Optimal function estimation with photonic quantum sensor networks
- URL: http://arxiv.org/abs/2401.16472v2
- Date: Wed, 20 Mar 2024 16:34:29 GMT
- Title: Optimal function estimation with photonic quantum sensor networks
- Authors: Jacob Bringewatt, Adam Ehrenberg, Tarushii Goel, Alexey V. Gorshkov,
- Abstract summary: We solve the problem of optimally measuring an analytic function of unknown local parameters each linearly coupled to a qubit sensor.
In particular, we derive lower bounds on the achievable mean square error in estimating a linear function of either local phase shifts or quadrature displacements.
For quadrature displacements, we extend bounds to the case of arbitrary linear functions.
- Score: 0.0
- License: http://creativecommons.org/licenses/by-sa/4.0/
- Abstract: The problem of optimally measuring an analytic function of unknown local parameters each linearly coupled to a qubit sensor is well understood, with applications ranging from field interpolation to noise characterization. Here, we resolve a number of open questions that arise when extending this framework to Mach-Zehnder interferometers and quadrature displacement sensing. In particular, we derive lower bounds on the achievable mean square error in estimating a linear function of either local phase shifts or quadrature displacements. In the case of local phase shifts, these results prove, and somewhat generalize, a conjecture by Proctor et al. [arXiv:1702.04271 (2017)]. For quadrature displacements, we extend proofs of lower bounds to the case of arbitrary linear functions. We provide optimal protocols achieving these bounds up to small (multiplicative) constants and describe an algebraic approach to deriving new optimal protocols, possibly subject to additional constraints. Using this approach, we prove necessary conditions for the amount of entanglement needed for any optimal protocol for both local phase and displacement sensing.
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