STUDENT MATHEMATICAL LIBRARY Volume 75 Mathematics++ Selected Topics Beyond the Basic Courses
Ida Kantor Jirˇí Matousˇek Robert ˇSámal Mathematics++ Selected Topics Beyond the Basic Courses
http://dx.doi.org/10.1090/stml/075
STUDENT MATHEMATICAL LIBRARY Volume 75
Mathematics++ Selected Topics Beyond the Basic Courses
Ida Kantor Jirˇí Matousˇek Robert Sˇámal
American Mathematical Society Providence, Rhode Island Editorial Board Satyan L. Devadoss John Stillwell (Chair) Erica Flapan Serge Tabachnikov
2010 Mathematics Subject Classification. Primary 14-01; 20Cxx, 28-01, 43-01, 52Axx, 54-01, 55-01.
For additional information and updates on this book, visit www.ams.org/bookpages/stml-75
Library of Congress Cataloging-in-Publication Data Kantor, Ida, 1981- Mathematics++ : selected topics beyond the basic courses / Ida Kantor, Jiˇr´ı Matouˇsek, Robert S´ˇamal. pages cm. – (Student mathematical library ; volume 75) Includes bibliographical references and index. ISBN 978-1-4704-2261-5 (alk. paper) 1. Mathematics–Study and teaching (Graduate) 2. Computer science– Mathematics. I. Matouˇsek, Jiˇr´ı, 1963–2015 II. S´ˇamal, Robert, 1977- III. Title. QA11.2.K36 2015 510–dc23 2015016136
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Preface ix
Chapter 1. Measure and Integral 1 §1. Measure 6 §2. The Lebesgue Integral 22 §3. Foundations of Probability Theory 31 §4. Literature 36 Bibliography 37
Chapter 2. High-Dimensional Geometry and Measure Concentration 39 §1. Peculiarities of Large Dimensions 41 §2. The Brunn–Minkowski Inequality and Euclidean Isoperimetry 44 §3. The Standard Normal Distribution and the Gaussian Measure 53 §4. Measure Concentration 61 §5. Literature 81 Bibliography 82
Chapter 3. Fourier Analysis 85 §1. Characters 87 §2. The Fourier Transform 94
v vi Contents
§3. Two Unexpected Applications 99 §4. Convolution 106 §5. Poisson Summation Formula 109 §6. Influence of Variables 113 §7. Infinite Groups 124 §8. Literature 137 Bibliography 138
Chapter 4. Representations of Finite Groups 141 §1. Basic Definitions and Examples 142 §2. Decompositions into Irreducible Representations 145 §3. Irreducible Decompositions, Characters, Orthogonality 150 §4. Irreducible Representations of the Symmetric Group 160 §5. An Application in Communication Complexity 163 §6. More Applications and Literature 168 Bibliography 169
Chapter 5. Polynomials 173 §1. Rings, Fields, and Polynomials 173 §2. The Schwartz–Zippel Theorem 175 §3. Polynomial Identity Testing 176 §4. Interpolation, Joints, and Contagious Vanishing 180 §5. Varieties, Ideals, and the Hilbert Basis Theorem 185 §6. The Nullstellensatz 188 §7. B´ezout’s Inequality in the Plane 195 §8. More Properties of Varieties 200 §9. B´ezout’s Inequality in Higher Dimensions 219 §10. Bounding the Number of Connected Components 226 §11. Literature 232 Bibliography 232 Contents vii
Chapter 6. Topology 235 §1. Topological Spaces and Continuous Maps 236 §2. Bits of General Topology 240 §3. Compactness 247 §4. Homotopy and Homotopy Equivalence 253 §5. The Borsuk–Ulam Theorem 257 §6. Operations on Topological Spaces 262 §7. Simplicial Complexes and Relatives 271 §8. Non-embeddability 283 §9. Homotopy Groups 289 §10. Homology of Simplicial Complexes 301 §11. Simplicial Approximation 309 §12. Homology Does Not Depend on Triangulation 314 §13. A Quick Harvest and Two More Theorems 318 §14. Manifolds 321 §15. Literature 330 Bibliography 330
Index 333
Preface
This book introduces six selected areas of mostly 20th century math- ematics. We assume that the reader has gone through the usual un- dergraduate courses and is used to rigorous presentation with proofs. Mathematics is beautiful, and useful all over, but extensive. Even in computer science, one of the most mathematical fields besides mathematics itself, university curricula mostly teach only mathemat- ics developed prior to the 20th century (with the exception of areas more directly related to computing, such as logic or discrete mathe- matics). This is not because of lack of modernity, but because build- ing proper foundations takes a lot of time and there is hardly room for anything else, even when the mathematical courses occupy the maximum politically acceptable part of the curriculum. This observation was the starting point of a project resulting in this book. Contemporary research in computer science (but in other fields as well) uses numerous mathematical tools not covered in the basic courses. We had the experience of struggling with papers containing mathematical terminology unknown to us, and we saw a number of other people having similar problems. We decided to teach a course, mainly for Ph.D. students of the- oretical computer science, introducing various mathematical areas in a concise and accessible way. With expected periodicity of three semesters, the course covered one to three areas per semester.
ix x Preface
This book is a significantly extended version of our lecture notes. In six chapters, it deals with measure theory, high-dimensional geom- etry, Fourier analysis, representations of groups, multivariate poly- nomials (or, in fancier terms, rudimentary algebraic geometry), and topology. The chapters are independent of one another and can be studied in any order. In the selection of the areas, the reader has to rely on our expe- rience and opinions (although we have also asked colleagues and stu- dents what they would consider most helpful for their work). This, of course, is subjective and someone else would perhaps recommend dif- ferent areas, but we believe that it is at least a reasonable suggestion— and better than no suggestion.1 For each of the areas, we aim at presenting basic notions, basic examples, and basic results. Exercises form an integral part of the presentation, since we believe that the only way of really grasping sophisticated notions is to actively work with them. Results too ad- vanced to be developed rigorously in a limited space but too nice to be omitted are described, sometimes slightly informally, in encyclopedia- like passages. Since our goal was an introductory textbook, we try to keep ci- tations to a (reasonable) minimum. We also do not always recall notions that are usually treated on undergraduate level, since we do notwanttoclutterthetext,andsincenowadaysitiseasytolook up definitions in trustworthy Internet resources—which we encourage the readers to do when in doubt. There is only so much information one can fit in a single chapter; moreover, we do not try to write as compactly as possible, preferring accessibility. Even this limited amount of knowledge can often be sufficient—as a rule, among results and notions in a given field, the simpler ones have a greater chance to be applied in other fields than the advanced and fancy ones.
1There is a small Internet company, whose main component is apparently an ex- perienced man scanning and reading lots of articles from world’s leading periodicals every day. For a modest yearly fee, the company then provides access to his recommen- dations of most interesting and important articles. We believe that, when practically any opinion can be “confirmed” by some Internet pages, such trust-based services will become more and more valuable. Preface xi
Once it becomes clear that one needs to know more, one can go the “standard” way, i.e., to take a full-fledged course for math- ematicians or to study a textbook. This represents a considerably greater time investment, though, and very few people have the time and energy to pursue this approach for more than two or three areas. A possible suggestion of what to add to our list of topics is prob- ability theory. However, we believe that probability is so crucial and widely used that it is definitely worth taking a course of one, or better, two semesters.
Prerequisites. As was mentioned above, we assume that the reader has gone through the basic mathematical courses with rigorous de- velopment, including proofs. Sometimes we use bits of mathematical analysis, discrete mathematics, and very basic probability, but by far the most important background we expect is linear algebra, includ- ing vector spaces and linear maps—indeed, in current research, one encounters linear algebra at every corner.
Readership. Our course was targeted at Ph.D. students in theoret- ical computer science and in discrete mathematics; the applications we present are drawn from these areas. However, the book can be useful for a much wider audience, such as mathematicians specialized in other areas, mathematics students deciding what specialization to pursue and/or preparing for gradu- ate school, or experts in engineering or other fields using advanced mathematics. Readers not familiar with the topics of our examples are invited to look at them, but if they find some of them incompre- hensible, they are free to skip such parts.
Conventions. The main notions are set in boldface,lessimpor- tant or only tangentially mentioned ones in italics.Exercisesarein- terspersed through the text, and each ends with the symbol. In the index, you will find “Fubini’s theorem” both under T and under F. Mathematical symbols beginning with fixed letters, such as Bn or GL(n, R) are indexed alphabetically. Notation including special sym- ∼ ∼ bols, such as X = Y or [X] (note that we may also have A = Z or R[Y ], so no letters are fixed), and Greek letters are listed at the beginning of the index. xii Preface
Acknowledgments. Since the chapters are self-contained, we have usually asked people to read through just one, and accordingly, most acknowledgments are postponed to the ends of the chapters. Globally we would like to thank Tom´aˇs Toufar for proofreading the almost-finished book. Despite the efforts, no book is ever perfect. We would appreci- ate to learn about mistakes and suggestions of how to improve the exposition. It was a great pleasure to work with people from the AMS Pub- lishing. Especially Ina Mette was incredibly helpful, and Barbara Beeton was a model of an efficient TEXexpert. We dedicate this book to our families. Index
D f dμ,25 πk(X)(k-th homotopy group), 297 x (Euclidean norm), 41 σ-algebra, 12 At (t-neighborhood), 47 σ-field, 12 u, v (inner product), 87 σ-finite measure, 30 u (norm), 87 V ⊕ W (direct sum), 146 V ⊗ W (tensor product), 149 abstract nonsense, 271 R[x1,...,xn] (polynomial ring), additivity 174 countable, 8 F F √ (ideal generated by ), 186 finite, 8 I (radical), 190 affine variety, 185