Multiparameter transmission estimation at the quantum Cram\'er-Rao limit on a cloud quantum computer
Aaron Z. Goldberg, Khabat Heshami

TL;DR
This paper demonstrates quantum multiparameter transmission estimation at the quantum Cramér-Rao limit using a cloud-based quantum photonic device, achieving high-precision parameter estimates through maximum likelihood estimation.
Contribution
It introduces a protocol for simultaneous loss parameter estimation in a quantum optical system on a cloud quantum computer, approaching fundamental quantum limits.
Findings
Achieved transmission estimates with uncertainties near the quantum Cramér-Rao bound.
Successfully performed maximum likelihood estimation on over a million photon detection events.
Provided insights into quantum multiparameter estimation and device characterization.
Abstract
Estimating transmission or loss is at the heart of spectroscopy. To achieve the ultimate quantum resolution limit, one must use probe states with definite photon number and detectors capable of distinguishing the number of photons impinging thereon. In practice, one can outperform classical limits using two-mode squeezed light, which can be used to herald definite-photon-number probes, but the heralding is not guaranteed to produce the desired probes when there is loss in the heralding arm or its detector is imperfect. We show that this paradigm can be used to simultaneously measure distinct loss parameters in both modes of the squeezed light, with attainable quantum advantages. We demonstrate this protocol on Xanadu's X8 chip, accessed via the cloud, building photon-number probability distributions from shots and performing maximum likelihood estimation (MLE) on these…
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Taxonomy
TopicsQuantum Information and Cryptography · Neural Networks and Reservoir Computing · Quantum Computing Algorithms and Architecture
