2024/08/17 by Prabhat Anand, Ankit Khandelwal, Anand, Prabhat +13
Engineering · Materials Science · Physics and Astronomy · #Emerging Technologies (cs.ET) #FOS: Computer and information sciences #FOS: Physical sciences #Instrumentation and Detectors (physics.ins-det) #Magnetic Field Sensors Techniques #Magnetic Properties and Applications #Magnetic properties of thin films #Quantum Physics (quant-ph)
paper · pdf · doi:10.48550/arxiv.2408.11069
openalex publication_date 2024/08/17 · openalex created_date 2024/12/20 · openalex updated_date 2026/07/28
With the second quantum revolution underway, quantum-enhanced sensors are moving from laboratory demonstrations to field deployments, providing enhanced and even new capabilities. Signal processing and operational software is becoming integral parts of these emerging sensing systems to reap the benefits of this progress. This paper looks into widefield Nitrogen Vacancy Center-based magnetometry and focuses on estimating the magnetic field from the Optically Detected Magnetic Resonances (ODMR) signal, a crucial output for various applications. Mapping the shifts of ODMR signals to phase estimation, a computationally efficient approaches are proposed. Involving Fourier Transform and Filtering as pre-processing steps, the suggested approaches involve linear curve fit or complex frequency estimation based on well-known super-resolution technique Estimation of Signal Parameters via Rotational Invariant Techniques (ESPRIT). The existing methods in the quantum sensing literature take different routes based on Lorentzian fitting for determining magnetic field maps. To showcase the functionality and effectiveness of the suggested techniques, relevant results, based on experimental data are provided, which shows a significant reduction in computational time with the proposed method over existing methods