Connections Between Extremal Combinatorics, Probabilistic Methods, Ricci Curvature of Graphs, and Linear Algebra

This thesis studies some problems in extremal and probabilistic combinatorics, Ricci curvature of graphs, spectral hypergraph theory and the interplay between these areas. The first main focus of this thesis is to investigate several Ramsey-type problems on graphs, hypergraphs and sequences using probabilistic, combinatorial, algorithmic and spectral techniques: The size-Ramsey number Rˆ(G, r) is defined as the minimum number of edges in a hypergraph H such that every r-edge-coloring of H contains a monochromatic copy of G in H. We improved a result of Dudek, La Fleur, Mubayi and Rödl [ J. Graph Theory 2017 ] on the size-Ramsey number of tight paths and extended it to more colors. An edge-colored graph G is called rainbow if every edge of G receives a different color. The anti-Ramsey number of t edge-disjoint rainbow spanning trees, denoted by r(n, t), is defined as the maximum number of colors in an edge-coloring of Kn containing no t edge-disjoint rainbow spanning trees. Confirming a conjecture of Jahanbekam and West [J. Graph Theory 2016], we determine the anti-Ramsey number of t edge-disjoint rainbow spanning trees for all values of n and t. We study the extremal problems on Berge hypergraphs. Given a graph G = (V, E), a hypergraph H is called a Berge-G, denoted by BG, if there exists an injection i ∶ V (G) → V (H) and a bijection f ∶ E(G) → E(H) such that for every e = uv ∈ E(G), (i(u), i(v)) ⊆ f(e). We investigate the hypergraph Ramsey number of Berge cliques, the cover-Ramsey number of Berge hypergraphs, the cover-Turán desity of Berge hypergraphs as well as Hamiltonian Berge cycles in 3-uniform hypergraphs. The second part of the thesis uses the ‘geometry’ of graphs to derive concentration inequalities in probabilities spaces. We prove an Azuma-Hoeffding-type inequality in several classical models of random configurations, including the Erdős-Rényi random graph models G(n, p) and G(n,M), the random d-out(in)-regular directed graphs, and the space of random permutations. The main idea is using Ollivier’s work on the Ricci curvature of Markov chairs on metric spaces. We give a cleaner form of such concentration inequality in graphs. Namely, we show that for any Lipschitz function f on any graph (equipped with an ergodic random walk and thus an invariant distribution ν) with Ricci curvature at least κ \u3e 0, we have ν (∣f − Eνf∣ ≥ t) ≤ 2 exp (-t 2κ/7). The third part of this thesis studies a problem in spectral hypergraph theory, which is the interplay between graph theory and linear algebra. In particular, we study the maximum spectral radius of outerplanar 3-uniform hypergraphs. Given a hypergraph H, the shadow of H is a graph G with V (G) = V (H) and E(G) = {uv ∶ uv ∈ h for some h ∈ E(H)}. A 3-uniform hypergraph H is called outerplanar if its shadow is outerplanar and all faces except the outer face are triangles, and the edge set of H is the set of triangle faces of its shadow. We show that the outerplanar 3-uniform hypergraph on n vertices of maximum spectral radius is the unique hypergraph with shadow K1 + Pn−1

A hierarchy of randomness for graphs

AbstractIn this paper we formulate four families of problems with which we aim at distinguishing different levels of randomness.The first one is completely non-random, being the ordinary Ramsey–Turán problem and in the subsequent three problems we formulate some randomized variations of it. As we will show, these four levels form a hierarchy. In a continuation of this paper we shall prove some further theorems and discuss some further, related problems

New recursive constructions of amoebas and their balancing number

The definition of amoeba graphs is based on iterative \emph{feasible edge-replacements}, where, at each step, an edge from the graph is removed and placed in an available spot in a way that the resulting graph is isomorphic to the original graph. Broadly speaking, amoebas are graphs that, by means of a chain of feasible edge-replacements, can be transformed into any other copy of itself on a given vertex set (which is defined according to whether these are local or global amoebas). Global amoebas were born as examples of \emph{balanceable} graphs, which are graphs that appear with half of their edges in each color in any $2$-edge coloring of a large enough complete graph with a sufficient amount of edges in each color. The least amount of edges required in each color is called the \emph{balancing number} of $G$. In a work by Caro et al., an infinite family of global amoeba trees with arbitrarily large maximum degree is presented, and the question if they were also local amoebas is raised. In this paper, we provide a recursive construction to generate very diverse infinite families of local and global amoebas, by which not only this question is answered positively, it also yields an efficient algorithm that, given any copy of the graph on the same vertex set, provides a chain of feasible edge-replacements that one can perform in order to move the graph into the aimed copy. All results are illustrated by applying them to three different families of local amoebas, including the Fibonacci-type trees. Concerning the balancing number of a global amoeba $G$, we are able to express it in terms of the extremal number of a class of subgraphs of $G$. By means of this, we give a general lower bound for the balancing number of a global amoeba $G$, and we provide linear (in terms of order) lower and upper bounds for the balancing number of our three case studies.Comment: 27 pages, 10 figure

A lower bound on the multicolor size-Ramsey numbers of paths in hypergraphs

The r-color size-Ramsey number of a k-uniform hypergraph H, denoted by R^r(H), is the minimum number of edges in a k-uniform hypergraph G such that for every r-coloring of the edges of G there exists a monochromatic copy of H. In the case of 2-uniform paths Pn, it is known that Ω(r2n)=R^r(Pn)=O((r2logr)n) with the best bounds essentially due to Krivelevich. In a recent breakthrough result, Letzter, Pokrovskiy, and Yepremyan gave a linear upper bound on the r-color size-Ramsey number of the k-uniform tight path P(k)n; i.e. R^r(P(k)n)=Or,k(n). Winter gave the first non-trivial lower bounds on the 2-color size-Ramsey number of P(k)n for k≥3; i.e. R^2(P(3)n)≥8/3n−O(1) and R^2(P(k)n)≥⌈log2(k+1)⌉n−Ok(1) for k≥4.We consider the problem of giving a lower bound on the r-color size-Ramsey number of P(k)n (for fixed k and growing r). Our main result is that R^r(P(k)n)=Ωk(rkn) which generalizes the best known lower bound for graphs mentioned above. One of the key elements of our proof is a determination of the correct order of magnitude of the r-color size-Ramsey number of every sufficiently short tight path; i.e. R^r(P(k)k+m) = Θk(rm) for all 1≤m≤k.All of our results generalize to ℓ-overlapping k-uniform paths P(k,ℓ)n. In particular we note that when 1≤ℓ≤k/2, we have Ωk(r2n)=R^r(P(k,ℓ)n)=O((r2logr)n) which essentially matches the best known bounds for graphs mentioned above. Additionally, in the case k=3, ℓ=2, and r=2, we give a more precise estimate which implies R^2(P(3)n)≥28/9n−O(1), improving on the above-mentioned lower bound of Winter in the case k=3

Spanning-Tree Games

We introduce and study a game variant of the classical spanning-tree problem. Our spanning-tree game is played between two players, min and max, who alternate turns in jointly constructing a spanning tree of a given connected weighted graph G. Starting with the empty graph, in each turn a player chooses an edge that does not close a cycle in the forest that has been generated so far and adds it to that forest. The game ends when the chosen edges form a spanning tree in G. The goal of min is to minimize the weight of the resulting spanning tree and the goal of max is to maximize it. A strategy for a player is a function that maps each forest in G to an edge that is not yet in the forest and does not close a cycle. We show that while in the classical setting a greedy approach is optimal, the game setting is more complicated: greedy strategies, namely ones that choose in each turn the lightest (min) or heaviest (max) legal edge, are not necessarily optimal, and calculating their values is NP-hard. We study the approximation ratio of greedy strategies. We show that while a greedy strategy for min guarantees nothing, the performance of a greedy strategy for max is satisfactory: it guarantees that the weight of the generated spanning tree is at least w(MST(G))/2, where w(MST(G)) is the weight of a maximum spanning tree in G, and its approximation ratio with respect to an optimal strategy for max is 1.5+1/w(MST(G)), assuming weights in [0,1]. We also show that these bounds are tight. Moreover, in a stochastic setting, where weights for the complete graph K_n are chosen at random from [0,1], the expected performance of greedy strategies is asymptotically optimal. Finally, we study some variants of the game and study an extension of our results to games on general matroids

Polynomial growth of concept lattices, canonical bases and generators:: extremal set theory in Formal Concept Analysis

We prove that there exist three distinct, comprehensive classes of (formal) contexts with polynomially many concepts. Namely: contexts which are nowhere dense, of bounded breadth or highly convex. Already present in G. Birkhoff's classic monograph is the notion of breadth of a lattice; it equals the number of atoms of a largest boolean suborder. Even though it is natural to define the breadth of a context as being that of its concept lattice, this idea had not been exploited before. We do this and establish many equivalences. Amongst them, it is shown that the breadth of a context equals the size of its largest minimal generator, its largest contranominal-scale subcontext, as well as the Vapnik-Chervonenkis dimension of both its system of extents and of intents. The polynomiality of the aforementioned classes is proven via upper bounds (also known as majorants) for the number of maximal bipartite cliques in bipartite graphs. These are results obtained by various authors in the last decades. The fact that they yield statements about formal contexts is a reward for investigating how two established fields interact, specifically Formal Concept Analysis (FCA) and graph theory. We improve considerably the breadth bound. Such improvement is twofold: besides giving a much tighter expression, we prove that it limits the number of minimal generators. This is strictly more general than upper bounding the quantity of concepts. Indeed, it automatically implies a bound on these, as well as on the number of proper premises. A corollary is that this improved result is a bound for the number of implications in the canonical basis too. With respect to the quantity of concepts, this sharper majorant is shown to be best possible. Such fact is established by constructing contexts whose concept lattices exhibit exactly that many elements. These structures are termed, respectively, extremal contexts and extremal lattices. The usual procedure of taking the standard context allows one to work interchangeably with either one of these two extremal structures. Extremal lattices are equivalently defined as finite lattices which have as many elements as possible, under the condition that they obey two upper limits: one for its number of join-irreducibles, other for its breadth. Subsequently, these structures are characterized in two ways. Our first characterization is done using the lattice perspective. Initially, we construct extremal lattices by the iterated operation of finding smaller, extremal subsemilattices and duplicating their elements. Then, it is shown that every extremal lattice must be obtained through a recursive application of this construction principle. A byproduct of this contribution is that extremal lattices are always meet-distributive. Despite the fact that this approach is revealing, the vicinity of its findings contains unanswered combinatorial questions which are relevant. Most notably, the number of meet-irreducibles of extremal lattices escapes from control when this construction is conducted. Aiming to get a grip on the number of meet-irreducibles, we succeed at proving an alternative characterization of these structures. This second approach is based on implication logic, and exposes an interesting link between number of proper premises, pseudo-extents and concepts. A guiding idea in this scenario is to use implications to construct lattices. It turns out that constructing extremal structures with this method is simpler, in the sense that a recursive application of the construction principle is not needed. Moreover, we obtain with ease a general, explicit formula for the Whitney numbers of extremal lattices. This reveals that they are unimodal, too. Like the first, this second construction method is shown to be characteristic. A particular case of the construction is able to force - with precision - a high number of (in the sense of "exponentially many'') meet-irreducibles. Such occasional explosion of meet-irreducibles motivates a generalization of the notion of extremal lattices. This is done by means of considering a more refined partition of the class of all finite lattices. In this finer-grained setting, each extremal class consists of lattices with bounded breadth, number of join irreducibles and meet-irreducibles as well. The generalized problem of finding the maximum number of concepts reveals itself to be challenging. Instead of attempting to classify these structures completely, we pose questions inspired by Turán's seminal result in extremal combinatorics. Most prominently: do extremal lattices (in this more general sense) have the maximum permitted breadth? We show a general statement in this setting: for every choice of limits (breadth, number of join-irreducibles and meet-irreducibles), we produce some extremal lattice with the maximum permitted breadth. The tools which underpin all the intuitions in this scenario are hypergraphs and exact set covers. In a rather unexpected, but interesting turn of events, we obtain for free a simple and interesting theorem about the general existence of "rich'' subcontexts. Precisely: every context contains an object/attribute pair which, after removed, results in a context with at least half the original number of concepts