Computational Efflux from Coherent Actual Objects: Theory, Algorithm, and Empirical Demonstration

Computational efflux — the surplus radiated by coherent actual objects as a structural consequence of their coherence — exists independently of whether any system exploits it. This paper is the first to formalize the phenomenon: specifying the conditions under which a structure qualifies as a coherent actual object (consequence chain closure, non-depletion, Noether invariance), proving that positive computational surplus follows necessarily from those conditions, quantifying the surplus as an MDL differential, and deriving a general algorithm for deliberate exploitation. Prior methods that benefit from coherent structure — equivariant networks, transfer learning, compressed sensing — harvest efflux without naming it. Their existence confirms the phenomenon; this paper provides the formalization that makes systematic exploitation possible across arbitrary coherent structures, not only the ones prior methods happened to encode.