Eindhoven University of Technology BACHELOR on the K-Independent
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The Unit Distance Graph Problem and Equivalence Relations
Math/CCS 103 Professor: Padraic Bartlett Lecture 11: The Unit Distance Graph Week 8 UCSB 2014 (Source: \The Mathematical Coloring Book," by Alexander Soifer.) 1 The Unit Distance Graph Problem 2 Definition. Consider the following method for turning R into a graph: 2 • Vertices: all points in R . • Edges: connect any two points (a; b) and (c; d) iff the distance between them is exactly 1. This graph is called the unit distance graph. Visualizing this is kinda tricky | it's got an absolutely insane number of vertices and edges. However, we can ask a question about it: Question. How many colors do we need in order to create a proper coloring of the unit distance graph? So: the answer isn't immediately obvious (right?) Instead, what we're going to try to do is just bound the possible answers, to get an idea of what the answers might be. How can we even bound such a thing? Well: to get a lower bound, it suffices to consider finite graphs G that we can draw in the plane using only straight edges of length 1. Because 2 our graph on R must contain any such graph \inside" of itself, examining these graphs will give us some easy lower bounds! So, by examining a equilateral triangle T , which has χ(T ) = 3, we can see that 2 χ(R ) ≥ 3: This is because it takes three colors to color an equilateral triangle's vertices in such a way that no edge has two endpoints of the same color. Similarly, by examining the following pentagonal construction (called a Moser spindle,) 1 we can actually do one better and say that 2 χ(R ) ≥ 4: Verify for yourself that you can't color this graph with three colors! 2 Conversely: to exhibit an upper bound on χ(R ) of k, it suffices to create a way of \painting" the plane with k-colors in such a way that no two points distance 1 apart get the same color. -
A New Approach to the Snake-In-The-Box Problem
462 ECAI 2012 Luc De Raedt et al. (Eds.) © 2012 The Author(s). This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License. doi:10.3233/978-1-61499-098-7-462 A New Approach to the Snake-In-The-Box Problem David Kinny1 Abstract. The “Snake-In-The-Box” problem, first described more Research on the SIB problem initially focused on applications in than 50 years ago, is a hard combinatorial search problem whose coding [14]. Coils are spread-k circuit codes for k =2, in which solutions have many practical applications. Until recently, techniques n-words k or more positions apart in the code differ in at least k based on Evolutionary Computation have been considered the state- bit positions [12]. (The well-known Gray codes are spread-1 circuit of-the-art for solving this deterministic maximization problem, and codes.) Longest snakes and coils provide the maximum number of held most significant records. This paper reviews the problem and code words for a given word size (i.e., hypercube dimension). prior solution techniques, then presents a new technique, based on A related application is in encoding schemes for analogue-to- Monte-Carlo Tree Search, which finds significantly better solutions digital converters including shaft (rotation) encoders. Longest SIB than prior techniques, is considerably faster, and requires no tuning. codes provide greatest resolution, and single bit errors are either recognised as such or map to an adjacent codeword causing an off- 1 INTRODUCTION by-one error. -
Degree in Mathematics
Degree in Mathematics Title: An Experimental Study of the Minimum Linear Colouring Arrangement Problem. Author: Montserrat Brufau Vidal Advisor: Maria José Serna Iglesias Department: Computer Science Department Academic year: 2016-2017 ii An experimental study of the Minimum Linear Colouring Arrangement Problem Author: Montserrat Brufau Vidal Advisor: Maria Jos´eSerna Iglesias Facultat de Matem`atiquesi Estad´ıstica Universitat Polit`ecnicade Catalunya 26th June 2017 ii Als meus pares; a la Maria pel seu suport durant el projecte; al meu poble, Men`arguens. iii iv Abstract The Minimum Linear Colouring Arrangement problem (MinLCA) is a variation from the Min- imum Linear Arrangement problem (MinLA) and the Colouring problem. The objective of the MinLA problem is finding the best way of labelling each vertex of a graph in such a manner that the sum of the induced distances between two adjacent vertices is the minimum. In our case, instead of labelling each vertex with a different integer, we group them with the condition that two adjacent vertices cannot be in the same group, or equivalently, by allowing the vertex labelling to be a proper colouring of the graph. In this project, we undertake the task of broadening the previous studies for the MinLCA problem. The main goal is developing some exact algorithms based on backtracking and some heuristic algorithms based on a maximal independent set approach and testing them with dif- ferent instances of graph families. As a secondary goal we are interested in providing theoretical results for particular graphs. The results will be made available in a simple, open-access bench- marking platform. -
The Snake-In-The-Box Problem: a Primer
THE SNAKE-IN-THE-BOX PROBLEM: A PRIMER by THOMAS E. DRAPELA (Under the Direction of Walter D. Potter) ABSTRACT This thesis is a primer designed to introduce novice and expert alike to the Snake-in-the- Box problem (SIB). Using plain language, and including explanations of prerequisite concepts necessary for understanding SIB throughout, it introduces the essential concepts of SIB, its origin, evolution, and continued relevance, as well as methods for representing, validating, and evaluating snake and coil solutions in SIB search. Finally, it is structured to serve as a convenient reference for those exploring SIB. INDEX WORDS: Snake-in-the-Box, Coil-in-the-Box, Hypercube, Snake, Coil, Graph Theory, Constraint Satisfaction, Canonical Ordering, Canonical Form, Equivalence Class, Disjunctive Normal Form, Conjunctive Normal Form, Heuristic Search, Fitness Function, Articulation Points THE SNAKE-IN-THE-BOX PROBLEM: A PRIMER by THOMAS E. DRAPELA B.A., George Mason University, 1991 A Thesis Submitted to the Graduate Faculty of The University of Georgia in Partial Fulfillment of the Requirements for the Degree MASTER OF SCIENCE ATHENS, GEORGIA 2015 © 2015 Thomas E. Drapela All Rights Reserved THE SNAKE-IN-THE-BOX PROBLEM: A PRIMER by THOMAS E. DRAPELA Major Professor: Walter D. Potter Committee: Khaled Rasheed Pete Bettinger Electronic Version Approved: Julie Coffield Interim Dean of the Graduate School The University of Georgia May 2015 DEDICATION To my dearest Kristin: For loving me enough to give me a shove. iv ACKNOWLEDGEMENTS I wish to express my deepest gratitude to Dr. Potter for introducing me to the Snake-in-the-Box problem, for giving me the freedom to get lost in it, and finally, for helping me to find my way back. -
SAT Approach for Decomposition Methods
SAT Approach for Decomposition Methods DISSERTATION submitted in partial fulfillment of the requirements for the degree of Doktorin der Technischen Wissenschaften by M.Sc. Neha Lodha Registration Number 01428755 to the Faculty of Informatics at the TU Wien Advisor: Prof. Stefan Szeider Second advisor: Prof. Armin Biere The dissertation has been reviewed by: Daniel Le Berre Marijn J. H. Heule Vienna, 31st October, 2018 Neha Lodha Technische Universität Wien A-1040 Wien Karlsplatz 13 Tel. +43-1-58801-0 www.tuwien.ac.at Erklärung zur Verfassung der Arbeit M.Sc. Neha Lodha Favoritenstrasse 9, 1040 Wien Hiermit erkläre ich, dass ich diese Arbeit selbständig verfasst habe, dass ich die verwen- deten Quellen und Hilfsmittel vollständig angegeben habe und dass ich die Stellen der Arbeit – einschließlich Tabellen, Karten und Abbildungen –, die anderen Werken oder dem Internet im Wortlaut oder dem Sinn nach entnommen sind, auf jeden Fall unter Angabe der Quelle als Entlehnung kenntlich gemacht habe. Wien, 31. Oktober 2018 Neha Lodha iii Acknowledgements First and foremost, I would like to thank my advisor Prof. Stefan Szeider for guiding me through my journey as a Ph.D. student with his patience, constant motivation, and immense knowledge. His guidance helped me during the time of research and writing of this thesis. I could not have imagined having a better advisor and mentor. Next, I would like to thank my co-advisor Prof. Armin Biere, my reviewers, Prof. Daniel Le Berre and Dr. Marijn Heule, and my Ph.D. committee, Prof. Reinhard Pichler and Prof. Florian Zuleger, for their insightful comments, encouragement, and patience. -
An Archive of All Submitted Project Proposals
CS 598 JGE ] Fall 2017 One-Dimensional Computational Topology Project Proposals Theory 0 Bhuvan Venkatesh: embedding graphs into hypercubes ....................... 1 Brendan Wilson: anti-Borradaile-Klein? .................................. 4 Charles Shang: vertex-disjoint paths in planar graphs ......................... 6 Hsien-Chih Chang: bichromatic triangles in pseudoline arrangements ............. 9 Sameer Manchanda: one more shortest-path tree in planar graphs ............... 11 Implementation 13 Jing Huang: evaluation of image segmentation algorithms ..................... 13 Shailpik Roy: algorithm visualization .................................... 15 Qizin (Stark) Zhu: evaluation of r-division algorithms ........................ 17 Ziwei Ba: algorithm visualization ....................................... 20 Surveys 22 Haizi Yu: topological music analysis ..................................... 22 Kevin Hong: topological data analysis .................................... 24 Philip Shih: planarity testing algorithms .................................. 26 Ross Vasko: planar graph clustering ..................................... 28 Yasha Mostofi: image processing via maximum flow .......................... 31 CS 598JGE Project Proposal Name and Netid: Bhuvan Venkatesh: bvenkat2 Introduction Embedding arbitrary graphs into Hypercubes has been the study of research for many practical implementation purposes such as interprocess communication or resource. A hypercube graph is any graph that has a set of 2d vertexes and all the vertexes are -
Connectivity 1
Ma/CS 6b Class 5: Graph Connectivity By Adam Sheffer A Connectivity Problem Prove. The vertices of a connected graph 퐺 can always be ordered as 푣1, 푣2, … , 푣푛 such that for every 1 < 푖 ≤ 푛, if we remove 푣푖, 푣푖+1, … , 푣푛 and the edges adjacent to these vertices, 퐺 remains connected. 푣3 푣4 푣1 푣2 푣5 Proof Pick any vertex as 푣1. Pick a vertex that is connected to 푣1 in 퐺 and set it as 푣2. Pick a vertex that is connected either to 푣1 or to 푣2 in 퐺 and set it as 푣3. … Communications Network We are given a set of routers and wish to connect pairs of them to obtain a connected communications network. The network should be reliable – a few malfunctioning routers should not disable the entire network. ◦ What condition should we require from the network? ◦ That after removing any 푘 routers, the network remains connected. 푘-connected Graphs An graph 퐺 = (푉, 퐸) is said to be 푘- connected if 푉 > 푘 and we cannot obtain a non-connected graph by removing 푘 − 1 vertices from 푉. Is the graph in the figure ◦ 1-connected? Yes. ◦ 2-connected? Yes. ◦ 3-connected? No! Connectivity Which graphs are 1-connected? ◦ These are exactly the connected graphs. The connectivity of a graph 퐺 is the maximum integer 푘 such that 퐺 is 푘- connected. What is the connectivity of the complete graph 퐾푛? 푛 − 1. The graph in the figure has a connectivity of 2. Hypercube A hypercube is a generalization of the cube into any dimension. -
A Proof of Tomescu's Graph Coloring Conjecture
A proof of Tomescu’s graph coloring conjecture Jacob Fox,∗ Xiaoyu He,† Freddie Manners‡ October 23, 2018 Abstract In 1971, Tomescu conjectured that every connected graph G on n vertices with chromatic number n−k k ≥ 4 has at most k!(k − 1) proper k-colorings. Recently, Knox and Mohar proved Tomescu’s conjecture for k = 4 and k = 5. In this paper, we complete the proof of Tomescu’s conjecture for all k ≥ 4, and show that equality occurs if and only if G is a k-clique with trees attached to each vertex. 1 Introduction Let k be a positive integer and G = (V, E) be a graph1.A proper k-coloring, or simply a k-coloring, of G is a function c : V → [k] (here [k] = {1, . , k}) such that c(u) 6= c(v) whenever uv ∈ E. The chromatic number χ(G) is the minimum k for which there exists a k-coloring of G. Let PG(k) denote the number of k-colorings of G. This function is a polynomial in k and is thus called the chromatic polynomial of G. In 1912, Birkhoff [5] introduced the chromatic polynomial for planar graphs in an attempt to solve the Four Color Problem using tools from analysis. The chromatic polynomial was later defined and studied for general graphs by Whitney [41]. Despite a great deal of attention over the past century, our understanding of the chromatic polynomial is still quite poor. In particular, proving general bounds on the chromatic polynomial remains a major challenge. The first result of this type, due to Birkhoff [6], states that n−3 PG(k) ≥ k(k − 1)(k − 2)(k − 3) for any planar graph G on n vertices and any real number k ≥ 5. -
Layout Volumes of the Hypercube∗
Layout Volumes of the Hypercube¤ Lubomir Torok Institute of Mathematics and Computer Science Severna 5, 974 01 Banska Bystrica, Slovak Republic Imrich Vrt'o Department of Informatics Institute of Mathematics, Slovak Academy of Sciences Dubravska 9, 841 04 Bratislava, Slovak Republic Abstract We study 3-dimensional layouts of the hypercube in a 1-active layer and general model. The problem can be understood as a graph drawing problem in 3D space and was addressed at Graph Drawing 2003 [5]. For both models we prove general lower bounds which relate volumes of layouts to a graph parameter cutwidth. Then we propose tight bounds on volumes of layouts of N-vertex hypercubes. Especially, we 2 3 3 have VOL (Q ) = N 2 log N + O(N 2 ); for even log N and VOL(Q ) = p 1¡AL log N 3 log N 3 2 6 2 4=3 9 N + O(N log N); for log N divisible by 3. The 1-active layer layout can be easily extended to a 2-active layer (bottom and top) layout which improves a result from [5]. 1 Introduction The research on three-dimensional circuit layouts started in seminal works [15, 17] as a response to advances in VLSI technology. Their model of a 3-dimensional circuit was a natural generalization of the 2-dimensional model [18]. Several basic results have been proved since then which show that the 3-dimensional layout may essentially reduce ma- terial, measured as volume [6, 12]. The problem may be also understood as a special 3-dimensional orthogonal drawing of graphs, see e.g., [9]. -
Toward a Unit Distance Embedding for the Heawood Graph
Toward a Unit Distance Embedding for the Heawood graph Mitchell A. Harris1 Harvard Medical School Department of Radiology Boston, MA 02114, USA [email protected] Abstract. The unit distance embeddability of a graph, like planarity, involves a mix of constraints that are combinatorial and geometric. We construct a unit distance embedding for H − e in the hope that it will lead to an embedding for H. We then investigate analytical methods for a general decision procedure for testing unit distance embeddability. 1 Introduction Unit distance embedding of a graph is an assignment of coordinates in the plane to the vertices of a graph such that if there is an edge between two vertices, then their respective coordinates are exactly distance 1 apart. To bar trivial embed- dings, such as for bipartite graphs having all nodes in one part located at (0, 0), for the other part at (0, 1), it is also required that the embedded points be dis- tinct. There is no restriction on edge crossing. A graph is said to be unit distance embeddable if there exists such an embedding (with the obvious abbreviations arXiv:0711.1157v1 [math.CO] 7 Nov 2007 employed, such as UD embeddable, a UDG, etc). For some well-known examples, K4 is not UDG but K4 e is. The Moser spindle is UDG, and is also 4 colorable [5], giving the largest− currently known lower bound to the Erd¨os colorability of the plane [3]. The graph K2,3 is not be- cause from two given points in the plane there are exactly two points of distance 1, but the graph wants three; removing any edge allows a UD embedding. -
PERFECT DOMINATING SETS Ý Marilynn Livingston£ Quentin F
In Congressus Numerantium 79 (1990), pp. 187-203. PERFECT DOMINATING SETS Ý Marilynn Livingston£ Quentin F. Stout Department of Computer Science Elec. Eng. and Computer Science Southern Illinois University University of Michigan Edwardsville, IL 62026-1653 Ann Arbor, MI 48109-2122 Abstract G G A dominating set Ë of a graph is perfect if each vertex of is dominated by exactly one vertex in Ë . We study the existence and construction of PDSs in families of graphs arising from the interconnection networks of parallel computers. These include trees, dags, series-parallel graphs, meshes, tori, hypercubes, cube-connected cycles, cube-connected paths, and de Bruijn graphs. For trees, dags, and series-parallel graphs we give linear time algorithms that determine if a PDS exists, and generate a PDS when one does. For 2- and 3-dimensional meshes, 2-dimensional tori, hypercubes, and cube-connected paths we completely characterize which graphs have a PDS, and the structure of all PDSs. For higher dimensional meshes and tori, cube-connected cycles, and de Bruijn graphs, we show the existence of a PDS in infinitely many cases, but our characterization d is not complete. Our results include distance d-domination for arbitrary . 1 Introduction = ´Î; Eµ Î E i Suppose G is a graph with vertex set and edge set . A vertex is said to dominate a E i j i = j Ë Î vertex j if contains an edge from to or if . A set of vertices is called a dominating G Ë G set of G if every vertex of is dominated by at least one member of . -
Arxiv:2008.08856V2 [Math.CO] 5 Dec 2020 Graphs Correspond Exactly to the Graphs Induced by the Two Middle Layers of Odd-Dimensional Hypercubes
Fast recognition of some parametric graph families Nina Klobas∗ and Matjaž Krnc† December 8, 2020 Abstract We identify all [1, λ, 8]-cycle regular I-graphs and all [1, λ, 8]-cycle reg- ular double generalized Petersen graphs. As a consequence we describe linear recognition algorithms for these graph families. Using structural properties of folded cubes we devise a o(N log N) recognition algorithm for them. We also study their [1, λ, 4], [1, λ, 6] and [2, λ, 6]-cycle regularity and settle the value of parameter λ. 1 Introduction Important graph classes such as bipartite graphs, (weakly) chordal graphs, (line) perfect graphs and (pseudo)forests are defined or characterized by their cycle structure. A particularly strong description of a cyclic structure is the notion of cycle-regularity, introduced by Mollard [24]: For integers l, λ, m a simple graph is [l, λ, m]-cycle regular if ev- ery path on l+1 vertices belongs to exactly λ different cycles of length m. It is perhaps natural that cycle-regularity mostly appears in the literature in the context of symmetric graph families such as hypercubes, Cayley graphs or circulants. Indeed, Mollard showed that certain extremal [3, 1, 6]-cycle regular arXiv:2008.08856v2 [math.CO] 5 Dec 2020 graphs correspond exactly to the graphs induced by the two middle layers of odd-dimensional hypercubes. Also, for [2, 1, 4]-cycle regular graphs, Mulder [25] showed that their degree is minimized in the case of Hadamard graphs, or in the case of hypercubes. In relation with other graph families, Fouquet and Hahn [12] described the symmetric aspect of certain cycle-regular classes, while in [19] authors describe all [1, λ, 8]-cycle regular members of generalized ∗Department of Computer Science, Durham University, UK.