Skip to content
aiqbench takeQuantum Computing

aiqbench analysis

This paper introduces Heisenberg-echo symmetrization (HES), a novel technique for quantum error mitigation that corrects the noise amplification scaling failures of standard gate insertion methods in realistic, non-commuting environments. By combining gate insertion with an echo inspired by the Heisenberg representation, HES significantly reduces fidelity errors while maintaining compatibility with various hardware platforms and offering resilience against temporal noise drift. The method is particularly effective for rank-one observables, providing a robust alternative to existing mitigation strategies like Layered-KIK without requiring deep circuit access.
Source coveringarXiv
What this isA model's reading of the article and related coverage, written for aiqbench. Not the publisher's words.

Heisenberg Echo Symmetrization for Gate-Insertion Error Mitigation

arXiv2 min read

arXiv:2610.11372v1 Announce Type: new Abstract: Gate insertion (GI) quantum error mitigation replaces involutory gates such as CZ and CX with 2j+1 repetitions of the same gates to nominally amplify noise by the same factor. Analytical and experimental results show that this amplification scaling fails for non-commuting gate noise, as typically encountered in realistic devices. Here we introduce Heisenberg-echo symmetrization (HES), which combines standard GI with an echo inspired by the Heisenberg representation to cancel the leading GI error. In our simulations, HES reduces the absolute fidelity error by one to two orders of magnitude compared with GI. Unlike the more accurate Layered-KIK method, HES is compatible with any hardware and requires only circuit-level access. It enables virtual noise scaling across platforms, potentially reducing sampling overhead substantially. Its agnostic noise amplification also provides full resilience to temporal noise drift. For pure initial states, however, high-rank observables can substantially increase the echo variance relative to non-echoed circuits, whereas rank-one observables incur no additional sampling overhead compared with GI or Layered-KIK. HES is therefore particularly suited to rank-one or nearly rank-one observables.

Abstract:Gate insertion (GI) quantum error mitigation replaces involutory gates such as CZ and CX with 2j+1 repetitions of the same gates to nominally amplify noise by the same factor. Analytical and experimental results show that this amplification scaling fails for non-commuting gate noise, as typically encountered in realistic devices. Here we introduce Heisenberg-echo symmetrization (HES), which combines standard GI with an echo inspired by the Heisenberg representation to cancel the leading GI error. In our simulations, HES reduces the absolute fidelity error by one to two orders of magnitude compared with GI. Unlike the more accurate Layered-KIK method, HES is compatible with any hardware and requires only circuit-level access. It enables virtual noise scaling across platforms, potentially reducing sampling overhead substantially. Its agnostic noise amplification also provides full resilience to temporal noise drift. For pure initial states, however, high-rank observables can substantially increase the echo variance relative to non-echoed circuits, whereas rank-one observables incur no additional sampling overhead compared with GI or Layered-KIK. HES is therefore particularly suited to rank-one or nearly rank-one observables.

arXiv:2610.11372 [quant-ph]

(or arXiv:2610.11372v1 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2610.11372 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Full text under the publisher's open licence · 265 words

Related coverage