Quantum Process Tomography with Digital Twins of Error Matrices

TL;DR

This paper introduces an improved quantum process tomography method that uses digital twins of error matrices to enhance accuracy and robustness, especially in the presence of SPAM errors, validated through simulations and superconducting qubit experiments.

Contribution

The paper presents a novel QPT approach integrating digital twin error matrices to refine SPAM error learning and improve process fidelity measurement.

Findings

Achieves at least tenfold fidelity improvement over standard QPT.

Enables more accurate and reliable quantum gate characterization.

Validated through numerical simulations and superconducting qubit experiments.

Abstract

Accurate and robust quantum process tomography (QPT) is crucial for verifying quantum gates and diagnosing implementation faults in experiments aimed at building universal quantum computers. However, the reliability of QPT protocols is often compromised by faulty probes, particularly state preparation and measurement (SPAM) errors, which introduce fundamental inconsistencies in traditional QPT algorithms. We propose and investigate enhanced QPT for multi-qubit systems by integrating the error matrix in a digital twin of the identity process matrix, enabling statistical refinement of SPAM error learning and improving QPT precision. Through numerical simulations, we demonstrate that our approach enables highly accurate and faithful process characterization. We further validate our method experimentally using superconducting quantum gates, achieving at least an order-of-magnitude fidelity improvement over standard QPT. Our results provide a practical and precise method for assessing quantum gate fidelity and enhancing QPT on a given hardware.