Selective and noise-resilient wave estimation with quantum sensor networks

Fuente: arXiv
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Main Authors: Hamann, Arne, Aigner, Paul, Sekatski, Pavel, Dür, Wolfgang
Format: Preprint
Published: 2024
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author Hamann, Arne
Aigner, Paul
Sekatski, Pavel
Dür, Wolfgang
author_facet Hamann, Arne
Aigner, Paul
Sekatski, Pavel
Dür, Wolfgang
contents We consider the selective sensing of planar waves in the presence of noise. We present different methods to control the sensitivity of a quantum sensor network, which allow one to decouple it from arbitrarily selected waves while retaining sensitivity to the signal. Comparing these methods with classical (non-entangled) sensor networks we demonstrate two advantages. First, entanglement increases precision by enabling the Heisenberg scaling. Second, entanglement enables the elimination of correlated noise processes corresponding to waves with different propagation directions, by exploiting decoherence-free subspaces. We then provide a theoretical and numerical analysis of the advantage offered by entangled quantum sensor networks, which is not specific to waves and can be of general interest. We demonstrate an exponential advantage in the regime where the number of sensor locations is comparable to the number of noise sources. Finally, we outline a generalization to other waveforms, e.g., spherical harmonics and general time-dependent fields.
format Preprint
id arxiv_https___arxiv_org_abs_2412_12291
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Selective and noise-resilient wave estimation with quantum sensor networks
Hamann, Arne
Aigner, Paul
Sekatski, Pavel
Dür, Wolfgang
Quantum Physics
We consider the selective sensing of planar waves in the presence of noise. We present different methods to control the sensitivity of a quantum sensor network, which allow one to decouple it from arbitrarily selected waves while retaining sensitivity to the signal. Comparing these methods with classical (non-entangled) sensor networks we demonstrate two advantages. First, entanglement increases precision by enabling the Heisenberg scaling. Second, entanglement enables the elimination of correlated noise processes corresponding to waves with different propagation directions, by exploiting decoherence-free subspaces. We then provide a theoretical and numerical analysis of the advantage offered by entangled quantum sensor networks, which is not specific to waves and can be of general interest. We demonstrate an exponential advantage in the regime where the number of sensor locations is comparable to the number of noise sources. Finally, we outline a generalization to other waveforms, e.g., spherical harmonics and general time-dependent fields.
title Selective and noise-resilient wave estimation with quantum sensor networks
topic Quantum Physics
url https://arxiv.org/abs/2412.12291