Gap-closing experimental estimation of quantum Fisher information.

Authors

Qian-Xi Zhang, Qi-Ming Ding, Hu Chen, Shan Ling, Ya-Li Mao, Da-Jian Zhang, Xiao Yuan, Zheng-Da Li

Published in

Science advances. Volume 12. Issue 37. Pages eaef4342. Sep 11, 2026. Epub Sep 09, 2026.

Abstract

Estimating the quantum Fisher information (QFI) is a central task in quantum science and technology, underpinning the benchmarking of measurement devices and the certification of metrological advantages. Owing to the highly nonlinear dependence of the QFI on the quantum state, achieving efficient estimates that reliably converge to the true value, which is a property known as gap closing, has remained a challenge. Here, we address it experimentally by implementing the recently proposed Krylov shadow tomography (KST) protocol on a versatile photonic platform capable of generating Greenberger-Horne-Zeilinger states of up to six qubits with controllable noise. By comparing KST with leading methods under matched resources, we show that it exhibits the predicted gap-closing behavior and yields a substantially lower mean absolute error. Moreover, we demonstrate that the resulting high-accuracy QFI estimates correctly predict the ultimate precision achievable in a phase estimation experiment, as dictated by the quantum Cramér-Rao bound. These results establish KST as a scalable and practical experimental tool for the efficient characterization and utilization of quantum resources in metrological applications.

PMID:
42715322
Bibliographic data and abstract were imported from PubMed on 10 Sep 2026.

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