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The platform of silicon-based spin qubits holds significant potential for the hardware implementation of quantum computing. Charge noise, however, notably hinders the performance and scalability of silicon-spin-based quantum computing technologies. Here we computationally investigated correlated charge noise in silicon spin quantum computing devices by developing and applying a Green’s transfer function approach. The approach allows for the systematic simulation and analysis of both the noise's auto-correlation and cross-correlation spectrums in a physics-based manner. We simulate the correlated noise's power spectral density (PSD) in silicon spin qubit devices. The results indicate strong cross-correlation and show phase-flipping features in neighboring silicon spin qubits, in agreement with a recent experiment. Given that each spin qubit device is small and influenced by a limited number of two-level fluctuators (TLFs), the arrangement of these TLFs plays a crucial role in the correlation of noise. The simulation study highlights the need to consider noise correlation and its related spectral features in developing robust quantum computing technologies based on silicon spin qubits. 

Silicon-based spin qubits represent a promising technology for scalable quantum computing. However, the complex nature of this field, which requires a deep understanding of quantum mechanics, materials science, and nanoelectronics, poses a significant challenge in making it accessible to future engineers and scientists. Spin Quantum Gate Lab, a spin qubit simulation tool, is proposed in this paper to address this obstacle. This tool is designed to introduce key concepts of spin qubit to undergraduate students, enabling the simulation of single-qubit rotational gates and two-qubit controlled-phase gates. By providing hands-on experience with quantum gate operations, it effectively links theoretical quantum concepts to practical experience, fostering a deeper understanding of silicon-based quantum computing.