Effect of Stochastic Charge Noise in Si/SiGe Quantum-Dot Spin Qubits

TL;DR

This paper develops a stochastic spin-phonon model incorporating 1/f charge noise to accurately predict decoherence in Si/SiGe quantum-dot spin qubits, leading to improved gate fidelity and noise robustness.

Contribution

It introduces a novel non-Markovian noise model based on electric dipole resonance and 1/f spectrum, enhancing decoherence simulation and control pulse optimization.

Findings

More precise decoherence prediction with the stochastic model.

Optimized control pulses significantly reduce error contributions.

Enhanced robustness of pulses against coherent noise.

Abstract

In Si/SiGe quantum dots, the decoherence behavior of spin qubits usually comes from the non-Markovian effect of the charge noise. To improve the performance of using the coherent noise models in the decoherence simulation and tomography analysis, here we propose a spin-phonon model derived from the electric dipole spin resonance to characterize the decoherence behavior of the spin qubit in a Si/SiGe quantum dot. Utilizing a 1/f spectrum to characterize quantum noise correlation, our stochastic model can yield a more precise prediction of decoherence compared to a random coherence model. We also use gate set tomography (GST) to address the error generator and analyze the model violation coming from the non-Markovian effect. Based on the results, we attribute certain error generators of this model to the incoherence error, which avoids the scenario of using too large a coherent noise strength in the previous study to account for the experimentally observed decoherence times, and thus underestimates the gate fidelity. We also perform a gate optimization and show that our optimized control pulse can substantially reduce the error contribution of the incoherent non-Markovian 1/f charge noise. We further demonstrate that the optimized pulse against incoherent noise is more robust against coherent noise than the regular Gaussian pulse through a filter function analysis in a CPMG protocol, demonstrating the significant effectiveness of the optimized pulse.