NV<sup>-</sup> center magnetometry using Bayesian inference and sequential experiment design
ORAL
Abstract
In magnetometry using NV- centers, we demonstrate more than order-of-magnitude speed up with sequential Bayesian experiment design as compared with the conventional frequency-swept measurements.
The NV- center is a quantum defect with spin 1 and coherence time up to several milliseconds at room temperature. Zeeman splitting of the NV- energy levels allows detection of the magnetic field via photoluminescence. NV- center is a promising platform for magnetometry, quantum computing and sensing.
We compare conventional magnetic field measurement of fluorescence under pre-determined sweeps of microwave frequency with the measurement using a Bayesian inference and sequential experiment design. In the Bayesian experiment design, the frequency of each measurement is determined in real-time from utility predictions based on the accumulated experimental data. We report 45 times speedup with sequential Bayesian experimental design, compared with the conventional NV- magnetometry [1,2].
[1] S. Dushenko. K. Ambal, R.D. McMichael, “Sequential Bayesian experiment design for optically detected magnetic resonance of nitrogen-vacancy centers”, Phys. Rev. Appl. accepted (2020).
[2] R.D. McMichael, Optimal Bayesian Experiment Design Software Documentation "https://pages.nist.gov/optbayesexpt/"
The NV- center is a quantum defect with spin 1 and coherence time up to several milliseconds at room temperature. Zeeman splitting of the NV- energy levels allows detection of the magnetic field via photoluminescence. NV- center is a promising platform for magnetometry, quantum computing and sensing.
We compare conventional magnetic field measurement of fluorescence under pre-determined sweeps of microwave frequency with the measurement using a Bayesian inference and sequential experiment design. In the Bayesian experiment design, the frequency of each measurement is determined in real-time from utility predictions based on the accumulated experimental data. We report 45 times speedup with sequential Bayesian experimental design, compared with the conventional NV- magnetometry [1,2].
[1] S. Dushenko. K. Ambal, R.D. McMichael, “Sequential Bayesian experiment design for optically detected magnetic resonance of nitrogen-vacancy centers”, Phys. Rev. Appl. accepted (2020).
[2] R.D. McMichael, Optimal Bayesian Experiment Design Software Documentation "https://pages.nist.gov/optbayesexpt/"
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Presenters
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Sergey Dushenko
National Institute of Standards and Technology, UMD/NIST
Authors
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Sergey Dushenko
National Institute of Standards and Technology, UMD/NIST
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Sean M Blakley
National Institute of Standards and Technology, UMD/NIST
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Kapildeb Ambal
Wichita State University
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Robert McMichael
National Institute of Standards and Technology