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We study the complexity of the problems of finding, given a graph G, a largest induced subgraph of G with all degrees odd (called an odd subgraph), and the smallest number of odd subgraphs that partition V(G). We call these parameters mos (G) and χ odd (G) , respectively. We prove that deciding whether χ odd (G) ≤ q is polynomial-time solvable if q ≤ 2 , and NP-complete otherwise. We provide algorithms in time 2 O (rw) · n O (1) and 2 O (q · rw) · n O (1) to compute mos (G) and to decide whether χ odd (G) ≤ q on n-vertex graphs of rank-width at most rw , respectively, and we prove that the dependency on rank-width is asymptotically optimal under the ETH. Finally, we give some tight bounds for these parameters on restricted graph classes or in relation to other parameters. [ABSTRACT FROM AUTHOR]

A matching cut is a partition of the vertex set of a graph into two sets A and B such that each vertex has at most one neighbor in the other side of the cut. The Matching Cut problem asks whether a graph has a matching cut, and has been intensively studied in the literature. Motivated by a question posed by Komusiewicz et al. [Discrete Applied Mathematics, 2020], we introduce a natural generalization of this problem, which we call d-Cut: for a positive integer d, a d-cut is a bipartition of the vertex set of a graph into two sets A and B such that each vertex has at most d neighbors across the cut. We generalize (and in some cases, improve) a number of results for the Matching Cut problem. Namely, we begin with an NP-hardness reduction for d-Cut on (2 d + 2) -regular graphs and a polynomial algorithm for graphs of maximum degree at most d + 2 . The degree bound in the hardness result is unlikely to be improved, as it would disprove a long-standing conjecture in the context of internal partitions. We then give FPT algorithms for several parameters: the maximum number of edges crossing the cut, treewidth, distance to cluster, and distance to co-cluster. In particular, the treewidth algorithm improves upon the running time of the best known algorithm for Matching Cut. Our main technical contribution, building on the techniques of Komusiewicz et al. [DAM, 2020], is a polynomial kernel for d-Cut for every positive integer d, parameterized by the vertex deletion distance of the input graph to a cluster graph. We also rule out the existence of polynomial kernels when parameterizing simultaneously by the number of edges crossing the cut, the treewidth, and the maximum degree. Finally, we provide an exact exponential algorithm slightly faster than the naive brute force approach running in time O ∗ 2 n . [ABSTRACT FROM AUTHOR]

In the last years, kernelization with structural parameters has been an active area of research within the field of parameterized complexity. As a relevant example, Gajarský et al. (J Comput Syst Sci 84:219–242, 2017) proved that every graph problem satisfying a property called finite integer index admits a linear kernel on graphs of bounded expansion and an almost linear kernel on nowhere dense graphs, parameterized by the size of a c-treedepth modulator, which is a vertex set whose removal results in a graph of treedepth at most c, where c ≥ 1 is a fixed integer. The authors left as further research to investigate this parameter on general graphs, and in particular to find problems that, while admitting polynomial kernels on sparse graphs, behave differently on general graphs. In this article we answer this question by finding two very natural such problems: we prove that Vertex Cover admits a polynomial kernel on general graphs for any integer c ≥ 1 , and that Dominating Set does not for any integer c ≥ 2 even on degenerate graphs, unless NP ⊆ coNP / poly . For the positive result, we build on the techniques of Jansen and Bodlaender (Proceedings of the 28th symposium on theoretical aspects of computer science (STACS), volume 9 of LIPIcs, pp 177–188, 2011), and for the negative result we use a polynomial parameter transformation for c ≥ 3 and an or-cross-composition for c = 2 . As existing results imply that Dominating Set admits a polynomial kernel on degenerate graphs for c = 1 , our result provides a dichotomy about the existence of polynomial kernels for Dominating Set on degenerate graphs with this parameter. [ABSTRACT FROM AUTHOR]

During the last years, several algorithmic meta-theorems have appeared (Bodlaender et al. [FOCS 2009], Fomin et al. [SODA 2010], Kim et al. [ICALP 2013]) guaranteeing the existence of linear kernels on sparse graphs for problems satisfying some generic conditions. The drawback of such general results is that it is usually not clear how to derive from them constructive kernels with reasonably low explicit constants. To fill this gap, we recently presented [STACS 2014] a framework to obtain explicit linear kernels for some families of problems whose solutions can be certified by a subset of vertices. In this article we enhance our framework to deal with packing problems, that is, problems whose solutions can be certified by collections of subgraphs of the input graph satisfying certain properties. F -Packing is a typical example: for a family F of connected graphs that we assume to contain at least one planar graph, the task is to decide whether a graph G contains k vertex-disjoint subgraphs such that each of them contains a graph in F as a minor. We provide explicit linear kernels on sparse graphs for the following two orthogonal generalizations of F -Packing: for an integer ℓ ⩾ 1 , one aims at finding either minor-models that are pairwise at distance at least ℓ in G (ℓ - F -Packing), or such that each vertex in G belongs to at most ℓ minors-models (F -Packing with ℓ -Membership). Finally, we also provide linear kernels for the versions of these problems where one wants to pack subgraphs instead of minors. [ABSTRACT FROM AUTHOR]

Given two graphs G and H, we define v-coverH(G) (resp. e-coverH(G)) as the minimum number of vertices (resp. edges) whose removal from G produces a graph without any minor isomorphic to H. Also v-packH(G) (resp. e-packH(G)) is the maximum number of vertex- (resp. edge-) disjoint subgraphs of G that contain a minor isomorphic to H. We denote by θr the graph with two vertices and r parallel edges between them. When H=θr, the parameters v-coverH, e-coverH, v-packH, and e-packH are NP-hard to compute (for sufficiently big values of r). Drawing upon combinatorial results in Chatzidimitriou et al. (Minors in graphs of large θr-girth, 2015, arXiv:1510.03041), we give an algorithmic proof that if v-packθr(G)≤k, then v-coverθr(G)=O(klogk), and similarly for e-packθr and  e-coverθr. In other words, the class of graphs containing θr as a minor has the vertex/edge Erdős-Pósa property, for every positive integer r. Using the algorithmic machinery of our proofs we introduce a unified approach for the design of an O(logOPT)-approximation algorithm for v-packθr, v-coverθr, e-packθr, and e-coverθr that runs in O(n·log(n)·m) steps. Also, we derive several new Erdős-Pósa-type results from the techniques that we introduce. [ABSTRACT FROM AUTHOR]

A blocking set in a graph G is a subset of vertices that intersects every maximum independent set of G. Let mmbs (G) be the size of a maximum (inclusion-wise) minimal blocking set of G. This parameter has recently played an important role in the kernelization of Vertex Cover with structural parameterizations. We provide a panorama of the complexity of computing mmbs parameterized by the natural parameter and the independence number of the input graph. We also consider the closely related parameter mmhs , which is the size of a maximum minimal hitting set of a hypergraph. Finally, we consider the problem of computing mmbs parameterized by treewidth, especially relevant in the context of kernelization. Since a blocking set intersects every maximum-sized independent set of a given graph and properties involving counting the sizes of arbitrarily large sets are typically non-expressible in monadic second-order logic, its tractability does not seem to follow from Courcelle's theorem. Our main technical contribution is a fixed-parameter tractable algorithm for this problem. [ABSTRACT FROM AUTHOR]

In the Maximum Minimal Vertex Cover (MMVC) problem, we are given a graph G and a positive integer k, and the objective is to decide whether G contains a minimal vertex cover of size at least k. Motivated by the kernelization of MMVC with parameter k, our main contribution is to introduce a simple general framework to obtain kernelization lower bounds for a certain type of kernels for optimization problems, which we call lop-kernels. Informally, this type of kernel is required to preserve large optimal solutions in the reduced instance, and captures the vast majority of existing kernels in the literature. As a consequence of this framework, we show that the trivial quadratic kernel for MMVC is essentially optimal, answering a question of Boria et al. Discrete Appl Math 196:62–71, 2015. https://doi.org/10.1016/j.dam.2014.06.001), and that the known cubic kernel for Maximum Minimal Feedback Vertex Set is also essentially optimal. We present further applications for Tree Deletion Set and for Maximum Independent Set on K t -free graphs. Back to the MMVC problem, given the (plausible) non-existence of subquadratic kernels for MMVC on general graphs, we provide subquadratic kernels on H-free graphs for several graphs H, such as the bull, the paw, or the complete graphs, by making use of the Erdős–Hajnal property. Finally, we prove that MMVC does not admit polynomial kernels parameterized by the size of a minimum vertex cover of the input graph, even on bipartite graphs, unless NP ⊆ coNP / poly . [ABSTRACT FROM AUTHOR]

Given a graph G, a properk-coloring of G is a partition c = (S i) i ∈ [ 1 , k ] of V(G) into k stable sets S 1 , ... , S k . Given a weight function w : V (G) → R + , the weight of a color S i is defined as w (i) = max v ∈ S i w (v) and the weight of a coloringc as w (c) = ∑ i = 1 k w (i) . Guan and Zhu (Inf Process Lett 61(2):77–81, 1997) defined the weighted chromatic number of a pair (G, w), denoted by σ (G , w) , as the minimum weight of a proper coloring of G. The problem of determining σ (G , w) has received considerable attention during the last years, and has been proved to be notoriously hard: for instance, it is NP-hard on split graphs, unsolvable on n-vertex trees in time n o (log n) unless the ETH fails, and W[1]-hard on forests parameterized by the size of a largest tree. We focus on the so-called dual parameterization of the problem: given a vertex-weighted graph (G, w) and an integer k, is σ (G , w) ≤ ∑ v ∈ V (G) w (v) - k ? This parameterization has been recently considered by Escoffier (in: Proceedings of the 42nd international workshop on graph-theoretic concepts in computer science (WG). LNCS, vol 9941, pp 50–61, 2016), who provided an FPT algorithm running in time 2 O (k log k) · n O (1) , and asked which kernel size can be achieved for the problem. We provide an FPT algorithm in time 9 k · n O (1) , and prove that no algorithm in time 2 o (k) · n O (1) exists under the ETH. On the other hand, we present a kernel with at most (2 k - 1 + 1) (k - 1) vertices, and rule out the existence of polynomial kernels unless NP ⊆ coNP / poly , even on split graphs with only two different weights. Finally, we identify classes of graphs allowing for polynomial kernels, namely interval graphs, comparability graphs, and subclasses of circular-arc and split graphs, and in the latter case we present lower bounds on the degrees of the polynomials. [ABSTRACT FROM AUTHOR]

For two positive integers k and ℓ , a (k × ℓ) -spindle is the union of k pairwise internally vertex-disjoint directed paths with ℓ arcs each between two vertices u and v. We are interested in the (parameterized) complexity of several problems consisting in deciding whether a given digraph contains a subdivision of a spindle, which generalize both the Maximum Flow and Longest Path problems. We obtain the following complexity dichotomy: for a fixed ℓ ≥ 1 , finding the largest k such that an input digraph G contains a subdivision of a (k × ℓ) -spindle is polynomial-time solvable if ℓ ≤ 3 , and NP-hard otherwise. We place special emphasis on finding spindles with exactly two paths and present FPT algorithms that are asymptotically optimal under the ETH. These algorithms are based on the technique of representative families in matroids, and use also color-coding as a subroutine. Finally, we study the case where the input graph is acyclic, and present several algorithmic and hardness results. [ABSTRACT FROM AUTHOR]

The tree-cut width of a graph is a graph parameter defined by Wollan (J Combin Theory, Ser B, 110:47-66, 2015) with the help of tree-cut decompositions. In certain cases, tree-cut width appears to be more adequate than treewidth as an invariant that, when bounded, can accelerate the resolution of intractable problems. While designing algorithms for problems with bounded tree-cut width, it is important to have a parametrically tractable way to compute the exact value of this parameter or, at least, some constant approximation of it. In this paper we give a parameterized 2-approximation algorithm for the computation of tree-cut width; for an input n-vertex graph G and an integer w, our algorithm either confirms that the tree-cut width of G is more than w or returns a tree-cut decomposition of G certifying that its tree-cut width is at most 2 w, in time $$2^{O(w^2\log w)} \cdot n^2$$ . Prior to this work, no constructive parameterized algorithms, even approximated ones, existed for computing the tree-cut width of a graph. As a consequence of the Graph Minors series by Robertson and Seymour, only the existence of a decision algorithm was known. [ABSTRACT FROM AUTHOR]

Minor Containment is a fundamental problem in Algorithmic Graph Theory used as a subroutine in numerous graph algorithms. A model of a graph H in a graph G is a set of disjoint connected subgraphs of G indexed by the vertices of H, such that if { u, v} is an edge of H, then there is an edge of G between components C and C. A graph H is a minor of G if G contains a model of H as a subgraph. We give an algorithm that, given a planar n-vertex graph G and an h-vertex graph H, either finds in time $\mathcal{O}(2^{\mathcal{O}(h)} \cdot n +n^{2}\cdot\log n)$ a model of H in G, or correctly concludes that G does not contain H as a minor. Our algorithm is the first single-exponential algorithm for this problem and improves all previous minor testing algorithms in planar graphs. Our technique is based on a novel approach called partially embedded dynamic programming. [ABSTRACT FROM AUTHOR]