Real-time adaptive sensing of nuclear spins by a single-spin quantum sensor

TL;DR

This paper enhances quantum sensing efficiency by integrating expected information gain with Bayesian experimental design, enabling real-time adaptive control and significantly speeding up nuclear spin detection with nitrogen-vacancy centers.

Contribution

It introduces a real-time Bayesian experimental design method using expected information gain and accelerated computation for quantum sensing.

Findings

Achieved up to tenfold speed-up in sensing multiple nuclear spins.

Demonstrated real-time adaptive control of quantum sensors.

Validated the approach with a simulated nitrogen-vacancy center.

Abstract

Quantum sensing is considered to be one of the most promising subfields of quantum information to deliver practical quantum advantages in real-world applications. However, its impressive capabilities, including high sensitivity, are often hindered by the limited quantum resources available. Here, we incorporate the expected information gain (EIG) and techniques such as accelerated computation into Bayesian experimental design (BED) in order to use quantum resources more efficiently. A simulated nitrogen-vacancy center in diamond is used to demonstrate real-time operation of the BED. Instead of heuristics, the EIG is used to choose optimal control parameters in real-time. Moreover, combining the BED with accelerated computation and asynchronous operations, we find that up to a tenfold speed-up in absolute time cost can be achieved in sensing multiple surrounding C13 nuclear spins. Our work explores the possibilities of applying the EIG to BED-based quantum-sensing tasks and provides techniques useful to integrate BED into more generalized quantum sensing systems.