Admissibility Before Optimisation in Quantum Control: An Evidence-Governed Framework for Prospective Hardware Validation
Year: 2026
Type: preprint
Abstract: Quantum-control optimisation typically begins with calibration records assumed to remain applicable to the intended operation. Yet coherence, phase references, coupling, read-out response and subsystem interactions vary with time and operating context. Local calibration success may therefore be insuffi- cient to justify joint or changed-context control, allowing optimisation to pursue candidates founded on stale, incomplete or inapplicable evidence. We propose an evidence-governed admissibility framework that checks evidence role, scope, freshness, provenance and composition authority before constructing control candidates. Its computational layers have distinct functions: Layer 1 classifies routes as Permit, Withhold or Revalidate, retaining auditable native states and reasons; Layer 2A constructs and screens reduced-model candidates only for permitted routes; and Layer 2B checks applicable end-to-end workflows. Synthetic integration and authority-ablation tests demonstrate enforceable differences in permission, and the implementation passed 150/150 core and 10/10 slew-specific tests. These are computational findings, not hardware validation. We also provide two complementary prospective experimental arms for evaluating practical benefit. Arm 1 (predictive lift) freezes assessments before hardware outcomes are known and tests whether they predict the performance of independently authorised ordinary-baseline operations better than calibration- or availability-only benchmarks. Arm 2 (constructive recovery) tests whether initially unsuitable cases can yield authorised alternative controls after evidence refresh or reconfirmation, a new Layer 1 decision and downstream construction, while preserving the original classification. We release code, schemas, guided workbooks, fixtures and prespecified protocols for independent pilots. Hardware validation could establish whether this approach reduces wasted searches and improves control reliability or qubit performance.
Source: Preprints.org
Author: Paul Swann
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7224961801