Experimental demonstration of a quantum model learning agent

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.