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Quantum Process Tomography with Digital Twins of Error Matrices

Tangyou Huang1,2, Akshay Gaikwad1,*, Ilya Moskalenko2, Anuj Aggarwal1, Tahereh Abad1, Marko Kuzmanović2, Yu-Han Chang2, Ognjen Stanisavljević2, Emil Hogedal1 et al.

Christhopher Warren1, Irshad Ahmad1, Janka Biznárová1, Amr Osman1, Mamta Dahiya1, Marcus Rommel1, Anita Fadavi Rousari1, Andreas Nylander1, Liangyu Chen1, Jonas Bylander1, Gheorghe Sorin Paraoanu2, Anton Frisk Kockum1, and Giovanna Tancredi1

  • *Contact author: akshayga@chalmers.se
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Phys. Rev. Lett. 135, 230601 – Published 1 December, 2025

DOI: https://doi.org/10.1103/dpgy-rtxr

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 multiqubit 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 in superconducting quantum processors, 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.

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Phys. Rev. Lett. 135, 230601– Published 1 December, 2025
  • Received 26 May 2025
  • Revised 18 September 2025
  • Accepted 13 November 2025
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Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI. Funded by Bibsam.

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