Sequential Bayesian Experiment Design for Optically Detected Magnetic Resonance of Nitrogen-Vacancy Centers

With a room-temperature coherence time as long as milliseconds, the nitrogen-vacancy (N-V) center in diamond is used at the leading edge in quantum computing, cryptography, and memory; biocompatible markers and drug delivery; and mechanical, thermal, and magnetic sensors. Despite this prominence, experiments with N-V centers are often hampered by poor photon-collection efficiency. The authors use the machine-learning technique of B00exa00exy00exe00exs00exi00exa00exn i00exn00exf00exe00exr00exe00exn00exc00exe to maximize the information obtained from each photon, which for example speeds up N-V-center magnetometry by more than an order of magnitude.