ExpandQISE: Track 1: Micron Scale Solid State Quantum Sensors Optimized through Machine Learning

Non-technical Abstract: Quantum sensing is a disruptive technology that has already found applications in various research fields. Quantum sensing with defects is one of the leading approaches owing its success mostly to the room temperature operation capability of nitrogen vacancy (NV) color center defects in diamond. The project aims to expand the current research capabilities on quantum sensing with defects at Morgan State University (MSU). The outcomes of this project will accelerate the development of products that benefit the broader community directly. This project will also contribute to the diversity of Quantum Information Science and Engineering (QISE) workforce by training minority students in quantum sensing experimental projects. More minority students will be trained on QISE concepts and applications through new quantum science courses at MSU. Two weeks long summer workshops will be organized to train at least eight minority serving K12 teachers each year on how to teach quantum science to their students. A QISE certificate program will be established. Over a thousand K-12 students and parents will be exposed to quantum science concepts at the annual MSU STEM Expo via lectures and hands-on demonstrations. Technical Abstract: Quantum sensing of extremely small changes in temperature, host material strain, magnetic and electric fields was successfully demonstrated with NV defects in diamond, where optically detected magnetic resonance (ODMR) method is a key component. However, current sensitivities of solid-state defect-based quantum sensors are orders of magnitude less than the predicted theoretical limits. A range of continuous wave (CW) and pulsed ODMR protocols were developed for improving detection limits of quantum sensing experiments with defects. Machine learning (ML) algorithms have the potential to enhance the sensitivities of these quantum sensors. In addition, there are numerous aspects of NV physics, including charge dynamics in ensembles, that are still not well understood and thus require further research and exploration. Furthermore, current experimental solid-state defect-based quantum sensor setups are bulky and small footprint versions are yet to be demonstrated. There is also an increasing interest in other defects in wide bandgap semiconductors for their use in quantum sensing applications as alternatives to NV defects in diamond. The project team will collaborate with an expert in solid-state defect-based quantum sensors at the University of Chicago/Argonne National Laboratory to improve the existing setups by implementing pulsed, AC, and resonant coupling ODMR protocols and other hardware additions. New ML algorithms will pave the way to demonstrate enhanced sensitivities approaching predicted theoretical limits. Diamond growth and treatment methods will be established to obtain high-quality diamond samples with high NV concentrations. Micron-scale solid-state defect-based integrated circuit quantum sensors will be demonstrated for the first time. Extending the improved capabilities for characterization and device fabrication to other defects in wide bandgap semiconductors will advance the understanding of their properties and will facilitate their application in a wide range of quantum sensing applications. This project is jointly funded by the Historically Black Colleges and Universities - Undergraduate Program (HBCU-UP), the Office of Multidisciplinary Activities (MPS/OMA), and the Technology Frontiers Program (TIP/TF). This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.