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Robust spin relaxometry with fast adaptive Bayesian estimation



Michael Caouette-Mansour, Adrian Solyom, Brandon Ruffolo, Robert D. McMichael, Jack Childress (Sankey), Lilian Childress


Spin relaxometry with nitrogen-vacancy (NV) centers in diamond offers a spectrally selective, atomically localized, and calibrated measurement of microwave-frequency magnetic noise, presenting a versatile probe for condensed matter and biological systems. Typically, relaxation rates are estimated with curve-fitting techniques that cannot provide optimal sensitivity, often leading to long acquisition times that are particularly detrimental in systems prone to drift or other dynamics of interest. Here we show that adaptive Bayesian estimation is well suited to this problem, producing dynamic relaxometry pulse sequences that rapidly seek an optimal operating regime. In many situations (including the system we employ), this approach can speed the acquisition by an order of magnitude. We also present a four-signal measurement protocol that is robust to drifts in spin readout contrast, polarization, and microwave pulse fidelity while still achieving near-optimal sensitivity. The combined technique offers a practical, hardware-agnostic approach for a wide range of NV relaxometry applications.
Physical Review Applied


Quantum sensing, relaxometry, Nitrogen vacancy, Bayesian, experiment design


Caouette-Mansour, M. , Solyom, A. , Ruffolo, B. , McMichael, R. , Childress (Sankey), J. and Childress, L. (2022), Robust spin relaxometry with fast adaptive Bayesian estimation, Physical Review Applied, [online],, (Accessed July 19, 2024)


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Created June 15, 2022, Updated November 29, 2022