We present a learning task for quantum channels that exhibits an exponential separation in query complexity (in terms of the number of qubits) between two access models: i) black-box channel access and ii) access to a Stinespring dilation unitary of the channel along with its inverse. We consider the task of learning h...
Manaki Arihara, Satoshi Yoshida, Philip Taranto et al.· 0 citations
The collective tomography protocols for quantum states and channels with known symmetries are given, using random purification and dilation to reduce learning to pure-state estimation and resolve an open problem in quantum tomography of constructing efficient quantum circuits.
Satoshi Yoshida, K. Okigami, P. M. Posta et al.· 0 citations
The results show that forward-only access cannot provide an asymptotic query-complexity advantage over learning from classical data or quantum data copies in this worst-case setting, and establish the essential role of inverse access in the known realizable-setting improvement.
Natsuto Isogai, Satoshi Yoshida, M. Murao· 0 citations
The optimal fidelity for the dual problem of noisy unitary conjugation, where the goal is to obtain the best approximation of the complex conjugate of the original unknown unitary from access to noisy queries, coincides with that of noisy unitary purification to the leading-order in the low-noise and large-query limit.
Ryotaro Niwa, Satoshi Yoshida, M. Murao· 0 citations
A closed-form expression for the optimal fidelity is derived and it is proved that a parallel protocol is optimal even among general quantum superchannels, including adaptive and indefinite-causal-order strategies.
Satoshi Yoshida, M. Murao· 1 citation
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