Constraint Geometry and the Limits of Scalable Computation: Toward Coherence-Preserving Architectures

Modern computational systems face persistent scaling limits despite advances in hardware and algorithms. As size increases, coordination overhead, correlated failures, and control bottlenecks degrade performance in both classical distributed systems and emerging quantum architectures. Building on the Constraint-based Epistemology of Scaling (CES), this work argues that these limits arise from coherence budget exhaustion: constraint burden grows faster than control capacity, shifting system behavior from controllable dynamics to domination by constraint geometry. Beyond this transition, local component improvements yield diminishing returns. We examine CES manifestations in classical and quantum computation and propose coherencepreserving architectural principles: modularity, locality, constraint slack, hierarchical control, and topology-aware scheduling. These findings suggest that sustainable scaling depends primarily on managing constraint structure rather than solely enhancing component performance. This paper concludes the CES trilogy by linking structural theory, operational diagnostics, and architectural design for future computational systems.