ObservationScaleFiniteCover #
Ported from scottnarmstrong/Superdiffusion at 7f20476385d4af418f110303085ad0740c9eba46. Module imports, support namespace and local option directives adapted for Lean Pool.
Observation-scale finite-cover transport #
This module transports the lower-clause two-term homogenization-error bound
from the cutoff cube to a larger observation cube. The transport is carried
out on the genuine measurable representative. Translation covariance is
used only through the cutoff-sample action, and the spatial enlargement is
paid for by descendant averages, finite maxima, and the geometric depth
weights already present in the q = 2 error.
The declarations here are internal Provider estimates.
The common constant for squaring the two-term observation-scale tail estimate.
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The measurable square of the cutoff-scale error at a translated
scale-L cell. The coefficient and normalizer stay frozen at L.
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Raw/representative finite cover #
The squared homogenization error for one cutoff cell against the isotropic comparator.
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The geometrically weighted block-response error at one observation depth.
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The infinite error tail below the cutoff scale.
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The largest parent-cube average of normalized cutoff-cell errors at one depth.
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The finite weighted envelope of coarse parent-cube error averages.
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The maximum normalized cutoff-cell error at the cutoff scale.
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Probabilistic aggregation over the finite cover #
The dimension- and depth-dependent stochastic scale for the observation error.
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The geometric depth factor bounding the fine part of the observation error.
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The common constant for the observation-scale finite-cover estimate.
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Dimension-only finite-cover transport of the lower homogenization-error
clause from the cutoff cube at 1/16 to the observation cube at 1/8.
The legal-window premise only specializes the displayed lower clause; the constant is chosen before the model, induction scale, and amplitude parameter. This is a Provider endpoint and carries no source-node status by itself.