Noisy distributed sensing in the Bayesian regime

Abstract

We consider non-local sensing of scalar signals with specific spatial dependence in the Bayesian regime. We design schemes that allow one to achieve optimal scaling and are immune to noise sources with a different spatial dependence than the signal. This is achieved by using a sensor array of spatially separated sensors and constructing a multi-dimensional decoherence free subspace. While in the Fisher regime with sharp prior and multiple measurements only the spectral range $\Delta$ is important, in single-shot sensing with broad prior the number of available energy levels $L$ is crucial. We study the influence of $L$ and $\Delta$ also in intermediate scenarios, and show that these quantities can be optimized separately in our setting. This provides us with a flexible scheme that can be adapted to different situations, and is by construction insensitive to given noise sources.

9 pages, 1 figure

References in corpus (7)

• The Quantum Internet
• Quantum metrology from a quantum information science perspective
• Robust Online Hamiltonian Learning
• Quantum Metrological Limits via a Variational Approach
• Does nonlinear metrology offer improved resolution? Answers from quantum information theory
• Phase-noise protection in quantum-enhanced differential interferometry
• Optimized parameter estimation in the presence of collective phase noise

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