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For a fixed finite collection of graphs F, the F-M-DELETION problem is as follows: given an n-vertex input graph G, find the minimum number of vertices that intersect all minor models in G of the graphs in F. by Courcelle's Theorem, this problem can be solved in time fF(tw) - n°(1), where tw is the treewidth of G for some function ƒ depending on F. In a recent series of articles, we have initiated the program of optimizing asymptotically the function ff. Here we provide an algorithm showing that fF(tw) = 2° (tw.log tw) for every collection F. Prior to this work, the best known function ƒ was double- exponential in tw. In particular, our algorithm vastly extends the results of Jansen, Lokshtanov, and Saurabh [Proc. of the 25th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), SIAM, 2014, pp. 1802-1811] for the particular case F = {K5, K3,3} and of Kociumaka and Pilipczuk [Algorithmica, 81 (2019), pp. 3655-3691] for graphs of bounded genus, and answers an open problem posed by Cygan et al. [Inform. Comput., 256 (2017), pp. 62-82]. We combine several ingredients such as the machinery of boundaried graphs in dynamic programming via representatives, the Flat Wall Theorem, bidimensionality, the irrelevant vertex technique, treewidth modulators, and protrusion replacement. Together with our previous results providing single-exponential algorithms for particular collections F [J. Baste, I. Sau, and D. M. Thilikos, Theoret. Comput. Sci., 814 (2020), pp. 135-152] and general lower bounds [J. Baste, I. Sau, and D. M. Thilikos, J. Comput. Syst. Sci., 109 (2020), pp. 56-77], our algorithm yields the following complexity dichotomy when F = {H} contains a single connected graph H, assuming the Exponential Time Hypothesis: ƒH(tw) = 2Θ(tw) if H is a contraction of the chair or the banner, and fH(tw) = 2Θ(tw-log tw) otherwise. [ABSTRACT FROM AUTHOR]

Let G be a minor-closed graph class. We say that a graph G is a k-apex of G if G contains a set S of at most k vertices such that G ∖ S belongs to G. We denote by A k (G) the set of all graphs that are k -apices of G. We prove that every graph in the obstruction set of A k (G) , i.e., the minor-minimal set of graphs not belonging to A k (G) , has order at most 2 2 2 2 poly (k) , where poly is a polynomial function whose degree depends on the order of the minor-obstructions of G. This bound drops to 2 2 poly (k) when G excludes some apex graph as a minor. [ABSTRACT FROM AUTHOR]

Let G be a minor-closed graph class. We say that a graph G is a k-apex of G if G contains a set S of at most k vertices such that G\S belongs to G. We denote by Ak (G) the set of all graphs that are k-apices of G. In the first paper of this series, we obtained upper bounds on the size of the graphs in the minor-obstruction set of Ak (G), i.e., the minor-minimal set of graphs not belonging to Ak (G). In this article, we provide an algorithm that, given a graph G on n vertices, runs in time 2poly(k) · n3 and either returns a set S certifying that G ∈ Ak (G), or reports that G ∉ Ak (G). Here poly is a polynomial function whose degree depends on the maximum size of a minor-obstruction of G. In the special case where G excludes some apex graph as a minor, we give an alternative algorithm running in 2poly(k) · n²-time. [ABSTRACT FROM AUTHOR]

For a finite collection of graphs F, the F-M-DELETION problem consists in, given a graph G and an integer k, deciding whether there exists S ⊆ V (G) with |S| ≤ k such that G\S does not contain any of the graphs in F as a minor. We are interested in the parameterized complexity of F-M-Deletion when the parameter is the treewidth of G, denoted by tw. Our objective is to determine, for a fixed F, the smallest function fF such that F-M-DELETION can be solved in time fF(tw) . nO(1) on n-vertex graphs. We prove that fF(tw) = 2²O(tw.logtw) for every collection F, that fF(tw) = 2O(tw.log tw) if F contains a planar graph, and that fF(tw) = 2O(tw) if in addition the input graph G is planar or embedded in a surface. We also consider the version of the problem where the graphs in F are forbidden as topological minors, called F-TM-Deletion. We prove similar results for this problem, except that in the last two algorithms, instead of requiring F to contain a planar graph, we need it to contain a subcubic planar graph. This is the first of a series of articles on this topic. [ABSTRACT FROM AUTHOR]

For a finite fixed collection of graphs F , the F -M-Deletion problem consists in, given a graph G and an integer k , decide whether there exists S ⊆ V (G) with | S | ≤ k such that G ∖ S does not contain any of the graphs in F as a minor. We provide lower bounds under the ETH on the smallest function f F such that F -M-Deletion can be solved in time f F (tw) ⋅ n O (1) on n -vertex graphs, where tw denotes the treewidth of G. We first prove that for any F containing connected graphs of size at least two, f F (tw) = 2 Ω (tw) , even if G is planar. Our main result is that if F contains a single connected graph H that is either P 5 or is not a minor of the b a n n e r , then f F (tw) = 2 Ω (tw ⋅ log ⁡ tw). [ABSTRACT FROM AUTHOR]

For a finite collection of graphs F , the F -M-Deletion (resp. F -TM-Deletion) problem consists in, given a graph G and an integer k , decide whether there exists S ⊆ V (G) with | S | ≤ k such that G ∖ S does not contain any of the graphs in F as a minor (resp. topological minor). We are interested in the parameterized complexity of both problems when the parameter is the treewidth of G , denoted by tw , and specifically in the cases where F contains a single connected planar graph H. We present algorithms running in time 2 O (tw) ⋅ n O (1) , called single-exponential , when H is either P 3 , P 4 , C 4 , the paw , the chair , and the banner for both { H } -M-Deletion and { H } -TM-Deletion , and when H = K 1 , i , with i ≥ 1 , for { H } -TM-Deletion. Some of these algorithms use the rank-based approach introduced by Bodlaender et al. (2015) [7]. This is the second of a series of articles on this topic, and the results given here together with other ones allow us, in particular, to provide a tight dichotomy on the complexity of { H } -M-Deletion in terms of H. [ABSTRACT FROM AUTHOR]

Several algorithmic meta-theorems on kernelization have appeared in the last years, starting with the result of Bodlaender et al. [(Meta) kernelization, in Proceedings of the 50th IEEE Symposium on Foundations of Computer Science (FOCS), IEEE Computer Society, 2009, pp. 629– 638] on graphs of bounded genus, then generalized by Fomin et al. [Bidimensionality and kernels, in Proceedings of the 21st ACM-SIAM Symposium on Discrete Algorithms (SODA), SIAM, Philadephia, 2010, pp. 503–510] to graphs excluding a fixed minor, and by Kim et al. [Linear kernels and single-exponential algorithms via protrusion decompositions, in Proceedings of the 40th International Colloquium on Automata, Languages and Programming (ICALP), Lecture Notes in Comput. Sci., 7965 (2013), pp. 613–624] to graphs excluding a fixed topological minor. Typically, these results guarantee the existence of linear or polynomial kernels on sparse graph classes for problems satisfying some generic conditions, but, mainly due to their generality, it is not clear how to derive from them constructive kernels with explicit constants. In this paper, we make a step toward a fully constructive meta-kernelization theory on sparse graphs. Our approach is based on a more explicit protrusion replacement machinery that, instead of expressibility in counting monadic second order logic, uses dynamic programming, which allows us to find an explicit upper bound on the size of the derived kernels. We demonstrate the usefulness of our techniques by providing the first explicit linear kernels for r-Dominating Set and r-Scattered Set on apex-minor-free graphs, and for PLANAR-F-DELETION on graphs excluding a fixed (topological) minor in the case where all the graphs in F are connected. [ABSTRACT FROM AUTHOR]

The c-pumpkin is the graph with two vertices linked by c ≥ 1 parallel edges. A c-pumpkin-model in a graph G is a pair {A, B} of disjoint subsets of vertices of G, each inducing a connected subgraph of G, such that there are at least c edges in G between A and B. We focus on hitting and packing c-pumpkin-models in a given graph in the realm of approximation algorithms and parameterized algorithms. We give a fixed-parameter tractable (FPT) algorithm running in time 2...(κ)(n...(1) deciding, for any fixed c ≥ 1, whether all c-pumpkin-models can be hit by at most k vertices. This generalizes known single-exponential FPT algorithms for Vertex Cover and Feedback Vertex SET, which correspond to the cases c = 1, 2 respectively. Finally, we present an ...(log n)-approximation algorithm for both the problems of hitting all c-pumpkin-models with a smallest number of vertices and packing a maximum number of vertex-disjoint c-pumpkin-models. [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]

Abstract: We present subexponential parameterized algorithms on planar graphs for a family of problems of the following shape: given a graph, find a connected (induced) subgraph with bounded maximum degree and with maximum number of edges (or vertices). These problems are natural generalisations of the Longest Path problem. Our approach uses bidimensionality theory combined with novel dynamic programming techniques over branch decompositions of the input graph. These techniques can be applied to a more general family of problems that deal with finding connected subgraphs under certain degree constraints. [Copyright &y& Elsevier]

Abstract: We present subexponential parameterized algorithms on planar graphs for a family of problems that consist in, given a graph G, finding a connected (induced) subgraph H with bounded maximum degree, while maximising the number of edges (or vertices) of H. These problems are natural generalisations of Longest Path. Our approach uses bidimensionality theory combined with novel dynamic programming techniques over branch decompositions of the input graph. These techniques can be applied to a more general family of problems that deal with finding connected subgraphs under certain degree constraints. [Copyright &y& Elsevier]

Abstract: The -Minor containment problem asks whether a graph contains some fixed graph as a minor, that is, whether can be obtained by some subgraph of after contracting edges. The derivation of a polynomial-time algorithm for -Minor containment is one of the most important and technical parts of the Graph Minor Theory of Robertson and Seymour and it is a cornerstone for most of the algorithmic applications of this theory. -Minor containment for graphs of bounded branchwidth is a basic ingredient of this algorithm. The currently fastest solution to this problem, based on the ideas introduced by Robertson and Seymour, was given by Hicks in [I.V. Hicks, Branch decompositions and minor containment, Networks 43 (1) (2004) 1–9], providing an algorithm that in time decides if a graph with edges and branchwidth , contains a fixed graph on vertices as a minor. In this work we improve the dependence on of Hicks’ result by showing that checking if is a minor of can be done in time . We set up an approach based on a combinatorial object called rooted packing, which captures the properties of the subgraphs of that we seek in our dynamic programming algorithm. This formulation with rooted packings allows us to speed up the algorithm when is embedded in a fixed surface, obtaining the first algorithm for minor containment testing with single-exponential dependence on branchwidth. Namely, it runs in time , with . Finally, we show that slight modifications of our algorithm permit to solve some related problems within the same time bounds, like induced minor or contraction containment. [Copyright &y& Elsevier]