Hamiltonian Learning at Scale

Learning a quantum system's Hamiltonian is crucial for understanding and controlling its dynamics and has recently become a topic of widespread interest. To understand the learning protocol's error tolerances, i.e. its stability in the presence of inevitable errors, this work utilizes tensor network