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IndisputableMonolith.Cosmology.RefineTrigger

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Selective reconstruction of a fine cell from a coarse partition: only blocks chosen by a decision predicate D are expanded, while cross-block events are always kept. Cosmogenesis and equilibrium arguments cite it when a rung-coarsened ledger must be refined without reopening every block. The module packages the reconstruction map, lossless criteria, and a descent law tying refinement to J-cost.

claimGiven a coarse partition of a fine cell and a decision predicate $D$ on blocks, reconstruct the fine ledger by retaining every cross-block event and expanding internal postings of a block if and only if $D$ holds on that block. Blocks left coarse contribute no internal postings. The module also records when this reconstruction is lossless and when refinement descends in $J$-cost.

background

Scale-adaptive cosmogenesis works with rung-coarsened ledgers: fine recognition events are grouped into blocks so that sigma and cost can be tracked exactly at coarser rungs. The upstream module RungCoarsen discharges theorem T-1: rung-coarsening is sigma-exact and cost-exact (the "literal" theorem of the Cosmogenesis north-star plan).

This module sits one step above that exact coarsening. A decision predicate $D$ marks which coarse blocks should be opened again. Reconstruction keeps the global cross-block skeleton fixed and only re-expands internal postings inside selected blocks; unselected blocks stay coarse and contribute nothing internal.

Sibling material introduces the reconstruction map, a losslessness criterion (round-trip fidelity under $D$), a descent law relating refinement to the Recognition Science $J$-cost $J(x)=(x+x^{-1})/2-1$, positivity and smallness facts for that cost, and a simple demand/bit interface used to drive which blocks open.

proof idea

Definition-heavy module with supporting lemmas rather than a single deep theorem. It defines the selective reconstruction operator from a coarse cell and predicate $D$, then proves characterizations of lossless reconstruction (when expanding exactly the $D$-selected blocks recovers the fine postings of interest). Descent and necessity lemmas connect the decision to monotone decrease of $J$-cost, using positivity of $J$ on the positive reals and the fact that $J$ can be arbitrarily small yet positive. Bit-level helpers package the open/closed choice per block.

why it matters in Recognition Science

Recognition equilibrium (the downstream consumer) needs a controlled way to refine a coarsened field while the forward dynamics posts forced mean-resolving events toward the $J$-minimal ground state. Without selective refine-under-$D$, every descent step would have to reopen the full fine ledger, breaking the T-1 coarsening discipline.

The module therefore supplies the refine trigger that lets Phase-7 forward dynamics stay on the coarse spine until a block's demand forces expansion. It links the literal coarsening theorem T-1 to the equilibrium convergence facts: dynamics may descend in $J$ at coarse grain and only pay the fine internal postings where $D$ fires. That is the bridge between rung-exact bookkeeping and the claim that recognition levels flow to the $J$-cost ground state on the coupling graph.

scope and limits

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declarations in this module (17)