Improving quantum sensing using variational quantum optimization algorithms

The laws of quantum mechanics govern the ultimate precision limits of sensing. Novel sensors that use quantum effects such as superposition states and entanglement are known to be capable of attaining these fundamental limits in principle. Successful quantum sensor applications include atomic clocks for GPS navigation and nuclear spin control for magnetic resonance imaging (MRI). Among the different physical platforms that are being currently explored, nitrogen vacancy (NV) defects in diamond offer unique advantages for quantum magnetometers. They can provide nano-scale spatial resolution, optical interrogation, nanotesla sensitivity, and a wide range of temperature operation (from mK to 600 K). However, it is an outstanding challenge to achieve the ultimate sensitivity limits for these quantum sensors in the presence of environmental noise and other inefficiencies. In this project, we propose to take a novel variational approach to overcome this challenge. It will involve developing and using hybrid quantum-classical algorithms to variationally optimize the state preparation, generalized measurements, and quantum circuits for control operations on the NV-center based quantum sensors towards achieving quantum-limited sensitivity. Our team brings together a diverse set of expertise (from physics, and computing and information) to seed this new effort in what is a nascent area of research