False-twin class 2026-10-07
A false-twin class is an equivalence class of vertices with identical open neighbourhoods. In edge-triangle symmetrization, merging nonadjacent false-twin classes by cloning the better local score never decreases the objective. A secondary maximization of squared class sizes forces all distinct classes to be adjacent, giving a complete multipartite graph.
For a fixed uniform hypergraph with vertices, uniformity , and at least one edge, define its Turán density by
where is the maximum edge count of an -free hypergraph. The limit exists: averaging the edge count over all -vertex subsets of an extremal -vertex hypergraph, with , shows that the displayed normalized extremal numbers are nonincreasing. Thus their limit is their infimum.
For hypergraph supersaturation by sampling, choose so that . The expected edge count in a uniform -vertex subset of is at least . A subset containing no copy of has at most edges, while any subset has at most . Hence at least an fraction of the subsets contain . Every particular copy of lies in exactly such subsets, so their number is at least
for . Take
For , the requested integer lower bound is zero; for , the calculation proves it. This positive depends only on and . If the density hypothesis is impossible there is nothing to prove. For an edgeless , every -set is already a copy and the conclusion follows directly.
For the edge-triangle objective, let be the open neighbourhood of and define its local score
It counts the contribution to of edges and triangles in a graph containing . If are nonadjacent, making a false twin of changes the objective by , since no edge or triangle in a graph uses both. More generally, partition vertices into false-twin classes, meaning equal open neighbourhoods. If distinct classes have no edges between them, making every vertex of a twin of a representative of changes the objective by . Choose the direction with nonnegative change.
Among graphs maximizing the objective, choose one maximizing the sum of squared false-twin class sizes. The operation cannot split any old false-twin class and merges , so it would strictly increase that secondary quantity. Therefore no two distinct classes can be nonadjacent. An objective maximizer is a complete multipartite graph. This edge-triangle symmetrization works for every real , with no assumption on its sign.
For positive part sizes , the correct multipartite formula is
The first sum in the printed intermediate formula has inconsistent indices; the edge count is the pairwise-product sum above. Fix two part sizes with sum and let be the sum of all other sizes. All terms varying with the pair have the form
Choose a maximizing partition with the fewest nonempty parts. If , merging those two parts cannot decrease and reduces the number of parts, a contradiction. Therefore this coefficient is positive for every pair. If two integer sizes differ by at least two, moving one vertex from the larger to the smaller increases their product and hence , again a contradiction. All sizes differ by at most one, so a maximizer is a Turan graph. This is balancing a multipartite edge-triangle objective.
Next maximize the same polynomial on the compact simplex of nonnegative real sizes summing to , starting with at least two possible parts. Choose a maximizer with the smallest positive support. The merging argument still applies, and now varying two positive unequal sizes towards equality improves the product. Thus every positive size is for some integer . A two-part choice has value when , so . The optimum is attained at rational sizes, and therefore
One may take the initial simplex to have coordinates, so it includes every multipartite graph obtained above; zero coordinates are discarded.
Set . Dividing the right side by gives
because is an integer at least two. Rearranging proves
Equality in the continuous calculation occurs at two or three equal parts, explaining the triangle support line between bipartite and tripartite Turan graphs.
Symmetrization for an arbitrary real coefficient. Among graphs maximizing , choose one maximizing
For a vertex , put . This is the contribution of edges and triangles in a graph containing . If are nonadjacent, Zykov symmetrization replacing by a clone of changes by ; the opposite replacement changes it by . Maximality implies , so both changes preserve .
Let and . In the first replacement the vertex degrees in increase by one and those in decrease by one; in the opposite replacement these changes reverse. The changes to cancel when the two replacements are added. Since ,
If the two vertex neighbourhoods differ, one replacement increases , a contradiction. Thus every pair of nonadjacent vertices has the same vertex neighbourhood. Nonadjacency, with equality allowed, is an equivalence relation: if and are nonadjacent and and are nonadjacent, their identical vertex neighbourhoods forbid as well. Its classes are independent sets and every cross-class edge is present. Therefore
This edge-triangle symmetrization works for either sign of .
The exact supporting line. For , write
We prove the triangle support line between bipartite and tripartite Turan graphs by maximizing . First . For , its values are respectively . For , the exact balancing of the Turán graph gives , while and the arithmetic-geometric mean inequality gives . Hence
By edge-triangle symmetrization a maximizing graph can be taken complete multipartite graph; among such maximizers use one with the fewest nonempty parts. If there are at least four parts, let be the two smallest sizes. Then . Merging them loses edges and triangles in a graph, so the objective changes by
This contradicts the choice of the number of parts. Thus at most three parts remain.
For three part sizes , the objective is
If , merging the parts of sizes does not decrease it, again contradicting minimality. If and , transferring one vertex from the largest to the smallest part raises by and strictly increases the objective. Thus a three-part maximizer has all sizes differing by at most one, and is . A maximizer with at most two parts has objective at most , since it has no triangles in a graph and the Mantel theorem bounds its edges. Finally,
Therefore every graph satisfies . At the prescribed edge count this gives
For , the conclusion is simply the nonnegative lower bound zero. All rounding in the Turán graphs has been retained.
One edge above the bipartite threshold. Write . We prove the Triangle lower bound one edge above the Mantel threshold by induction on , allowing at least edges. For , five edges on four vertices give two triangles in a graph, and adding edges preserves this bound.
We will also use the following consequence of an inductive bound: on vertices, at least edges, for an integer , force at least triangles in a graph. Delete surplus edges first to leave exactly . Repeatedly delete an edge in a triangle in a graph until edges remain. The Mantel theorem guarantees such a triangle in a graph at every step; each deletion destroys at least one distinct triangle in a graph. Apply the inductive bound to the remaining graph.
Now take exactly edges. If every edge lies in a triangle in a graph, the edge-triangle incidence bound gives . This is at least for ; the base case was handled separately.
Otherwise choose an edge in no triangle in a graph. Its endpoints have disjoint vertex neighbourhoods, so . Deleting removes exactly edges and leaves at least edges. If , it leaves at least edges, and the strengthened inductive bound gives at least triangles in a graph already.
If , induction gives at least triangles in a graph after deletion. There must be an additional triangle in a graph containing or . Otherwise both and are independent sets; since they are disjoint and cover all vertices, would be bipartite graph, contradicting by the Mantel theorem. Hence
The bound is sharp: add one internal edge to one class of the complete bipartite graph . Its triangles in a graph are precisely that edge together with each of the vertices in the other class.
For , put , , and . Every graph on vertices satisfies
Thus an edge count forces at least triangles in a graph. This is an exact finite bound, with the rounding in the Turán graph retained. To prove it, use edge-triangle symmetrization. The inequality allows merging the two smallest classes when there are at least four classes. With three classes, fixing the middle class makes the objective affine in the product of the other two sizes; either merge them or balance them. Only and need remain.