38 citations · 212 across the 12 of their papers we have counts for
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quant-ph2022★ 35 cited
A comparative study of different machine learning methods for dissipative quantum dynamics
Luis E. Herrera Rodriguez, Arif Ullah, Kennet J. Rueda Espinosa +2
It has been recently shown that supervised machine learning (ML) algorithms can accurately and efficiently predict the long-time populations dynamics of dissipative quantum systems…
quant-ph2022★ 27 cited
One-shot trajectory learning of open quantum systems dynamics
Arif Ullah, Pavlo O. Dral
Nonadiabatic quantum dynamics are important for understanding light-harvesting processes, but their propagation with traditional methods can be rather expensive. Here we present a…