DOCSLIB.ORG

AMS / MAA TEXTBOOKS VOL 41 Journey Into VOL Discrete Mathematics AMS / MAA TEXTBOOKS 41

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
AMS / MAA TEXTBOOKS VOL 41 Journey Into VOL Discrete Mathematics AMS / MAA TEXTBOOKS 41 AMS / MAA TEXTBOOKS VOL 41 Journey into VOL Discrete Mathematics AMS / MAA TEXTBOOKS 41 Owen D. Byer, Deirdre L. Smeltzer, and Kenneth L. Wantz Journey into Discrete Mathematics Discrete into Journey Journey into Discrete Mathematics is designed for use in a fi rst course in mathematical abstraction for early-career undergraduate mathematics majors. The important ideas of discrete mathematics are included— Wantz L. and Kenneth Smeltzer, L. Deirdre Byer, D. Owen logic, sets, proof writing, relations, counting, number theory, and graph theory—in a manner that promotes development of a mathematical mindset and prepares students for further study. While the treatment is designed to prepare the student reader for the mathematics major, the book remains attractive and appealing to students of computer science and other problem-solving disciplines. The exposition is exquisite and engaging and features detailed descrip- tions of the thought processes that one might follow to attack the problems of mathematics. The problems are appealing and vary widely in depth and diffi culty. Careful design of the book helps the student reader learn to think like a mathematician through the exposition and the prob- lems provided. Several of the core topics, including counting, number theory, and graph theory, are visited twice: once in an introductory manner and then again in a later chapter with more advanced concepts and with a deeper perspective. Owen D. Byer and Deirdre L. Smeltzer are both Professors of Mathematics at Eastern Mennonite University. Kenneth L. Wantz is Professor of Mathematics at Regent University. Collectively the authors have special- ized expertise and research publications ranging widely over discrete mathematics and have over fi fty semesters of combined experience in teaching this subject. For additional information and updates on this book, visit www.ams.org/bookpages/text-41 AMSMAA / PRESS TEXT/41 4-Color Process 400 pages on 50lb stock • Backspace 1 1/2'' 10.1090/text/041 AMS/MAA TEXTBOOKS VOL 41 Journey into Discrete Mathematics Owen D. Byer, Deirdre L. Smeltzer, and Kenneth L. Wantz Committee on Books Jennifer J. Quinn, Chair MAA Textbooks Editorial Board Stanley E. Seltzer, Editor William Robert Green, Co-Editor Bela Bajnok Suzanne Lynne Larson Jeffrey L. Stuart Matthias Beck John Lorch Ron D. Taylor, Jr. Heather Ann Dye Michael J. McAsey Elizabeth Thoren Charles R. Hampton Virginia Noonburg Ruth Vanderpool 2010 Mathematics Subject Classification. Primary 97K20, 97K30, 97F60, 97N70, 97E30. For additional information and updates on this book, visit www.ams.org/bookpages/text-41 Library of Congress Cataloging-in-Publication Data Names: Byer, Owen, author. | Smeltzer, Deirdre L., author. | Wantz, Kenneth L., 1965- author. Title: Journey into discrete mathematics / Owen D. Byer, Deirdre L. Smeltzer, Kenneth L. Wantz. Description: Providence, Rhode Island : MAA Press, an imprint of the American Mathematical Society, [2018] | Series: AMS/MAA textbooks ; volume 41 | Includes bibliographical references and index. Identifiers: LCCN 2018023584 | ISBN 9781470446963 (alk. paper) Subjects: LCSH: Set theory. | Number theory. | Mathematical analysis. | Combinatorial analysis. | AMS: Mathematics education – Combinatorics, graph theory, probability theory, statistics – Combinatorics. msc | Mathematics education – Combinatorics, graph theory, probability theory, statistics – Graph the- ory. msc | Mathematics education – Arithmetic, number theory – Number theory. msc | Mathematics education – Numerical mathematics – Discrete mathematics. msc | Mathematics education – Founda- tions of mathematics – Logic. msc Classification: LCC QA248 .B9657 2018 | DDC 511/.1–dc23 LC record available at https://lccn.loc.gov/2018023584 Color graphic policy. Any graphics created in color will be rendered in grayscale for the printed version unless color printing is authorized by the Publisher. In general, color graphics will appear in color in the online version. Copying and reprinting. Individual readers of this publication, and nonprofit libraries acting for them, are permitted to make fair use of the material, such as to copy select pages for use in teaching or research. Permission is granted to quote brief passages from this publication in reviews, provided the customary ac- knowledgment of the source is given. Republication, systematic copying, or multiple reproduction of any material in this publication is permit- ted only under license from the American Mathematical Society. Requests for permission to reuse portions of AMS publication content are handled by the Copyright Clearance Center. For more information, please visit www.ams.org/publications/pubpermissions. Send requests for translation rights and licensed reprints to [email protected]. © 2018 by the American Mathematical Society. All rights reserved. The American Mathematical Society retains all rights except those granted to the United States Government. Printed in the United States of America. ⃝1 The paper used in this book is acid-free and falls within the guidelines established to ensure permanence and durability. Visit the AMS home page at https://www.ams.org/ 10 9 8 7 6 5 4 3 2 1 23 22 21 20 19 18 Contents Preface vii What Is Discrete Mathematics? vii Goals of the Book vii Features of the Book viii Course Outline ix Acknowledgments xi 1 Convince Me! 1 1.1 Opening Problems 2 1.2 Solutions 4 2 Mini-Theories 9 2.1 Introduction 9 2.2 Divisibility of Integers 14 2.3 Matrices 22 3 Logic and Sets 31 3.1 Propositions 31 3.2 Sets 33 3.3 Logical Operators and Truth Tables 38 3.4 Operations on Sets 44 3.5 Truth Values of Compound Propositions 51 3.6 Set Identities 54 3.7 Infinite Sets and Paradoxes 58 4 Logic and Proof 67 4.1 Logical Equivalences 67 4.2 Predicates 73 4.3 Nested Quantifiers 77 4.4 Rules of Inference 83 4.5 Methods of Proof 91 5 Relations and Functions 101 5.1 Relations 101 5.2 Properties of Relations on a Set 106 5.3 Functions 113 5.4 Sequences 123 iii iv Contents 6 Induction 133 6.1 Inductive and Deductive Thinking 133 6.2 Well-Ordering Principle 135 6.3 Method of Mathematical Induction 137 6.4 Strong Induction 147 6.5 Proof of the Division Theorem 151 7 Number Theory 155 7.1 Primes 155 7.2 The Euclidean Algorithm 159 7.3 Linear Diophantine Equations 165 7.4 Congruences 169 7.5 Applications 176 7.6 Additional Problems 178 8 Counting 183 8.1 What Is Counting? 183 8.2 Counting Techniques 184 8.3 Permutations and Combinations 193 8.4 The Binomial Theorem 203 8.5 Additional Problems 207 9 Graph Theory 211 9.1 The Language of Graphs 212 9.2 Traversing Edges and Visiting Vertices 221 9.3 Vertex Colorings 230 9.4 Trees 238 9.5 Proofs of Euler’s and Ore’s Theorems 249 10 Invariants and Monovariants 253 10.1 Invariants 253 10.2 Monovariants 259 11 Topics in Counting 267 11.1 Inclusion-Exclusion 267 11.2 The Pigeonhole Principle 274 11.3 Multinomial Coefficients 278 11.4 Combinatorial Identities 282 11.5 Occupancy Problems 286 12 Topics in Number Theory 299 12.1 More on Primes 299 12.2 Integers in Other Bases 303 12.3 More on Congruences 311 12.4 Nonlinear Diophantine Equations 318 12.5 Cryptography: Rabin’s Method 319 Contents v 13 Topics in Graph Theory 327 13.1 Planar Graphs 327 13.2 Chromatic Polynomials 331 13.3 Spanning Tree Algorithms 337 13.4 Path and Circuit Algorithms 342 Hints 355 List of Names 381 Bibliography 383 Index 385 Preface What Is Discrete Mathematics? The word discrete in mathematics is in contrast to the word continuous. For example, the set of integers is discrete, while the set of real numbers is continuous. Thus, dis- crete mathematics describes a collection of branches of mathematics with the common characteristic that they focus on the study of things consisting of separate, irreducible, often finite parts. Although largely neglected in typical precollege mathematics cur- ricula, discrete mathematics is essential for developing logic and problem-solving abil- ities. Questions located within the realm of discrete mathematics naturally invite cre- ativity and innovative thinking that go beyond formulas. Furthermore, the cultivation of logical thinking forms a necessary foundation for proof-writing. For these reasons, discrete mathematics is critical for undergraduate study of both mathematics and com- puter science. Goals of the Book Simply stated, the goal of Journey into Discrete Mathematics is to nurture the develop- ment of skills needed to learn and do mathematics. These skills include the ability to read, write, and appreciate a good mathematical proof, as well as a basic fluency with core mathematical topics such as sets, relations and functions, graph theory, and num- ber theory. The content and the corresponding requisite mathematical thinking are appropriate for students in computer science and other problem-solving disciplines, but the content presentation and the nature of the problem sets reinforce the primary goal of training mathematicians. Throughout the book, we emphasize the language of mathematics and the essentials of proof-writing, and we underscore that the process is very important in mathematics. Entry-level discrete mathematics serves as an excellent gateway to upper-level math- ematics by priming students’ minds for upper-level concepts. Journey into Discrete Mathematics is designed for use in the first noncalculus course of a mathematics ma- jor, employing a writing style that models a high degree of mathematical accuracy while maintaining accessibility for early college students. For example, the treatment of inclusion-exclusion
Load more

Recommended publications
  • 1. Directed Graphs Or Quivers What Is Category Theory? • Graph Theory on Steroids • Comic Book Mathematics • Abstract Nonsense • the Secret Dictionary
    1. Directed graphs or quivers What is category theory? • Graph theory on steroids • Comic book mathematics • Abstract nonsense • The secret dictionary Sets and classes: For S = fX j X2 = Xg, have S 2 S , S2 = S Directed graph or quiver: C = (C0;C1;@0 : C1 ! C0;@1 : C1 ! C0) Class C0 of objects, vertices, points, . Class C1 of morphisms, (directed) edges, arrows, . For x; y 2 C0, write C(x; y) := ff 2 C1 j @0f = x; @1f = yg f 2C1 tail, domain / @0f / @1f o head, codomain op Opposite or dual graph of C = (C0;C1;@0;@1) is C = (C0;C1;@1;@0) Graph homomorphism F : D ! C has object part F0 : D0 ! C0 and morphism part F1 : D1 ! C1 with @i ◦ F1(f) = F0 ◦ @i(f) for i = 0; 1. Graph isomorphism has bijective object and morphism parts. Poset (X; ≤): set X with reflexive, antisymmetric, transitive order ≤ Hasse diagram of poset (X; ≤): x ! y if y covers x, i.e., x 6= y and [x; y] = fx; yg, so x ≤ z ≤ y ) z = x or z = y. Hasse diagram of (N; ≤) is 0 / 1 / 2 / 3 / ::: Hasse diagram of (f1; 2; 3; 6g; j ) is 3 / 6 O O 1 / 2 1 2 2. Categories Category: Quiver C = (C0;C1;@0 : C1 ! C0;@1 : C1 ! C0) with: • composition: 8 x; y; z 2 C0 ; C(x; y) × C(y; z) ! C(x; z); (f; g) 7! g ◦ f • satisfying associativity: 8 x; y; z; t 2 C0 ; 8 (f; g; h) 2 C(x; y) × C(y; z) × C(z; t) ; h ◦ (g ◦ f) = (h ◦ g) ◦ f y iS qq <SSSS g qq << SSS f qqq h◦g < SSSS qq << SSS qq g◦f < SSS xqq << SS z Vo VV < x VVVV << VVVV < VVVV << h VVVV < h◦(g◦f)=(h◦g)◦f VVVV < VVV+ t • identities: 8 x; y; z 2 C0 ; 9 1y 2 C(y; y) : 8 f 2 C(x; y) ; 1y ◦ f = f and 8 g 2 C(y; z) ; g ◦ 1y = g f y o x MM MM 1y g MM MMM f MMM M& zo g y Example: N0 = fxg ; N1 = N ; 1x = 0 ; 8 m; n 2 N ; n◦m = m+n ; | one object, lots of arrows [monoid of natural numbers under addition] 4 x / x Equation: 3 + 5 = 4 + 4 Commuting diagram: 3 4 x / x 5 ( 1 if m ≤ n; Example: N1 = N ; 8 m; n 2 N ; jN(m; n)j = 0 otherwise | lots of objects, lots of arrows [poset (N; ≤) as a category] These two examples are small categories: have a set of morphisms.
    [Show full text]
  • On Untouchable Numbers and Related Problems
    ON UNTOUCHABLE NUMBERS AND RELATED PROBLEMS CARL POMERANCE AND HEE-SUNG YANG Abstract. In 1973, Erd˝os proved that a positive proportion of numbers are untouchable, that is, not of the form σ(n) n, the sum of the proper divisors of n. We investigate the analogous question where σ is− replaced with the sum-of-unitary-divisors function σ∗ (which sums divisors d of n such that (d, n/d) = 1), thus solving a problem of te Riele from 1976. We also describe a fast algorithm for enumerating untouchable numbers and their kin. 1. Introduction If f(n) is an arithmetic function with nonnegative integral values it is interesting to con- sider Vf (x), the number of integers 0 m x for which f(n) = m has a solution. That is, one might consider the distribution≤ of the≤ range of f within the nonnegative integers. For some functions f(n) this is easy, such as the function f(n) = n, where Vf (x) = x , or 2 ⌊ ⌋ f(n) = n , where Vf (x) = √x . For f(n) = ϕ(n), Euler’s ϕ-function, it was proved by ⌊ ⌋ 1+o(1) Erd˝os [Erd35] in 1935 that Vϕ(x) = x/(log x) as x . Actually, the same is true for a number of multiplicative functions f, such as f = σ,→ the ∞ sum-of-divisors function, and f = σ∗, the sum-of-unitary-divisors function, where we say d is a unitary divisor of n if d n, | d > 0, and gcd(d,n/d) = 1. In fact, a more precise estimation of Vf (x) is known in these cases; see Ford [For98].
    [Show full text]
  • Research Statement
    D. A. Williams II June 2021 Research Statement I am an algebraist with expertise in the areas of representation theory of Lie superalgebras, associative superalgebras, and algebraic objects related to mathematical physics. As a post- doctoral fellow, I have extended my research to include topics in enumerative and algebraic combinatorics. My research is collaborative, and I welcome collaboration in familiar areas and in newer undertakings. The referenced open problems here, their subproblems, and other ideas in mind are suitable for undergraduate projects and theses, doctoral proposals, or scholarly contributions to academic journals. In what follows, I provide a technical description of the motivation and history of my work in Lie superalgebras and super representation theory. This is then followed by a description of the work I am currently supervising and mentoring, in combinatorics, as I serve as the Postdoctoral Research Advisor for the Mathematical Sciences Research Institute's Undergraduate Program 2021. 1 Super Representation Theory 1.1 History 1.1.1 Superalgebras In 1941, Whitehead dened a product on the graded homotopy groups of a pointed topological space, the rst non-trivial example of a Lie superalgebra. Whitehead's work in algebraic topol- ogy [Whi41] was known to mathematicians who dened new graded geo-algebraic structures, such as -graded algebras, or superalgebras to physicists, and their modules. A Lie superalge- Z2 bra would come to be a -graded vector space, even (respectively, odd) elements g = g0 ⊕ g1 Z2 found in (respectively, ), with a parity-respecting bilinear multiplication termed the Lie g0 g1 superbracket inducing1 a symmetric intertwining map of -modules.
    [Show full text]
  • Donald Knuth Fletcher Jones Professor of Computer Science, Emeritus Curriculum Vitae Available Online
    Donald Knuth Fletcher Jones Professor of Computer Science, Emeritus Curriculum Vitae available Online Bio BIO Donald Ervin Knuth is an American computer scientist, mathematician, and Professor Emeritus at Stanford University. He is the author of the multi-volume work The Art of Computer Programming and has been called the "father" of the analysis of algorithms. He contributed to the development of the rigorous analysis of the computational complexity of algorithms and systematized formal mathematical techniques for it. In the process he also popularized the asymptotic notation. In addition to fundamental contributions in several branches of theoretical computer science, Knuth is the creator of the TeX computer typesetting system, the related METAFONT font definition language and rendering system, and the Computer Modern family of typefaces. As a writer and scholar,[4] Knuth created the WEB and CWEB computer programming systems designed to encourage and facilitate literate programming, and designed the MIX/MMIX instruction set architectures. As a member of the academic and scientific community, Knuth is strongly opposed to the policy of granting software patents. He has expressed his disagreement directly to the patent offices of the United States and Europe. (via Wikipedia) ACADEMIC APPOINTMENTS • Professor Emeritus, Computer Science HONORS AND AWARDS • Grace Murray Hopper Award, ACM (1971) • Member, American Academy of Arts and Sciences (1973) • Turing Award, ACM (1974) • Lester R Ford Award, Mathematical Association of America (1975) • Member, National Academy of Sciences (1975) 5 OF 44 PROFESSIONAL EDUCATION • PhD, California Institute of Technology , Mathematics (1963) PATENTS • Donald Knuth, Stephen N Schiller. "United States Patent 5,305,118 Methods of controlling dot size in digital half toning with multi-cell threshold arrays", Adobe Systems, Apr 19, 1994 • Donald Knuth, LeRoy R Guck, Lawrence G Hanson.
    [Show full text]
  • Introduction to Computational Social Choice
    1 Introduction to Computational Social Choice Felix Brandta, Vincent Conitzerb, Ulle Endrissc, J´er^omeLangd, and Ariel D. Procacciae 1.1 Computational Social Choice at a Glance Social choice theory is the field of scientific inquiry that studies the aggregation of individual preferences towards a collective choice. For example, social choice theorists|who hail from a range of different disciplines, including mathematics, economics, and political science|are interested in the design and theoretical evalu- ation of voting rules. Questions of social choice have stimulated intellectual thought for centuries. Over time the topic has fascinated many a great mind, from the Mar- quis de Condorcet and Pierre-Simon de Laplace, through Charles Dodgson (better known as Lewis Carroll, the author of Alice in Wonderland), to Nobel Laureates such as Kenneth Arrow, Amartya Sen, and Lloyd Shapley. Computational social choice (COMSOC), by comparison, is a very young field that formed only in the early 2000s. There were, however, a few precursors. For instance, David Gale and Lloyd Shapley's algorithm for finding stable matchings between two groups of people with preferences over each other, dating back to 1962, truly had a computational flavor. And in the late 1980s, a series of papers by John Bartholdi, Craig Tovey, and Michael Trick showed that, on the one hand, computational complexity, as studied in theoretical computer science, can serve as a barrier against strategic manipulation in elections, but on the other hand, it can also prevent the efficient use of some voting rules altogether. Around the same time, a research group around Bernard Monjardet and Olivier Hudry also started to study the computational complexity of preference aggregation procedures.
    [Show full text]
  • Modified Moments for Indefinite Weight Functions [2Mm] (A Tribute
    Modified Moments for Indefinite Weight Functions (a Tribute to a Fruitful Collaboration with Gene H. Golub) Martin H. Gutknecht Seminar for Applied Mathematics ETH Zurich Remembering Gene Golub Around the World Leuven, February 29, 2008 Martin H. Gutknecht Modified Moments for Indefinite Weight Functions My education in numerical analysis at ETH Zurich My teachers of numerical analysis: Eduard Stiefel [1909–1978] (first, basic NA course, 1964) Peter Läuchli [b. 1928] (ALGOL, 1965) Hans-Rudolf Schwarz [b. 1930] (numerical linear algebra, 1966) Heinz Rutishauser [1917–1970] (follow-up numerical analysis course; “selected chapters of NM” [several courses]; computer hands-on training) Peter Henrici [1923–1987] (computational complex analysis [many courses]) The best of all worlds? Martin H. Gutknecht Modified Moments for Indefinite Weight Functions My education in numerical analysis (cont’d) What did I learn? Gauss elimination, simplex alg., interpolation, quadrature, conjugate gradients, ODEs, FDM for PDEs, ... qd algorithm [often], LR algorithm, continued fractions, ... many topics in computational complex analysis, e.g., numerical conformal mapping What did I miss to learn? (numerical linear algebra only) QR algorithm nonsymmetric eigenvalue problems SVD (theory, algorithms, applications) Lanczos algorithm (sym., nonsym.) Padé approximation, rational interpolation Martin H. Gutknecht Modified Moments for Indefinite Weight Functions My first encounters with Gene H. Golub Gene’s first two talks at ETH Zurich (probably) 4 June 1971: “Some modified eigenvalue problems” 28 Nov. 1974: “The block Lanczos algorithm” Gene was one of many famous visitors Peter Henrici attracted. Fall 1974: GHG on sabbatical at ETH Zurich. I had just finished editing the “Lectures of Numerical Mathematics” of Heinz Rutishauser (1917–1970).
    [Show full text]
  • Proofs from the BOOK.Pdf
    Martin Aigner Günter M. Ziegler Proofs from THE BOOK Fourth Edition Martin Aigner Günter M. Ziegler Proofs from THE BOOK Fourth Edition Including Illustrations by Karl H. Hofmann 123 Prof. Dr. Martin Aigner Prof.GünterM.Ziegler FB Mathematik und Informatik Institut für Mathematik, MA 6-2 Freie Universität Berlin Technische Universität Berlin Arnimallee 3 Straße des 17. Juni 136 14195 Berlin 10623 Berlin Deutschland Deutschland [email protected] [email protected] ISBN 978-3-642-00855-9 e-ISBN 978-3-642-00856-6 DOI 10.1007/978-3-642-00856-6 Springer Heidelberg Dordrecht London New York c Springer-Verlag Berlin Heidelberg 2010 This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer. Violations are liable to prosecution under the German Copyright Law. The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. Cover design: deblik, Berlin Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com) Preface Paul Erdosliked˝ to talk aboutThe Book, in which God maintainsthe perfect proofsfor mathematical theorems, following the dictum of G.
    [Show full text]
  • Mathematical Analysis of the Accordion Grating Illusion: a Differential Geometry Approach to Introduce the 3D Aperture Problem
    Neural Networks 24 (2011) 1093–1101 Contents lists available at SciVerse ScienceDirect Neural Networks journal homepage: www.elsevier.com/locate/neunet Mathematical analysis of the Accordion Grating illusion: A differential geometry approach to introduce the 3D aperture problem Arash Yazdanbakhsh a,b,∗, Simone Gori c,d a Cognitive and Neural Systems Department, Boston University, MA, 02215, United States b Neurobiology Department, Harvard Medical School, Boston, MA, 02115, United States c Universita' degli studi di Padova, Dipartimento di Psicologia Generale, Via Venezia 8, 35131 Padova, Italy d Developmental Neuropsychology Unit, Scientific Institute ``E. Medea'', Bosisio Parini, Lecco, Italy article info a b s t r a c t Keywords: When an observer moves towards a square-wave grating display, a non-rigid distortion of the pattern Visual illusion occurs in which the stripes bulge and expand perpendicularly to their orientation; these effects reverse Motion when the observer moves away. Such distortions present a new problem beyond the classical aperture Projection line Line of sight problem faced by visual motion detectors, one we describe as a 3D aperture problem as it incorporates Accordion Grating depth signals. We applied differential geometry to obtain a closed form solution to characterize the fluid Aperture problem distortion of the stripes. Our solution replicates the perceptual distortions and enabled us to design a Differential geometry nulling experiment to distinguish our 3D aperture solution from other candidate mechanisms (see Gori et al. (in this issue)). We suggest that our approach may generalize to other motion illusions visible in 2D displays. ' 2011 Elsevier Ltd. All rights reserved. 1. Introduction need for line-ends or intersections along the lines to explain the illusion.
    [Show full text]
  • 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.
    [Show full text]
  • Input for Carnival of Math: Number 115, October 2014
    Input for Carnival of Math: Number 115, October 2014 I visited Singapore in 1996 and the people were very kind to me. So I though this might be a little payback for their kindness. Good Luck. David Brooks The “Mathematical Association of America” (http://maanumberaday.blogspot.com/2009/11/115.html ) notes that: 115 = 5 x 23. 115 = 23 x (2 + 3). 115 has a unique representation as a sum of three squares: 3 2 + 5 2 + 9 2 = 115. 115 is the smallest three-digit integer, abc , such that ( abc )/( a*b*c) is prime : 115/5 = 23. STS-115 was a space shuttle mission to the International Space Station flown by the space shuttle Atlantis on Sept. 9, 2006. The “Online Encyclopedia of Integer Sequences” (http://www.oeis.org) notes that 115 is a tridecagonal (or 13-gonal) number. Also, 115 is the number of rooted trees with 8 vertices (or nodes). If you do a search for 115 on the OEIS website you will find out that there are 7,041 integer sequences that contain the number 115. The website “Positive Integers” (http://www.positiveintegers.org/115) notes that 115 is a palindromic and repdigit number when written in base 22 (5522). The website “Number Gossip” (http://www.numbergossip.com) notes that: 115 is the smallest three-digit integer, abc, such that (abc)/(a*b*c) is prime. It also notes that 115 is a composite, deficient, lucky, odd odious and square-free number. The website “Numbers Aplenty” (http://www.numbersaplenty.com/115) notes that: It has 4 divisors, whose sum is σ = 144.
    [Show full text]
  • An Application of Graph Theory in Markov Chains Reliability Analysis
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by DSpace at VSB Technical University of Ostrava STATISTICS VOLUME: 12 j NUMBER: 2 j 2014 j JUNE An Application of Graph Theory in Markov Chains Reliability Analysis Pavel SKALNY Department of Applied Mathematics, Faculty of Electrical Engineering and Computer Science, VSB–Technical University of Ostrava, 17. listopadu 15/2172, 708 33 Ostrava-Poruba, Czech Republic [email protected] Abstract. The paper presents reliability analysis which the production will be equal or greater than the indus- was realized for an industrial company. The aim of the trial partner demand. To deal with the task a Monte paper is to present the usage of discrete time Markov Carlo simulation of Discrete time Markov chains was chains and the flow in network approach. Discrete used. Markov chains a well-known method of stochastic mod- The goal of this paper is to present the Discrete time elling describes the issue. The method is suitable for Markov chain analysis realized on the system, which is many systems occurring in practice where we can easily not distributed in parallel. Since the analysed process distinguish various amount of states. Markov chains is more complicated the graph theory approach seems are used to describe transitions between the states of to be an appropriate tool. the process. The industrial process is described as a graph network. The maximal flow in the network cor- Graph theory has previously been applied to relia- responds to the production. The Ford-Fulkerson algo- bility, but for different purposes than we intend.
    [Show full text]
  • Introduction to Computational Social Choice Felix Brandt, Vincent Conitzer, Ulle Endriss, Jérôme Lang, Ariel D
    Introduction to Computational Social Choice Felix Brandt, Vincent Conitzer, Ulle Endriss, Jérôme Lang, Ariel D. Procaccia To cite this version: Felix Brandt, Vincent Conitzer, Ulle Endriss, Jérôme Lang, Ariel D. Procaccia. Introduction to Computational Social Choice. Felix Brandt, Vincent Conitzer, Ulle Endriss, Jérôme Lang, Ariel D. Procaccia, Handbook of Computational Social Choice, Cambridge University Press, pp.1-29, 2016, 9781107446984. 10.1017/CBO9781107446984. hal-01493516 HAL Id: hal-01493516 https://hal.archives-ouvertes.fr/hal-01493516 Submitted on 21 Mar 2017 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. 1 Introduction to Computational Social Choice Felix Brandta, Vincent Conitzerb, Ulle Endrissc, J´er^omeLangd, and Ariel D. Procacciae 1.1 Computational Social Choice at a Glance Social choice theory is the field of scientific inquiry that studies the aggregation of individual preferences towards a collective choice. For example, social choice theorists|who hail from a range of different disciplines, including mathematics, economics, and political science|are interested in the design and theoretical evalu- ation of voting rules. Questions of social choice have stimulated intellectual thought for centuries. Over time the topic has fascinated many a great mind, from the Mar- quis de Condorcet and Pierre-Simon de Laplace, through Charles Dodgson (better known as Lewis Carroll, the author of Alice in Wonderland), to Nobel Laureates such as Kenneth Arrow, Amartya Sen, and Lloyd Shapley.
    [Show full text]