Characterizing non-Markovian Quantum Process by Fast Bayesian Tomography

TL;DR

This paper demonstrates how Fast Bayesian Tomography (FBT) can effectively characterize non-Markovian errors in quantum gates, aiding the development of fault-tolerant quantum computing.

Contribution

The paper introduces experimental protocols and software tools for FBT to diagnose non-Markovian errors in two-qubit silicon quantum dot systems.

Findings

FBT successfully characterizes non-Markovian error processes.

Development of an online FBT software stack enhances scalability.

Native readout and warm boot strategies reduce experiment cost and time.

Abstract

To push gate performance to levels beyond the thresholds for quantum error correction, it is important to characterize the error sources occurring on quantum gates. However, the characterization of non-Markovian error poses a challenge to current quantum process tomography techniques. Fast Bayesian Tomography (FBT) is a self-consistent gate set tomography protocol that can be bootstrapped from earlier characterization knowledge and be updated in real-time with arbitrary gate sequences. Here we demonstrate how FBT allows for the characterization of key non-Markovian error processes. We introduce two experimental protocols for FBT to diagnose the non-Markovian behavior of two-qubit systems on silicon quantum dots. To increase the efficiency and scalability of the experiment-analysis loop, we develop an online FBT software stack. To reduce experiment cost and analysis time, we also introduce a native readout method and warm boot strategy. Our results demonstrate that FBT is a useful tool for probing non-Markovian errors that can be detrimental to the ultimate realization of fault-tolerant operation on quantum computing.