❄️ cond-mat.stat-mech
cond-mat.dis-nnphysics.data-anquant-ph
keywords
quantumapproachinformationprioribayesiandatapotentialsadvantages
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A nonparametric Bayesian approach is developed to determine quantum potentials from empirical data for quantum systems at finite temperature. The approach combines the likelihood model of quantum mechanics with a priori information over potentials implemented in form of stochastic processes. Its specific advantages are the possibilities to deal with heterogeneous data and to express a priori information explicitly, i.e., directly in terms of the potential of interest. A numerical solution in maximum a posteriori approximation was feasible for one--dimensional problems. Using correct a priori information turned out to be essential.
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