Select a passage or formula to leave a suggestion here. Saved suggestions remain private until reviewed.
Unit 3, extension: finite counting on sparse scales
This part gives a step-by-step proof of H Lemma 9.1, October 5, 2026 version, pp.81–87. It supplies the counting gain at a power below one in D §6.6. Its connection with amplitude interpolation is explained in Sections 5–6 of “Counting core tuples and interpolating amplitudes.”
The proof concerns only the finite proposition under the five stated hypotheses. The source version and its citation in D have been checked against each other. D's application must still supply the frequency gaps, positionwise counts, and scalar kernel estimates.
1. The finite proposition and its five hypotheses
The four positions are . Three or four are core, forming the set . Given
each core position has a finite real-label set , with distinct labels within the position and .
Fix . For finitely many distinct integers , specify
The quantity is reciprocal scale. A tuple appearing at different scales contributes a separate occurrence at each.
Assume:
(1) Labels in two distinct core positions determine at most one complete core tuple, and that pair appears at at most scales. (2) If there is a side position , there are weights with such that at scale at most tuples contain any specified core label. (3) For distinct labels in one core position appearing at scales , and every integer vector satisfying ,
(4) For every three-core subset, let be the omitted position and set . Every tuple at scale has an integer vector satisfying such that
Each coefficient belongs to . (5) At every occupied scale, for all ,
Also assume that a fixed sufficiently large absolute constant satisfies
We will prove that, for ,
The constant is independent of dimension, the number of scales, and the number of labels.
2. Placing the real data on a common fine grid
The labels, scales, and shifts with form finite sets. Approximate all real data on a common grid of spacing , placing original coordinates at a fixed integer multiple of so that later division by stays on the common fine grid.
Choose after all the finite data. Making every error a sufficiently small multiple of the smallest preserves:
- The separation constant ;
- The annulus lower bound and upper bound ;
- A narrower interval strictly inside the original pure-shift exclusion interval, still with a fixed margin.
Specifically, use working parameters , , and , leaving fixed-factor margins in the original . The grid proof needs only
This interval lies strictly inside the original wider forbidden interval, so sufficiently fine approximation of the finite data preserves it. Rounding is not asserted to preserve the entire thousandfold forbidden interval for the renamed parameters.
Rounding a width upward to the grid adds at most . The absolute margins in (Reserves) absorb these fixed factors. Below, reuse the original letters for the gridded data, but use only (Grid-gap) in the pure-shift contradiction. The interval obtained in Section 10 lies strictly inside this narrower forbidden interval. Every estimate is independent of and ultimately applies to the original real data.
3. A bipartite graph with many four-step colored paths
Suppose each side of a bipartite graph has at most vertices, with at least edges and . There are at most edge colors, and edges incident to one vertex have distinct colors. We seek a left-side set of size at least such that every pair of its vertices has at least four-step paths between them.
3.1 A random neighborhood and bad pairs
Add isolated vertices to the right side until it has vertices. Choose one uniformly and let be its left neighborhood. Then
Call an ordered left-side pair bad if it has fewer than common neighbors. The probability that both endpoints lie in is their common-neighbor count divided by . Thus the number of bad ordered pairs in , denoted by , satisfies
For sufficiently small ,
Hence some satisfies and .
3.2 Removing a few vertices
Within , remove vertices with more than bad partners. Fewer than vertices are removed. The remaining set still satisfies
For , at least middle vertices are good partners of both. Each pair and has at least common right neighbors, chosen independently. The number of four-step paths is therefore at least
Repeated vertices are allowed. A starting vertex and four ordered edge colors uniquely determine each successive step. For fixed endpoints, distinct paths therefore give distinct ordered color quadruples.
4. Blocking the counting mass and covering difference sets
First treat sufficiently small . Larger will be handled at the end by the crude total-mass bound. Retain only scales with . Uniqueness and scale multiplicity for any pair of core positions give
Choose parameters, to be fixed later,
Order retained scales by decreasing and greedily divide them into consecutive counting blocks of mass at most . Every block except the last has mass greater than . Their number satisfies
These blocks are defined by counting mass, unlike the consecutive-depth analysis blocks used earlier.
4.1 Finite shift neighborhoods for each block
Let be the largest reciprocal scale in block , and set
For a sufficiently fine grid, . For integers , define the finite symmetric set
It contains zero and satisfies
4.2 Constructing a graph from uncovered occurrences
Fix a core position and a block. As long as occurrences involving its uncovered labels have mass greater than , choose two other core positions .
Project these occurrences to a simple bipartite graph on the labels in positions , keeping one scale witness in the block for each pair. Since each pair appears at most times, there are more than
edges. Color each edge by its third-position label. The coloring is proper: two incident edges of the same color would share two core labels and hence be the same complete tuple and edge.
Set . Section 3 gives
and (Four-paths).
4.3 Four annulus relations eliminate the intermediate labels
A four-step path has successive left vertices , right vertices , and colors . Add and subtract its four three-position annulus relations alternately. The intermediate labels cancel. Division by gives
where depends only on the color quadruple.
The color term is explicitly
The shift coefficient is an integer multiple of six. Combining four shifts gives, in the grid, an index of size at most . The scalar error is at most and is contained in .
4.4 A maximal separated subset of the difference set
Choose a maximal subset of in which differences of distinct elements lie outside . Choose endpoints for each selected difference. Each endpoint pair has at least color quadruples.
Two selected differences cannot share a color quadruple: by (Color-difference), their difference would lie in
a contradiction. There are at most color quadruples altogether, so the number of selected differences is at most
By maximality, translates of centered at these differences cover all of .
Remove this batch of labels and repeat. Each step removes at least labels, so there are at most steps. Thus, for every core position in every block, apart from uncovered occurrences of mass at most , the labels are covered by at most
sets . Each difference set is in turn covered by at most translates of .
5. Removing occurrences with fewer than three future positions
First discard occurrences with an uncovered label in any core position in the current block. The total loss is at most
For a remaining occurrence, call a core position future if its label also belongs to a covering set in that position in a later counting block. Otherwise call it nonfuture.
For a fixed position, permitted nonfuture labels from different counting blocks are disjoint. A label covered in a later block would be future in an earlier block. Let count the nonfuture labels in each block. Then
A side position , when present, is always nonfuture. Define
An occurrence with fewer than three future positions has at least two nonfuture positions. Assign it a pair by a fixed rule. In block , its class has mass at most
For two core positions, this follows from label pairs and scale multiplicity. For one core and one side position, use the side incidence bound; the extra factor is harmless.
By and Cauchy–Schwarz,
At most six pairs are possible, costing only an absolute constant.
6. Three fixed future covering sets and four scale segments
Every remaining occurrence has at least three future core positions. Use a fixed rule to select three positions and a later-block covering set for each label. The number of configurations is at most
Fix a configuration of positive mass . It specifies the current counting block, three core positions, and covering sets from strictly later blocks. The indices merely enumerate these positions; the original coefficients remain unchanged.
Set
If , the required small-mass bound already holds. Assume below, with a sufficiently large absolute constant.
Order this configuration's mass by decreasing reciprocal scale, split it into four quartiles, and discard the scale cells crossing the three boundaries. Each cell has mass at most , so each segment retains at least
mass and contains at least occupied dyadic scales. Let be the largest reciprocal scale in the second segment.
6.1 Separated anchors from the first segment
A fixed core label is incident to at most occurrences altogether. The first segment therefore provides, in each , an anchor set with
Every anchor has an occurrence witness at reciprocal scale at least . By (Separated), distinct anchors remain more than apart under permitted shifts.
6.2 Many actual triples in the last segment
A complete triple occurs at most times. Choose distinct actual triples from the last segment, with one scale witness per triple, so that
6.3 Scale gaps from the second and third segments
The third segment contains at least distinct dyadic scales. Since , every second-segment reciprocal scale is at least times every last-segment reciprocal scale. Strictly later blocks have still smaller reciprocal scales and satisfy the same gap.
Greedily retain second-segment scales with successive reciprocal-scale ratios at least . Each choice removes at most scales, leaving
scales. At each selected , choose an actual triple . We will consider the indexed outputs with .
7. One small-growth step avoids an exponential dimension cost
Let denote the neighborhood and width for the counting block containing the future covering set .
Partitioning the integer-coefficient intervals and scalar interval covers the larger neighborhood by at most
translates of , namely a cover of . Consequently, some odd integer
satisfies
Otherwise cardinality would double every two steps. By , exponential growth would exceed the stated bound in of degree .
The dimension-dependent exponent is used only to find one small-growth step. Subsequent bounds use the fixed factor two; they do not include in the final constant.
7.1 Anchor neighborhoods are disjoint
The sets
are pairwise disjoint. An intersection would put an anchor difference in , with shift index at most and scalar width at most , contrary to (Reserves) and anchor separation.
Set
Then . The cover of gives
8. A minimal-growth subset and covers of double and triple sumsets
Choose a nonempty minimizing
over all nonempty subsets. By (Small-expansion),
8.1 Full proof of the iteration inequality
Temporarily write . Given a finite shift set , define
Then
Every point of already belongs to an earlier . The number of new points at step is therefore at most
By minimal growth of , a nonempty satisfies
The empty-set case also holds. Thus there are at most new points; summation gives
Successively taking proves by induction
8.2 Separated subsets of sumsets
The set consists of at most anchor neighborhoods. The part of the minimizing set in some one neighborhood,
satisfies and
If distinct elements of have differences outside , the translates for are disjoint and lie in . By (Iterated-growth),
A maximal separated set therefore gives a cover of by the same number of neighborhood translates. Only is needed here.
9. Anchors remove the third label-count factor
Set
Consider outputs in satisfying
as stated.
Each of the first two coordinates is covered by at most translates of . Fix one pair of covering boxes and solve (Slab) for the third coordinate. It lies in the intersection of with
Division by introduces no noninteger shift indices. The neighborhood shift coefficient is six and the annulus coefficient is thirty-six; both are divisible by .
In this local third-coordinate set, choose a maximal subset separated by the neighborhood . The set
is still separated. For one anchor this follows from the definition of . A collision from different anchors would, by (Third-location), make their difference after a permitted shift only , contradicting anchor separation.
Thus (Sumset-packing) with gives
Using all separated anchors removes the third factor .
The entire slab is therefore covered by at most
translates of .
10. At most one indexed output per covering box
Every satisfies (Slab), by adding the second- and last-segment annulus relations. We must also show that these indexed outputs are separated at the covering scale.
10.1 Distinct triples under one translation
If are distinct, at least one coordinate label differs. Their last-segment occurrence witnesses precede every future block, so their reciprocal scales are larger. The separation in (Separated) therefore exceeds the corresponding shift and scalar widths of .
Coordinate differences within one covering box must belong to . Thus and cannot lie in the same box.
10.2 Outputs from different translations
Consider and , and let be the larger second-segment reciprocal scale. The absolute annulus residual of its triple lies in
The other second-segment residual and the two last-segment residuals have total absolute value at most , by the gap.
The linear form of the output difference, plus a shift with index , consequently has absolute value in
If the outputs lie in one covering box, their coordinate differences belong to . The box width introduces additional scalar error at most
The combined shift index is still at most . This would produce a pure shift of absolute value in
contradicting the narrower forbidden interval in (Grid-gap).
Each covering box therefore contains at most one indexed output. This excludes coincidences both within a single translation and between different translations.
11. Comparing the output and covering counts
By (Translators) and (Last-triples),
Compare with (Slab-cover) and cancel to get
Since , we may weaken this slightly to
The previously omitted case satisfies this bound as well.
12. Choosing the two auxiliary small parameters
Equation (Configurations) controls the number of configurations. Add their mass, the uncovered mass, and (Nonfuture), obtaining
The factor in the last term comes from
corresponding respectively to configuration mass, the four counting-block choices, and four difference-cover costs.
For sufficiently small , choose
Then . The three powers of are
Since , the smallest exponent gives a common bound. With , (Before-choice) becomes (Sparse-count).
For the remaining , use total mass and enlarge an absolute constant. Rounding preserves the discrete label and tuple indices and every . The working ratio is four times the original ratio, so
The grid estimate therefore returns the same factor in the original proposition, changing only an absolute constant. All bounds are independent of . For the given finite data, one sufficiently fine grid suffices; no infinite-scale limit is required.
13. Applying this gain in D
Set
Group scales by dyadic sizes of relative to . The factor in (Sparse-count) offsets the amplification of small counts by , giving
D then interpolates this bound with the first-power incidence count and uses cross-group positionwise counts to sum amplitudes. This finite lemma alone supplies neither the scalar kernel estimate, the positionwise counts, nor the pure-shift gap. Their hypotheses retain their separate sources.
This finite proof has been independently reviewed. The checked scope is the stated finite combinatorial proposition and its correspondence with D §6.6, excluding H's other analytic and geometric proofs and the multiple-mixing result from R used by A and B.