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This research introduces round-trip state echo (RTSE) as a workload-specific diagnostic metric for evaluating quantum hardware performance, distinguishing it from static calibration scores. By analyzing execution snapshots across superconducting and trapped-ion systems, the study demonstrates that hardware reliability metrics are highly sensitive to compilation details and specific task batches rather than being universally transferable. These findings provide a rigorous framework for benchmarking quantum processors based on actual execution outcomes rather than theoretical error suppression claims.
From Round-Trip State Echo to Error Recovery: Snapshot-Resolved Quantum-Hardware Diagnostics
arXiv:2608.26010v1 Announce Type: new Abstract: End-to-end quantum-hardware scores need not transfer across workloads, compilations, or execution times. We specify a compilation-explicit screen-and-stress profile whose opening diagnostic is round-trip state echo (RTSE): prepare one of four tetrahedral qubit states at a route root, move it out and back by swaps, apply inverse preparation at the root, and record zero. An execution snapshot means a dated submitted task batch together with its captured capability document where available, not a certified calibration epoch. On sparse superconducting hardware, a byte-identical communication rerun changed route-level contrasts although the aggregate RTSE estimates differed by only 0.00125. In a separate prospectively frozen two-window length study, RTSE and the remote-inverse do-nothing predecessor's root marginal both fell from length 2 to length 10; the prespecified interaction did not support superior RTSE retention. The mean selected-output return probability across 64 deletion-recovery cells changed from 0.738 to 0.624 between IQM execution snapshots. On a trapped-ion service advertising all-to-all connectivity among five submitted virtual wires, recovery was 0.911 and 0.923 in two windows, exceeding the frozen two-thirds reference; recovery-minus-adjoint-control differences were 0.446 and 0.443. These are execution-workload diagnostics, not coding-gain, error-suppression, physical-loss, fault-tolerance, or architecture-ranking claims. The results support assessment indexed by workload, placement or virtual-wire contract, compilation, architecture, and execution snapshot.
Abstract:End-to-end quantum-hardware scores need not transfer across workloads, compilations, or execution times. We specify a compilation-explicit screen-and-stress profile whose opening diagnostic is round-trip state echo (RTSE): prepare one of four tetrahedral qubit states at a route root, move it out and back by swaps, apply inverse preparation at the root, and record zero. An execution snapshot means a dated submitted task batch together with its captured capability document where available, not a certified calibration epoch. On sparse superconducting hardware, a byte-identical communication rerun changed route-level contrasts although the aggregate RTSE estimates differed by only 0.00125. In a separate prospectively frozen two-window length study, RTSE and the remote-inverse do-nothing predecessor's root marginal both fell from length 2 to length 10; the prespecified interaction did not support superior RTSE retention. The mean selected-output return probability across 64 deletion-recovery cells changed from 0.738 to 0.624 between IQM execution snapshots. On a trapped-ion service advertising all-to-all connectivity among five submitted virtual wires, recovery was 0.911 and 0.923 in two windows, exceeding the frozen two-thirds reference; recovery-minus-adjoint-control differences were 0.446 and 0.443. These are execution-workload diagnostics, not coding-gain, error-suppression, physical-loss, fault-tolerance, or architecture-ranking claims. The results support assessment indexed by workload, placement or virtual-wire contract, compilation, architecture, and execution snapshot.
43 pages, 11 figures, 10 tables. Reproducibility package: doi:https://doi.org/10.5281/zenodo.21969397
arXiv:2608.26010 [quant-ph]
(or arXiv:2608.26010v1 [quant-ph] for this version)
https://doi.org/10.48550/arXiv.2608.26010 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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