AI & ML
Realization Divergence in Multi-Provider Quantum Computing: A Pre-Registered Study of What Survives Measurement
arXiv cs.SE0 views
arXiv:2610.21714v1 Announce Type: new Abstract: Quantum programs pass through compilers, transpilers and vendor services before execution. However, the distance between what was written and what runs is rarely measured. We call this distance realization divergence: the observable difference in how an identical source circuit is realized and behaves across quantum software stacks. We report a hardware study across three vendors and four devices, combining pre-registered predictions with explicitly identified exploratory analyses and amendments. In a compilation experiment with assigned placement policies, embedding radius correlates with two-qubit overhead at Spearman 0.805, against 0.492 for circuit size. Under a fixed lowest-index policy, an eight-qubit Bernstein-Vazirani circuit exhibits greater execution divergence than a twelve-qubit circuit on IQM Emerald. The opposite ordering occurs on IQM Garnet. Both comparisons replicate across two repetitions with disjoint confidence intervals. These results support a placement-dependent explanation, without isolating individual hardware noise mechanisms. The same ordering inversion is absent on the all-to-all IonQ control. On Rigetti Cepheus, a follow-up using topology-aware native placement found no consistent advantage in correct-answer probability for either submission track, but did not establish equivalence between the tracks. Structural comparisons depend on metric weighting, placement and device generation. Provider interfaces also limit observability: Rigetti's supported-operation list remained unchanged across a device generation that replaced the native entangler. We classify silent interface failures in composed toolchains and identify checks at toolchain boundaries, connecting valid cross-provider comparisons with concrete software-quality practices.
Source:https://arxiv.org/abs/2610.21714PreviousPoison Valleys: Diagnosing Path-Dependent Failure in LLM Code RepairNextCodeHealth Predicts the Token Cost of Agentic Code Review: A Pre-Registered Study of 465 Agent-Authored Pull Requests
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