Theory of Inversive Symmetry: Record-Constrained Dynamics (Restrictive Accumulation) and Emergent Plateaus under Adversarial Stress Tests

What if “laws” are not fundamental forces—but the residue of history becoming active?Theory of Inversive Symmetry reframes Manifestation (T) and Non‑Manifestation (∅) as dual phases of a single informational totality, organized by a Consistency–Resolution duality. The guiding bet is simple and sharp: instead of inventing new microphysics, treat accumulated constraint as a selection principle that repeatedly sculpts what becomes stable, measurable, and “law‑like” inside a realized regime. To make this falsifiable in a minimal setting, the preprint introduces Restrictive Accumulation (RA): a tiny record‑feedback rule where deposited traces bias and constrain subsequent transitions. RA is not claimed to be the universe’s microdynamics; it is used as a controlled proxy for a deeper idea—history is not a passive archive, it can become an active control parameter. A matched history‑free control (FREE) deposits identical records but removes feedback from the transition rule, cleanly separating “trace formation” from genuine history‑dependence. Across many small but convergent simulations (all sharing the same underlying rules), the same pattern keeps reappearing: when feedback from records is switched on, the system enters a distinct informational regime. Order plateaus emerge; event‑throughput changes; “time” measured in executed events becomes state‑dependent; reversibility degrades asymmetrically under forward–backward stress; and shared‑history effects persist under later competing evolution—signatures that are absent or strongly reduced in FREE. The point is not that any one toy model is “the world”, but that a minimal accumulation constraint can repeatedly produce regime‑level structure across orthogonal diagnostics. This work is an invitation to stress‑test a provocative thesis: constants and effective laws may be the sediment of saturation—what remains when a system has largely exhausted its capacity to keep “learning” new structure under accumulating constraints. If these signatures survive broader sweeps and scaling, they become candidates for scale‑robust bounds or invariant couplings. If they fail, the framework gains clear falsifiers and a concrete path to refinement.