Optimal use of time-dependent probability density data to extract potential-energy surfaces

Lukas Kurtz; Herschel Rabitz; Regina De Vivie-Riedle

doi:10.1103/PhysRevA.65.032514

Optimal use of time-dependent probability density data to extract potential-energy surfaces

Lukas Kurtz, Herschel Rabitz, Regina De Vivie-Riedle

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11 Scopus citations

Abstract

An overview is given on results that improve and extend a recently suggested procedure to extract potential-energy surfaces (PES) from the emerging experimentally observable probability density ψ(x,t)^-2 data. An easy to implement regularization scheme is introduced, which increases the accuracy of the computed PES without loss of numerical stability. Furthermore, an optimal reconstruction method is presented which combines data from different measurements.

Original language	English (US)
Article number	032514
Pages (from-to)	1-11
Number of pages	11
Journal	Physical Review A - Atomic, Molecular, and Optical Physics
Volume	65
Issue number	3
DOIs	https://doi.org/10.1103/PhysRevA.65.032514
State	Published - Mar 2002

All Science Journal Classification (ASJC) codes

Atomic and Molecular Physics, and Optics

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10.1103/PhysRevA.65.032514

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title = "Optimal use of time-dependent probability density data to extract potential-energy surfaces",

abstract = "An overview is given on results that improve and extend a recently suggested procedure to extract potential-energy surfaces (PES) from the emerging experimentally observable probability density ψ(x,t)-2 data. An easy to implement regularization scheme is introduced, which increases the accuracy of the computed PES without loss of numerical stability. Furthermore, an optimal reconstruction method is presented which combines data from different measurements.",

author = "Lukas Kurtz and Herschel Rabitz and {De Vivie-Riedle}, Regina",

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AB - An overview is given on results that improve and extend a recently suggested procedure to extract potential-energy surfaces (PES) from the emerging experimentally observable probability density ψ(x,t)-2 data. An easy to implement regularization scheme is introduced, which increases the accuracy of the computed PES without loss of numerical stability. Furthermore, an optimal reconstruction method is presented which combines data from different measurements.

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Optimal use of time-dependent probability density data to extract potential-energy surfaces

Abstract

All Science Journal Classification (ASJC) codes

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