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Incidence moment rounding
This is a proved restricted result, not a resolution of the unrestricted Erdős problem. All hypergraphs are finite families of nonempty sets; rank means maximum edge size. Write when every subfamily of at most edges has a transversal of size at most two. For a vertex set , let
Write for fractional transversal number. All logarithms are natural.
Fractional transversal number is the minimum total nonnegative vertex weight giving every edge weight at least one. Its linear-program dual is the maximum total edge weight giving every vertex weighted degree at most one. The VC dimension is the largest size of a set for which the traces realize every subset of .
If the local hypothesis is instead stated for exactly distinct edges, it implies whenever the family has at least edges. Families with fewer than edges have and should be handled separately; the deletion theorem below uses the at-most- formulation.
The deletion theorem
Theorem. Let , and let have rank at most and property . For every real , there is a vertex set such that
Proof. Put and . Suppose every residual obtained by deleting at most vertices has fractional transversal number greater than .
For any such nonempty residual, normalize an optimal fractional matching to a probability distribution on its edges. Finite linear-program duality shows that the probability of any vertex is at most .
We choose reference edges successively, maintaining maximum vertex degree at most . After choices, let be the vertex degrees and put
Binomial coefficients with negative lower argument or lower argument greater than upper argument are zero. All coefficients in (2) are nonnegative, and the coefficient of is .
Let be the set of vertices currently of degree . Because degrees are at most , . Inductively we will have , so . Sample the next edge from the fractional-matching distribution in . This preserves the degree bound. Writing , Pascal's identity gives
Indeed, adding an edge changes by , and every vertex has selection probability at most .
Put , with . The identity
and (3) cancel all terms involving the old , leaving
Choose a realization satisfying this bound. Since and
every intermediate potential is at most , justifying each residual sampling step.
After choices, , so . The hypothesis gives , so this residual contains an edge. Choose it as one further edge. The resulting edges all have vertex degrees at most ; two vertices therefore meet at most of them. This contradicts . Repeated selected edges are harmless: removing repetitions preserves the absence of a two-cover.
No assumption is needed. In particular, for , deletion of at most vertices leaves fractional transversal number at most .
For any integer , the same proof applies when every at-most--edge subfamily has an -point transversal: replace throughout by . The deletion budget becomes .
A hereditary fractional-to-integral consequence
Suppose additionally that for every vertex set ,
Only vertex-deletion residuals are required, not arbitrary subfamilies. A set from (1), together with a transversal of , covers . Thus for every ,
The right side is minimized at , giving
A self-contained VC estimate
If a nonempty hypergraph has VC dimension at most and fractional transversal number , then
Here VC dimension is the ordinary dimension of the edge family on its vertex ground set.
For completeness, normalize a fractional transversal to a vertex probability measure , under which every edge has measure at least . Put , , and take two independent samples of size , with replacement. If misses an edge , its number of occurrences in is at least with probability at least : its mean is at least , variance is at most its mean, and Chebyshev applies since .
Equivalently, first generate a pooled labeled sample of independent vertices and assign its positions uniformly to two halves. Conditional on this pool, there are at most edge traces, by the elementary Sauer trace bound. Each trace of size at least lies entirely in the second half with probability at most . Thus the probability that is not a transversal is at most
To check the constants, and
The probability is therefore at most . The Sauer bound itself follows from the induction ; sample repetitions cannot increase VC dimension. This proves (8).
Suppose now that has , rank at most , and VC dimension . A maximal matching has at most two edges, so . Every residual has VC dimension at most and transversal number at most . Consequently (5) holds with
Indeed, for a nonempty residual of fractional transversal number , apply (8). If , its transversal number is at most . Empty residuals cause no issue.
Combining (7) and (9) gives
In particular, for , take :
Every fixed therefore gives when . A nonempty family of VC dimension zero has only one distinct edge and transversal number one.
Robust VC consequence for . Suppose , and fix . After deleting any vertex set of size at most , the residual has transversal number at least . If its VC dimension is , then, for , it is positive and satisfies
Since as , this forces for some , uniformly over all such deletions. Thus a putative linear-transversal counterexample retains linear VC dimension under every deletion that leaves a fixed positive linear transversal number.
Checks on scope and sharpness
The local threshold five for the conclusion cannot be lowered to four: projective-plane lines have , VC dimension two, and .
For fixed , the power in (10) is sharp up to logarithmic factors when VC dimension is bounded. Take the hyperplanes of , where is a prime power. Their rank is , their transversal number is , and their VC dimension is . Any hyperplanes intersect, so the family even has . A projective line is a transversal. There are hyperplanes and each point is on of them; since , at most points cannot meet all hyperplanes. For VC dimension, a shattered collection must be linearly independent and lie in a hyperplane, so has size at most ; the coordinate points of one hyperplane attain this bound.
A caution about VC-sensitive set-pair compression
The VC reduction suggested replacing the usual exponential critical set-pair bound by a polynomial depending on VC dimension. Formal cross-intersection certificates alone do not justify this. In a full binary tree of depth , let be the nonroot vertices on the path to leaf , and let contain the sibling of each vertex on that path. Then
The cross-intersection occurs at the first divergence of the paths. There are pairs, but the family of the has VC dimension one: comparable vertices cannot realize the descendant-only trace, while incomparable vertices cannot occur together. Thus even a fixed-degree polynomial bound in fails at VC dimension one for general set-pair systems.
The actual transversal number of the path family is two, witnessed by the two children of the root, and it is not transversal-critical. This does not refute a stronger bound assuming genuine transversal-criticality and certificate size . No such stronger bound was proved here.
The transversal inequalities also extend to infinite families by the finite-witness compactness argument, since every finite subfamily has no larger VC dimension. The deletion theorem itself was proved above only for finite families.
No bound here controls the remaining regime , which includes the complete-family examples at the conjectured three-quarter scale. Neither unrestricted assertion of the original problem follows.
An unconditional stronger deletion target is false
One proposed strengthening was that deleting vertices from any family should leave fractional transversal number at most . This assertion, without a high-transversal hypothesis, is false.
For sufficiently large , let , take two disjoint -point blocks, and let consist of all -sets in either block. Every at-most-six edges in one block have a common point, since . A selection of at most seven edges meeting both components therefore has a one-point cover in each component. A selection lying in one component is covered by one point for its first at-most-six rows and one for the remaining row. Thus has .
For a complete -uniform family on points, the fractional transversal number is . Uniform weights give the upper bound; summing all edge constraints gives the lower bound. Consequently
After deleting any vertices, both residual components are still complete -uniform families on points. Their fractional transversal numbers still sum to , rather than .
This rules out only the unconditional deletion target. It does not rule out a theorem assuming , nor an estimate balancing the deletion cost against the residual fractional transversal number. No such estimate sufficient for Problem 644 was proved.