A unified semiparametric efficiency theory for classical and quantum models, with singular-value analysis of channels, shows spatial-mode demultiplexing approaches the quantum limit for subdiffraction incoherent imaging.
Criteria for unbiased estimation: applications to noise-agnostic sensing and quantum channel estimation
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abstract
We establish the necessary and sufficient conditions for {local} unbiased estimation in multi-parameter estimation tasks. More specifically, we first consider quantum state estimation, where multiple parameters are encoded in a quantum state, and derive simple and intuitive necessary and sufficient conditions for a {local} unbiased estimation based on the derivatives of the encoded state. To demonstrate the utility of our framework, we consider phase estimation under unknown Pauli noise. We show that while {local} unbiased phase estimation is infeasible with a naive scheme, employing an entangled probe with a noiseless ancilla enables local unbiased estimation. We then extend our analysis to quantum channel estimation and derive a necessary and sufficient condition for local unbiased estimability of channel parameters, allowing noiseless ancillae, general CPTP controls, and multiple uses of the channel. As a concrete application, we analyze unbiased estimation of noise parameters affecting non-Clifford gates via cycle benchmarking under SPAM errors.
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quant-ph 1years
2026 1verdicts
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Unified theory of classical and quantum semiparametric efficiency
A unified semiparametric efficiency theory for classical and quantum models, with singular-value analysis of channels, shows spatial-mode demultiplexing approaches the quantum limit for subdiffraction incoherent imaging.