Optimal distributed multiparameter estimation in noisy environments
arXiv:2306.01077 · doi:10.1088/2058-9565/ad37d5
Abstract
We consider the task of multiple parameter estimation in the presence of strong correlated noise with a network of distributed sensors. We study how to find and improve noise-insensitive strategies. We show that sequentially probing GHZ states is optimal up to a factor of at most 4. This allows us to connect the problem to single parameter estimation, and to use techniques such as protection against correlated noise in a decoherence-free subspace, or read-out by local measurements.
arXiv comment8 pages, 2 figures
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