Documentation

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

Aggregation #

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

The descendant b-matrix estimate and its geometric resummation #

Source: ABK26.

Provider.Multiscale.GeometricResummation already performs the resummation

Lambda_{s,2}(cu_0; a₁) ≤ 4 Lambda_{s,2}(cu_0; a₀)
                            + K (3/8 - s)^{-1} lambda_{s,2}^{-1}(cu_0; a₀)

from the per-descendant estimate with the fixed same-index factor 4. The free-δ statement needs the same resummation with a general coefficient c.

coarseBMatrixNorm_perturb_le is the per-descendant input: the pure-potential J-sensitivity of BigLambda.CubeJSensitivity combined with the identity 2 J(R,p,0;a) = p·b(R;a)p of BigLambda.BMatrix.

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

The resummation with a general same-index coefficient #

The descendant b-matrix estimate #