Computational Electromagnetics Meets Spin Qubits: Controlling Noise Effects in Quantum Sensing and Computing

TL;DR

This paper introduces a computational electromagnetics framework using volume integral equation solvers to control electromagnetic noise in spin qubit devices, improving their performance in quantum sensing and computing.

Contribution

It develops a novel quantum computational electromagnetics approach to effectively model and mitigate low-frequency electromagnetic noise in spin qubit systems.

Findings

Successfully applied the framework to realistic quantum devices.

Enhanced control of magnetic fluctuation noise in spin qubit applications.

Demonstrated improved device performance through noise mitigation.

Abstract

Solid-state spin qubits have emerged as promising platforms for quantum information. 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 lossy material components 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 devices, 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 quantum computational electromagnetics framework to control low-frequency magnetic fluctuation noise and enhance spin qubit device performance. Our framework extends the application of computational electromagnetics to spin qubit quantum devices. Furthermore, we demonstrate the application of our framework in realistic quantum devices. Our work paves the way for device engineering to control magnetic fluctuations and improve the performance of spin qubit quantum sensing and computing.