Adinkras and Arithmetical Graphs Madeleine Weinstein Harvey Mudd College
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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. -
Applications of the Quantum Algorithm for St-Connectivity
Applications of the quantum algorithm for st-connectivity KAI DELORENZO1 , SHELBY KIMMEL1 , AND R. TEAL WITTER1 1Middlebury College, Computer Science Department, Middlebury, VT Abstract We present quantum algorithms for various problems related to graph connectivity. We give simple and query-optimal algorithms for cycle detection and odd-length cycle detection (bipartiteness) using a reduction to st-connectivity. Furthermore, we show that our algorithm for cycle detection has improved performance under the promise of large circuit rank or a small number of edges. We also provide algo- rithms for detecting even-length cycles and for estimating the circuit rank of a graph. All of our algorithms have logarithmic space complexity. 1 Introduction Quantum query algorithms are remarkably described by span programs [15, 16], a linear algebraic object originally created to study classical logspace complexity [12]. However, finding optimal span program algorithms can be challenging; while they can be obtained using a semidefinite program, the size of the program grows exponentially with the size of the input to the algorithm. Moreover, span programs are designed to characterize the query complexity of an algorithm, while in practice we also care about the time and space complexity. One of the nicest span programs is for the problem of undirected st-connectivity, in which one must decide whether two vertices s and t are connected in a given graph. It is “nice” for several reasons: It is easy to describe and understand why it is correct. • It corresponds to a quantum algorithm that uses logarithmic (in the number of vertices and edges of • the graph) space [4, 11]. -
The Normalized Laplacian Spectrum of Subdivisions of a Graph
The normalized Laplacian spectrum of subdivisions of a graph Pinchen Xiea,b, Zhongzhi Zhanga,c, Francesc Comellasd aShanghai Key Laboratory of Intelligent Information Processing, Fudan University, Shanghai 200433, China bDepartment of Physics, Fudan University, Shanghai 200433, China cSchool of Computer Science, Fudan University, Shanghai 200433, China dDepartment of Applied Mathematics IV, Universitat Polit`ecnica de Catalunya, 08034 Barcelona Catalonia, Spain Abstract Determining and analyzing the spectra of graphs is an important and excit- ing research topic in mathematics science and theoretical computer science. The eigenvalues of the normalized Laplacian of a graph provide information on its structural properties and also on some relevant dynamical aspects, in particular those related to random walks. In this paper, we give the spec- tra of the normalized Laplacian of iterated subdivisions of simple connected graphs. As an example of application of these results we find the exact val- ues of their multiplicative degree-Kirchhoff index, Kemeny's constant and number of spanning trees. Keywords: Normalized Laplacian spectrum, Subdivision graph, Degree-Kirchhoff index, Kemeny's constant, Spanning trees 1. Introduction Spectral analysis of graphs has been the subject of considerable research effort in mathematics and computer science [1, 2, 3], due to its wide appli- cations in this area and in general [4, 5]. In the last few decades a large body of scientific literature has established that important structural and dynamical properties -
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. -
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 -
Eindhoven University of Technology BACHELOR on the K-Independent
Eindhoven University of Technology BACHELOR On the k-Independent Set Problem Koerts, Hidde O. Award date: 2021 Link to publication Disclaimer This document contains a student thesis (bachelor's or master's), as authored by a student at Eindhoven University of Technology. Student theses are made available in the TU/e repository upon obtaining the required degree. The grade received is not published on the document as presented in the repository. The required complexity or quality of research of student theses may vary by program, and the required minimum study period may vary in duration. General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain On the k-Independent Set Problem Hidde Koerts Supervised by Aida Abiad February 1, 2021 Hidde Koerts Supervised by Aida Abiad Abstract In this thesis, we study several open problems related to the k-independence num- ber, which is defined as the maximum size of a set of vertices at pairwise dis- tance greater than k (or alternatively, as the independence number of the k-th graph power). Firstly, we extend the definitions of vertex covers and cliques to allow for natural extensions of the equivalencies between independent sets, ver- tex covers, and cliques. -
Matroidal Structure of Rough Sets from the Viewpoint of Graph Theory
Hindawi Publishing Corporation Journal of Applied Mathematics Volume 2012, Article ID 973920, 27 pages doi:10.1155/2012/973920 Research Article Matroidal Structure of Rough Sets from the Viewpoint of Graph Theory Jianguo Tang,1, 2 Kun She,1 and William Zhu3 1 School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China 2 School of Computer Science and Engineering, XinJiang University of Finance and Economics, Urumqi 830012, China 3 Lab of Granular Computing, Zhangzhou Normal University, Zhangzhou 363000, China Correspondence should be addressed to William Zhu, [email protected] Received 4 February 2012; Revised 30 April 2012; Accepted 18 May 2012 Academic Editor: Mehmet Sezer Copyright q 2012 Jianguo Tang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Constructing structures with other mathematical theories is an important research field of rough sets. As one mathematical theory on sets, matroids possess a sophisticated structure. This paper builds a bridge between rough sets and matroids and establishes the matroidal structure of rough sets. In order to understand intuitively the relationships between these two theories, we study this problem from the viewpoint of graph theory. Therefore, any partition of the universe can be represented by a family of complete graphs or cycles. Then two different kinds of matroids are constructed and some matroidal characteristics of them are discussed, respectively. The lower and the upper approximations are formulated with these matroidal characteristics. -
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. -
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]. -
Permutation of Elements in Double Semigroups
PERMUTATION OF ELEMENTS IN DOUBLE SEMIGROUPS MURRAY BREMNER AND SARA MADARIAGA Abstract. Double semigroups have two associative operations ◦, • related by the interchange relation: (a • b) ◦ (c • d) ≡ (a ◦ c) • (b ◦ d). Kock [13] (2007) discovered a commutativity property in degree 16 for double semigroups: as- sociativity and the interchange relation combine to produce permutations of elements. We show that such properties can be expressed in terms of cycles in directed graphs with edges labelled by permutations. We use computer alge- bra to show that 9 is the lowest degree for which commutativity occurs, and we give self-contained proofs of the commutativity properties in degree 9. 1. Introduction Definition 1.1. A double semigroup is a set S with two associative binary operations •, ◦ satisfying the interchange relation for all a,b,c,d ∈ S: (⊞) (a • b) ◦ (c • d) ≡ (a ◦ c) • (b ◦ d). The symbol ≡ indicates that the equation holds for all values of the variables. We interpret ◦ and • as horizontal and vertical compositions, so that (⊞) ex- presses the equivalence of two decompositions of a square array: a b a b a b (a ◦ b) • (c ◦ d) ≡ ≡ ≡ ≡ (a • c) ◦ (b • d). c d c d c d This interpretation of the operations extends to any double semigroup monomial, producing what we call the geometric realization of the monomial. The interchange relation originated in homotopy theory and higher categories; see Mac Lane [15, (2.3)] and [16, §XII.3]. It is also called the Godement relation by arXiv:1405.2889v2 [math.RA] 26 Mar 2015 some authors; see Simpson [21, §2.1]. -
G-Parking Functions and Tree Inversions
G-PARKING FUNCTIONS AND TREE INVERSIONS DAVID PERKINSON, QIAOYU YANG, AND KUAI YU Abstract. A depth-first search version of Dhar’s burning algorithm is used to give a bijection between the parking functions of a graph and labeled spanning trees, relating the degree of the parking function with the number of inversions of the spanning tree. Specializing to the complete graph solves a problem posed by R. Stanley. 1. Introduction Let G = (V, E) be a connected simple graph with vertex set V = {0,...,n} and edge set E. Fix a root vertex r ∈ V and let SPT(G) denote the set of spanning trees of G rooted at r. We think of each element of SPT(G) as a directed graph in which all paths lead away from the root. If i, j ∈ V and i lies on the unique path from r to j in the rooted spanning tree T , then i is an ancestor of j and j is a descendant of i in T . If, in addition, there are no vertices between i and j on the path from the root, then i is the parent of its child j, and (i, j) is a directed edge of T . Definition 1. An inversion of T ∈ SPT(G) is a pair of vertices (i, j), such that i is an ancestor of j in T and i > j. It is a κ-inversion if, in addition, i is not the root and i’s parent is adjacent to j in G. The number of κ-inversions of T is the tree’s κ-number, denoted κ(G, T ).