KAIST Discrete Math Seminar

Graphs are mathematical structures used to model pairwise relations between objects.
Graph decomposition problems ask to partition the edges of large/dense graphs into small/sparse graphs.
In this talk, we introduce several famous graph decomposition problems, related puzzles and known results on the problems.

We say a subgraph H of an edge-colored graph is rainbow if all edges in H has distinct colors. The concept of rainbow subgraphs generalizes the concept of transversals in latin squares.
In this talk, we discuss how these concepts are related and we introduce a result regarding approximate decompositions of graphs into rainbow subgraphs. This has implications on transversals in latin square. It is based on a joint work with Kühn, Kupavskii and Osthus.

In this lecture, we aim to learn several techniques to find sufficient conditions on a dense graph G to contain a sparse graph H as a subgraph.

Lecture note (PDF file)

Tentative plan for the course (June 25, 26, 27, 28, 29)
Lecture 1 : Basic probabilistic methods
Lecture 2 : Extremal number of graphs
Lecture 3 : Extremal number of even cycles
Lecture 4 : Dependent random choice
Lecture 5 : The regularity lemma and its applications
Lecture 6 : Embedding large graphs
Lecture 7 : The blow-up lemma and its applications I
Lecture 8 : The blow-up lemma and its applications II
Lecture 9 : The absorbing method I
Lecture 10 : The absorbing method II

A classical result of Komlós, Sárközy and Szemerédi states that every n-vertex graph with minimum degree at least (1/2 +o(1))n contains every n-vertex tree with maximum degree at most O(n/log n) as a subgraph, and the bounds on the degree conditions are sharp.
On the other hand, Krivelevich, Kwan and Sudakov recently proved that for every n-vertex graph G with minimum degree at least αn for any fixed α>0 and every n-vertex tree T with bounded maximum degree, one can still find a copy of T in G with high probability after adding O(n) randomly-chosen edges to G.
We extend this result to trees with unbounded maximum degree. More precisely, for a given n^ε ≤ Δ≤ cn/log n and α>0, we determined the precise number (up to a constant factor) of random edges that we need to add to an arbitrary n-vertex graph G with minimum degree αn in order to guarantee with high probability a copy of any fixed T with maximum degree at most Δ. This is joint work with Felix Joos.

We provide a combinatorial characterization of all testable properties of k-graphs (i.e. k-uniform hypergraphs).
Here, a k-graph property ? is testable if there is a randomized algorithm which quickly distinguishes with high probability between k-graphs that satisfy ? and those that are far from satisfying ?. For the 2-graph case, such a combinatorial characterization was obtained by Alon, Fischer, Newman and Shapira. This is joint work with Felix Joos, Deryk Osthus and Daniela Kühn.