Efficient learning of quantum states prepared with few fermionic non-Gaussian gates
AA Mele, Y Herasymenko - arXiv preprint arXiv:2402.18665, 2024 - arxiv.org
The experimental realization of increasingly complex quantum states underscores the
pressing need for new methods of state learning and verification. In one such framework,
quantum state tomography, the aim is to learn the full quantum state from data obtained by
measurements. Without prior assumptions on the state, this task is prohibitively hard. Here,
we present an efficient algorithm for learning states on $ n $ fermion modes prepared by any
number of Gaussian and at most $ t $ non-Gaussian gates. By Jordan-Wigner mapping, this …
pressing need for new methods of state learning and verification. In one such framework,
quantum state tomography, the aim is to learn the full quantum state from data obtained by
measurements. Without prior assumptions on the state, this task is prohibitively hard. Here,
we present an efficient algorithm for learning states on $ n $ fermion modes prepared by any
number of Gaussian and at most $ t $ non-Gaussian gates. By Jordan-Wigner mapping, this …
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