781 research outputs found

    The Erd\H{o}s-Rothschild problem on edge-colourings with forbidden monochromatic cliques

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    Let k:=(k1,,ks)\mathbf{k} := (k_1,\dots,k_s) be a sequence of natural numbers. For a graph GG, let F(G;k)F(G;\mathbf{k}) denote the number of colourings of the edges of GG with colours 1,,s1,\dots,s such that, for every c{1,,s}c \in \{1,\dots,s\}, the edges of colour cc contain no clique of order kck_c. Write F(n;k)F(n;\mathbf{k}) to denote the maximum of F(G;k)F(G;\mathbf{k}) over all graphs GG on nn vertices. This problem was first considered by Erd\H{o}s and Rothschild in 1974, but it has been solved only for a very small number of non-trivial cases. We prove that, for every k\mathbf{k} and nn, there is a complete multipartite graph GG on nn vertices with F(G;k)=F(n;k)F(G;\mathbf{k}) = F(n;\mathbf{k}). Also, for every k\mathbf{k} we construct a finite optimisation problem whose maximum is equal to the limit of log2F(n;k)/(n2)\log_2 F(n;\mathbf{k})/{n\choose 2} as nn tends to infinity. Our final result is a stability theorem for complete multipartite graphs GG, describing the asymptotic structure of such GG with F(G;k)=F(n;k)2o(n2)F(G;\mathbf{k}) = F(n;\mathbf{k}) \cdot 2^{o(n^2)} in terms of solutions to the optimisation problem.Comment: 16 pages, to appear in Math. Proc. Cambridge Phil. So

    Partitioning de Bruijn Graphs into Fixed-Length Cycles for Robot Identification and Tracking

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    We propose a new camera-based method of robot identification, tracking and orientation estimation. The system utilises coloured lights mounted in a circle around each robot to create unique colour sequences that are observed by a camera. The number of robots that can be uniquely identified is limited by the number of colours available, qq, the number of lights on each robot, kk, and the number of consecutive lights the camera can see, \ell. For a given set of parameters, we would like to maximise the number of robots that we can use. We model this as a combinatorial problem and show that it is equivalent to finding the maximum number of disjoint kk-cycles in the de Bruijn graph dB(q,)\text{dB}(q,\ell). We provide several existence results that give the maximum number of cycles in dB(q,)\text{dB}(q,\ell) in various cases. For example, we give an optimal solution when k=q1k=q^{\ell-1}. Another construction yields many cycles in larger de Bruijn graphs using cycles from smaller de Bruijn graphs: if dB(q,)\text{dB}(q,\ell) can be partitioned into kk-cycles, then dB(q,)\text{dB}(q,\ell) can be partitioned into tktk-cycles for any divisor tt of kk. The methods used are based on finite field algebra and the combinatorics of words.Comment: 16 pages, 4 figures. Accepted for publication in Discrete Applied Mathematic

    Defective and Clustered Choosability of Sparse Graphs

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    An (improper) graph colouring has "defect" dd if each monochromatic subgraph has maximum degree at most dd, and has "clustering" cc if each monochromatic component has at most cc vertices. This paper studies defective and clustered list-colourings for graphs with given maximum average degree. We prove that every graph with maximum average degree less than 2d+2d+2k\frac{2d+2}{d+2} k is kk-choosable with defect dd. This improves upon a similar result by Havet and Sereni [J. Graph Theory, 2006]. For clustered choosability of graphs with maximum average degree mm, no (1ϵ)m(1-\epsilon)m bound on the number of colours was previously known. The above result with d=1d=1 solves this problem. It implies that every graph with maximum average degree mm is 34m+1\lfloor{\frac{3}{4}m+1}\rfloor-choosable with clustering 2. This extends a result of Kopreski and Yu [Discrete Math., 2017] to the setting of choosability. We then prove two results about clustered choosability that explore the trade-off between the number of colours and the clustering. In particular, we prove that every graph with maximum average degree mm is 710m+1\lfloor{\frac{7}{10}m+1}\rfloor-choosable with clustering 99, and is 23m+1\lfloor{\frac{2}{3}m+1}\rfloor-choosable with clustering O(m)O(m). As an example, the later result implies that every biplanar graph is 8-choosable with bounded clustering. This is the best known result for the clustered version of the earth-moon problem. The results extend to the setting where we only consider the maximum average degree of subgraphs with at least some number of vertices. Several applications are presented
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