pith. sign in
module module high

IndisputableMonolith.Masses.BaselineDerivation

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BaselineDerivation module defines the J recognition cost and computes baseline mass quantities such as neutrino_baseline_int using the phi-ladder at D=3. Mass researchers working from first principles cite its T_min_at_D3 and total_geometric_at_D3 results. The module assembles definitions and short algebraic lemmas on J and geometric content.

claim$J(x) = \frac12(x + x^{-1}) - 1$ for $x > 0$, with $T_{\min}$ at three dimensions, octave offset, total geometric content, and neutrino baseline integral.

background

The module sits in the Masses domain and imports the RS time quantum $\tau_0 = 1$ tick from Constants, the $\alpha^{-1}$ derivation from cubic ledger geometry in AlphaDerivation, and canonical mass anchors from Masses.Anchor.

It introduces the J-cost functional $J(x) = \frac12(x + x^{-1}) - 1$ (equivalently $\cosh(\log x) - 1$), its nonnegativity, value at one, and the Recognition Composition Law. Sibling definitions cover $T_{\min}$, octave_offset, total_geometric_content at D=3, and neutrino_baseline_int.

proof idea

This is a definition module, no proofs.

why it matters in Recognition Science

Supplies the J-cost and baseline objects that support the mass formula yardstick $\times \phi^{{\rm rung}-8+{\rm gap}(Z)}$ on the phi-ladder. It fills the T5 J-uniqueness and T7 eight-tick octave steps, linking the alpha band and D=3 geometry to mass baselines in the Anchor module.

scope and limits

depends on (3)

Lean names referenced from this declaration's body.

declarations in this module (35)