If a bipartite graph with parts has at least edges, then the number of ordered tuples for which every is an edge is at leastIndeed, if is the number of common neighbours of in , two applications of the Cauchy-Schwarz inequality give
This is the part-preserving homomorphism density of a four-cycle in a bipartite graph with independently uniform labels in the first part and in the second. Repeated labels are included. It equals the fourth power of the four-cycle norm of the adjacency indicator function. It differs at finite sizes from a count requiring four distinct vertices.
For fixed and positive density threshold , sufficiently regular pairwise dense bipartite graphs between disjoint equal-sized vertex classes contain at least transversal cliques, for some . A greedy embedding maintains common neighbourhoods and discards the small set of vertices with atypical degrees into them. The constants depend only on .
If three disjoint vertex classes have size , and their three pairs are -regular pairs of vertex sets of edge density of a bipartite graph at least , where and , they contain at least the displayed number of transversal triangles in a graph. All but vertices in the first class have at least neighbours in both other classes. Regularity between those two neighbour sets supplies the third edge. This strengthens a mere triangle embedding lemma for regular pairs to a cubic lower count.
Let and be set partitions of the two parts of a bipartite graph. The pair of partitions is -regular whenThus a uniformly random pair in lies in an irregular cell pair with probability at most .
For every there is a positive integer such that every finite bipartite graph has an -regular pair of partitions with at most cells on each side.
To prove this, give the uniform probability measure, let be the indicator function of the edge set, and for partitions define their energy byThis conditional expectation is an orthogonal projection, so . If the partitions are not -regular, choose witnesses and in every irregular cell pair and refine each by all its and each by all its . The refined energy exceeds the old energy byOn the absolute value function of the mean of the difference is greater than , while this rectangle occupies at least an fraction of . The Cauchy-Schwarz inequality therefore contributes more than from that cell pair. Irregular pairs have total weight greater than , so every refinement raises the energy by more than . The process stops after at most refinements. If the current cell counts are , the construction gives at most new cells, so a finite iterated bound depending only on supplies .
For every and there are such that every graph on at least vertices has a partitionwhere , , the other parts have equal size, and all but at most pairs are -regular.
For fixed forbidden induced patterns, a regularity and Ramsey refinement uses internal clique/independent types and sparse, almost-complete, or intermediate cross pairs. A clique of intermediate pairs realizes every bounded induced pattern consistent with those internal types, using both edge and nonedge regularity. This is the induced embedding consequence used in hereditary graph enumeration theorem; the exceptional-pair budget can be arbitrarily small.
For fixed and every , some has the following property for all sufficiently large : a graph with fewer than copies of can be made -free by deleting at most edges. A Szemerédi regularity lemma partition and the regular clique counting lemma prove this. It converts sparse counts of a forbidden clique into a small edit distance from clique-freeness.
For every , some and have this property: a graph on vertices with fewer than unordered triangles in a graph can be made triangle-free by deleting at most edges. A Szemerédi regularity lemma partition deletes exceptional, intraclass, irregular and sparse-pair edges cheaply. A surviving triangle in a graph would force a positive cubic count by the regular triangle counting lemma.
For a set partition of the vertices of a graph of order , definewhere the sum is ordered, the adjacency indicator defines the density also on diagonal pairs, and exceptional vertices are treated as singleton parts. Refinement cannot decrease this energy, by the Cauchy-Schwarz inequality. An irregular pair of equal cells of size , with witnesses of relative size at least and density discrepancy greater than , increases the energy by more than for each orientation. Splitting refined atoms into equal chunks and leftover singleton parts is a further refinement, so restoring equitability causes no energy loss.
In a proof of the Szemerédi regularity lemma, suppose equal classes have size and witness splitting creates at most atoms per class. Divide every atom into blocks of size , putting leftovers into the exceptional set. At most vertices are lost. When , at most blocks remain. For equitable regularity energy defined by omitting exceptional vertices, the loss from discarding a fraction is at most : only ordered pairs incident with discarded vertices are removed, and every squared edge density of a bipartite graph is at most one. This provides a quantitative way to restore equal class sizes after each energy increment.
If a set partition refines a rectangle of a graph into rectangles , write for its edge density of a bipartite graph. The weighted variance identity isIt follows by expanding the square and using . In particular, equitable regularity energy cannot decrease under refinement. If a witness rectangle has relative sizes at least and edge density of a bipartite graph discrepancy greater than , its contribution, after division by the squared total vertex count, exceeds .
For every finite graph and density , sufficiently large vertex classes joined according to by regular pairs of density at least contain a copy of . The regularity parameter must be sufficiently small in terms of and .
For any fixed odd length , positive triangle in a graph density forces positive density of -cycles. A Szemerédi regularity lemma partition retains a triangle in a graph of regular dense pairs after the sparse and exceptional pairs are removed. Count embeddings of a proper three-colouring of into those three clusters. The constants depend on and , not on graph order.
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