English

Robust spin relaxometry with fast adaptive Bayesian estimation

Quantum Physics 2023-04-18 v2 Mesoscale and Nanoscale Physics

Abstract

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 do not 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 find 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.

Keywords

Cite

@article{arxiv.2202.12218,
  title  = {Robust spin relaxometry with fast adaptive Bayesian estimation},
  author = {Michael Caouette-Mansour and Adrian Solyom and Brandon Ruffolo and Robert D. McMichael and Jack Sankey and Lilian Childress},
  journal= {arXiv preprint arXiv:2202.12218},
  year   = {2023}
}

Comments

Accepted version

R2 v1 2026-06-24T09:52:44.477Z