Documentation

LeanPool.Superdiffusion.Algsuperdiff.Section3.Provider.Diffusivity.ApproximateRecurrence.Closure.GammaTenStripEnergy

GammaTenStripEnergy #

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

The energy leg of hstrip: the exact tiling fold of the cell second moments #

ABK26, Step 2 of l.approximate.recurrence.formula, e.nablaw.in.L.eight.

What this module is #

Closure.GammaTenStripBound.gammaTenStrip_cell_average_sq_le leaves exactly two grid binders: the mesh averages of the sample second moments of the two cell data D_R, F_R of the crude elliptic majorant. This module folds those two averages onto the localization cube by the exact mesh tiling identity LocalizationGrid.cubeAverage_originCube_eq_mesoGridAverage, whose constant is 1 and which loses nothing at boundary cells:

  avsum_{R in 3^n Zd cap cu_K} ( fint_R |u|^2 )^2
      <=  avsum_R fint_R |u|^4  =  fint_{cu_K} |u|^4  =  originCubeFourthEnergy K u .

The first step is the per-cell Jensen inequality of CoarseGraining (sq_cubeAverage_le_cubeAverage_sq_of_memLp); the second is the tiling identity; the third is the definition of the annealed fourth energy of LocalizationEnvelopeMesh. Its consumer Closure.GammaTenStripRemainder composes the fold with LocalizationFluctuationGridEighth.cubeFamilyAverage_integral_le_of_pointwise in the sample, which reduces the two grid binders to one expectation per leg,

  E[ fint_{cu_K} | e' + grad w_D |^4 ]   and   E[ fint_{cu_K} | e + F |^4 ] ,

which is the shape e.nablaw.in.L.eight controls through LocalizationEnvelopeSpatial.originCubeFourthEnergy_le_sq_of_cubeEuclideanLpNorm_sq_le and LocalizationEnvelopeMoment's Gamma_1 second moment.

The load legs cost nothing #

Both cell data are energy + |load|^2 with the load the cell average of the same field, so the vector Jensen inequality (vecNormSq_const_add_cubeAverageVec_le, the constant-shifted form proved here) gives |load|^2 <= energy at every cell and hence D_R <= 2 Epot_R, F_R <= 2 Eflux_R. No separate load moment is needed: the P_z legs are absorbed by a factor 4 in the constant.

What is proved #

A pair of grid statements assembling these into the two binders of Closure.GammaTenStripBound.gammaTenStrip_cell_average_sq_le directly from an annealed fourth energy per leg once stood here too. Their callers moved to the pathwise-majorant form Closure.GammaTenStripRemainder states (..._le_of_majorant), they lost every consumer, and they were removed; git history keeps them.

Binders #

Beyond the typing binders: the mesh scale gate hn (which only names the mesh); the per-sample spatial L^8 membership of the leg field on the localization cube; and the per-cell L^2 membership used by the two cell-datum comparisons. No smallness gate, no induction state, no measurable selection and no interior-mesh restriction occurs.

Scope #

Internal Provider infrastructure for the Step-2 fluctuation estimate. There is no sorry, no admit, no custom axiom and no set_option maxHeartbeats.

References #

Membership bookkeeping #

The constant-shifted vector Jensen step #

The pathwise fold #

The exact mesh fold of the squared cell energies.

  avsum_{R in 3^n Zd cap cu_K} ( fint_R |u|^2 )^2  <=  fint_{cu_K} |u|^4 .

Per cell this is Jensen; over the mesh it is the tiling identity, whose constant is 1. Boundary cells are included: nothing in the statement distinguishes them.

on the scale gate hn, which only names the mesh, and on the spatial L^8 membership hu on the localization cube.

The two cell energies as cube averages #

The load legs are below their own cell energies #

The potential load leg is below the potential cell energy. This is the constant-shifted Jensen inequality at the cell, read through the two closed forms; the gauge shom^{-1} is common to both sides.

only on the cell L^2 membership of the corrector gradient.

The flux load leg is below the flux cell energy.

only on the cell L^2 membership of the flux leg field.