Quantum computational sensing using quantum signal processing, quantum neural networks, and Hamiltonian engineering

Saeed A. Khan; Sridhar Prabhu; Logan G. Wright; Peter L. McMahon

doi:10.1038/s41534-026-01235-w

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Quantum computational sensing using quantum signal processing, quantum neural networks, and Hamiltonian engineering

Saeed A. Khan, Sridhar Prabhu, Logan G. Wright, Peter L. McMahon

2026npj Quantum Information 12, 119CC BY 4.0LCP000070

Fig. 5, panel (e-5)

Single instance of the estimator $\mathcal{F}_{\mathrm{QCS}}$ for the XOR task passed through the thresholding function (shaded class) over $(\alpha_x, \alpha_y)$, with the training points. One sampled realization, not the printed one.

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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). 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. 5: (d-1) (d-2) (d-3) (d-4) (d-5) (d-6) (d-7) (e-1) (e-2) (e-3) (e-4) (e-6) (e-7) (e-8) (f-1) (f-2) (f-3) (f-4) (f-5) (f-6) (f-7) (f-8)

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