claimroutineinferred_dep
Axis maps contract with error dp^2
Axis maps contract; axes give error
carries 1D error and cost bounds to axes
Statement (paper)
Each axis map, which acts independently on its valid lines and is zero on the other lines, is a contraction and has error less than . Hence the composition of the axis maps is a contraction with error less than . For axis at most lines invoke the one-dimensional algorithm, so the total time in the one-dimensional algorithms is .
In plain English
Each axis map, which applies the one-dimensional approximation on valid lines and gives zero on other lines, is a contraction with error below . Composing the axis maps gives a contraction with error below , and the one-dimensional algorithms take total time .
Why it's here
This turns the one-dimensional bounds of the no-sort resampling lemma into the contraction, error and time claims for and in the tensor lemma. Lines act independently, so contraction and the error carry over from one axis to the next and the errors add up over axes. For axis at most lines call the one-dimensional algorithm at cost each, so each axis costs and the sum over axes gives the stated total.
Classified routine:
Direct bookkeeping consequence of the one-dimensional no-sort resampling lemma. Contractions compose, errors add under composition of contractions, and the per-axis time is summed over lines and axes.
Uses
Used by
Nothing in the paper
Sources
PaperOpen
- Section
- §8.2 Growing dimension and the padded array
- Page
- —
- Label
—- Line
sections/07-resampling.tex:362
Leannot aligned
Phase 2 aligns this node to a Lean declaration.
Friction
- infoinferred_depoutline: "Axis maps contract; error dp^2 and line cost" rests on claim-lem-tensor-resampling-1
- infoinferred_depoutline: "Axis maps contract; error dp^2 and line cost" rests on lem:no-sort-resampling