Bayesian Approach to Inverse Quantum Statistics
- 6 March 2000
- journal article
- research article
- Published by American Physical Society (APS) in Physical Review Letters
- Vol. 84 (10) , 2068-2071
- https://doi.org/10.1103/physrevlett.84.2068
Abstract
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 on potentials implemented in the form of stochastic processes. Its specific advantages are the possibilities to deal with heterogeneous data and to express a priori information explicitly in terms of the potential of interest. A numerical solution in maximum a posteriori approximation is obtained for one-dimensional problems. As nonparametric estimates, the results depend strongly on the implemented a priori information.Keywords
All Related Versions
This publication has 9 references indexed in Scilit:
- New situation in quantum mechanics (wonderful potentials from the inverse problem)Inverse Problems, 1997
- An Introduction to Inverse Scattering and Inverse Spectral ProblemsPublished by Society for Industrial & Applied Mathematics (SIAM) ,1997
- Graphical ModelsPublished by Oxford University Press (OUP) ,1996
- An Introduction to the Mathematical Theory of Inverse ProblemsPublished by Springer Nature ,1996
- Regularization Theory and Neural Networks ArchitecturesNeural Computation, 1995
- Introduction to the Theory of Neural ComputationPhysics Today, 1991
- Spline Models for Observational DataPublished by Society for Industrial & Applied Mathematics (SIAM) ,1990
- Inverse Schrödinger Scattering in Three DimensionsPublished by Springer Nature ,1989
- Statistical Decision Theory and Bayesian AnalysisPublished by Springer Nature ,1985