One-Way Trail Orientations
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Strongly Connected Component
Graph IV Ian Things that we would talk about ● DFS ● Tree ● Connectivity Useful website http://codeforces.com/blog/entry/16221 Recommended Practice Sites ● HKOJ ● Codeforces ● Topcoder ● Csacademy ● Atcoder ● USACO ● COCI Term in Directed Tree ● Consider node 4 – Node 2 is its parent – Node 1, 2 is its ancestors – Node 5 is its sibling – Node 6 is its child – Node 6, 7, 8 is its descendants ● Node 1 is the root DFS Forest ● When we do DFS on a graph, we would obtain a DFS forest. Noted that the graph is not necessarily a tree. ● Some of the information we get through the DFS is actually very useful, such as – Starting time of a node – Finishing time of a node – Parent of the node Some Tricks Using DFS Order ● Suppose vertex v is ancestor(not only parent) of u – Starting time of v < starting time of u – Finishing time of v > starting time of u ● st[v] < st[u] <= ft[u] < ft[v] ● O(1) to check if ancestor or not ● Flatten the tree to store subtree information(maybe using segment tree or other data structure to maintain) ● Super useful !!!!!!!!!! Partial Sum on Tree ● Given queries, each time increase all node from node v to node u by 1 ● Assume node v is ancestor of node u ● sum[u]++, sum[par[v]]-- ● Run dfs in root dfs(v) for all child u dfs(u) d[v] = d[v] + d[u] Types of Edges ● Tree edges – Edges that forms a tree ● Forward edges – Edges that go from a node to its descendants but itself is not a tree edge. -
CLRS B.4 Graph Theory Definitions Unit 1: DFS Informally, a Graph
CLRS B.4 Graph Theory Definitions Unit 1: DFS informally, a graph consists of “vertices” joined together by “edges,” e.g.,: example graph G0: 1 ···················•······························· ····························· ····························· ························· ···· ···· ························· ························· ···· ···· ························· ························· ···· ···· ························· ························· ···· ···· ························· ············· ···· ···· ·············· 2•···· ···· ···· ··· •· 3 ···· ···· ···· ···· ···· ··· ···· ···· ···· ···· ···· ···· ···· ···· ···· ···· ······· ······· ······· ······· ···· ···· ···· ··· ···· ···· ···· ···· ···· ··· ···· ···· ···· ···· ···· ···· ···· ···· ···· ···· ··············· ···· ···· ··············· 4•························· ···· ···· ························· • 5 ························· ···· ···· ························· ························· ···· ···· ························· ························· ···· ···· ························· ····························· ····························· ···················•································ 6 formally a graph is a pair (V, E) where V is a finite set of elements, called vertices E is a finite set of pairs of vertices, called edges if H is a graph, we can denote its vertex & edge sets as V (H) & E(H) respectively if the pairs of E are unordered, the graph is undirected if the pairs of E are ordered the graph is directed, or a digraph two vertices joined by an edge -
Graph Theory
1 Graph Theory “Begin at the beginning,” the King said, gravely, “and go on till you come to the end; then stop.” — Lewis Carroll, Alice in Wonderland The Pregolya River passes through a city once known as K¨onigsberg. In the 1700s seven bridges were situated across this river in a manner similar to what you see in Figure 1.1. The city’s residents enjoyed strolling on these bridges, but, as hard as they tried, no residentof the city was ever able to walk a route that crossed each of these bridges exactly once. The Swiss mathematician Leonhard Euler learned of this frustrating phenomenon, and in 1736 he wrote an article [98] about it. His work on the “K¨onigsberg Bridge Problem” is considered by many to be the beginning of the field of graph theory. FIGURE 1.1. The bridges in K¨onigsberg. J.M. Harris et al., Combinatorics and Graph Theory , DOI: 10.1007/978-0-387-79711-3 1, °c Springer Science+Business Media, LLC 2008 2 1. Graph Theory At first, the usefulness of Euler’s ideas and of “graph theory” itself was found only in solving puzzles and in analyzing games and other recreations. In the mid 1800s, however, people began to realize that graphs could be used to model many things that were of interest in society. For instance, the “Four Color Map Conjec- ture,” introduced by DeMorgan in 1852, was a famous problem that was seem- ingly unrelated to graph theory. The conjecture stated that four is the maximum number of colors required to color any map where bordering regions are colored differently. -
Vizing's Theorem and Edge-Chromatic Graph
VIZING'S THEOREM AND EDGE-CHROMATIC GRAPH THEORY ROBERT GREEN Abstract. This paper is an expository piece on edge-chromatic graph theory. The central theorem in this subject is that of Vizing. We shall then explore the properties of graphs where Vizing's upper bound on the chromatic index is tight, and graphs where the lower bound is tight. Finally, we will look at a few generalizations of Vizing's Theorem, as well as some related conjectures. Contents 1. Introduction & Some Basic Definitions 1 2. Vizing's Theorem 2 3. General Properties of Class One and Class Two Graphs 3 4. The Petersen Graph and Other Snarks 4 5. Generalizations and Conjectures Regarding Vizing's Theorem 6 Acknowledgments 8 References 8 1. Introduction & Some Basic Definitions Definition 1.1. An edge colouring of a graph G = (V; E) is a map C : E ! S, where S is a set of colours, such that for all e; f 2 E, if e and f share a vertex, then C(e) 6= C(f). Definition 1.2. The chromatic index of a graph χ0(G) is the minimum number of colours needed for a proper colouring of G. Definition 1.3. The degree of a vertex v, denoted by d(v), is the number of edges of G which have v as a vertex. The maximum degree of a graph is denoted by ∆(G) and the minimum degree of a graph is denoted by δ(G). Vizing's Theorem is the central theorem of edge-chromatic graph theory, since it provides an upper and lower bound for the chromatic index χ0(G) of any graph G. -
Superposition and Constructions of Graphs Without Nowhere-Zero K-flows
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Europ. J. Combinatorics (2002) 23, 281–306 doi:10.1006/eujc.2001.0563 Available online at http://www.idealibrary.com on Superposition and Constructions of Graphs Without Nowhere-zero k-flows M ARTIN KOCHOL Using multi-terminal networks we build methods on constructing graphs without nowhere-zero group- and integer-valued flows. In this way we unify known constructions of snarks (nontrivial cubic graphs without edge-3-colorings, or equivalently, without nowhere-zero 4-flows) and provide new ones in the same process. Our methods also imply new complexity results about nowhere-zero flows in graphs and state equivalences of Tutte’s 3- and 5-flow conjectures with formally weaker statements. c 2002 Elsevier Science Ltd. All rights reserved. 1. INTRODUCTION Nowhere-zero flows in graphs have been introduced by Tutte [38–40]. Primarily he showed that a planar graph is face-k-colorable if and only if it admits a nowhere-zero k-flow (its edges can be oriented and assigned values ±1,..., ±(k − 1) so that the sum of the incoming values equals the sum of the outcoming ones for every vertex of the graph). Tutte also proved the classical equivalence result that a graph admits a nowhere-zero k-flow if and only if it admits a flow whose values are the nonzero elements of a finite abelian group of order k. Seymour [35] has proved that every bridgeless graph admits a nowhere-zero 6-flow, thereby improving the 8-flow theorem of Jaeger [16] and Kilpatrick [20]. -
Finding Articulation Points and Bridges Articulation Points Articulation Point
Finding Articulation Points and Bridges Articulation Points Articulation Point Articulation Point A vertex v is an articulation point (also called cut vertex) if removing v increases the number of connected components. A graph with two articulation points. 3 / 1 Articulation Points Given I An undirected, connected graph G = (V; E) I A DFS-tree T with the root r Lemma A DFS on an undirected graph does not produce any cross edges. Conclusion I If a descendant u of a vertex v is adjacent to a vertex w, then w is a descendant or ancestor of v. 4 / 1 Removing a Vertex v Assume, we remove a vertex v 6= r from the graph. Case 1: v is an articulation point. I There is a descendant u of v which is no longer reachable from r. I Thus, there is no edge from the tree containing u to the tree containing r. Case 2: v is not an articulation point. I All descendants of v are still reachable from r. I Thus, for each descendant u, there is an edge connecting the tree containing u with the tree containing r. 5 / 1 Removing a Vertex v Problem I v might have multiple subtrees, some adjacent to ancestors of v, and some not adjacent. Observation I A subtree is not split further (we only remove v). Theorem A vertex v is articulation point if and only if v has a child u such that neither u nor any of u's descendants are adjacent to an ancestor of v. Question I How do we determine this efficiently for all vertices? 6 / 1 Detecting Descendant-Ancestor Adjacency Lowpoint The lowpoint low(v) of a vertex v is the lowest depth of a vertex which is adjacent to v or a descendant of v. -
Strong Subgraph Connectivity of Digraphs: a Survey
Strong Subgraph Connectivity of Digraphs: A Survey Yuefang Sun1 and Gregory Gutin2 1 Department of Mathematics, Shaoxing University Zhejiang 312000, P. R. China, [email protected] 2 School of Computer Science and Mathematics Royal Holloway, University of London Egham, Surrey, TW20 0EX, UK, [email protected] Abstract In this survey we overview known results on the strong subgraph k- connectivity and strong subgraph k-arc-connectivity of digraphs. After an introductory section, the paper is divided into four sections: basic results, algorithms and complexity, sharp bounds for strong subgraph k-(arc-)connectivity, minimally strong subgraph (k,ℓ)-(arc-) connected digraphs. This survey contains several conjectures and open problems for further study. Keywords: Strong subgraph k-connectivity; Strong subgraph k-arc- connectivity; Subdigraph packing; Directed q-linkage; Directed weak q-linkage; Semicomplete digraphs; Symmetric digraphs; Generalized k- connectivity; Generalized k-edge-connectivity. AMS subject classification (2010): 05C20, 05C35, 05C40, 05C70, 05C75, 05C76, 05C85, 68Q25, 68R10. 1 Introduction arXiv:1808.02740v1 [cs.DM] 8 Aug 2018 The generalized k-connectivity κk(G) of a graph G = (V, E) was intro- duced by Hager [14] in 1985 (2 ≤ k ≤ |V |). For a graph G = (V, E) and a set S ⊆ V of at least two vertices, an S-Steiner tree or, simply, an S-tree is a subgraph T of G which is a tree with S ⊆ V (T ). Two S-trees T1 and T2 are said to be edge-disjoint if E(T1) ∩ E(T2)= ∅. Two edge-disjoint S-trees T1 and T2 are said to be internally disjoint if V (T1) ∩ V (T2)= S. -
Shattering, Graph Orientations, and Connectivity
Shattering, Graph Orientations, and Connectivity [Extended Abstract] László Kozma Shay Moran Saarland University Max Planck Institute for Informatics Saarbrücken, Germany Saarbrücken, Germany [email protected] [email protected] ABSTRACT ing orientations with forbidden subgraphs. These problems We present a connection between two seemingly disparate have close ties with the theory of random graphs. An exam- fields: VC-theory and graph theory. This connection yields ple of work of this type is the paper of Alon and Yuster [4], natural correspondences between fundamental concepts in concerned with the number of orientations that do not con- VC-theory, such as shattering and VC-dimension, and well- tain a copy of a fixed tournament. studied concepts of graph theory related to connectivity, combinatorial optimization, forbidden subgraphs, and oth- In this paper we prove statements concerning properties of ers. orientations and subgraphs of a given graph by introducing a connection between VC-theory and graph theory. The In one direction, we use this connection to derive results following are a few examples of the statements that we prove: in graph theory. Our main tool is a generalization of the Sauer-Shelah Lemma [30, 10, 12]. Using this tool we obtain 1. Let G be a graph. Then: a series of inequalities and equalities related to properties of orientations of a graph. Some of these results appear to be the number the number the number of connected of strong of 2-edge- new, for others we give new and simple proofs. ≥ ≥ subgraphs orientations connected In the other direction, we present new illustrative examples of G of G subgraphs of G. -
Incremental 2-Edge-Connectivity in Directed Graphs
Incremental 2-Edge-Connectivity In Directed Graphs Loukas Georgiadis Giuseppe F. Italiano Nikos Parotsidis University of Ioannina University of Rome University of Rome Greece Tor Vergata Tor Vergata Italy Italy ICALP 2016, Rome Outline Definitions • 2-edge-connectivity in undirected graphs • 2-edge-connectivity in directed graphs • Problem definition • Known algorithm and our result High-level idea Basic ingredients • Dominators • Auxiliary components Tools Conclusion ICALP 2016, Rome Outline Definitions • 2-edge-connectivity in undirected graphs • 2-edge-connectivity in directed graphs • Problem definition • Known algorithm and our result High-level idea Basic ingredients • Dominators • Auxiliary components Tools Conclusion ICALP 2016, Rome Undirected: Connected components Let 퐺 = (푉, 퐸) be a undirected graph. • 퐺 is connected if there is a path between any two vertices. • The connected components of 퐺 are its maximal connected subgraphs. ICALP 2016, Rome Undirected: Connected components Let 퐺 = (푉, 퐸) be a connected undirected graph. • An edge is a bridge, if its removal increases the number of connected components. ICALP 2016, Rome Undirected: Connected components Let 퐺 = (푉, 퐸) be a connected undirected graph. • An edge is a bridge, if its removal increases the number of connected components. ICALP 2016, Rome Undirected: Connected components By Menger’s theorem, two vertices are 2-edge- connected iff the removal of any bridge leaves them in the same connected component. ICALP 2016, Rome Undirected: Connected components By Menger’s theorem, two vertices are 2-edge- connected iff the removal of any bridge leaves them in the same connected component. ICALP 2016, Rome Undirected: Connected components By Menger’s theorem, two vertices are 2-edge- connected iff the removal of any bridge leaves them in the same connected component. -
Graph Theory (Connected Graphs)
Graph Theory (Connected Graphs) Dr. Shubh N. Singh Department of Mathematics Central University of South Bihar May 14, 2020 2 Lecture-01: 0.1 Walks, Paths, and Cycles Let G = (V; E). If we think of the vertices of G as locations and the edges of G as roads between certain pairs of locations, then the graph G can be considered as modeling some community. There is a variety of kinds of trips that can be taken in the community. Let's start at some vertex u of a graph G. If we proceed from u to a neighbor v of u and then to a neighbor of v and so on, until we finally come to a stop at a vertex w, then we have just described a walk from u to v in G. More formally, Definition 0.1.1. Let G = (V; E), and let u; v 2 V .A walk from u to v (in short, a u − v walk) in G is a nonempty finite sequence/list u = v0; v1; : : : ; vk = v of vertices in G, where k ≥ 0 and fvi; vi+1g 2 E for all i = 0; 1; 2; : : : ; k − 1. If the vertices in a walk are all distinct, we call it a path in G. Note that all vertices or edges lie on (or, belong to ) a u − v walk need not be distinct; in fact u and v are not required to be distinct. Provided we continue to proceed from a vertex to one of its neighbors (and eventually stop), there is essentially no condi- tions on a walk in a graph. -
One-Way Trail Orientations
One-wasy trail orientation Aamand, Anders; Hjuler, Niklas; Holm, Jacob; Rotenberg, Eva Published in: 45th International Colloquium on Automata, Languages, and Programming, ICALP 2018 DOI: 10.4230/LIPIcs.ICALP.2018.6 Publication date: 2018 Document version Publisher's PDF, also known as Version of record Document license: CC BY Citation for published version (APA): Aamand, A., Hjuler, N., Holm, J., & Rotenberg, E. (2018). One-wasy trail orientation. In C. Kaklamanis, D. Marx, I. Chatzigiannakis, & D. Sannella (Eds.), 45th International Colloquium on Automata, Languages, and Programming, ICALP 2018 [6] Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik. Leibniz International Proceedings in Informatics, LIPIcs Vol. 107 https://doi.org/10.4230/LIPIcs.ICALP.2018.6 Download date: 26. Sep. 2021 One-Way Trail Orientations Anders Aamand1 University of Copenhagen, Copenhagen, Denmark [email protected] https://orcid.org/0000-0002-0402-0514 Niklas Hjuler2 University of Copenhagen, Copenhagen, Denmark [email protected] https://orcid.org/0000-0002-0815-670X Jacob Holm3 University of Copenhagen, Copenhagen, Denmark [email protected] https://orcid.org/0000-0001-6997-9251 Eva Rotenberg4 Technical University of Denmark, Lyngby, Denmark [email protected] https://orcid.org/0000-0001-5853-7909 Abstract Given a graph, does there exist an orientation of the edges such that the resulting directed graph is strongly connected? Robbins’ theorem [Robbins, Am. Math. Monthly, 1939] asserts that such an orientation exists if and only if the graph is 2-edge connected. A natural extension of this problem is the following: Suppose that the edges of the graph are partitioned into trails. Can the trails be oriented consistently such that the resulting directed graph is strongly connected? We show that 2-edge connectivity is again a sufficient condition and we provide a linear time algorithm for finding such an orientation. -
NOWHERE-ZERO K-FLOWS on GRAPHS Let G = (V,E) Be a Graph
NOWHERE-ZERO ~k-FLOWS ON GRAPHS MATTHIAS BECK, ALYSSA CUYJET, GORDON ROJAS KIRBY, MOLLY STUBBLEFIELD, AND MICHAEL YOUNG Abstract. We introduce and study a multivariate function that counts nowhere-zero flows on a graph G, in which each edge of G has an individual capacity. We prove that the associated counting function is a piecewise-defined polynomial in these capacities, which satisfy a combinatorial reciprocity law that incorporates totally cyclic orientations of G. Let G = (V; E) be a graph, which we allow to have multiple edges. Fix an orientation of G, i.e., for each edge e = uv 2 E we assign one of u and v to be the head h(e) and the other to be the tail t(e) of e.A flow on (this orientation of) G is a labeling x 2 AE of the edges of G with values in an Abelian group A such that for every node v 2 V , X X xe = xe ; h(e)=v t(e)=v i.e., we have conservation of flow at each node. We are interested in counting such flows that are nowhere zero, i.e., xe 6= 0 for every edge e 2 E. The case A = Zk goes back to Tutte [11], who proved that the number '(k) of nowhere-zero Zk-flows is a polynomial in k. (Tutte introduced this counting function as a dual concept to the chromatic polynomial.) In the case A = Z, a k-flow takes on integer values in {−k + 1; : : : ; k − 1g. The fact that the number '(k) of nowhere-zero k-flows is also a polynomial in k is due to Kochol [7].