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A famous conjecture of Gyarfas and Sumner states for any tree $T$ and integer $k$, if the chromatic number of a graph is large enough, either the graph contains a clique of size $k$ or it contains $T$ as an induced subgraph. We discuss some results and open problems about extensions of this conjecture to oriented graphs. We conjecture that for every oriented star $S$ and integer $k$, if the chromatic number of a digraph is large enough, either the digraph contains a clique of size $k$ or it contains $S$ as an induced subgraph. As an evidence, we prove that for any oriented star $S$, every oriented graph with sufficiently large chromatic number contains either a transitive tournament of order $3$ or $S$ as an induced subdigraph. We then study for which sets ${cal P}$ of orientations of $P_4$ (the path on four vertices) similar statements hold. We establish some positive and negative results.
A grounded L-graph is the intersection graph of a collection of L shapes whose topmost points belong to a common horizontal line. We prove that every grounded L-graph with clique number $omega$ has chromatic number at most $17omega^4$. This improves
The second authors $omega$, $Delta$, $chi$ conjecture proposes that every graph satisties $chi leq lceil frac 12 (Delta+1+omega)rceil$. In this paper we prove that the conjecture holds for all claw-free graphs. Our approach uses the structure theorem
In 1998 the second author proved that there is an $epsilon>0$ such that every graph satisfies $chi leq lceil (1-epsilon)(Delta+1)+epsilonomegarceil$. The first author recently proved that any graph satisfying $omega > frac 23(Delta+1)$ contains a sta
We show that a simple Markov chain, the Glauber dynamics, can efficiently sample independent sets almost uniformly at random in polynomial time for graphs in a certain class. The class is determined by boundedness of a new graph parameter called bipa
We prove a Chernoff-like large deviation bound on the sum of non-independent random variables that have the following dependence structure. The variables $Y_1,...,Y_r$ are arbitrary Boolean functions of independent random variables $X_1,...,X_m$, mod