Strategies to Predict and Design Spin Defects for Quantum Technologies

The design of materials with functionalities optimally suited for quantum information applications is a critical need in the field of quantum science and engineering. This perspective focuses on a specific class of systems, spin defects in semiconductors and insulators, and on the manipulation of their electron spins, which can provide controllable qubits with long relaxation and coherence times, and they can be coupled to nuclear spins for long-lived quantum memories. We summarize our recent contributions to the development of integrated theoretical frameworks and high-performance codes to predict and design spin defects and present examples of validated predictions and interpretations of experimental results. Starting from a brief description of the structural and charge stability at zero temperature using density functional theory, we present simulations to understand the mechanism of spin defect formation with first-principles molecular dynamics and machine-learned potentials. We then discuss two classes of properties that are essential for the prediction of spin defects' functionalities: electronic and coherence properties. The discussion of computational frameworks is followed by that of results for specific systems illustrating successes, open problems, and future applications, with examples for heterogeneous solids, inclusive of surfaces and mesoscopic defects, and with a focus on quantum sensing and communication applications.