English

Observable Estimation in the Absence of Classical Verification

Quantum Physics 2026-07-28 v1

Abstract

The predictive success of quantum mechanics underpins many areas of modern science, even as the exact simulation of large, interacting quantum systems remains beyond the reach of classical computation. This success has been enabled by the remarkable advancement of scalable numerical approximation methods, which often demonstrate practical accuracy despite the absence of formal guarantees. As quantum simulation pushes into regimes where these approximations struggle, a fundamental challenge arises: How can quantum outcomes be trusted when reliable classical benchmarks are unavailable? Here, we establish a framework for the independent validation of quantum estimates in this setting and present evidence that they provide the most credible result among several considered methods, in the absence of an immediately accessible ground-truth solution. We apply our framework to the semi-scrambling dynamics of a physical model that strains several leading classical simulation methods yet remains experimentally accessible, in part through our introduction of the \textit{operator Loschmidt echo}. We systematically design a series of experiments using quantum heuristics that, taken together, test the underlying assumptions and provide strong confidence in the observable estimates obtained from the quantum computer. We then show how this framework can be extended to place accuracy bounds on quantum estimates via careful characterization and manipulation of the device noise, transforming the problem of validating the observable estimation to validating the noise model. These results establish a route towards trusted quantum computation for scientific discovery, independent of classical verification.

Cite

@article{arxiv.2607.25998,
  title  = {Observable Estimation in the Absence of Classical Verification},
  author = {Samantha V. Barron and Bradley Mitchell and Vinay Tripathi and Francesco Grieco and Ilan Rosen and Francesca Pietracaprina and Davide Materia and Alireza Seif and Darvin Wanisch and Ramón L. Panadés-Barrueta and Ewout van den Berg and Jay-U Chung and Andrew Eddins and Sam Ferracin and Guillermo García-Pérez and John Goold and Luke C. G. Govia and Holger Haas and Ian Hincks and Jesse C. Hoke and Zoë Holmes and Su-un Lee and Youngseok Kim and Swarnadeep Majumder and Sabrina Maniscalco and Simone Montangero and Daniel Puzzuoli and Tomaž Prosen and James Raftery and Ricardo Rivera Cardoso and Max Rossmannek and Manuel Rudolph and Brendan Saxberg and Liran Shirizly and Karthik Siva and Joshua Skanes-Norman and Ilaria Siloi and Kevin C Smith and Boris Sokolov and Maika Takita and Yanting Teng and Mao Tian Tan and Joseph Tindall and Zoltán Zimborás and Matteo A. C. Rossi and Minh C. Tran and Sergei N. Filippov and Abhinav Kandala},
  journal= {arXiv preprint arXiv:2607.25998},
  year   = {2026}
}