Approximation of quantum control correction scheme using deep neural networks View Full Text


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Article Info

DATE

2019-05

AUTHORS

M. Ostaszewski, J. A. Miszczak, L. Banchi, P. Sadowski

ABSTRACT

We study the functional relationship between quantum control pulses in the idealized case and the pulses in the presence of an unwanted drift. We show that a class of artificial neural networks called LSTM is able to model this functional relationship with high efficiency, and hence the correction scheme required to counterbalance the effect of the drift. Our solution allows studying the mapping from quantum control pulses to system dynamics and analysing its behaviour with respect to the local variations in the control profile. More... »

PAGES

126

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11128-019-2240-7

DOI

http://dx.doi.org/10.1007/s11128-019-2240-7

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1112947795


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