Abstract
Developing novel quantum devices poses the problem of their efficient characterization. We introduce and experimentally demonstrate a methodology to automatically formulate and rank Hamiltonian models, learning the most appropriate in reproducing the observed system’s dynamics.
© 2020 The Author(s)
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