End-to-end runtime of hardware-executed QCS

Quantify the end-to-end runtime of Interleaved Quantum Computational Sensing when the classical simulation of the sensing dynamics is replaced by physical Nitrogen-Vacancy evolution, requiring validation on quantum hardware.

Background

The paper reports QCS training times obtained by simulating and optimizing Lindblad NV dynamics on a classical CPU. These timings measure offline simulation and optimization cost rather than the latency of physical QCS inference.

The authors state that a hardware implementation would replace the classical simulation with physical NV evolution, but the resulting end-to-end runtime has not been quantified. Resolving this issue would establish the practical latency of the proposed one-setting measurement strategy and distinguish its measurement-efficiency advantage from its hardware execution cost.

References

Hardware execution would replace the classical simulation of the sensing dynamics with the physical NV evolution itself; quantifying the resulting end-to-end runtime requires a hardware implementation and is left for future work.

— When Measurement Constraints Favor Quantum Computational Sensing for Stealthy Power-Grid Attack Detection  (2609.10606 - Gopalakrishnan et al., 8 Sep 2026) in Appendix, Section "Measurement Controls, Reconstruction, and Compute Cost", subsection "Training compute"