This work presents a structural critique of calibration-based control frameworks for superconducting quantum computing systems, with particular focus on architectures relying on recursive calibration loops and dependency graph formalism. It is shown that the current paradigm does not resolve the fundamental problem of physical instability, but instead formalizes it as an operational requirement. Continuous recalibration, parameter drift, and dependency-driven control structures indicate the absence of stable, reproducible computational states. The analysis demonstrates that the system does not admit a stationary operational regime, and that control is effectively shifted from physical determinacy to procedural scheduling. Directed acyclic graphs and calibration routines are shown to reorganize instability rather than eliminate it. Furthermore, the framework lacks invariant quantities, external validation criteria, and any demonstrated convergence toward stable configurations. Validation remains internal and self-referential, preventing the establishment of physically meaningful computational states. Scalability is assumed through automation, but no structural argument is provided to ensure bounded error propagation or stability under system growth. As a result, increasing system size amplifies the instability it attempts to manage. The work concludes that the calibration-based paradigm represents a systematic redefinition of instability as workflow. The resulting architecture does not achieve control of a quantum system, but continuous management of its failure modes.
Livolsi Edoardo (Tue,) studied this question.