Discrete Geometry and Algebraic Combinatorics
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Algebraic Combinatorics and Finite Geometry
An Introduction to Algebraic Graph Theory Erdos-Ko-Rado˝ results Cameron-Liebler sets in PG(3; q) Cameron-Liebler k-sets in PG(n; q) Algebraic Combinatorics and Finite Geometry Leo Storme Ghent University Department of Mathematics: Analysis, Logic and Discrete Mathematics Krijgslaan 281 - Building S8 9000 Ghent Belgium Francqui Foundation, May 5, 2021 Leo Storme Algebraic Combinatorics and Finite Geometry An Introduction to Algebraic Graph Theory Erdos-Ko-Rado˝ results Cameron-Liebler sets in PG(3; q) Cameron-Liebler k-sets in PG(n; q) ACKNOWLEDGEMENT Acknowledgement: A big thank you to Ferdinand Ihringer for allowing me to use drawings and latex code of his slide presentations of his lectures for Capita Selecta in Geometry (Ghent University). Leo Storme Algebraic Combinatorics and Finite Geometry An Introduction to Algebraic Graph Theory Erdos-Ko-Rado˝ results Cameron-Liebler sets in PG(3; q) Cameron-Liebler k-sets in PG(n; q) OUTLINE 1 AN INTRODUCTION TO ALGEBRAIC GRAPH THEORY 2 ERDOS˝ -KO-RADO RESULTS 3 CAMERON-LIEBLER SETS IN PG(3; q) 4 CAMERON-LIEBLER k-SETS IN PG(n; q) Leo Storme Algebraic Combinatorics and Finite Geometry An Introduction to Algebraic Graph Theory Erdos-Ko-Rado˝ results Cameron-Liebler sets in PG(3; q) Cameron-Liebler k-sets in PG(n; q) OUTLINE 1 AN INTRODUCTION TO ALGEBRAIC GRAPH THEORY 2 ERDOS˝ -KO-RADO RESULTS 3 CAMERON-LIEBLER SETS IN PG(3; q) 4 CAMERON-LIEBLER k-SETS IN PG(n; q) Leo Storme Algebraic Combinatorics and Finite Geometry An Introduction to Algebraic Graph Theory Erdos-Ko-Rado˝ results Cameron-Liebler sets in PG(3; q) Cameron-Liebler k-sets in PG(n; q) DEFINITION A graph Γ = (X; ∼) consists of a set of vertices X and an anti-reflexive, symmetric adjacency relation ∼ ⊆ X × X. -
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. -
GL(N, Q)-Analogues of Factorization Problems in the Symmetric Group Joel Brewster Lewis, Alejandro H
GL(n, q)-analogues of factorization problems in the symmetric group Joel Brewster Lewis, Alejandro H. Morales To cite this version: Joel Brewster Lewis, Alejandro H. Morales. GL(n, q)-analogues of factorization problems in the sym- metric group. 28-th International Conference on Formal Power Series and Algebraic Combinatorics, Simon Fraser University, Jul 2016, Vancouver, Canada. hal-02168127 HAL Id: hal-02168127 https://hal.archives-ouvertes.fr/hal-02168127 Submitted on 28 Jun 2019 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. FPSAC 2016 Vancouver, Canada DMTCS proc. BC, 2016, 755–766 GLn(Fq)-analogues of factorization problems in Sn Joel Brewster Lewis1y and Alejandro H. Morales2z 1 School of Mathematics, University of Minnesota, Twin Cities 2 Department of Mathematics, University of California, Los Angeles Abstract. We consider GLn(Fq)-analogues of certain factorization problems in the symmetric group Sn: rather than counting factorizations of the long cycle (1; 2; : : : ; n) given the number of cycles of each factor, we count factorizations of a regular elliptic element given the fixed space dimension of each factor. We show that, as in Sn, the generating function counting these factorizations has attractive coefficients after an appropriate change of basis. -
Geometric Representations of Graphs
1 Geometric Representations of Graphs Laszl¶ o¶ Lovasz¶ Microsoft Research One Microsoft Way, Redmond, WA 98052 e-mail: [email protected] 2 Contents I Background 5 1 Eigenvalues of graphs 7 1.1 Matrices associated with graphs ............................ 7 1.2 The largest eigenvalue ................................. 8 1.2.1 Adjacency matrix ............................... 8 1.2.2 Laplacian .................................... 9 1.2.3 Transition matrix ................................ 9 1.3 The smallest eigenvalue ................................ 9 1.4 The eigenvalue gap ................................... 11 1.4.1 Expanders .................................... 12 1.4.2 Random walks ................................. 12 1.5 The number of di®erent eigenvalues .......................... 17 1.6 Eigenvectors ....................................... 19 2 Convex polytopes 21 2.1 Polytopes and polyhedra ................................ 21 2.2 The skeleton of a polytope ............................... 21 2.3 Polar, blocker and antiblocker ............................. 22 II Representations of Planar Graphs 25 3 Planar graphs and polytopes 27 3.1 Planar graphs ...................................... 27 3.2 Straight line representation and 3-polytopes ..................... 28 4 Rubber bands, cables, bars and struts 29 4.1 Rubber band representation .............................. 29 4.1.1 How to draw a graph? ............................. 30 4.1.2 How to lift a graph? .............................. 32 4.1.3 Rubber bands and connectivity ....................... -
Digital and Discrete Geometry Li M
Digital and Discrete Geometry Li M. Chen Digital and Discrete Geometry Theory and Algorithms 2123 Li M. Chen University of the District of Columbia Washington District of Columbia USA ISBN 978-3-319-12098-0 ISBN 978-3-319-12099-7 (eBook) DOI 10.1007/978-3-319-12099-7 Springer Cham Heidelberg New York Dordrecht London Library of Congress Control Number: 2014958741 © Springer International Publishing Switzerland 2014 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, 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. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com) To the researchers and their supporters in Digital Geometry and Topology. -
Eigenvalues of Graphs
Eigenvalues of graphs L¶aszl¶oLov¶asz November 2007 Contents 1 Background from linear algebra 1 1.1 Basic facts about eigenvalues ............................. 1 1.2 Semide¯nite matrices .................................. 2 1.3 Cross product ...................................... 4 2 Eigenvalues of graphs 5 2.1 Matrices associated with graphs ............................ 5 2.2 The largest eigenvalue ................................. 6 2.2.1 Adjacency matrix ............................... 6 2.2.2 Laplacian .................................... 7 2.2.3 Transition matrix ................................ 7 2.3 The smallest eigenvalue ................................ 7 2.4 The eigenvalue gap ................................... 9 2.4.1 Expanders .................................... 10 2.4.2 Edge expansion (conductance) ........................ 10 2.4.3 Random walks ................................. 14 2.5 The number of di®erent eigenvalues .......................... 16 2.6 Spectra of graphs and optimization .......................... 18 Bibliography 19 1 Background from linear algebra 1.1 Basic facts about eigenvalues Let A be an n £ n real matrix. An eigenvector of A is a vector such that Ax is parallel to x; in other words, Ax = ¸x for some real or complex number ¸. This number ¸ is called the eigenvalue of A belonging to eigenvector v. Clearly ¸ is an eigenvalue i® the matrix A ¡ ¸I is singular, equivalently, i® det(A ¡ ¸I) = 0. This is an algebraic equation of degree n for ¸, and hence has n roots (with multiplicity). The trace of the square matrix A = (Aij ) is de¯ned as Xn tr(A) = Aii: i=1 1 The trace of A is the sum of the eigenvalues of A, each taken with the same multiplicity as it occurs among the roots of the equation det(A ¡ ¸I) = 0. If the matrix A is symmetric, then its eigenvalues and eigenvectors are particularly well behaved. -
SEMIGROUP ALGEBRAS and DISCRETE GEOMETRY By
S´eminaires & Congr`es 6, 2002, p. 43–127 SEMIGROUP ALGEBRAS AND DISCRETE GEOMETRY by Winfried Bruns & Joseph Gubeladze Abstract.— In these notes we study combinatorial and algebraic properties of affine semigroups and their algebras:(1) the existence of unimodular Hilbert triangulations and covers for normal affine semigroups, (2) the Cohen–Macaulay property and num- ber of generators of divisorial ideals over normal semigroup algebras, and (3) graded automorphisms, retractions and homomorphisms of polytopal semigroup algebras. Contents 1.Introduction .................................................... 43 2.Affineandpolytopalsemigroupalgebras ........................ 44 3.Coveringandnormality ........................................ 54 4.Divisoriallinearalgebra ........................................ 70 5.Fromvectorspacestopolytopalalgebras ...................... 88 Index ..............................................................123 References ........................................................125 1. Introduction These notes, composed for the Summer School on Toric Geometry at Grenoble, June/July 2000, contain a major part of the joint work of the authors. In Section 3 we study a problemthat clearly belongs to the area of discrete ge- ometry or, more precisely, to the combinatorics of finitely generated rational cones and their Hilbert bases. Our motivation in taking up this problem was the attempt 2000 Mathematics Subject Classification.—13C14, 13C20, 13F20, 14M25, 20M25, 52B20. Key words and phrases.—Affine semigroup, lattice polytope, -
Discrete Differential Geometry
Oberwolfach Seminars Volume 38 Discrete Differential Geometry Alexander I. Bobenko Peter Schröder John M. Sullivan Günter M. Ziegler Editors Birkhäuser Basel · Boston · Berlin Alexander I. Bobenko John M. Sullivan Institut für Mathematik, MA 8-3 Institut für Mathematik, MA 3-2 Technische Universität Berlin Technische Universität Berlin Strasse des 17. Juni 136 Strasse des 17. Juni 136 10623 Berlin, Germany 10623 Berlin, Germany e-mail: [email protected] e-mail: [email protected] Peter Schröder Günter M. Ziegler Department of Computer Science Institut für Mathematik, MA 6-2 Caltech, MS 256-80 Technische Universität Berlin 1200 E. California Blvd. Strasse des 17. Juni 136 Pasadena, CA 91125, USA 10623 Berlin, Germany e-mail: [email protected] e-mail: [email protected] 2000 Mathematics Subject Classification: 53-02 (primary); 52-02, 53-06, 52-06 Library of Congress Control Number: 2007941037 Bibliographic information published by Die Deutsche Bibliothek Die Deutsche Bibliothek lists this publication in the Deutsche Nationalbibliografie; detailed bibliographic data is available in the Internet at <http://dnb.ddb.de>. ISBN 978-3-7643-8620-7 Birkhäuser Verlag, Basel – Boston – Berlin 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, re-use of illustrations, recitation, broadcasting, reproduction on microfilms or in other ways, and storage in data banks. For any kind of use permission of the copyright -
Handbook of Discrete and Computational Geometry
Handbook Of Discrete And Computational Geometry If smartish or unimpaired Clarence usually quilts his pricking cubes undauntedly or admitted homologous and carelessly, how unobserved is Glenn? Undocumented and orectic Munmro never jewelling impermanently when Randie souse his oppidans. Murderous Terrel mizzles attentively. How is opening soon grocery bag body from nothing a cost box? Discrepancy theory is also called the theory of irregularities of distribution. Discrete geometry has contributed signi? Ashley is a puff of Bowdoin College and received her Master of Public Administration from Columbia University. Over one or discrete and of computational geometry address is available on the advantage of. Our systems have detected unusual traffic from your computer network. Select your payment to handbook of discrete computational and geometry, and computational geometry, algebraic topology play in our courier partners team is based on local hiring. Contact support legal notice must quantify the content update: experts on an unnecessary complication at microsoft store your profile that of discrete computational geometry and similar problems. This hop been fueled partly by the advent of powerful computers and plumbing the recent explosion of activity in the relatively young most of computational geometry. Face Numbers of Polytopes and Complexes. Sometimes staff may be asked to alert the CAPTCHA if yourself are using advanced terms that robots are fail to read, or sending requests very quickly. We do not the firm, you have made their combinatorial and computational geometry intersects with an incorrect card expire shortly after graduate of such tables. Computational Real Algebraic Geometry. In desert you entered the wrong GST details while placing the page, you can choose to cancel it is place a six order with only correct details. -
Discrete Topology and Geometry Algorithms for Quantitative Human Airway Trees Analysis Based on Computed Tomography Images Michal Postolski
Discrete topology and geometry algorithms for quantitative human airway trees analysis based on computed tomography images Michal Postolski To cite this version: Michal Postolski. Discrete topology and geometry algorithms for quantitative human airway trees analysis based on computed tomography images. Other. Université Paris-Est, 2013. English. NNT : 2013PEST1094. pastel-00977514 HAL Id: pastel-00977514 https://pastel.archives-ouvertes.fr/pastel-00977514 Submitted on 11 Apr 2014 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. PARIS-EST UNIVERSITY DOCTORAL SCHOOL MSTIC A thesis submitted in partial fulfillment for the degree of Doctor of Philosophy in Computer Science Presented by Michal Postolski Supervised by Michel Couprie and Dominik Sankowski Discrete Topology and Geometry Algorithms for Quantitative Human Airway Trees Analysis Based on Computed Tomography Images December 18, 2013 Committee in charge: Piotr Kulczycki (reviewer) Nicolas Normand (reviewer) Nicolas Passat (reviewer) Jan Sikora (reviewer) Michel Couprie Yukiko Kenmochi Andrzej Napieralski Dominik Sankowski To my brilliant wife. ii Title: Discrete Topology and Geometry Algorithms for Quantitative Human Airway Trees Analysis Based on Computed Tomography Images. Abstract: Computed tomography is a very useful technique which allow non-invasive diagnosis in many applications for example is used with success in industry and medicine. -
Algebraic Combinatorics
ALGEBRAIC COMBINATORICS c C D Go dsil To Gillian Preface There are p eople who feel that a combinatorial result should b e given a purely combinatorial pro of but I am not one of them For me the most interesting parts of combinatorics have always b een those overlapping other areas of mathematics This b o ok is an intro duction to some of the interac tions b etween algebra and combinatorics The rst half is devoted to the characteristic and matchings p olynomials of a graph and the second to p olynomial spaces However anyone who lo oks at the table of contents will realise that many other topics have found their way in and so I expand on this summary The characteristic p olynomial of a graph is the characteristic p olyno matrix The matchings p olynomial of a graph G with mial of its adjacency n vertices is b n2c X k n2k G k x p k =0 where pG k is the numb er of k matchings in G ie the numb er of sub graphs of G formed from k vertexdisjoint edges These denitions suggest that the characteristic p olynomial is an algebraic ob ject and the matchings p olynomial a combinatorial one Despite this these two p olynomials are closely related and therefore they have b een treated together In devel oping their theory we obtain as a bypro duct a numb er of results ab out orthogonal p olynomials The numb er of p erfect matchings in the comple ment of a graph can b e expressed as an integral involving the matchings by which we p olynomial This motivates the study of moment sequences mean sequences of combinatorial interest which can b e represented -
Introduction to Algebraic Combinatorics: (Incomplete) Notes from a Course Taught by Jennifer Morse
INTRODUCTION TO ALGEBRAIC COMBINATORICS: (INCOMPLETE) NOTES FROM A COURSE TAUGHT BY JENNIFER MORSE GEORGE H. SEELINGER These are a set of incomplete notes from an introductory class on algebraic combinatorics I took with Dr. Jennifer Morse in Spring 2018. Especially early on in these notes, I have taken the liberty of skipping a lot of details, since I was mainly focused on understanding symmetric functions when writ- ing. Throughout I have assumed basic knowledge of the group theory of the symmetric group, ring theory of polynomial rings, and familiarity with set theoretic constructions, such as posets. A reader with a strong grasp on introductory enumerative combinatorics would probably have few problems skipping ahead to symmetric functions and referring back to the earlier sec- tions as necessary. I want to thank Matthew Lancellotti, Mojdeh Tarighat, and Per Alexan- dersson for helpful discussions, comments, and suggestions about these notes. Also, a special thank you to Jennifer Morse for teaching the class on which these notes are based and for many fruitful and enlightening conversations. In these notes, we use French notation for Ferrers diagrams and Young tableaux, so the Ferrers diagram of (5; 3; 3; 1) is We also frequently use one-line notation for permutations, so the permuta- tion σ = (4; 3; 5; 2; 1) 2 S5 has σ(1) = 4; σ(2) = 3; σ(3) = 5; σ(4) = 2; σ(5) = 1 0. Prelimaries This section is an introduction to some notions on permutations and par- titions. Most of the arguments are given in brief or not at all. A familiar reader can skip this section and refer back to it as necessary.