WorksMathematics
A power improvement in the Heilbronn triangle lower bound
Abstract
There are absolute constants such that, for every sufficiently large integer n, one can choose n points in the unit square so that every triangle they determine has area at least . Thus the almost n−2 upper-bound formulation of Heilbronn's triangle problem is false. The exponent η is fixed but extremely small.
Introduction
For three points , write
If is finite and , define
The minimum is over all unordered triples of distinct points. In particular, a collinear triple makes . The maximum defining exists: the minimum area is continuous on the compact space of ordered -tuples, it is positive for suitable points on a parabola, and a tuple with a repeated point has minimum area zero.
The original Heilbronn conjecture asked whether ; see Roth [12], p. 198. Two elementary constructions attain this scale. Erdős’s finite-field parabola, recorded in Roth [12], Appendix, gives a grid configuration whose triangle determinants are nonzero integers before scaling. Random sampling followed by deleting one point from each small triangle also gives . Komlós, Pintz and Szemerédi improved this to , disproving the original conjecture [10]. Their argument represents the small-area triples in a random point set as edges of a hypergraph, removes short cycles, and uses a stronger independence bound to select a large subset containing none of those triples [10], Section 2.
The almost formulation, discussed in Zakharov’s survey [18], Section 3, asks whether, for every , there are constants and such that
We disprove this formulation by a power improvement in the lower bound.
Theorem 1.1. There are absolute constants , and an integer such that
In particular, for every sufficiently large . The ratio of the theorem’s lower bound to is , which contradicts (1.1) at . Section 8 gives an explicit, though extremely small, admissible exponent.
On the upper-bound side, Roth [12] proved the first estimate by a density-increment argument, followed by refinements of Schmidt [16] and Roth [13, 14]. Komlós, Pintz and Szemerédi [9] refined Roth’s analytic method to obtain . Cohen, Pohoata and Zakharov developed new incidence-geometric approaches, first obtaining for sufficiently large [4], Theorem 1.1, and subsequently proving for every [5], Theorem 1.8.
Earlier preprints claim stronger power lower bounds than ours, with unresolved issues in the following versions. Ellmann’s version 12 acknowledges an unproved local uniformity assumption and describes the argument as heuristic [6], p. 3; the deletion estimate uses this assumption [6], Theorem 4, pp. 5–6. In Agama’s version 13, Theorem 4.1 [1], pp. 12–13, counting the center with the boundary points introduces a collinear triple consisting of the two endpoints of a diameter and their midpoint. Omitting the center leaves the every-triple estimate unproved, since the argument estimates triangles formed by the center and adjacent boundary points. These objections concern the cited arguments, not the impossibility of their asserted bounds.
The two congruence conditions
The proof works first with integer columns in a box of the form
Such a column represents the unit-square point . Three columns forming a matrix give a triangle of area
We therefore seek many columns for which proportional pairs and triples with small absolute determinant are sufficiently rare to delete.
The first congruence condition separates most triples before they are lifted to integers. Give each column an independent uniform label , where is fixed and odd and the prime grows. The columns have nonzero determinant whenever their labels are distinct. This is the finite-field parabola underlying Erdős’s construction recorded in Roth [12]. Taking the field norm to produces an alternating polynomial in three groups of coordinates. We express that polynomial as a sum of monomial determinants and encode it in one designated coefficient of a determinant whose entries are base- expansions. Large-base control of carries has classical precedents in the progression-free constructions of Salem and Spencer [15] and Behrend [3]; here it isolates a determinant coefficient. Modulo , with fixed, distinct labels then preclude a small determinant. Independent choices of digits with the prescribed residues leave enough randomness even when labels coincide.
A common random matrix of determinant one mixes the three rows modulo without changing their determinant. Conditional on the digit columns, the resulting matrix is uniform on a special-linear orbit. The rows of every integral lift lie in a lattice whose index, together with the orbit size, can be read from a diagonal form. An anisotropic lattice count controls lifts of any fixed nonzero determinant, while a conditional moment bound handles singular digit matrices and repeated labels.
The fixed nonzero-determinant count does not cover determinant zero, where all three rows can lie in one integral plane. We control this case with a second congruence condition. At an independent prime , choose residues from a small portion of an affine quadratic surface with no three points on a line. A carefully restricted random translation excludes short integer relations; a random invertible linear map permits uniform counting. The Chinese remainder theorem combines the two congruence conditions, and uniform lifting supplies integer columns in the box.
For a singular lifted matrix with pairwise distinct projected columns, a primitive integer null vector determines a rank-two row lattice. We sum over those vectors, treating equal residue columns and low rank modulo separately. This supplies the missing count for collinear projected triples.
The exceptional triples require repeated labels, whose probability provides the saving used in an elementary deletion argument. Thus the improvement comes from the arithmetic distribution of sampled points. Formula (1.2) then transfers the determinant bound to every triangle of the retained point set.
Organization and conventions
Section 2 proves the lattice estimates. Section 3 constructs the norm polynomial and digit distribution, and Section 4 estimates its matrix orbits. Section 5 constructs the auxiliary residues. Sections 6 and 7 count small determinants, including zero. Section 8 completes the deletion and scaling argument and passes to every sufficiently large cardinality. Appendix A gives the elementary prime-interval proof used in the parameter choices and interpolation.
Lengths are Euclidean. A primitive integer vector has coordinates with greatest common divisor one. The covolume of a lattice is measured in its real span. The notation means ; constants may depend on the fixed construction parameters, but never on the growing prime or on the sampled labels and columns. All logarithms are natural.
Lattice counts with a prescribed determinant
We prove a uniform bound for integer matrices whose rows belong to a fixed lattice and whose determinant is a prescribed nonzero integer. The lattice may have very different scales in different directions, so the proof keeps track of three separate column bounds. We also record the plane counts needed when the determinant is zero.
All lengths in this section are Euclidean. The determinant of a lattice means its covolume in its real span. For a lattice of positive rank , choose successively, with a shortest lattice vector outside , and put . In particular, . The notation means for an absolute constant , unless dependence is indicated.
The classical geometry-of-numbers antecedent is Minkowski’s second theorem on successive minima; see Henk [8]. Only the weaker fixed-dimensional Euclidean product bound below is needed here, and we include its proof.
Lemma 2.1 (Successive lengths). For a lattice of positive rank and the lengths just defined,
Consequently, the lattice generated by has index at most in .
Proof. The determinant of the lattice generated by the is an integer multiple of and is at most . For the reverse bound, choose orthonormal coordinates whose first directions span for each . Let
If a nonzero lattice vector in has last nonzero coordinate , it lies outside the preceding span and has length strictly less than , a contradiction. The translates of by are therefore disjoint. Integrating their indicator functions over a fundamental domain of gives . Since , the result follows. □
Lemma 2.2 (Points in a plane lattice). Let be a rank-two Euclidean lattice with successive lengths . If , any translate of has at most points in any ball of radius . If , the points of in the ball of radius centered at zero lie in a line and number at most .
Proof. For the first assertion let . A half-open fundamental parallelogram for has diameter at most . For each coset of , attach such a parallelogram to every point in the ball. The parallelograms are disjoint and lie in a disk of radius at most in the affine span. Thus each coset contributes at most points. Summing over cosets proves the first assertion. For the second, every lattice vector outside has length at least . The lattice on is , since a shorter generator would contradict the choice of . Counting its multiples proves the bound. □
Lemma 2.3 (Covolumes of integral planes). Let be primitive, meaning that its coordinates have greatest common divisor one. Then has determinant . More generally, if is a full-rank lattice of index and with , then
Proof. Choose with . The map maps onto , has kernel , and splits by . Hence a basis of the kernel together with is a basis of . The height of above is , which proves the formula. For , primitivity gives .
We next count matrices with unequal column bounds. The difficult case occurs when the third-column radius reaches only one direction of its integral plane; we count those planes through their shortest vectors.
Lemma 2.4 (Unequal column bounds). Let and let . The number of triples satisfying and is at most
The constant is independent of and of the three radii.
Proof. The columns are independent. Choose a primitive normal to their plane, fixing its sign by requiring its first nonzero coordinate to be positive. Then for some nonzero integer , so . If are the successive lengths of , the columns imply and .
For fixed , the determinant equation is . Its integral solutions are either absent or form a translate of . By Lemmas 2.2 and 2.3, at most satisfy the first-column bound; the required hypothesis is . For a fixed normal , there are likewise at most choices for .
First suppose . There are at most choices for . The resulting bound, summed over normals, is
The last estimate follows by splitting the integer vectors into dyadic shells; a shell of radius has vectors.
It remains to treat . Group the normals by powers of two with
Lemma 2.1 gives . There are at most normals in such a group. Indeed, choose a shortest nonzero vector . It is primitive in , because division by a common divisor would produce a shorter vector in . Its length is in , giving choices. For each such , the possible normals lie in and have length less than . If are the successive lengths of , integrality gives , and the preceding lemmas give
Consequently Lemma 2.2, applied at radius , bounds their number by . This proves the claimed normal count.
For each of these normals, all eligible third columns lie on the line of a shortest vector. Lemma 2.2 gives at most choices, since . Thus the contribution of one dyadic group is at most
There are groups, since and . Combining both cases proves the assertion.
Proposition 2.5 (A fixed nonzero determinant). Let have index , let , and suppose its third successive length satisfies . For every , the number of by matrices with rows in , row lengths at most , and determinant is at most
The constant is absolute.
Proof. Let be the matrix whose rows are the successive shortest vectors , and let be their integer span. By Lemma 2.1,
Since the finite group has order , each has coordinates in relative to this basis. If and , Cramer’s rule gives
Thus the map is injective and takes the matrices under consideration to integral matrices. Their common determinant is . If this number is not an integer, there are no such matrices; otherwise Lemma 2.4 applies.
The th column of has length at most , where is an absolute constant chosen sufficiently large. These radii satisfy . Moreover, integrality of gives , and Lemma 2.1 gives
The bound in Lemma 2.4 is therefore the claimed one.
A determinant obstruction from field norms
We construct random columns modulo a prime power, each carrying a label in a finite field. Three distinct labels will force the determinant residue to have no small integer representative. The construction first expresses a field norm as a sum of determinants, then places these summands at one specified coefficient in a base expansion.
The norm polynomial
Fix
Let be an odd prime. We recall the elementary finite-field facts needed here; see [11] for background. In a splitting field over , the roots of form a field: the Frobenius identity shows closure under addition, subtraction and multiplication, and nonzero roots are closed under inversion. The derivative is , so there are exactly distinct roots. This field, denoted , consequently has dimension over . Its automorphism has th power equal to the identity, and its fixed elements are exactly the roots of , namely . For , the product is therefore fixed by Frobenius and belongs to ; it is nonzero if . Choose an -basis of . For a group of variables, define
For three disjoint variable groups , put
Let act on this polynomial ring by applying to coefficients in and fixing every variable. Define
The action of permutes the factors, so has coefficients in . It is homogeneous of degree in each group. At arguments in , it evaluates to the field norm of the corresponding determinant:
Indeed, coefficient conjugation commutes with evaluation at such arguments. Transposing two variable groups changes the sign of each factor in (2). Since is odd, is alternating.
Lemma 3.1. There exist homogeneous degree- polynomials (allowing the zero polynomial), for and , such that
For each , the three polynomials are obtained from three distinct degree- monomials by multiplying the first by a scalar that may be zero.
Proof. List the degree- monomials in variables as . Expand in products . If two of coincide, the coefficient equals its negative under the corresponding transposition, and hence is zero because is odd. For each , let be the coefficient of . Alternation identifies the other five coefficients with the signs in
Enumerate the triples by , and take
This argument uses no division by , so it applies also when .
For a label , set and let be its coordinates in the chosen basis, so that . The Vandermonde determinant gives
whenever the three labels are distinct. Although the basis and the coefficients may depend on , the numbers in (3.1) do not.
Encoding the polynomial in a base expansion
Two prime choices will keep the construction parameters polynomial in . We use the following sufficiently-large form of Bertrand’s postulate; Appendix A gives its elementary binomial proof, following Erdős [7].
Lemma 3.2. For every sufficiently large integer , there is a prime with .
Set . For all sufficiently large , apply Lemma 3.2 with to choose a prime satisfying
For , designate positions in rows , respectively, by
These positions lie in and are distinct within each row: they lie respectively in the intervals , , and . The only designated positions whose sum is are the matched triples:
To prove the forward implication, rewrite the equation as . Reduction modulo , together with , gives ; substitution then gives . The reverse implication follows from (3.6).
A random column is now defined as follows. First choose uniformly from . For each row and each position , choose an integer digit . Its required residue modulo is when , when , and when . At every other position its required residue is zero. Conditional on , choose all digits independently and uniformly subject to these requirements, and set
Every required residue has exactly possible digits, including the zero residue. In particular a digit prescribed to be zero modulo is still a positive integer. Since , the lowest digit is a unit modulo ; thus every entry of is a unit in . Different columns use independent labels and fresh independent digits, even when their labels coincide.
Lemma 3.3 (Determinant obstruction). Let be a matrix of three columns constructed by (3.8), with labels . If these labels are distinct, then the residue has no integer representative in .
Proof. Write for the digit at row , position , in column . Form the integer polynomial
For a fixed exponent and each of the six determinant permutations, choosing the first two digit positions determines the third. Therefore
Alternatively expanding by rows, is the sum of determinants of digit rows at positions whose sum is . Modulo , all terms with an undesignated position vanish. By (3.7), the surviving terms are exactly those in (2), evaluated at the three label vectors. Consequently
which is nonzero by (3). In particular as an integer.
The integer
represents modulo , because all omitted terms in are divisible by . Since , the coefficient bound gives
It follows that
By (6), every other representative , , has absolute value greater than . This proves the assertion.
In particular, if and an integer matrix satisfies and , then at least two labels of coincide: multiplication by preserves its determinant residue. For three independently sampled labels, the probability of such a coincidence is at most by the union bound.
Residue orbits and a conditional divisor estimate
We now describe the lattice of possible rows after a change of coordinates modulo a prime power. The size of the corresponding special-linear orbit will control the probability of a prescribed lifted matrix. Two divisors measure the singularity of the residue matrix; the smaller one has bounded expectation even after all three labels have been fixed.
Throughout this section, let be a prime, let be an integer, and put and . We interpret as zero when it occurs as an entry of a matrix over , but as the positive integer in counting formulas. The row span of a matrix over is the -submodule generated by its rows.
The diagonal reduction below is the prime-power-ring form of Smith’s normal form; see Smith [17], Articles 12–16 for the classical integer reduction and determinantal divisors. We include the elementary proof needed here, including singular cases.
Lemma 4.1 (Diagonal form and the row lattice). Let have at least one unit entry. There are invertible matrices and integers $0 \le b \le e \le k$ such that
Set , , and , all as positive integers. The subgroup
is a full lattice satisfying
Moreover, , for , if and only if every minor of vanishes modulo .
Proof. Move a unit entry into the first position, scale it to , and clear the rest of its row and column by invertible operations. In the remaining block choose a nonzero entry of least -adic valuation , move it to the first position of that block, and multiply by a unit to make it . Every other entry of the block is divisible by in , so row and column subtraction clear its row and column. The final entry is still divisible by ; scaling it by a unit makes it with . If the block is zero, take . This proves the stated form, including all zero-pivot cases.
Invertible row and column operations preserve the ideal generated by the minors: each new minor is a linear combination of old minors, and the inverse operations give the reverse inclusion. For the diagonal matrix this ideal is . Its image modulo is zero exactly when , proving the last assertion and, in particular, showing that is independent of the diagonalization.
Write for the row span of . Left multiplication by does not change the row span, while multiplication on the right by is an automorphism of . Hence
The reduction map identifies with , which proves the index formula. Since divides , the diagonal row span contains . Right multiplication by preserves , so also contains . Taking inverse images proves the containment in (4.1).
The preceding description permits singular matrices: either or both of the last two diagonal entries may be zero. The orbit estimate must retain these cases, because zero determinants are included in the triangle problem.
Lemma 4.2 (A special-linear orbit bound). Under the hypotheses and notation of Lemma 4.1, define
There is an absolute constant such that
For a uniformly chosen , the matrix is uniform on . Every matrix in this orbit has the same row span and determinant as .
Proof. Let , and let be the stabilizer of under left multiplication. Conjugation by identifies with the stabilizer of and preserves determinants. An element of this latter stabilizer has first column exactly . Its second column differs from by three entries annihilated by , and its third column differs from by three entries annihilated by . The respective annihilators have and elements. Discarding the invertibility condition gives
For every unit with , the matrix stabilizes . If , there are exactly such units. If , this congruence imposes no restriction, so there are of them. Consequently, in all cases,
Here denotes the image of the determinant homomorphism on . The determinant map from onto has kernel . Applying the orbit–stabilizer formula in these two groups gives the exact identity
Reduction modulo shows that
Together with (4.3) and (4.4), this proves (4.2), for example with . Every fiber of the map is a coset of its stabilizer, which proves uniformity. The assertions about row spans and determinants follow directly from invertibility and .
We next estimate the smaller divisor for digit columns. Only the independence and number of digit choices matter here; their prescribed residues may be arbitrary functions of the labels.
Lemma 4.3 (Conditional digit estimate). Let be positive integers with , , and . Let be a label set, and for each , , and , prescribe a residue . Fix any three labels , allowing repetitions. Independently for every , choose uniformly from
and define by
Let and be as in Lemma 4.1, and put . Then, for every ,
If , then
Proof. Every prescribed digit set has exactly elements. Since the lowest digit belongs to and , every entry of is a unit in .
In addition to the three labels, condition on the complete first column of and the first entries of its other two columns. If , Lemma 4.1 implies, for ,
The right sides are fixed under this conditioning. Each congruence determines the first base- digits of its entry, since all chosen digits lie between and . It therefore has probability either zero or . The four entries use disjoint independent digit draws, even if their labels agree. Their joint probability is at most . Averaging over the additional conditioning proves (12), including .
Finally, the pointwise identity
For the parameters and of the digit construction, we have
Thus, for fixed and all sufficiently large ,
In particular, suppose the labels are independent and uniform in a set of size , and let be the event that at least two labels coincide. The union bound and conditioning on the labels yield
This is the estimate needed when the digit obstruction restricts a small determinant to triples with repeated labels.
An auxiliary cap and its inclusion probabilities
The determinant obstruction at the main modulus leaves triples with repeated labels. We now impose an independent restriction at a second prime. This restriction excludes short integer relations among three distinct residue columns and gives bounds for the probability of each remaining triple, including triples with equal residue columns.
Retain the main modulus , and choose a prime with
Lemma 3.2 supplies such a prime for all sufficiently large . These choices imply , and hence
We identify the integers with their residues in .
The following construction uses an affine part of a classical elliptic quadric, a cap with no three collinear points; see Barlotti [2]. The proof also gives the required intersection with a small box.
Lemma 5.1. Let be an odd prime and an integer. There is a set with such that no affine line contains three distinct points of .
Proof. Choose a nonsquare and put
The form vanishes only at . On a line with nonzero direction in its first two coordinates, the equation defining is a quadratic equation in the line parameter with nonzero leading coefficient . Such a line meets at most twice. A line with direction meets exactly once. Thus , and every translate of it, has the asserted line property.
For a uniform , every point belongs to with probability . Therefore the average of is . Choose a translate attaining at least this average and take its intersection with the box. □
Fix one such set for the parameters in (5.1), and write . In particular,
The set is fixed before any random choices are made.
For , write for the least absolute value of an integer representative of . Three distinct cap points already exclude nontrivial relations over whose coefficients sum to zero. For a shift , a relation among three points of with integer coefficients and nonzero sum would force . We exclude this possibility by defining the set of allowed shifts
Choose uniformly from , and independently choose uniformly from . Our auxiliary set is
Here and below a triple is affinely independent if and are linearly independent. This allows the three columns to have linear rank two.
Lemma 5.2. Let be an integer, let be prime, and put . Suppose contains no three distinct collinear points. The set in (16) has at least elements. For every and every invertible , the set in (5.4) has elements, does not contain zero, and contains no three distinct collinear points.
Moreover, let satisfy , where is the Euclidean norm. For any , the relation
is impossible if . If , it is impossible whenever the three columns are affinely independent. Consequently, (17) is impossible for three distinct elements of .
Proof. For each integer , multiplication by permutes . Since , a uniform shift violates the condition for this with probability . The union bound gives
Thus the required uniform choice of is defined. Invertible affine maps preserve cardinality and the line property. If for some , then , contrary to the condition with . Hence .
Write with , and let . If , then . Applying to (17) and taking first coordinates gives
The integer on the right, using the representatives , has absolute value at most . Since , this contradicts (16).
If , the coefficients in (17) have sum zero also in . They are not all zero there, since and . Such a relation contradicts affine independence: substituting would give a nontrivial linear relation between and . Finally, three distinct elements of are affinely independent by the line property.
The restricted shift excludes short relations. We next show that this restriction costs only a constant in the inclusion probability of an affinely independent triple, and obtain the weaker bounds needed when residue columns coincide.
For an integer matrix , define
The probability is over and ; remains fixed.
Proposition 5.3. For the distribution in (5.4), with , the following bounds hold with absolute constants:
If , no column of is zero, and its columns are either affinely independent or include two equal columns. For an affinely independent triple with , there is no nonzero with and .
Proof. First replace the allowed shift by an unconditional uniform . Under this replacement the map is uniform in the affine group: conditional on , its translation is uniform. Conditioning back on increases the probability of any event by at most two, by Lemma [5].
The affine group acts transitively on the ordered affinely independent triples in , whose number is
There are such triples in . Therefore, for an affinely independent triple of columns,
For the other two bounds, fix any allowed and put . If two specified target columns are linearly independent, their inverse images under a uniform are uniform among the ordered independent pairs. At most of these pairs belong to . Requiring all three columns to belong to can only reduce this probability. Consequently,
whenever the target matrix has rank at least two. This estimate holds for each allowed shift, so also after averaging over .
If any target column is zero, its inclusion probability is zero. Otherwise fix one target column. Its inverse image under is uniform among the nonzero vectors, and consists of nonzero vectors. Thus
This also covers all patterns of equal columns. The remaining assertions follow from the line property and short-relation conclusion in Lemma [5].
In the sampling construction, choose independently of all labels, all digit choices, and the random change of coordinates at the main modulus. Given , choose the auxiliary residues of the sampled columns independently and uniformly from . Since for every outcome, the probability of any prescribed ordered triple of auxiliary residues is
where is any integer lift of that triple. This identity includes repeated residues and is unchanged on conditioning on any main-modulus data. It is the normalization used when the two residue conditions are combined by the Chinese remainder theorem.
Sampling integral columns
We now combine the two residue constructions and lift them to integral columns. The purpose of this section is to express the probability of a small determinant as a weighted lattice count. The main and auxiliary changes of coordinates are shared by all samples; fresh labels, digits, auxiliary columns, and lifts are chosen for each sample.
Set
For , define its projection by
Choose uniformly in , independently of the auxiliary set . Conditional on , sample columns independently as follows:
Draw a label uniformly from and its digit column by the main-modulus construction, using fresh independent digit choices. Prescribe .
Independently choose uniformly from .
Among columns with those residues, choose uniformly in .
Since and are coprime and divides , each pair of prescribed residues has exactly lifts. This also shows that the sampling rule is defined for every outcome of the residue choices. The samples need not be independent after averaging over ; all estimates below retain the shared choices.
Lemma 6.1 (Proportional pairs). For two sampled columns , one has
Proof. Equality of the projections is equivalent to proportionality of and , because their third coordinates are positive. Every column in is a positive integer multiple of a unique primitive integral vector with . The number of its multiples in is at most . Therefore the total number of ordered proportional pairs in , including equal columns, is at most
For the last estimate, dyadic shells of radius contain integral vectors and contribute to the sum.
Condition on both columns’ residues at both moduli and on the shared random choices. Their lifts are independent, each uniform on exactly columns. The preceding count bounds the number of proportional pairs within any two such sets of lifts. Dividing by and averaging proves the claim.
For three samples, write for the integral matrix of columns, and for their digit matrix before multiplication by . With fixed, use Lemma 4.1 to define and the row lattice , and write for the orbit in Lemma 4.2. Thus is the inverse image in of the row span of modulo , and . Recall also the auxiliary weight from (5.6):
Here the probability defining averages only over the auxiliary choices.
Lemma 6.2 (Exact lifting identity). Condition on all three labels and digit columns, hence on . For any set of integral matrices,
Proof. The matrix is uniform on , since every point of an orbit has the same number of group elements mapping to it. Given , the three auxiliary residues are independent and uniform on its elements. Consequently, for each specified ordered triple of auxiliary residues, its probability is its inclusion probability in , divided by . This remains true when some residues coincide. Independence of the main and auxiliary choices and the exact number of lifts give, for each fixed integral with , the conditional probability
For other matrices the probability is zero. Summation proves the identity.
We call a sampled triple bad if its projected points are pairwise distinct and . Every matrix in has determinant modulo . Since , at most one integer can occur as the determinant of a bad triple with . If the labels are all distinct, Lemma 3.3 rules out every such .
The following estimate handles the one remaining determinant value. Its nonzero case follows immediately from the lattice count; the zero case requires the auxiliary construction and is proved in the next section.
Proposition 6.3 (Weighted count at a fixed determinant). Fix a digit matrix , with row lattice of index and special-linear orbit modulo . For each integer with , let consist of the matrices whose columns lie in , whose projected columns are pairwise distinct, and which satisfy and . Then
Proof. Suppose first that . Since , the reduction of modulo has rank three. Its columns are therefore affinely independent, and Proposition 5.3 gives . Every row of belongs to and has norm less than . Moreover gives . Proposition 2.5, applied with , proves the estimate.
For , Proposition 7.1 below proves the stronger bound for all matrices with rows in and pairwise distinct projected columns. The orbit restriction only reduces this set, so it gives the claimed estimate as well.
Corollary 6.4 (Probability of a bad triple). Three sampled columns satisfy
Proof. Conditional on the labels and digit matrix , the probability is zero when all labels are distinct. Otherwise Lemma 6.2 and Proposition 6.3, together with the bound from (4.2), bound it by
Let be the event that two of the three labels agree. The uniform conditional moment estimate (14) gives
This step uses the moment estimate for every fixed label triple, including repeated labels; the corresponding digit draws remain independent. Averaging the conditional bound proves the corollary.
Counting determinant-zero triples
The remaining part of the weighted count concerns collinear projected points. We organize these triples by their integral linear relation. The auxiliary modulus excludes short relations when the three residues are affinely independent. When two residues coincide, the equality usually imposes an additional lattice condition; the relations for which it does not are sufficiently sparse.
Keep the digit matrix fixed, and write for its row lattice from Lemma 4.1. Write
Thus has diagonal form over , , and . Recall also , , the box , and the weight from (18). For a column , its projection means .
Proposition 7.1. For the lattice and weight above, let be the set of integer matrices whose columns belong to , whose rows belong to , whose determinant is zero, and whose three projected columns are pairwise distinct. Then
The implied constant is independent of the fixed digit matrix .
The orbit restriction in Proposition 6.3 only reduces this sum. We first record the lattice estimates needed for the null vectors.
Lemma 7.2. For a primitive vector , put
where . Then
The reduction of modulo is the entire plane
If is a sublattice of index , the number of ordered triples of vectors in , all of length at most and spanning a plane over , is at most
Proof. Primitivity gives . Since , we have , so . Lemma 2.3 gives the formula for , and .
Primitivity also implies , with no restriction on the size of . To prove surjectivity, choose with . If an integral lift of a point of has , then is another lift of the same point. Thus reduces onto . Its multiple by lies in and still reduces onto , because .
Finally, a triple counted in (7.3) contains two independent vectors of length at most . Therefore the second successive minimum of is at most whenever the count is nonzero. Lemma 2.2 then bounds the choices for each vector by , and .
Lemma 7.3. For ,
In particular, this estimate holds when .
Proof. Since , write with . For , the condition is equivalent to . Indeed, if is any integral lift of , then is the sum of the integral row span of and , and . The diagonal form of shows that the fraction of residue classes modulo satisfying this congruence is
Indeed, the first diagonal coordinate must vanish, the second must be divisible by , and the third is unrestricted since .
Because , each residue class contains integral vectors of length less than . We may discard primitivity for this upper bound. Consequently,
The exponents in the last sum strictly increase to , so its bound is uniform in . Finally, implies .
Proof of Proposition 7.1. Every has rational rank two. Indeed, its columns are nonzero, and no two are proportional because their projections are distinct. Its right nullspace therefore has a primitive integral generator , unique up to sign. Every coordinate of is nonzero: otherwise the relation would make two columns proportional. Taking the cross product of two independent rows and dividing by the gcd of its coordinates gives
Every row of lies in and has length at most . Thus records a relation among the columns, while the rows are lattice vectors perpendicular to . We may sum over both choices of sign of for an upper bound.
Partition the possible vectors into dyadic shells , . By (26), there are shells. We will bound the weighted contribution of each shell by . For a fixed primitive in such a shell, a condition confining every row to an index- sublattice of gives at most
matrices of rational rank two, by (7.3) and . In the affine case we will sum using Lemma 7.3. In the equal-pair cases we instead use , together with an extra row congruence or a smaller number of possible null vectors. The support statement and the three weight bounds in Proposition 5.3 give the following exhaustive cases.
Affinely independent residues. If and the columns of mod are affinely independent, Lemma 5.2 excludes the relation when . To see both parts of this exclusion, if use the restricted shift; if the sum is zero, use affine independence and . Hence a contributing shell satisfies . Using , (7.6) with , and Lemma 7.3, its contribution is at most
An equal pair with an additional equation. Every other matrix of positive weight has two equal columns modulo . Fix one pair with this property, and put , where the are the standard basis vectors. Summing over the three pairs only changes the implied constant. First suppose that . The functional is nonzero on : the annihilator of is precisely . By Lemma 7.2, the rows of therefore belong to the index- sublattice
There are integral in any shell. Using (7.6) with , the pointwise bound , and , the contribution is at most
Here and below we use and . This argument includes matrices of every rank modulo .
An equal pair without an additional equation. It remains to consider . The coordinate of outside the pair is divisible by and, by (7.5), is a nonzero integer. Thus , and a contributing shell has . The nonzero multiples of give residue classes for modulo . Each class contains vectors of length less than , so the number of possible in this shell is
Rank at least two modulo $q. The weight bound now gives
for the contribution of the shell.
Rank at most one modulo . All rows reduce into one of the one-dimensional linear subspaces of . This also covers the zero row space. For each such line , surjectivity in Lemma 7.2 shows that
has index in . Formula (7.3) thus bounds the rank-two rational row triples, summed over all these lines, by
Using (7.9) and the general weight bound, the weighted contribution is at most
The affine and equal-pair cases cover the support of . Their bounds are uniform over the dyadic shells, so summing over the shells proves (24).
Deletion and projective normalization
The preceding estimates allow us to remove every repeated projected point and every small triangle while retaining many columns. We first construct a set for each sufficiently large prime , compare its area bound with its cardinality, and then pass to every sufficiently large cardinality. All constants below may depend on the fixed integer ; none depends on the growing prime .
This final step is an elementary alteration argument. The earlier probabilistic lower bound of Komlós, Pintz and Szemerédi [10] uses a stronger hypergraph independence lemma; no such lemma is needed below.
Proof of Theorem 1.1. Keep the parameters constructed above, with , and set
Here and is an odd prime, so . Take samples with the shared random choices and independent conditional draws specified in Section 6. Let count the unordered pairs of sample indices with equal projected points, plus the unordered triples whose projected points are pairwise distinct and whose determinant has absolute value at most . Linearity of expectation, Lemma 6.1, and Corollary 6.4 give
No independence between the counted events is needed.
Both terms tend to zero. Indeed, and give
For the other term, the definition of gives
Since , the definition of implies , and hence . The bounds , , and also give . Thus the second term in (29) is . Thus .
For sufficiently large , choose an outcome with . For each violating pair or triple in that outcome, mark one of its indices for deletion. This marks at most indices and meets every original violation. After deleting all marked indices, at least remain; retain any of them. Their projections form a set of distinct points in , and every triple of retained columns satisfies . In particular, the construction excludes every zero-area triple as well.
For a retained triple, divide the th column of by its positive third coordinate . The resulting columns have the form , so the determinant formula for triangle area gives the exact identity
Since for each , every retained triangle has area at least . Consequently
Also and give . Hence and eventually . Combining this with (8.4) yields
We now express both the cardinality and the area bound in terms of . The parameter choices give
Consequently, if
then
Since for sufficiently large , there are fixed constants such that
for every sufficiently large prime . In particular, put
The upper bound in (30) gives . Combining this with (8.5), we obtain
Thus the same cardinality estimate that will permit interpolation also converts the factor into a fixed power of the number of points.
For a sufficiently large integer , put . Lemma 3.2 supplies a prime with . Once , we have , so (30) gives
This uses only the two-sided cardinality bounds, not monotonicity of . Retain any points of . Deleting points cannot decrease the minimum triangle area. Since , (32) therefore yields
Taking proves Theorem 1.1. All constants are absolute because is fixed independently of and . The formula (31) is explicit; no attempt has been made to optimize the construction parameters.
An elementary prime-interval estimate
We prove Lemma 3.2, the form of Bertrand’s postulate used to choose the two moduli and to pass to every sufficiently large cardinality. The argument is the elementary binomial proof of Erdős [7].
Proof of Lemma 3.2. Write , where the product is over primes. First, for . It suffices to prove this for integer by induction. The cases are immediate. An even integer is composite, so . For , every prime in divides . The two central binomial coefficients are equal and their sum is strictly less than , whence . Thus
Suppose now that there is no prime in . The largest binomial coefficient in gives . For any prime , its exponent in this coefficient is
Each summand is zero or one, so the entire prime power contributed by is at most . The primes at most therefore contribute at most . Larger primes have exponent at most one. Those in have exponent zero, and by assumption there are none in . For sufficiently large it follows that
Taking logarithms contradicts for sufficiently large .
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