00919nas a2200145   4500000000100000000000100001008004100002100002400043700002200067700002500089700001400114245008200128490000700210520055600217       2019                            d1 aMateusz Ostaszewski1 aJaroslaw Miszczak1 aPrzemysław Sadowski1 aL. Banchi00aApproximation of quantum control correction scheme using deep neural networks0 v183 a<p>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 then analysing the robustness of the latter against local variations in the control profile.</p>