Engine #
Ported from scottnarmstrong/Superdiffusion at 7f20476385d4af418f110303085ad0740c9eba46. Module imports, support namespace and local option directives adapted for Lean Pool.
The ratio engine of the conditional lambda_{s,q} sensitivity estimate #
Source: ABK26. This module assembles the two previous steps into the ratio
engine consumed by Provider.Lambda.Bootstrap:
- on each triadic descendant
Rof the unit cube and at each loadingw, the pure-flux responset ↦ J(R; a + t h; 0, w)is differentiable with derivative one half of theD_hflux form (Provider.Lambda.PathGronwall), so the per-cubeD_hbound is a differential inequality, and Grönwall turns it into a multiplicative ratio over any subinterval; - that ratio is uniform in
Randw, so it aggregates to a ratio forlambda_{s,q}^{-1}(Provider.Lambda.DescendantBridge) at everys > 0and every admissibleq, includingq = infinity.
The per-cube D_h bound is the analytic input hcube; it is a premise of the
internal helpers here and is discharged where they are used. No aggregate is
ever differentiated.
Every declaration is an internal helper for the Section 2.4 sensitivity providers.
The two path functions #
The frozen coarse gauge lambda_{3/8,2}^{-1} along the perturbation
path.
Equations
- One or more equations did not get rendered due to their size.
Instances For
The frozen coarse gauge lambda_{s,q}^{-1} along the perturbation path.
Equations
- One or more equations did not get rendered due to their size.
Instances For
The per-cube Grönwall step #
The per-cube D_h bound at p = 0, valid along the whole path, is a
Grönwall differential inequality for the pure-flux response and therefore gives
a multiplicative ratio over any subinterval.
The aggregated ratio engine #
The ratio engine. Given the per-cube D_h bound at p = 0 on all
triadic descendants and along the whole path, with the root gauge as the
coefficient, the frozen aggregate lambda_{s,q}^{-1} satisfies a multiplicative
ratio estimate on every subinterval of [0,1] on which the root gauge is
bounded by C.