To date, the best circle graph recognition algorithm, due to Gioan et al. [E. Gioan et al., 2014] runs in almost linear time as it relies on a split decomposition algorithm [E. Gioan et al., 2014] that uses the union-find data-structure [B.A. Galler and M.J. Fischer, 1964; R. Tarjan, 1975]. We show that in the case of circle graphs, the PC-tree data-structure [W. K. Shih and W. L. Hsu, 1999] allows one to avoid the union-find data-structure to compute the split decomposition in linear time. As a consequence, we obtain the first linear-time recognition algorithm for circle graphs.

International audience

Let$\mathcal{G}$and$\mathcal{H}$be minor-closed graph classes. We say that the pair$(\mathcal{H},\ \mathcal{G})$is an Erdös-Pósa pair (EP-pair) if there exists a function$f$such that for every$k$and every graph$G\in \mathcal{G}$, either$G$has$k$pairwise vertex-disjoint sub graphs which do not belong to$\mathcal{H}$, or there exists a set$S\subseteq V(G)$of size at most$f(k)$for which$G-S\in \mathcal{H}$. The classic result of Erdös and Pósa says that if$\mathcal{F}$is the class of forests, then$(\mathcal{F}, \mathcal{G})$is an EP-pair for all graph classes$\mathcal{G}$. A minor-closed graph class$\mathcal{G}$is an EP-counterexample for$\mathcal{H}$if$\mathcal{G}$is minimal with the property that$(\mathcal{H},\ \mathcal{G})$is not an EP-pair. In this paper, we prove that for every minor-closed graph class$\mathcal{H}$the set$\mathfrak{C}_{\mathcal{H}}$of all EP-counterexamples for$\mathcal{H}$is finite. In particular, we provide a complete characterization of$\mathfrak{C}_{\mathcal{H}}$for every$\mathcal{H}$and give a constructive upper bound on its size. We show that each class$\mathcal{G}$in$\mathfrak{C}_{\mathcal{H}}$can be described as the set of all minors of some, suitably defined, sequence of grid-like graphs$\langle{W}_{k}\rangle_{k\in \mathbb{N}}$. Moreover, each$\mathrm{W}_{k}$admits a half-integral packing, i.e.,$k$copies of some$H\not\in \mathcal{H}$where no vertex is used more than twice. This implies a complete delineation of the half-integrality threshold of the Erdös-Pósa property for minors and as a corollary, we obtain a constructive proof of Thomas' conjecture on the half-integral Erdös-Pósa property for minors which was recently confirmed by Liu. Our results are algorithmic. Let$h=h(\mathcal{H})$denote the maximum size of an obstruction to$\mathcal{H}$. For every minor-closed graph class$\mathcal{H}$, we construct an algorithm that, given a graph$G$and an integer$k$, either outputs a half-integral packing of$k$copies of some$H\not\in \mathcal{H}$or outputs a set of at most$2^{k^{\overline{\mathcal{O}}_{h}(1)}}$vertices whose deletion creates a graph in$\mathcal{H}$in time$2^{2^{k^{\mathcal{O}_{h}(1)}}}\cdot\vert G\vert ^{4}\log\vert G\vert$. Moreover, as a consequence of our results, for every minor-closed class$\mathcal{H}$, we obtain min-max-dualities, which may be seen as analogues of the celebrated Grid Theorem of Robertson and Seymour, for the recently introduced parameters$\mathcal{H}$-treewidth and elimination distance to$\mathcal{H}$.

In 1986 Robertson and Seymour proved a generalization of the seminal result of Erdős and Pósa on the duality of packing and covering cycles: A graph has the Erdős-Pósa property for minors if and only if it is planar. In particular, for every non-planar graph H they gave examples showing that the Erdős-Pósa property does not hold for H. Recently, Liu confirmed a conjecture of Thomas and showed that every graph has the half-integral Erdős-Pósa property for minors. Liu’s proof is non-constructive and to this date, with the exception of a small number of examples, no constructive proof is known. In this paper, we initiate the delineation of the half-integrality of the Erdős-Pósa property for minors. We conjecture that for every graph H, there exists a unique (up to a suitable equivalence relation on graph parameters) graph parameter EP_H such that H has the Erdős-Pósa property in a minor-closed graph class 𝒢 if and only if sup{EP_H(G) ∣ G ∈ 𝒢} is finite. We prove this conjecture for the class ℋ of Kuratowski-connected shallow-vortex minors by showing that, for every non-planar H ∈ ℋ, the parameter EP_H(G) is precisely the maximum order of a Robertson-Seymour counterexample to the Erdős-Pósa property of H which can be found as a minor in G. Our results are constructive and imply, for the first time, parameterized algorithms that find either a packing, or a cover, or one of the Robertson-Seymour counterexamples, certifying the existence of a half-integral packing for the graphs in ℋ.

Many important graph classes are characterized by means of layouts (a vertex ordering) excluding some patterns. For example, a graph G = (V,E) is a proper interval graph if and only if G has a layout 𝐋 such that for every triple of vertices such that x≺_𝐋 y≺_𝐋 z, if xz ∈ E, then xy ∈ E and yz ∈ E. Such a triple x, y, z is called an indifference triple. In this paper, we investigate the concept of excluding a set of patterns in tree-layouts rather than layouts. A tree-layout 𝐓_G = (T,r,ρ_G) of a graph G = (V,E) is a tree T rooted at some node r and equipped with a one-to-one mapping ρ_G between V and the nodes of T such that for every edge xy ∈ E, either x is an ancestor of y, denoted x≺_{𝐓_G} y, or y is an ancestor of x. Excluding patterns in a tree-layout is now defined using the ancestor relation. This leads to an unexplored territory of graph classes. In this paper, we initiate the study of such graph classes with the class of proper chordal graphs defined by excluding indifference triples in tree-layouts. Our results combine characterization, compact and canonical representation as well as polynomial time algorithms for the recognition and the graph isomorphism of proper chordal graphs. For this, one of the key ingredients is the introduction of the concept of FPQ-hierarchy generalizing the celebrated PQ-tree data-structure.

The graph parameter of pathwidth can be seen as a measure of the topological resemblance of a graph to a path. A popular definition of pathwidth is given in terms of node search, where we are given a system of tunnels (represented by a graph) that is contaminated by some infectious substance and we are looking for a search strategy that, at each step, either places a searcher on a vertex or removes a searcher from a vertex and where an edge is cleaned when both endpoints are simultaneously occupied by searchers. It was proved that the minimum number of searchers required for a successful cleaning strategy is equal to the pathwidth of the graph plus one. Two desired characteristics for a cleaning strategy are to be monotone (no recontamination occurs) and connected (clean territories always remain connected). Under these two demands, the number of searchers is equivalent to a variant of pathwidth called connected pathwidth. We prove that connected pathwidth is fixed parameter tractable; in particular we design a $2^{O(k^2)}\cdot n$ time algorithm that checks whether the connected pathwidth of $G$ is at most $k.$ This resolves an open question by Dereniowski, Osula, and Rzaͅżewski [ Theoret. Comput. Sci., 794 (2019), pp. 85--100]. For our algorithm, we enrich the typical sequence technique that is able to deal with the connectivity demand. Typical sequences have been introduced by Bodlaender and Kloks [ J. Algorithms, 21 (1996), pp. 358--402] for the design of linear parameterized algorithms for treewidth and pathwidth. While this technique has been later applied to other parameters, none of its advancements was able to deal with the connectivity demand, as it is a “global” demand that concerns an unbounded number of parts of the graph of unbounded size. The proposed extension is based on an encoding of the connectivity property that is quite versatile and may be adapted to deliver linear parameterized algorithms for the connected variants of other width parameters as well. An immediate consequence of our result is a $2^{O(k^2)}\cdot n$ time algorithm for the monotone and connected version of the edge search number.

This special issue contains five articles which are based on extended abstracts presented at the 35th Symposium on Theoretical Aspects of Computer Science (STACS).The conference was held at the Technical University of Berlin from March 13 to March 16, 2019.The extended abstracts were chosen among the top papers of those which were selected for presentation in a highly competitive peer-review process (after which only 54 papers out of 260 submissions were accepted, putting it among the most competitive conferences in Theoretical Computer Science).Compared with the original conference papers, the articles have been extended with a description of the context, full proofs, and additional results.They underwent a rigorous reviewing process, following the TOCS journal standards, completely independent from the selection process of STACS 2019.The topics of the chosen papers cover various areas of Theoretical Computer Science, that is, algorithmic graph theory, automata theory, linear dynamical systems, parameterized complexity analysis, and distributed algorithms.In what follows, we briefly describe the contributions of the papers, ordered alphabetically by author names.Significantly extending the results of the conference version, the article "First-Order Orbit Queries" by Shaull Almagor, Joel Quaknine, and James Worrell studies fundamental reachability questions, so-called orbit problems: Here, for example, we are given a square matrix A of dimension d over the rationals and two semialgebraic This article belongs to the Topical

We study the complexity of finding an optimal hierarchical clustering of an unweighted similarity graph under the recently introduced Dasgupta objective function. We introduce a proof technique, called the normalization procedure, that takes any such clustering of a graph $G$ and iteratively improves it until a desired target clustering of G is reached. We use this technique to show both a negative and a positive complexity result. Firstly, we show that in general the problem is NP-complete. Secondly, we consider min-well-behaved graphs, which are graphs $H$ having the property that for any $k$ the graph $H(k)$ being the join of $k$ copies of $H$ has an optimal hierarchical clustering that splits each copy of $H$ in the same optimal way. To optimally cluster such a graph $H(k)$ we thus only need to optimally cluster the smaller graph $H$. Co-bipartite graphs are min-well-behaved, but otherwise they seem to be scarce. We use the normalization procedure to show that also the cycle on 6 vertices is min-well-behaved.

Abstract We study the minimum diameter spanning tree problem under the reload cost model (Diameter‐Treefor short) introduced by Wirth and Steffan. In this problem, given an undirected edge‐colored graphG, reload costs on a path arise at a node where the path uses consecutive edges of different colors. The objective is to find a spanning tree ofGof minimum diameter with respect to the reload costs. We initiate a systematic study of the parameterized complexity of theDiameter‐Treeproblem by considering the following parameters: the cost of a solution, and the treewidth and the maximum degree Δ of the input graph. We prove thatDiameter‐Treeispara‐NP‐hard for any combination of two of these three parameters, and that it isFPTparameterized by the three of them. We also prove that the problem can be solved in polynomial time on cactus graphs. This result is somehow surprising since we proveDiameter‐Treeto beNP‐hard on graphs of treewidth two, which is best possible as the problem can be trivially solved on forests. When the reload costs satisfy the triangle inequality, Wirth and Steffan proved that the problem can be solved in polynomial time on graphs with Δ = 3, and Galbiati proved that it isNP‐hard if Δ = 4. Our results show, in particular, that without the requirement of the triangle inequality, the problem isNP‐hard if Δ = 3, which is also best possible. Finally, in the case where the reload costs are polynomially bounded by the size of the input graph, we prove thatDiameter‐Treeis inXPandW[1]‐hard parameterized by the treewidth plus Δ.

The node search game against a lazy (or, respectively, agile) invisible robber has been introduced as a search-game analogue of the treewidth parameter (and, respectively, pathwidth). In the connected variants of the above two games, we additionally demand that, at each moment of the search, the clean territories are connected. The connected search game against an agile and invisible robber has been extensively examined. The monotone variant (where we also demand that the clean territories are progressively increasing) of this game, corresponds to the graph parameter of connected pathwidth. It is known that the price of connectivty to search for an agile robber is bounded by 2, that is the connected pathwidth of a graph is at most twice (plus some constant) its pathwidth. In this paper, we investigate the connected search game against a lazy robber. A lazy robber moves only when the searchers' strategy threatens the location that he currently occupies. We introduce two alternative graph-theoretic formulations of this game, one in terms of connected tree decompositions, and one in terms of (connected) layouts, leading to the graph parameter of connected treewidth. We observe that connected treewidth parameter is closed under contractions and prove that for every k >= 2, the set of contraction obstructions of the class of graphs with connected treewidth at most k is infinite. Our main result is a complete characterization of the obstruction set for k=2. One may observe that, so far, only a few complete obstruction sets are explicitly known for contraction closed graph classes. We finally show that, in contrast to the agile robber game, the price of connectivity is unbounded.

A simple digraph is semicomplete if for any two of its vertices u and v , at least one of the arcs ( u , v ) and ( v , u ) is present. We study the complexity of computing two layout parameters of semicomplete digraphs: cutwidth and optimal linear arrangement (O la ). We prove the following: • Both parameters are NP-hard to compute and the known exact and parameterized algorithms for them have essentially optimal running times, assuming the Exponential Time Hypothesis. • The cutwidth parameter admits a quadratic Turing kernel, whereas it does not admit any polynomial kernel unless NP ⊆ coNP/poly. By contrast, O la admits a linear kernel. These results essentially complete the complexity analysis of computing cutwidth and O la on semicomplete digraphs (with respect to standard parameters). Our techniques also can be used to analyze the sizes of minimal obstructions for having a small cutwidth under the induced subdigraph relation.

We study the minimum diameter spanning tree problem under the reload cost model (DIAMETER-TREE for short) introduced by Wirth and Steffan (2001). In this problem, given an undirected edge-colored graph G, reload costs on a path arise at a node where the path uses consecutive edges of different colors. The objective is to find a spanning tree of G of minimum diameter with respect to the reload costs. We initiate a systematic study of the parameterized complexity of the DIAMETER-TREE problem by considering the following parameters: the cost of a solution, and the treewidth and the maximum degree Delta of the input graph. We prove that DIAMETER-TREE is para-np-hard for any combination of two of these three parameters, and that it is FPT parameterized by the three of them. We also prove that the problem can be solved in polynomial time on cactus graphs. This result is somehow surprising since we prove DIAMETER-TREE to be NP-hard on graphs of treewidth two, which is best possible as the problem can be trivially solved on forests. When the reload costs satisfy the triangle inequality, Wirth and Steffan (2001) proved that the problem can be solved in polynomial time on graphs with Delta=3, and Galbiati (2008) proved that it is NP-hard if Delta=4. Our results show, in particular, that without the requirement of the triangle inequality, the problem is NP-hard if Delta=3, which is also best possible. Finally, in the case where the reload costs are polynomially bounded by the size of the input graph, we prove that DIAMETER-TREE is in XP and W[1]-hard parameterized by the treewidth plus Delta.

Linear rankwidth is a linearized variant of rankwidth, introduced by Oum and Seymour (J Comb Theory Ser B 96(4):514–528, 2006). Motivated from recent development on graph modification problems regarding classes of graphs of bounded treewidth or pathwidth, we study the Linear Rankwidth-1 Vertex Deletion problem (shortly, LRW1-Vertex Deletion). In the LRW1-Vertex Deletion problem, given an n-vertex graph G and a positive integer k, we want to decide whether there is a set of at most k vertices whose removal turns G into a graph of linear rankwidth at most 1 and find such a vertex set if one exists. While the meta-theorem of Courcelle, Makowsky, and Rotics implies that LRW1-Vertex Deletion can be solved in time $$f(k)\cdot n^3$$ for some function f, it is not clear whether this problem allows a running time with a modest exponential function. We first establish that LRW1-Vertex Deletion can be solved in time $$8^k\cdot n^{{\mathcal {O}}(1)}$$ . The major obstacle to this end is how to handle a long induced cycle as an obstruction. To fix this issue, we define necklace graphs and investigate their structural properties. Later, we reduce the polynomial factor by refining the trivial branching step based on a cliquewidth expression of a graph, and obtain an algorithm that runs in time $$2^{{\mathcal {O}}(k)}\cdot n^4$$ . We also prove that the running time cannot be improved to $$2^{o(k)}\cdot n^{{\mathcal {O}}(1)}$$ under the Exponential Time Hypothesis assumption. Lastly, we show that the LRW1-Vertex Deletion problem admits a polynomial kernel.

BACKGROUND: Orthologs inference is the starting point of most comparative genomics studies, and a plethora of methods have been designed in the last decade to address this challenging task. In this paper we focus on the problems of deciding consistency with a species tree (known or not) of a partial set of orthology/paralogy relationships [Formula: see text] on a collection of n genes. RESULTS: ) time algorithm - to decide whether [Formula: see text] is consistent, even when the species tree is unknown. We also investigate a biologically meaningful optimization version of these problems, in which we wish to minimize the number of duplication events; unfortunately, we show that all these optimization problems are NP-hard and are unlikely to have good polynomial time approximation algorithms. CONCLUSIONS: Our polynomial algorithm for checking consistency has been implemented in Python and is available at https://github.com/UdeM-LBIT/OrthoPara-ConstraintChecker .

We present a linear-time algorithm to compute a decomposition scheme for graphs G that have a set X ⊆ V ( G ), called a treewidth-modulator , such that the treewidth of G − X is bounded by a constant. Our decomposition, called a protrusion decomposition , is the cornerstone in obtaining the following two main results. Our first result is that any parameterized graph problem (with parameter k ) that has a finite integer index and such that Y es -instances have a treewidth-modulator of size O ( k ) admits a linear kernel on the class of H -topological-minor-free graphs, for any fixed graph H . This result partially extends previous meta-theorems on the existence of linear kernels on graphs of bounded genus and H -minor-free graphs. Let F be a fixed finite family of graphs containing at least one planar graph. Given an n -vertex graph G and a non-negative integer k , P lanar - F -D eletion asks whether G has a set X ⊆ V ( G ) such that | X | ⩽ k and G − X is H -minor-free for every H ϵ F . As our second application, we present the first single-exponential algorithm to solve P lanar - F -D eletion . Namely, our algorithm runs in time 2 O ( k ) · n 2 , which is asymptotically optimal with respect to k . So far, single-exponential algorithms were only known for special cases of the family F .

In this paper we design FPT-algorithms for two parameterized problems. The first is List Digraph Homomorphism: given two digraphs G and H and a list of allowed vertices of H for every vertex of G, the question is whether there exists a homomorphism from G to H respecting the list constraints. The second problem is a variant of Multiway Cut, namely Min-Max Multiway Cut: given a graph G, a non-negative integer l, and a set T of r terminals, the question is whether we can partition the vertices of G into r parts such that (a) each part contains one terminal and (b) there are at most l edges with only one endpoint in this part. We parameterize List Digraph Homomorphism by the number w of edges of G that are mapped to non-loop edges of H and we give a time 2^{O(l * log(h) + l^{2 * log(l)}} * n^{4} * log(n) algorithm, where h is the order of the host graph H.We also prove that Min-Max Multiway Cut can be solved in time 2^{O((l * r)^2 * log(l *r))} * n^{4} * log(n). Our approach introduces a general problem, called List Allocation, whose expressive power permits the design of parameterized reductions of both aforementioned problems to it. Then our results are based on an FPT-algorithm for the List Allocation problem that is designed using a suitable adaptation of the randomized contractions technique (introduced by [Chitnis, Cygan, Hajiaghayi, Pilipczuk, and Pilipczuk, FOCS 2012]).

Linear rankwidth is a linearized variant of rankwidth, introduced by Oum and Seymour [Approxi-mating clique-width and branch-width. J. Combin. Theory Ser. B, 96(4):514-528, 2006.], and it is similar to pathwidth, which is the linearized variant of treewidth. Motivated from the results on graph modification problems into graphs of bounded treewidth or pathwidth, we investigate a graph modification problem into the class of graphs having linear rankwidth at most one, called the Linear Rankwidth-1 Vertex Deletion (shortly, LRW1-Vertex Deletion). In this problem, given an n-vertex graph G and a positive integer k, we want to decide whether there is a set of at most k vertices whose removal turns G into a graph of linear rankwidth at most one and if one exists, find such a vertex set. While the meta-theorem of Courcelle, Makowsky, and Rotics implies that LRW1-Vertex Deletion can be solved in time f (k) · n 3 for some function f , it is not clear whether this problem allows a runtime with a modest exponential function. We establish that LRW1-Vertex Deletion can be solved in time 8 k · n O(1). The major obstacle to this end is how to handle a long induced cycle as an obstruction. To fix this issue, we define the necklace graphs and investigate their structural properties. We also show that the LRW1-Vertex Deletion has a polynomial kernel.

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-$\mathcal{F}$-Deletion on graphs excluding a fixed (topological) minor in the case where all the graphs in $\mathcal{F}$ are connected.

The Hadwiger number of a graph $G$ is the largest integer $h$ such that $G$ has the complete graph $K_h$ as a minor. We show that the problem of determining the Hadwiger number of a graph is \sf NP-hard on co-bipartite graphs but can be solved in polynomial time on cographs and on bipartite permutation graphs. We also consider a natural generalization of this problem that asks for the largest integer $h$ such that $G$ has a minor with $h$ vertices and diameter at most $s$. We show that this problem can be solved in polynomial time on AT-free graphs when $s\geq 2$ but is \sf NP-hard on chordal graphs for every fixed $s\geq 2$.

Several algorithmic meta-theorems on kernelization have appeared in the last years, starting with the result [Bodlaender et al., FOCS 2009] on graphs of bounded genus, then generalized by [Fomin et al., SODA 2010] to graphs excluding a fixed minor, and by [Kim et al., ICALP 2013] 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 CMSO 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.

The $c$-pumpkin is the graph with two vertices linked by $c \geq 1$ 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 $2^{\mathcal{O}(k)} n^{\mathcal{O}(1)}$ deciding, for any fixed $c \geq 1$, 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 $\mathcal{O}(\log n)$-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.

The Bipartite Contraction problem takes as input an $n$-vertex graph $G$ and an integer $k$, and the task is to determine whether we can obtain a bipartite graph from $G$ by a sequence of at most $k$ edge contractions. We show that Bipartite Contraction is fixed-parameter tractable when parameterized by $k$. Despite a strong resemblance between Bipartite Contraction and the classical Odd Cycle Transversal (OCT) problem, the methods developed to tackle OCT do not seem to be directly applicable to Bipartite Contraction. To obtain our result, we combine several techniques and concepts that are central in parameterized complexity: iterative compression, irrelevant vertices, and important separators. To the best of our knowledge, this is the first time the irrelevant vertex technique and the concept of important separators are applied in unison. Furthermore, our algorithm may serve as a comprehensible example of the usage of the irrelevant vertex technique.

We initiate the study of the Bipartite Contraction problem from the perspective of parameterized complexity. In this problem we are given a graph $G$ and an integer $k$, and the task is to determine whether we can obtain a bipartite graph from $G$ by a sequence of at most $k$ edge contractions. Our main result is an $f(k) n^{O(1)}$ time algorithm for Bipartite Contraction. Despite a strong resemblance between Bipartite Contraction and the classical Odd Cycle Transversal (OCT) problem, the methods developed to tackle OCT do not seem to be directly applicable to Bipartite Contraction. Our algorithm is based on a novel combination of the irrelevant vertex technique, introduced by Robertson and Seymour, and the concept of important separators. Both techniques have previously been used as key components of algorithms for fundamental problems in parameterized complexity. However, to the best of our knowledge, this is the first time the two techniques are applied in unison.

A tournament $T = (V,A)$ is a directed graph in which there is exactly one arc between every pair of distinct vertices. Given a digraph on $n$ vertices and an integer parameter $k$, the {\sc Feedback Arc Set} problem asks whether thegiven digraph has a set of $k$ arcs whose removal results in an acyclicdigraph. The {\sc Feedback Arc Set} problem restricted to tournaments is knownas the {\sc $k$-Feedback Arc Set in Tournaments ($k$-FAST)} problem. In thispaper we obtain a linear vertex kernel for \FAST{}. That is, we give apolynomial time algorithm which given an input instance $T$ to \FAST{} obtains an equivalent instance $T'$ on $O(k)$ vertices. In fact, given any fixed $\epsilon > 0$, the kernelized instance has at most $(2 + \epsilon)k$ vertices.Our result improves the previous known bound of $O(k^2)$ on the kernel size for\FAST{}. Our kernelization algorithm solves the problem on a subclass of tournaments in polynomial time and uses a known polynomial time approximation scheme for \FAST.

MOTIVATION: Developing methods for computing phylogenetic networks from biological data is an important problem posed by molecular evolution and much work is currently being undertaken in this area. Although promising approaches exist, there are no tools available that biologists could easily and routinely use to compute rooted phylogenetic networks on real datasets containing tens or hundreds of taxa. Biologists are interested in clades, i.e. groups of monophyletic taxa, and these are usually represented by clusters in a rooted phylogenetic tree. The problem of computing an optimal rooted phylogenetic network from a set of clusters, is hard, in general. Indeed, even the problem of just determining whether a given network contains a given cluster is hard. Hence, some researchers have focused on topologically restricted classes of networks, such as galled trees and level-k networks, that are more tractable, but have the practical draw-back that a given set of clusters will usually not possess such a representation. RESULTS: In this article, we argue that galled networks (a generalization of galled trees) provide a good trade-off between level of generality and tractability. Any set of clusters can be represented by some galled network and the question whether a cluster is contained in such a network is easy to solve. Although the computation of an optimal galled network involves successively solving instances of two different NP-complete problems, in practice our algorithm solves this problem exactly on large datasets containing hundreds of taxa and many reticulations in seconds, as illustrated by a dataset containing 279 prokaryotes. AVAILABILITY: We provide a fast, robust and easy-to-use implementation of this work in version 2.0 of our tree-handling software Dendroscope, freely available from http://www.dendroscope.org.

We present an algorithm with runtime $O(k^{2k}n^3m)$ for the following NP-complete problem [M. Garey and D. Johnson, Computers and Intractability: A Guide to the Theory of NP-Completeness, W. H. Freeman and Co., San Francisco, 1979, problem GT35]: Given an arbitrary graph G on n vertices and m edges, can we obtain an interval graph by adding at most k new edges to G? This resolves the long-standing open question [H. Kaplan, R. Shamir, and R. E. Tarjan, SIAM J. Comput., 28 (1999), pp. 1906–1922; R. G. Downey and M. R. Fellows, Parameterized Complexity, Springer-Verlag, New York, 1999; M. Serna and D. Thilikos, Bull. Eur. Assoc. Theory Comput. Sci. EATCS, 86 (2005), pp. 41–65; G. Gutin, S. Szeider, and A. Yeo, in Proceedings IWPEC 2006, Lecture Notes in Comput. Sci. 4169, Springer-Verlag, Berlin, 2006, pp. 60–71], first posed by Kaplan, Shamir, and Tarjan, of whether this problem was fixed parameter tractable. The problem has applications in profile minimization for sparse matrix computations [J. A. George and J. W. H. Liu, Computer Solution of Large Sparse Positive Definite Systems, Prentice-Hall, Englewood Cliffs, NJ, 1981; R. E. Tarjan, in Sparse Matrix Computations, J. R. Bunch and D. J. Rose, eds., Academic Press, 1976, pp. 3–22], and our results show tractability for the case of a small number k of zero elements in the envelope. Our algorithm performs bounded search among possible ways of adding edges to a graph to obtain an interval graph and combines this with a greedy algorithm when graphs of a certain structure are reached by the search.

Given a set of leaf-labeled trees with identical leaf sets, the well-known Maximum Agreement SubTree (MAST) problem consists in finding a subtree homeomorphically included in all input trees and with the largest number of leaves. MAST and its variant called Maximum Compatible Tree (MCT) are of particular interest in computational biology. This article presents a linear-time approximation algorithm to solve the complement version of MAST, namely identifying the smallest set of leaves to remove from input trees to obtain isomorphic trees. We also present an O ( n 2 + kn ) algorithm to solve the complement version of MCT. For both problems, we thus achieve significantly lower running times than previously known algorithms. Fast running times are especially important in phylogenetics where large collections of trees are routinely produced by resampling procedures, such as the nonparametric bootstrap or Bayesian MCMC methods.

Recently lexicographic breadth first search (LexBFS) has been shown to be a very powerful tool for the development of linear time, easily implementable recognition algorithms for various families of graphs. In this paper, we add to this work by producing a simple two LexBFS sweep algorithm to recognize the family of cographs. This algorithm extends to other related graph families such as $P_4$-reducible, $P_4$-sparse, and distance hereditary. It is an open question whether our cograph recognition algorithm can be extended to a similarly easy algorithm for modular decomposition.

A distance labeling scheme is a distributed graph representation that assigns labels to the vertices and enables answering distance queries between any pair $(x,y)$ of vertices by using only the labels of x and y. This paper presents an optimal distance labeling scheme with labels of $\mathcal{O}(\log n)$ bits for the n-vertex interval graphs family. It improves by $\log n$ factor the best known upper bound of [M. Katz, N. A. Katz, and D. Peleg, Distance labeling schemes for well-separated graph classes, in Proceedings of the 17th Annual Symposium on Theoretical Aspects of Computer Science, Lecture Notes in Comput. Sci. 1770, Springer-Verlag, Berlin, 2000, pp. 516–528]. Moreover, the scheme supports constant time distance queries, and if the interval representation of the input graph is given and the intervals are sorted, then the set of labels can be computed in $\mathcal{O}(n)$ time. Our result is tight as we show that the length of any label is at least $3\log n-\mathcal{O}(\log\log n)$ bits. This lower bound derives from a new estimator of the number of unlabeled n-vertex interval graphs, that is, $2^{\Omega(n \log n)}$. To our knowledge, interval graphs are thereby the first known nontrivial hereditary family with $2^{\Omega(n f(n))}$ unlabeled elements and with a distance labeling scheme with $f(n)$ bit labels.

We present an algorithm with runtime O(k(2k)n3 * m) for the following NP-complete problem: Given an arbitrary graph G on n vertices and m edges, can we obtain an interval graph by adding at most k new edges to G? This resolves the long-standing open question, first posed by Kaplan, Shamir and Tarjan, of whether this problem could be solved in time f(k) * n(O(1)).The problem has applications in Physical Mapping of DNA and in Profile Minimization for Sparse Matrix Computations. For the first application, our results show tractability for the case of a small number k of false negative errors, and for the second, a small number k of zero elements in the envelope.

We propose new algorithms for computing pairwise rearrangement scenarios that conserve the combinatorial structure of genomes. More precisely, we investigate the problem of sorting signed permutations by reversals without breaking common intervals. We describe a combinatorial framework for this problem that allows us to characterize classes of signed permutations for which one can compute, in polynomial time, a shortest reversal scenario that conserves all common intervals. In particular, we define a class of permutations for which this computation can be done in linear time with a very simple algorithm that does not rely on the classical Hannenhalli-Pevzner theory for sorting by reversals. We apply these methods to the computation of rearrangement scenarios between permutations obtained from 16 synteny blocks of the X chromosomes of the human, mouse, and rat.

We consider small world graphs as defined by Kleinberg (2000), i.e., graphs obtained from a d-dimensional mesh by adding links chosen at random according to the d-harmonic distribution. This model aims at giving formal support to the "six degrees of separation" between individuals experienced by Milgram (1967),and verified recently by Dodds, Muhamad, and Watts (2003). In particular, Kleinberg shows that greedy routing performs in O(log2n) expected number of steps in d-dimensional augmented meshes, with O(log2n) bits of topological awareness per node, for any constant d ≥ 1. We show that giving O(log2n) bits of topological awareness per node decreases the expected number of steps of greedy routing to O(log1+1/dn) in d-dimensional augmented meshes. We also show that, independently of the amount of topological awareness given to the nodes, greedy routing performs in Ω(log1+1/dn) expected number of steps. In particular, augmenting the topological awareness above this optimum of O(log2n) bits would drastically decrease the performances of greedy routing. Moreover, our model demonstrates that the efficiency of greedy routing is sensible to the "world's dimension", in the sense that high dimensional worlds enjoy faster greedy routing than low dimensional ones. This could not be observed in Kleinberg's model. In addition to bringing new light to Milgram's experiment, our protocol presents several desirable properties. In particular, it is totally oblivious i.e., there is no header modification along the path from the source to the target, and the routing decision depends only on the target, and on information stored locally at each node. Finally, our protocol can obviously be used for the design of DHTs, in the same spirit as Symphony (2003).