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Scalably learning quantum many-body Hamiltonians from dynamical data
The dataset used in the paper is a collection of measurement outcomes from dynamical data, used to learn families of interacting many-body Hamiltonians. -
Quantum Many-Body Systems
The dataset used in the paper is a collection of quantum many-body systems, including the Heisenberg model, the transverse field Ising model, and the Heisenberg J1-J2 model.