Using Quantum Control to Achieve Spectral Super-resolution
By Taohan Lin
Quantum systems have long shown promise for detecting low magnitude environmental effects such as electric and magnetic fields. We consider the use of quantum systems to detect time-varying electromagnetic signals. Expanding on a recent application of quantum sensing obtaining spatial super-resolution in optical imaging, we aim to apply super-resolution techniques to resolve adjacent spectral peaks in frequency analysis.
Previous research showed that frequency super-resolution is possible, and discovered one control sequence that achieves it. The optical super-resolution techniques allow us to identify optimal conditions for the applied control to the quantum sensor. In this project, we numerically optimize control sequences for super-resolution, and compare the optimized sensing protocol with other methods for frequency analysis. We consider the family of two π-pulse sequences with specific evolution times and evaluate sequences by the Fisher information the corresponding sensing protocol provides. In this family, we find that the Carr-Purcell-Meiboom-Gill sequence (CPMG), a commonly used sequence in quantum sensing protocols, is optimal for resolving the frequency separation between spectral peaks. We show that the method using CPMG theoretically allows for peak resolution even as the frequency separation approaches zero, and we approximate protocol error bounds under experimental conditions. We identify conditions when the super-resolution protocol outperforms the classical discrete Fourier transform and quantum noise spectroscopy methods when data collection time is held constant. The protocol developed is applicable in current-day nitrogen vacancy diamond quantum sensors and can offer advances for frequency peak resolution within nuclear magnetic resonance spectroscopy, magnetometry, and orthogonal frequency division multiplexing.
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June 3, 2024
Full paper: https://drive.google.com/file/d/1AtsGeJFpOFjjZm2FMtS-mMGwA33_e9Rk/view?usp=sharing
Poster: https://drive.google.com/file/d/10SSlymhHa9mSyWUBb_Hd4gtZnNBbFY8p/view?usp=sharing