Journal article
Modelling of ultrafast coherent strong-field dynamics in potassium with neural networks



Publication Details
Authors:
Selle, R.; Brixner, T.; Bayer, T.; Wollenhaupt, M.; Baumert, T.
Publication year:
2008
Journal:
J. Phys. B., Special Issue on Coherent Control
Pages range:
074019-1 - 074019-7
Volume number:
41

Abstract
We investigate the applicability of neural networks ( NNs) for the automated generation of effective computer models for coherent light - matter interactions. The simulation of Autler - Townes doublets from strong-field ionization of potassium atoms is chosen as a test system that exhibits distinct quantum-mechanical effects. Shaped femtosecond laser pulses are employed for studying the response of a quantum-mechanical system to a large variety of different electric fields, and the resulting data can be used for training a NN. We show that a NN is able to approximate the investigated process in parameter regions sampled by the training data and that it can be employed for the interpolation of control landscapes.


Research Areas


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