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LeanPool.Superdiffusion.Algsuperdiff.Section24.Sensitivity.Provider.BigLambda.CubeGaugePath

CubeGaugePath #

Ported from scottnarmstrong/Superdiffusion at 7f20476385d4af418f110303085ad0740c9eba46. Module imports, support namespace and local option directives adapted for Lean Pool.

Descendant-gauge control along the perturbation path #

Source: ABK26, the scaled-norm inequalities that precede the descendant b-matrix estimate.

The pure-potential D_h bound of BigLambda.CubePotentialDh prices its Term A against the descendant gauge λ_{3/8,2}^{-1}(R; a + τh), so the Young/Grönwall absorption at the cube R needs that gauge to stay comparable to its value at the base point τ = 0.

The proof does not rerun the lambda_{s,q} spine at R: it reuses the per-descendant pure-flux estimate Provider.Lambda.abs_dhFluxForm_le_root_gauge (which already prices everything against the root gauge), turns it into the per-cube response ratio with Provider.Lambda.Engine, converts that into the one-cube σ_*^{-1} ratio with Provider.Lambda.DescendantBridge, and finally aggregates at R with the general-cube Provider.Multiscale.lambdaSq_inv_le_of_descendant_ratio. The aggregation is legitimate because every descendant of R is a descendant of the unit cube (Homogenization.mem_descendantsAtScale_trans).

Every declaration in this module is an internal helper for the Section 2.4 sensitivity providers.