  Solid-state spin qubits have emerged as promising quantum information
platforms but are susceptible to magnetic noise. Despite extensive efforts in
controlling noise in spin qubit quantum applications, one important but less
controlled noise source is near-field electromagnetic fluctuations.
Low-frequency (MHz and GHz) electromagnetic fluctuations are significantly
enhanced near nanostructured lossy material components essential in quantum
applications, including metallic/superconducting gates necessary for
controlling spin qubits in quantum computing devices and
materials/nanostructures to be probed in quantum sensing. Although controlling
this low-frequency electromagnetic fluctuation noise is crucial for improving
the performance of quantum sensing and computing, current efforts are hindered
by computational challenges. In this paper, we leverage advanced computational
electromagnetics techniques, especially fast and accurate volume integral
equation based solvers, to overcome the computational obstacle. We introduce a
theoretical and computational framework to control low-frequency magnetic
fluctuation noise for enhancing spin qubit quantum sensing and computing
performance. Our framework extends the application of computational
electromagnetics to spin qubit quantum devices. We further apply our
theoretical framework to control noise effects in realistic quantum computing
devices and quantum sensing applications. Our work paves the way for device
engineering to control magnetic fluctuations and improve the performance of
spin qubit quantum sensing and computing.
