Pith. sign in
module module moderate

IndisputableMonolith.Cost.GaugeOrbitFromRealCharacter

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Structural ledger data on the native cost imply the light hypothesis pack needed for real-character factorization. The module builds a sign-gauge native cost from that ledger, records its monotonicity, zero-calibration, and rational-trace properties, and packages it as a real-character candidate. Gauge-orbit classification cites this bridge. The argument is mostly structural unpacking plus elementary sign-gauge identities.

claimFrom the PRC native-cost structural ledger one obtains the light hypothesis pack for real-character factorization. A sign-gauge native cost $C_{\mathrm{sg}}$ is defined on the ledger data; it is monotone, zero-calibrated, sign-reversing in the appropriate sense, has rational trace two in the base case, and is a real-character candidate. In particular the structural data without anchor already satisfy real-character factorization.

background

Recognition Science treats cost as a J-type functional on positive reals (classically $J(x)=(x+x^{-1})/2-1$), subject to the Recognition Composition Law. The Primitive Recognition Calculus supplies a structural ledger for the native cost: a fixed package of algebraic and calibration fields that any admissible cost display must satisfy.

Real-character factorization isolates a lighter hypothesis pack under which a cost factors through a real character (a multiplicative map into ${\pm 1}$ times a positive radial part). That pack is what downstream gauge-orbit work needs, rather than the full ledger.

This module sits between those two layers. It reads the structural ledger, defines a sign-gauge presentation of the native cost (cost displayed after quotienting or fixing a sign gauge), and checks that the ledger fields already imply the factorization hypotheses.

proof idea

The module is not a single theorem; it is a short bridge. One direction constructs the light hypothesis pack from structural ledger fields (realCharacterFactorizationHypotheses_of_structural). Another specializes to the sans-anchor structural data and obtains real-character factorization directly.

In parallel it defines the sign-gauge native cost and its display form, then proves a checklist of elementary properties: conversion to rationals, base case without the factor two, sign-reversal, monotonicity, zero-calibration, sans-anchor reduction, rational trace equal to two, and finally that the object is a real-character candidate. Those lemmas are mostly rewriting and ledger-field projection rather than deep analysis.

why it matters in Recognition Science

Gauge-orbit classification imports this module: once native cost is known to be a real-character candidate under structural hypotheses, orbits under sign (and related) gauges can be named and compared without carrying the full ledger. That is the step that turns raw PRC cost structure into the language used for cost-gauge taxonomy in the Cost domain.

In the broader RS chain, cost uniqueness and the J-functional (T5) sit upstream; here the concern is representational: which gauge-fixed displays still carry the same recognition cost. Closing the ledger-to-factorization bridge removes a hypothesis interface between structural PRC data and orbit classification, so downstream statements can quote a single candidate object rather than an open pack of assumptions.

scope and limits

used by (1)

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depends on (2)

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declarations in this module (41)