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LINEAR ALGEBRA METHODS in COMBINATORICS László Babai
LINEAR ALGEBRA METHODS IN COMBINATORICS L´aszl´oBabai and P´eterFrankl Version 2.1∗ March 2020 ||||| ∗ Slight update of Version 2, 1992. ||||||||||||||||||||||| 1 c L´aszl´oBabai and P´eterFrankl. 1988, 1992, 2020. Preface Due perhaps to a recognition of the wide applicability of their elementary concepts and techniques, both combinatorics and linear algebra have gained increased representation in college mathematics curricula in recent decades. The combinatorial nature of the determinant expansion (and the related difficulty in teaching it) may hint at the plausibility of some link between the two areas. A more profound connection, the use of determinants in combinatorial enumeration goes back at least to the work of Kirchhoff in the middle of the 19th century on counting spanning trees in an electrical network. It is much less known, however, that quite apart from the theory of determinants, the elements of the theory of linear spaces has found striking applications to the theory of families of finite sets. With a mere knowledge of the concept of linear independence, unexpected connections can be made between algebra and combinatorics, thus greatly enhancing the impact of each subject on the student's perception of beauty and sense of coherence in mathematics. If these adjectives seem inflated, the reader is kindly invited to open the first chapter of the book, read the first page to the point where the first result is stated (\No more than 32 clubs can be formed in Oddtown"), and try to prove it before reading on. (The effect would, of course, be magnified if the title of this volume did not give away where to look for clues.) What we have said so far may suggest that the best place to present this material is a mathematics enhancement program for motivated high school students. -
Embedding Graphs Into Larger Graphs: Results, Methods, and Problems
Embedding graphs into larger graphs: results, methods, and problems Mikl´os Simonovits and Endre Szemer´edi Alfr´ed R´enyi Institute of Mathematics, Hungarian Academy of Sciences, email: [email protected], [email protected] arXiv:1912.02068v1 [math.CO] 4 Dec 2019 2 Mikl´os Simonovits and Endre Szemer´edi: March29, 2019 Contents 1 Introduction.............................. 6 2 Thebeginnings............................ 9 2.1 Veryearlyresults....................... 9 2.2 Constructions......................... 13 2.3 Somehistoricalremarks . .. .. .. .. .. .. .. 13 2.4 Earlyresults ......................... 14 2.5 WhichUniverse? ....................... 16 2.6 Ramseyordensity? ..................... 21 2.7 Whyaretheextremalproblemsinteresting? . 22 2.8 Ramsey Theory and the birth of the Random Graph Method 23 2.9 Dichotomy, randomness and matrix graphs . 24 2.10 Ramsey problems similar to extremal problems . 25 2.11 Applications in Continuous Mathematics . 26 2.12 TheStabilitymethod .................... 26 2.13 The“typicalstructure” . 29 2.14 SupersaturatedGraphs . 31 2.15 Lov´asz-Simonovits Stability theorem . 32 2.16 Degeneratevs Non-degenerateproblems . 33 2.17 Diractheorem:introduction. 36 2.18 Equitable Partition . 36 2.19 Packing, Covering, Tiling, L-factors ............ 37 3 “Classicalmethods” ......................... 40 3.1 DetourI:Induction? ..................... 40 3.2 Detour II: Applications of Linear Algebra . 41 4 Methods: Randomness and the Semi-random method . 43 4.1 Various ways to use randomness in Extremal Graph Theory 44 4.2 Thesemi-randommethod . 45 4.3 Independentsetsinuncrowdedgraphs . 45 4.4 Uncrowdedhypergraphs . 47 4.5 Ramseyestimates ...................... 48 4.6 InfiniteSidonsequences . .. .. .. .. .. .. .. 49 4.7 The Heilbronn problem, old results . 50 4.8 Generalizations of Heilbronn’s problem, new results . 50 4.9 TheHeilbronnproblem,anupperbound. 51 4.10 TheGowersproblem..................... 51 3 4 Mikl´os Simonovits and Endre Szemer´edi: March29, 2019 4.11 Pippenger-Spencertheorem . -
The Role of GH Hardy and the London Mathematical Society
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Historia Mathematica 30 (2003) 173–194 www.elsevier.com/locate/hm The rise of British analysis in the early 20th century: the role of G.H. Hardy and the London Mathematical Society Adrian C. Rice a and Robin J. Wilson b,∗ a Department of Mathematics, Randolph-Macon College, Ashland, VA 23005-5505, USA b Department of Pure Mathematics, The Open University, Milton Keynes MK7 6AA, UK Abstract It has often been observed that the early years of the 20th century witnessed a significant and noticeable rise in both the quantity and quality of British analysis. Invariably in these accounts, the name of G.H. Hardy (1877–1947) features most prominently as the driving force behind this development. But how accurate is this interpretation? This paper attempts to reevaluate Hardy’s influence on the British mathematical research community and its analysis during the early 20th century, with particular reference to his relationship with the London Mathematical Society. 2003 Elsevier Inc. All rights reserved. Résumé On a souvent remarqué que les premières années du 20ème siècle ont été témoins d’une augmentation significative et perceptible dans la quantité et aussi la qualité des travaux d’analyse en Grande-Bretagne. Dans ce contexte, le nom de G.H. Hardy (1877–1947) est toujours indiqué comme celui de l’instigateur principal qui était derrière ce développement. Mais, est-ce-que cette interprétation est exacte ? Cet article se propose d’analyser à nouveau l’influence d’Hardy sur la communauté britannique sur la communauté des mathématiciens et des analystes britanniques au début du 20ème siècle, en tenant compte en particulier de son rapport avec la Société Mathématique de Londres. -
Paul Erdos: the Master of Collaboration
Paul Erdos: The Master of Collaboration Jerrold W. Grossman Department of Mathematical Sciences, Oakland University, Rochester, MI48309- 4401 Over a span of more than 60 years, Paul Erdos has taken the art of col laborative research in mathematics to heights never before achieved. In this brief look at his collaborative efforts, we will explore the breadth of Paul's interests, the company he has kept, and the influence of his collaboration in the mathematical community. Rather than focusing on the mathematical content of his work or the man himself, we will see what conclusions can be drawn by looking mainly at publication lists. Thus our approach will be mostly bibliographical, rather than either mathematical or biographical. The data come mainly from the bibliography in this present volume and records kept by Mathematical Reviews (MR) [13]. Additional useful sources of infor mation include The Hypertext Bibliography Project (a database of articles in theoretical computer science) [11], Zentralblatt [16], the Jahrbuch [10]' vari ous necrological articles too numerous to list, and personal communications. Previous articles on these topics can be found in [3,4,7,8,14]. Paul has certainly become a legend, whose fame (as well as his genius and eccentricity) has spread beyond the circles of research mathematicians. We find a popular videotape about him [2], articles in general circulation maga zines [9,15] (as well as in mathematical publications-see [1] for a wonderful example), and graffiti on the Internet (e.g., his quotation that a mathemati cian is a device for turning coffee into theorems, on a World Wide Web page designed as a sample of the use of the html language [12]). -
Introduction to Ramsey Theory
Introduction to Ramsey Theory Lecture notes for undergraduate course Introduction to Ramsey Theory Lecture notes for undergraduate course Veselin Jungic Simon Fraser University Production Editor: Veselin Jungic Edition: Second Edition ©2014-–2021 Veselin Jungic This work is licensed under the Creative Commons Attribution-NonCommercialShareAlike 4.0 International License. Youcan view a copy of the license at http://creativecommons.org/ licenses/by-nc-sa/4.0/. To my sons, my best teachers. - Veselin Jungic Acknowledgements Drawings of Alfred Hale, Robert Jewett, Richard Rado, Frank Ramsey, Issai Schur, and Bartel van der Waerden were created by Ms. Kyra Pukanich under my directions. The drawing of Frank Ramsey displayed at the end of Section 1.3 was created by Mr. Simon Roy under my directions. I am grateful to Professor Tom Brown, Mr. Rashid Barket, Ms. Jana Caine, Mr. Kevin Halasz, Ms. Arpit Kaur, Ms. Ha Thu Nguyen, Mr. Andrew Poelstra, Mr. Michael Stephen Paulgaard, and Ms. Ompreet Kaur Sarang for their comments and suggestions which have been very helpful in improving the manuscript. I would like to acknowledge the following colleagues for their help in creating the PreTeXt version of the text. • Jana Caine, Simon Fraser University • David Farmer, American Institute of Mathematics • Sean Fitzpatrick , University of Lethbridge • Damir Jungic, Burnaby, BC I am particularly thankful to Dr. Sean Fitzpatrick for inspiring and encouraging me to use PreTeXt. Veselin Jungic vii Preface The purpose of these lecture notes is to serve as a gentle introduction to Ramsey theory for those undergraduate students interested in becoming familiar with this dynamic segment of contemporary mathematics that combines, among others, ideas from number theory and combinatorics. -
Claude Ambrose Rogers. 1 November 1920- 5 December 2005
Kenneth Falconer, Peter M. Gruber, Adam Ostaszewski and Trevor Stuart Claude Ambrose Rogers. 1 November 1920- 5 December 2005 Article (Published version) (Refereed) Original citation: Falconer, Kenneth, Gruber, Peter M., Ostaszewski, Adam and Stuart, Trevor (2015) Claude Ambrose Rogers. 1 November 1920 — 5 December 2005. Biographical Memoirs of Fellows of the Royal Society, 61 . pp. 403-435. ISSN 0080-4606 DOI: 10.1098/rsbm.2015.0007 © 2015 The Authors This version available at: http://eprints.lse.ac.uk/63494/ Available in LSE Research Online: November 2015 LSE has developed LSE Research Online so that users may access research output of the School. Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Users may download and/or print one copy of any article(s) in LSE Research Online to facilitate their private study or for non-commercial research. You may not engage in further distribution of the material or use it for any profit-making activities or any commercial gain. You may freely distribute the URL (http://eprints.lse.ac.uk) of the LSE Research Online website. Downloaded from http://rsbm.royalsocietypublishing.org/ on November 19, 2015 Claude Ambrose Rogers. 1 November 1920 −− 5 December 2005 Kenneth Falconer, Peter M. Gruber, Adam Ostaszewski and Trevor Stuart Biogr. Mems Fell. R. Soc. 2015 61, 403-435, published 2 September 2015 originally published online September 2, 2015 Supplementary data "Data Supplement" http://rsbm.royalsocietypublishing.org/content/suppl/2015/08 /27/rsbm.2015.0007.DC1.html Email alerting service Receive free email alerts when new articles cite this article - sign up in the box at the top right-hand corner of the article or click here To subscribe to Biogr. -
Arxiv:2011.03619V3 [Cs.DS] 12 Jul 2021
Algorithmic Extensions of Dirac's Theorem Fedor V. Fomin∗ Petr A. Golovach∗ Danil Sagunov† [email protected] [email protected] [email protected] Kirill Simonov∗ [email protected] Abstract In 1952, Dirac proved the following theorem about long cycles in graphs with large minimum vertex degrees: Every n-vertex 2-connected graph G with minimum vertex degree δ ≥ 2 contains a cycle with at least minf2δ; ng vertices. In particular, if δ ≥ n=2, then G is Hamiltonian. The proof of Dirac's theorem is constructive, and it yields an algorithm computing the corresponding cycle in polynomial time. The combinatorial bound of Dirac's theorem is tight in the following sense. There are 2-connected graphs that do not contain cycles of length more than 2δ + 1. Also, there are non-Hamiltonian graphs with all vertices but one of degree at least n=2. This prompts naturally to the following algorithmic questions. For k ≥ 1, (A) How difficult is to decide whether a 2-connected graph contains a cycle of length at least minf2δ + k; ng? (B) How difficult is to decide whether a graph G is Hamiltonian, when at least n − k vertices of G are of degrees at least n=2 − k? The first question was asked by Fomin, Golovach, Lokshtanov, Panolan, Saurabh, and Zehavi. The second question is due to Jansen, Kozma, and Nederlof. Even for a very special case of k = 1, the existence of a polynomial-time algorithm deciding whether G contains a cycle of length at least minf2δ + 1; ng was open. -
Set Theory and the Analyst
European Journal of Mathematics (2019) 5:2–48 https://doi.org/10.1007/s40879-018-0278-1 REVIEW ARTICLE Set theory and the analyst Nicholas H. Bingham1 · Adam J. Ostaszewski2 For Zbigniew Grande, on his 70th birthday, and in memoriam: Stanisław Saks (1897–1942), Cross of Valour, Paragon of Polish Analysis, Cousin-in-law Then to the rolling heaven itself I cried, Asking what lamp had destiny to guide Her little children stumbling in the dark. And ‘A blind understanding’ heaven replied. – The Rubaiyat of Omar Khayyam Received: 14 January 2018 / Revised: 15 June 2018 / Accepted: 12 July 2018 / Published online: 12 October 2018 © The Author(s) 2018 Abstract This survey is motivated by specific questions arising in the similarities and contrasts between (Baire) category and (Lebesgue) measure—category-measure duality and non-duality, as it were. The bulk of the text is devoted to a summary, intended for the working analyst, of the extensive background in set theory and logic needed to discuss such matters: to quote from the preface of Kelley (General Topology, Van Nostrand, Toronto, 1995): “what every young analyst should know”. Keywords Axiom of choice · Dependent choice · Model theory · Constructible hierarchy · Ultraproducts · Indiscernibles · Forcing · Martin’s axiom · Analytical hierarchy · Determinacy and large cardinals · Structure of the real line · Category and measure Mathematics Subject Classification 03E15 · 03E25 · 03E30 · 03E35 · 03E55 · 01A60 · 01A61 B Adam J. Ostaszewski [email protected] Nicholas H. Bingham [email protected] 1 Mathematics Department, Imperial College, London SW7 2AZ, UK 2 Mathematics Department, London School of Economics, Houghton Street, London WC2A 2AE, UK 123 Set theory and the analyst 3 Contents 1 Introduction ............................................ -
Combinatorial Geometry and Its Algorithmic Applications the Alcalá Lectures
Mathematical Surveys and Monographs Volume 152 Combinatorial Geometry and Its Algorithmic Applications The Alcalá Lectures János Pach Micha Sharir American Mathematical Society http://dx.doi.org/10.1090/surv/152 Combinatorial Geometry and Its Algorithmic Applications The Alcalá Lectures Mathematical Surveys and Monographs Volume 152 Combinatorial Geometry and Its Algorithmic Applications The Alcalá Lectures János Pach Micha Sharir American Mathematical Society Providence, Rhode Island EDITORIAL COMMITTEE Jerry L. Bona Michael G. Eastwood Ralph L. Cohen J. T. Stafford, Chair Benjamin Sudakov 2000 Mathematics Subject Classification. Primary 05C35, 05C62, 52C10, 52C30, 52C35, 52C45, 68Q25, 68R05, 68W05, 68W20. For additional information and updates on this book, visit www.ams.org/bookpages/surv-152 Library of Congress Cataloging-in-Publication Data Pach, Janos. Combinatorial geometry and its algorithmic applications : The Alcala lectures / Janos Pach, Micha Sharir. p. cm. — (Mathematical surveys and monographs ; v. 152) Includes bibliographical references and index. ISBN 978-0-8218-4691-9 (alk. paper) 1. Combinatorial geometry. 2. Algorithms. I. Sharir, Micha. II. Title. QA167.p332 2009 516.13–dc22 2008038876 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 a chapter for use in teaching or research. Permission is granted to quote brief passages from this publication in reviews, provided the customary acknowledgment of the source is given. Republication, systematic copying, or multiple reproduction of any material in this publication is permitted only under license from the American Mathematical Society. Requests for such permission should be addressed to the Acquisitions Department, American Mathematical Society, 201 Charles Street, Providence, Rhode Island 02904-2294, USA. -
Wheel Graph Ramsey Numbers
J. Math. and Its Appl. ISSN: 1829-605X Vol. 2, No. 2, Nov 2005, 61–69 Some Known Results and an Open Problem of Tree - Wheel Graph Ramsey Numbers Surahmat Department of Mathematics Education Universitas Islam Malang Jalan MT Haryono 193, Malang 65144,Indonesia [email protected] Abstract There are many famous problems on finding a regular substructure in a sufficiently large combinatorial structure, one of them i.e. Ramsey numbers. In this paper we list some known results and an open problem on graph Ramsey numbers. In the special cases, we list to determine graph Ramsey numbers for trees versus wheels. Keywords: Ramsey number, tree, wheel 1. Introduction Before we present about graph Ramsey numbers, we rewrite the story of classical Ramsey numbers in [26] as follows. ”The origins of Ramsey theory are diffuse. Frank Plumton Ramsey [23] was interested in decision procedures for logical systems. Issai Schur wanted to solve Fermats last theorem over finite fields. B.L. van der Waerden solved an amusing problem and immediately returned to his researches in algebraic geometry. The 61 62 Some Known Results and an Open Problem of Tree - Wheel Graph Ramsey Numbers emergence of Ramsey theory as a cohesive subdiscipline of combinatorial analysis occurred only in the last decade, see [14]. Issai Schur[25] proved the first theorem of what was later to be called Ramsey theory in 1916. He proved that: For every r ∈ N there exists an n ∈ N such that, given an arbitrary r−coloring of S = {1, 2, . , n}; there exist x, y, z ∈ S all the same color, satisfying x + y = z. -
Reflections on Paul Erd˝Os on His Birth Centenary
Reflections on Paul Erd˝os on His Birth Centenary Krishnaswami Alladi and Steven Krantz, Coordinating Editors This is Part I of a two-part feature on Paul Erd˝osfollowing his centennial. There are eleven articles by leading experts who have reflected on the remarkable life, contributions, and influence of this towering figure of twentieth century mathematics. Here in Part I we have contributions from Krishnaswami Alladi and Steven Krantz, László Lovász and Vera T. Sós, Ronald Graham and Joel Spencer, Jean-Pierre Kahane, and Mel Nathanson. Part II will contain articles by Noga Alon, Dan Goldston, András Sárközy, József Szabados, Gérald Tenenbaum, and Stephan Garcia and Amy Shoemaker. Krishnaswami Alladi and Steven Krantz One of the Most Influential Mathematicians of Our Time The 100th birth anniversary of the great Hun- garian mathematician Paul Erd˝oswas celebrated in Budapest in July 2013 with an international conference that attracted about 750 participants. Erd˝oswas one of the most influential mathemati- cians of the twentieth century for a variety of reasons. He made fundamental and pioneering contributions in several fields of mathematics, such as number theory, combinatorics, graph theory, analysis, geometry, and set theory. He was perhaps the most prolific mathematician in history after Euler, with more than 1,500 papers, but what was most interesting about this was that more than half of these were joint papers and many of his collaborators were very young. Thus through the fundamental ideas in his papers and through these Courtesy of Harold Diamond Krishnaswami Alladi is professor of mathematics at the Uni- Paul Erd˝osworking in his office at the Hungarian versity of Florida. -
Erdös and Set Theory
Erd}osand Set Theory Akihiro Kanamori October 9, 2014 Paul Erd}os(26 March 1913 - 20 September 1996) was a mathematician par excellence whose results and initiatives have had a large impact and made a strong imprint on the doing of and thinking about mathematics. A mathemati- cian of alacrity, detail, and collaboration, Erd}osin his six decades of work moved and thought quickly, entertained increasingly many parameters, and wrote over 1500 articles, the majority with others. His modus operandi was to drive mathe- matics through cycles of problem, proof, and conjecture, ceaselessly progressing and ever reaching, and his modus vivendi was to be itinerant in the world, stimulating and interacting about mathematics at every port and capital. Erd}os'main mathematical incentives were to count, to estimate, to bound, to interpolate, and to get at the extremal or delimiting, and his main em- phases were on elementary and random methods. These had a broad reach across mathematics but was particularly synergistic with the fields that Erd}os worked in and developed. His mainstays were formerly additive and multiplica- tive number theory and latterly combinatorics and graph theory, but he ranged across and brought in probability and ergodic theory, the constructive theory of functions and series, combinatorial geometry, and set theory. He had a prin- cipal role in establishing probabilistic number theory, extremal combinatorics, random graphs, and the partition calculus for infinite cardinals. Against this backdrop, this article provides an account of Erd}os'work and initiatives in set theory with stress put on their impact on the subject. Erd}os importantly contributed to set theory as it became a broad, sophisticated field of mathematics in two dynamic ways.