Gradient algorithm for Hamiltonian identification of open quantum systems

In this paper, we present a gradient algorithm for identifying unknown parameters in an open quantum system from the measurements of time traces local observables. The dynamics is described by general Markovian master equation based on which Hamiltonian identification problem can be formulated as minimizing distance between real observables and those predicted equation. then learned with descent measurement data. We verify effectiveness our circuit QED Jaynes-Cumming model whose has been rarely considered. also show that learn spectrum non-Markovian environment augmented model.