Experimental investigation of Bayesian bounds in multiparameter estimation

Abstract

Quantum parameter estimation offers solid conceptual grounds for the design of sensors enjoying quantum advantage. This is realised not only by means of hardware supporting and exploiting quantum properties, but data analysis has its impact and relevance, too. In this respect, Bayesian methods have emerged as an effective and elegant solution, with the perk of incorporating naturally the availability of a priori information. In this article we present an evaluation of Bayesian methods for multiple phase estimation, assessed based on bounds that work beyond the usual limit of large samples assumed in parameter estimation. Importantly, such methods are applied to experimental data generated from the output statistics of a three-arm interferometer seeded by single photons. Our studies provide a blueprint for a more comprehensive data analysis in quantum metrology.

8 pages, 6 figures

References in corpus (7)

• Quantum metrology from a quantum information science perspective
• Entanglement-free Heisenberg-limited phase estimation
• Robust Online Hamiltonian Learning
• Experimental multiphase estimation on a chip
• Non-asymptotic analysis of quantum metrology protocols beyond the Cramér-Rao bound
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