Adaptive Real-Time Protocols for Improved Sensing with NV Centers

The Quantum Machines' Quantum Orchestration Platform (QOP) has advanced real-time capabilities that can be used for various applications. Here we will present several results from groups working with the QOP that utilize its unique capabilities. We will show how real-time feedback and adaptive thresholding can improve the single-shot readout (SSRO) of a three-level nuclear spin next to an NV center.

Adaptive Bayesian estimation has been proven to improve the sensitivity of SSRO sensors. However, in the absence of SSRO, adaptive Bayesian estimation requires complex real-time calculations that were not experimentally demonstrated. We report the first real-time adaptive bayesian estimation with binomial distribution demonstrated using the QOP and an NV center. We calculate the binomial distribution, extract both the optimal phase and duration for the next sensing step.