Gate Set Tomography Under the Influence of Time-Correlated Noise

Abstract

This thesis investigates the robustness of Gate Set Tomography (GST) under the influence of time-correlated (non-Markovian) noise. GST is a widely used protocol for characterizing quantum gates, yet its efficacy traditionally relies on the assumption of Markovian noise, where errors are memoryless. This research challenges this assumption by introducing non-Markovian noise into simulated GST experiments using a custom-developed Python library. The study com- pares baseline GST performance under Markovian noise with GST results un- der various non-Markovian noise conditions. The findings highlight significant discrepancies in GST’s error reporting and reveal a distinct trade-off between GST’s accuracy and consistency in practical, non-Markovian settings. This work contributes to the broader understanding of error characterization in quantum computing and provides a robust framework for future studies in quantum gate fidelity under realistic noise conditions.