The neighbourhood complexity of a graph is a quantity measuring, for a graph and an integer , the maximum possible number (over all vertex subsets of size ) of -neighbourhoods in . This notion is important in structural graph theory and algorithm design (especially in parameterized complexity, in particular model checking and kernelization). While generally and this bound can be achieved, it is known that sparse graphs and structured dense graphs have linear neighbourhood complexity, that is, for any such graph . However, for many graph classes, the best possible constants are not known. We focus on graphs of bounded treewidth and pathwidth, showing that (when ) (i) if has treewidth , then , and (ii) if has pathwidth , then . Moreover, we provide constructions that reach these bounds, whenever and ( for pathwidth). Interestingly, in contrast, we also have the tight bound , for graphs with pathwidth 1 or treewidth 1.

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