We present and validate a method for noise injection of arbitrary spectra in quantum circuits that can be applied to any system capable of executing arbitrary single qubit rotations, including cloud-based quantum processors. As the consequences of temporally correlated noise on the performance of quantum algorithms are not well understood, the capability to engineer and inject such noise in quantum systems is paramount. To date, noise injection capabilities have been limited and highly platform specific, requiring low-level access to control hardware. We experimentally validate our method by comparing to a direct hardware-based noise-injection scheme. Using a combination of quantum noise spectroscopy and classical signal analysis, we show that the two approaches agree. These results showcase a highly versatile method for noise injection that can be utilized by theoretical and experimental researchers to verify, evaluate, and improve quantum characterization protocols and quantum algorithms for sensing and computing.

Silicon carbide is a promising host material for spin-defect-based quantum sensors owing to its commercial availability and established techniques for electrical and optical microfabricated device integration. The negatively charged silicon vacancy is one of the leading spin defects studied in silicon carbide owing to its near-telecom photoemission, high spin number, and nearly temperature-independent ground-state zero-field splitting. We report the realization of nanotesla shot-noise-limited ensemble magnetometry based on optically detected magnetic resonance with the silicon vacancy in 4H silicon carbide. By coarsely optimizing the anneal parameters and minimizing power broadening, we achieve a sensitivity of 50 nT/root Hz and a theoretical shot-noise-limited sensitivity of 3.5 nT/ root Hz. This is accomplished without utilizing complex photonic engineering, control protocols, or applying excitation powers greater than a watt. This work demonstrates that the silicon vacancy in silicon carbide provides a low-cost and simple approach to quantum sensing of magnetic fields.