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    Scalable protocol for coherence estimation from scarce data: Theory and experiment

    Qi-Ming Ding1,2,3,*, Ting Zhang1,2,*, Hui Li4, and Da-Jian Zhang5,†

    • 1Center on Frontiers of Computing Studies, Peking University, Beijing 100871, China
    • 2School of Computer Science, Peking University, Beijing 100871, China
    • 3ZQuantum (Beijing) Technology Co., Ltd, Beijing 100871, China
    • 4College of Engineering and Applied Sciences, Nanjing University, Nanjing 210093, China
    • 5Department of Physics, Shandong University, Jinan 250100, China

    • *These authors contributed equally to this work.
    • †Contact author: zdj@sdu.edu.cn

    Phys. Rev. A 113, 032444 – Published 26 March, 2026

    DOI: https://doi.org/10.1103/g8sh-hts2

    Abstract

    Key quantum features like coherence are the fundamental resources enabling quantum advantages and ascertaining their presence in quantum systems is crucial for developing quantum technologies. This task, however, faces severe challenges in the noisy intermediate-scale quantum era. On one hand, experimental data are typically scarce, rendering full state reconstruction infeasible. On the other hand, these features are usually quantified by highly nonlinear functionals that elude efficient estimations via existing methods. In this work, we propose a scalable protocol for estimating coherence from scarce data and further experimentally demonstrate its practical utility. The key innovation here is to relax the potentially NP-hard coherence estimation problem into a computationally efficient optimization. This renders the computational cost in our protocol insensitive to the system size, in sharp contrast to the exponential growth in traditional methods. This work opens a route toward estimating coherence of large-scale quantum systems under data-scarce conditions.

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