Quantum computational sensing using quantum signal processing, quantum neural networks, and Hamiltonian engineering
Fig. 2, panel (f)
Classification error (%) against the number of sensing periods $N$ (log-log) for conventional sensing with a Ramsey interferometer (QS (R)) and with quantum phase estimation (QS (QPE), dashed, open circles) and for quantum computational sensing with $L = 2^3$ to $2^6$ layers. Error bars are the spread over trained protocols; the grey line marks $N = 2^6$.
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- Data: data.csv
Provenance
This panel was regenerated by running the authors' plotting code and data from their public data deposit (Zenodo: https://doi.org/10.5281/zenodo.15692099, CC BY 4.0), with the QS (QPE) series recovered from the published vector figure. The plot shown here is re-rendered for interactive viewing and analysis. See the paper for the original figure and full scientific context.
License: CC BY 4.0.
npj Quantum Inf. 12, 119 (2026) · DOI: 10.1038/s41534-026-01235-w · arXiv: 2507.15845
Other panels of Fig. 2: (a) (c) (e-1) (e-2) (e-3) (f-inset)
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