Subexponential Parameterized Algorithms for Planar and Apex-Minor-Free Graphs via Low Treewidth Pattern Covering

We prove the following theorem. Given a planar graph $G$ and an integer $k$, it is possible in polynomial time to randomly sample a subset $A$ of vertices of $G$ with the following properties: (i) $A$ induces a subgraph of $G$ of treewidth $\mathcal{O}(\sqrt{k}\log k)$, and (ii) for every connected subgraph $H$ of $G$ on at most $k$ vertices, the probability that $A$ covers the whole vertex set of $H$ is at least $(2^{\mathcal{O}(\sqrt{k}\log^2 k)}\cdot n^{\mathcal{O}(1)})^{-1}$, where $n$ is the number of vertices of $G$. Together with standard dynamic programming techniques for graphs of bounded treewidth, this result gives a versatile technique for obtaining (randomized) subexponential parameterized algorithms for problems on planar graphs, usually with running time bound $2^{\mathcal{O}(\sqrt{k} \log^2 k)} n^{\mathcal{O}(1)}$. The technique can be applied to problems expressible as searching for a small, connected pattern with a prescribed property in a large host graph, examples of such problems include Directed $k$-Path, Weighted $k$-Path, Vertex Cover Local Search, and Subgraph Isomorphism, among others. Up to this point, it was open whether these problems can be solved in subexponential parameterized time on planar graphs, because they are not amenable to the classic technique of bidimensionality. Furthermore, all our results hold in fact on any class of graphs that exclude a fixed apex graph as a minor, in particular on graphs embeddable in any fixed surface

Scalable Parameterised Algorithms for two Steiner Problems

In the Steiner Problem, we are given as input (i) a connected graph with nonnegative integer weights associated with the edges; and (ii) a subset of vertices called terminals. The task is to find a minimum-weight subgraph connecting all the terminals. In the Group Steiner Problem, we are given as input (i) a connected graph with nonnegative integer weights associated with the edges; and (ii) a collection of subsets of vertices called groups. The task is to find a minimum-weight subgraph that contains at least one vertex from each group. Even though the Steiner Problem and the Group Steiner Problem are NP-complete, they are known to admit parameterised algorithms that run in linear time in the size of the input graph and the exponential part can be restricted to the number of terminals and the number of groups, respectively. In this thesis, we discuss two parameterised algorithms for solving the Steiner Problem, and by reduction, the Group Steiner Problem: (a) a dynamic programming algorithm presented by Dreyfus and Wagner in 1971; and (b) an improvement of the Dreyfus-Wagner algorithm presented by Erickson, Monma and Veinott in 1987 that runs in linear time in the size of the input graph. We develop a parallel implementation of the Erickson-Monma-Veinott algorithm, and carry out extensive experiments to study the scalability of our implementation with respect to its runtime, memory bandwidth, and memory usage. Our experimental results demonstrate that the implementation can scale up to a billion edges on a single modern compute node provided that the number of terminals is small. For example, using our parallel implementation a Steiner tree for a graph with hundred million edges and ten terminals can be found in approximately twenty minutes. For an input graph with one hundred million edges and ten terminals, our parallel implementation is at least fifteen times faster than its serial counterpart on a Haswell compute node with two processors and twelve cores in each processor. Our implementation of the Erickson-Monma-Veinott algorithm is available as open source

Exact bosonization of the Ising model

We present exact combinatorial versions of bosonization identities, which equate the product of two Ising correlators with a free field (bosonic) correlator. The role of the discrete free field is played by the height function of an associated bipartite dimer model. Some applications to the asymptotic analysis of Ising correlators are discussed.Comment: 35 page

Proceedings of the 8th Cologne-Twente Workshop on Graphs and Combinatorial Optimization

International audienceThe Cologne-Twente Workshop (CTW) on Graphs and Combinatorial Optimization started off as a series of workshops organized bi-annually by either Köln University or Twente University. As its importance grew over time, it re-centered its geographical focus by including northern Italy (CTW04 in Menaggio, on the lake Como and CTW08 in Gargnano, on the Garda lake). This year, CTW (in its eighth edition) will be staged in France for the first time: more precisely in the heart of Paris, at the Conservatoire National d’Arts et Métiers (CNAM), between 2nd and 4th June 2009, by a mixed organizing committee with members from LIX, Ecole Polytechnique and CEDRIC, CNAM

Non-abelian Quantum Statistics on Graphs

We show that non-abelian quantum statistics can be studied using certain topological invariants which are the homology groups of configuration spaces. In particular, we formulate a general framework for describing quantum statistics of particles constrained to move in a topological space $X$. The framework involves a study of isomorphism classes of flat complex vector bundles over the configuration space of $X$ which can be achieved by determining its homology groups. We apply this methodology for configuration spaces of graphs. As a conclusion, we provide families of graphs which are good candidates for studying simple effective models of anyon dynamics as well as models of non-abelian anyons on networks that are used in quantum computing. These conclusions are based on our solution of the so-called universal presentation problem for homology groups of graph configuration spaces for certain families of graphs.Comment: 50 pages, v3: updated to reflect the published version. Commun. Math. Phys. (2019

Online assessment of graph theory

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University London.The objective of this thesis is to establish whether or not online, objective questions in elementary graph theory can be written in a way that exploits the medium of computer-aided assessment. This required the identification and resolution of question design and programming issues. The resulting questions were trialled to give an extensive set of answer files which were analysed to identify whether computer delivery affected the questions in any adverse ways and, if so, to identify practical ways round these issues. A library of questions spanning commonly-taught topics in elementary graph theory has been designed, programmed and added to the graph theory topic within an online assessment and learning tool used at Brunel University called Mathletics. Distracters coded into the questions are based on errors students are likely to make, partially evidenced by final examination scripts. Questions were provided to students in Discrete Mathematics modules with an extensive collection of results compiled for analysis. Questions designed for use in practice environments were trialled on students from 2007 – 2008 and then from 2008 to 2014 inclusive under separate testing conditions. Particular focus is made on the relationship of facility and discrimination between comparable questions during this period. Data is grouped between topic and also year group for the 2008 – 2014 tests, namely 2008 to 2011 and 2011 to 2014, so that it may then be determined what factors, if any, had an effect on the overall results for these questions. Based on the analyses performed, it may be concluded that although CAA questions provide students with a means for improving their learning in this field of mathematics, what makes a question more challenging is not solely based on the number of ways a student can work out his/her solution but also on several other factors that depend on the topic itself