Quantum Computer Fingerprinting using Error Syndromes

TL;DR

This paper introduces a method to verify quantum hardware identity and authenticate computations by utilizing error syndrome data from quantum error correction, achieving high accuracy without extra quantum resources.

Contribution

It presents a novel approach to leverage error syndromes for quantum verification, integrating security into existing QEC protocols without additional quantum operations.

Findings

Achieved 99% accuracy in backend classification with 500 shots.

Validated approach on multiple error-correcting codes and quantum hardware.

Demonstrated seamless integration of verification into standard QEC procedures.

Abstract

As quantum computing matures and moves toward broader accessibility through cloud-based platforms, ensuring the authenticity and integrity of quantum computations becomes an urgent concern. In this work, we propose a strategy to leverage the byproducts of quantum error correction (QEC) to verify hardware identity and authenticate quantum computations for "free", without introducing any additional quantum computations or measurements. By treating syndrome measurements as a source of metadata, we embed verification seamlessly into standard QEC protocols and eliminate the need for separate challenge-response pairs. We validate our approach using multiple error-correcting codes, quantum states, and circuit compilation strategies on several generations of IBM quantum computers. Our classifiers achieve 99% accuracy with only 500 shots in distinguishing among five backends. Overall, we re-purpose the intrinsic overhead of error correction to be a mechanism for securing quantum computation.