Constraint Geometry as a Scaling Bottleneck in Quantum Systems: A Structured Residual Framework for Quantum Hardware

Efforts to scale quantum hardware are commonly framed as a challenge of suppressing local decoherence and stochastic noise through improved physical qubits and quantum error correction. Yet large-scale devices routinely exhibit performance degradation inconsistent with bounded-complexity local noise models, including nonstationary drift, bursty correlated events, and long-range crosstalk. We propose a constraint-based scaling framework in which the dominant limitation to scalability is not local error amplitude but the accumulation of constraint geometry: structured, correlated degrees of freedom that grow with system size and cannot be absorbed by standard endogenous noise models. We formalize this via (i) a bounded-complexity endogenous model class, (ii) a structured residual observable isolating unexplained degradation, and (iii) a coherence budget comparing effective control capacity to constraint burden. We identify a regime transition-the coherence wall-at which constraint burden outpaces control capacity, leading to rapid performance collapse despite stable local fidelities. We provide operational measurement protocols for extracting structured residual scaling, correlated dimensionality, and perturbation sensitivity from standard benchmarking data. The framework yields falsifiable architectural predictions and offers a diagnostic layer bridging quantum theory and scalable quantum engineering.