On the order of countable graphs

A set of graphs is said to be independent if there is no homomorphism between distinct graphs from the set. We consider the existence problems related to the independent sets of countable graphs. While the maximal size of an independent set of countable graphs is 2^omega the On Line problem of extending an independent set to a larger independent set is much harder. We prove here that singletons can be extended (``partnership theorem''). While this is the best possible in general, we give structural conditions which guarantee independent extensions of larger independent sets. This is related to universal graphs, rigid graphs and to the density problem for countable graphs

Linear Colouring of Binomial Random Graphs

We investigate the linear chromatic number $\chi_{\text{lin}}(G(n,p))$ of the binomial random graph $G(n,p)$ on $n$ vertices in which each edge appears independently with probability $p=p(n)$. For dense random graphs ($np \to \infty$ as $n \to \infty$), we show that asymptotically almost surely $\chi_{\text{lin}}(G(n,p)) \ge n (1 - O( (np)^{-1/2} ) ) = n(1-o(1))$. Understanding the order of the linear chromatic number for subcritical random graphs ($np < 1$) and critical ones ($np=1$) is relatively easy. However, supercritical sparse random graphs ($np = c$ for some constant $c > 1$) remain to be investigated

On treewidth and related parameters of random geometric graphs *

International audienceWe give asymptotically exact values for the treewidth tw(G) of a random geometric graph G ∈ G(n, r) in [0, sqrt(n)]^2. More precisely, let r_c denote the threshold radius for the appearance of the giant component in G(n, r). We then show that for any constant 0 < r < r_c , tw(G) = Θ(log n log log n), and for c being sufficiently large, and r = r(n) ≥ c, tw(G) = Θ(r sqrt(n)). Our proofs show that for the corresponding values of r the same asymptotic bounds also hold for the pathwidth and the treedepth of a random geometric graph

Generalised dualities and maximal finite antichains in the homomorphism order of relational structures

The motivation for this paper is threefold. First, we study the connectivity properties of the homomorphism order of directed graphs, and more generally for relational structures. As opposed to the homomorphism order of undirected graphs (which has no non-trivial finite maximal antichains), the order of directed graphs has finite maximal antichains of any size. In this paper, we characterise explicitly all maximal antichains in the homomorphism order of directed graphs. Quite surprisingly, these maximal antichains correspond to generalised dualities. The notion of generalised duality is defined here in full generality as an extension of the notion of finitary duality, investigated in [J. Nešetřil, C. Tardif, Duality theorems for finite structures (characterising gaps and good characterisations), J. Combin. Theory Ser. B 80 (1) (2000) 80–97]. Building upon the results of the cited paper, we fully characterise the generalised dualities. It appears that these dualities are determined by forbidding homomorphisms from a finite set of forests (rather than trees). Finally, in the spirit of [A. Atserias, On digraph coloring problems and treewidth duality, in: Proceedings of the 21st IEEE Symposium on Logic in Computer Science, LICS’06, IEEE Computer Society, 2006; B. Larose, C. Loten, C. Tardif, A characterisation of first-order constraint satisfaction problems, in: Proceedings of the 21st IEEE Symposium on Logic in Computer Science, LICS’06, IEEE Computer Society, 2006; V. Dalmau, A. Krokhin, B. Larose, First-order definable retraction problems for posets and reflexive graphs, in: Proceedings of the 19th IEEE Symposium on Logic in Computer Science, LICS’04, IEEE Computer Society, 2004 [5]] we shall characterise “generalised” constraint satisfaction problems (defined also here) that are first-order definable. These are again just generalised dualities corresponding to finite maximal antichains in the homomorphism order

On Treewidth and Related Parameters of Random Geometric Graphs

We give asymptotically exact values for the treewidth tw(G) of a random geometric graph G ¿ G(n, r) in [0, v n] 2 . More precisely, let rc denote the threshold radius for the appearance of the giant component in G(n, r). We then show that for any constant 0 < r < rc, tw(G) = T( log n log log n ), and for c being sufficiently large, and r = r(n) = c, tw(G) = T(r v n). Our proofs show that for the corresponding values of r the same asymptotic bounds also hold for the pathwidth and the treedepth of a random geometric graph.Postprint (author's final draft

Probabilistic methods and coloring problems in graphs

Aquest projecte està dedicat a estudiar el k-èssim nombre cromàtic generalitzat que sorgeix de les descomposicions Low Tree--Depth en grafs usant mètodes probabilístics.. Una extensió natural del nombre cromàtic d'un graf és l'estudi de particions de grafs en les que cada i parts indueixen un subgraf amb un cert paràmetre acotat en funció de i, per exemple cada i parts tenen com a molt i-1 arestes. En particular el nombre cromàtic generalitzat és le mínim nombre de parts per tal que cada i parts té 'treedepth' com a molt i. Resultats recents proven que grans classes de grafs tenen paràmetres d'aquest tipus acotats. L'objectiu del projecte és (i) fer servie mètodes probabilístics per donar cotas ajustades d'aquests paràmetres i (ii) estudiar el seu valor per grafs aleatoris

Aspects of random graphs

The present report aims at giving a survey of my work since the end of my PhD thesis "Spectral Methods for Reconstruction Problems". Since then I focussed on the analysis of properties of different models of random graphs as well as their connection to real-world networks. This report's goal is to capture these problems in a common framework. The very last chapter of this thesis about results in bootstrap percolation is different in the sense that the given graph is deterministic and only the decision of being active for each vertex is probabilistic; since the proof techniques resemble very much results on random graphs, we decided to include them as well. We start with an overview of the five random graph models, and with the description of bootstrap percolation corresponding to the last chapter. Some properties of these models are then analyzed in the different parts of this thesis