Members: Shir Giat

Supervisor: Prof. Nir Bar-Gill

Nitrogen-Vacancy (NV) centers in diamonds have emerged as a powerful tool for high-sensitivity magnetometry due to their unique properties. NV centers are atomic-scale defects in diamonds that exhibit spin-dependent fluorescence, allowing for the optical detection of magnetic fields. Optically Detected Magnetic Resonance (ODMR) is the standard technique for measuring magnetic fields using NV centers. It involves illuminating NV centers with microwaves and light, then analyzing changes in their optical emission by scanning over a range of microwave frequencies and measuring the fluorescence intensity. Despite its widespread use, the ODMR method has limitations in precision and sensitivity to noise.

This project aimed to overcome these limitations and improve the precision, accuracy, and efficiency of measuring magnetic fields using NV centers in diamonds by utilizing the Bayesian experiment design as an alternative to the conventional ODMR. The Bayesian method iteratively updates the probability distribution of model parameters based on new measurement data, allowing for more efficient and accurate parameter estimation. Simulations were conducted using the Electron Spin Resonance (ESR) model to compare the performance of the Bayesian approach with the usual ODMR technique, focusing on key aspects such as width dependency, sensitivity to parameter variations, noise dependency, and convergence speed. The results demonstrated significant improvements in NV center magnetometry using the Bayesian method. The Bayesian method exhibited higher precision in estimating the central frequency, increased sensitivity to subtle changes in the magnetic field, better noise mitigation, and faster convergence to accurate model parameters.