Abstract

Quantum systems are promising candidates for sensing of weak signals as they can be highly sensitive to external perturbations, thus providing excellent performance when estimating parameters of external fields. However, when trying to detect weak signals that are hidden by background noise, the signal-to-noise ratio is a more relevant metric than raw sensitivity. We identify, under modest assumptions about the statistical properties of the signal and noise, the optimal quantum control to detect an external signal in the presence of background noise using a quantum sensor. Interestingly, for white background noise, the optimal solution is the simple and well-known spin-locking control scheme. Using numerical techniques, we further generalize these results to the case of background noise with a Lorentzian spectrum. We show that for increasing correlation time, pulse based sequences, such as CPMG, are also close to the optimal control for detecting the signal, with the crossover dependent on the signal frequency. These results show that an optimal detection scheme can be easily implemented in near-term quantum sensors without the need for complicated pulse shaping.

Details

Title
Optimal control for quantum detectors
Author
Paraj, Titum 1   VIAFID ORCID Logo  ; Schultz, Kevin 2 ; Seif Alireza 3   VIAFID ORCID Logo  ; Quiroz, Gregory 2 ; Clader, B D 2 

 Johns Hopkins University Applied Physics Laboratory, Laurel, USA (GRID:grid.474430.0) (ISNI:0000 0004 0630 1170); NIST/University of Maryland, Joint Quantum Institute, College Park, USA (GRID:grid.94225.38) (ISNI:000000012158463X) 
 Johns Hopkins University Applied Physics Laboratory, Laurel, USA (GRID:grid.474430.0) (ISNI:0000 0004 0630 1170) 
 NIST/University of Maryland, Joint Quantum Institute, College Park, USA (GRID:grid.94225.38) (ISNI:000000012158463X); NIST/University of Maryland, Joint Center for Quantum Information and Computer Science, College Park, USA (GRID:grid.94225.38) (ISNI:000000012158463X); University of Maryland, Department of Physics, College Park, USA (GRID:grid.164295.d) (ISNI:0000 0001 0941 7177) 
Publication year
2021
Publication date
2021
Publisher
Nature Publishing Group
e-ISSN
20566387
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2505253315
Copyright
© The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.