Reflection Groups in Algebraic Geometry
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Hyperbolic Reflection Groups
Uspekhi Mat. N auk 40:1 (1985), 29 66 Russian Math. Surveys 40:1 (1985), 31 75 Hyperbolic reflection groups E.B. Vinberg CONTENTS Introduction 31 Chapter I. Acute angled polytopes in Lobachevskii spaces 39 § 1. The G ram matrix of a convex polytope 39 §2. The existence theorem for an acute angled polytope with given Gram 42 matrix §3. Determination of the combinatorial structure of an acute angled 46 polytope from its Gram matrix §4. Criteria for an acute angled polytope to be bounded and to have finite 50 volume Chapter II. Crystallographic reflection groups in Lobachevskii spaces 57 §5. The language of Coxeter schemes. Construction of crystallographic 57 reflection groups §6. The non existence of discrete reflection groups with bounded 67 fundamental polytope in higher dimensional Lobachevskii spaces References 71 Introduction 1. Let X" be the « dimensional Euclidean space Ε", the « dimensional sphere S", or the « dimensional Lobachevskii space Λ". A convex polytope PCX" bounded by hyperplanes //,·, i G / , is said to be a Coxeter polytope if for all /, / G / , i Φ j, the hyperplanes //, and Hj are disjoint or form a dihedral angle of π/rijj, wh e r e «,y G Ζ and η,γ > 2. (We have in mind a dihedral angle containing P.) If Ρ is a Coxeter polytope, then the group Γ of motions of X" generated by the reflections Λ, in the hyperplanes Hj is discrete, and Ρ is a fundamental polytope for it. This means that the polytopes yP, y G Γ, do not have pairwise common interior points and cover X"; that is, they form a tessellation for X". -
3.4 Finite Reflection Groups In
Chapter 3 Equations of order 2 This chapter is mostly devoted to Fuchsian equations L(y)=0oforder2.For these equations we shall describe all finite monodromy groups that are possible. In particular we discuss the projective monodromy groups of dimension 2. Most of the theory we give is based on the work of Felix Klein and of G.C. Shephard and J.A. Todd. Unless stated otherwise we let L(y)=0beaFuchsiandifferential equation order 2, with differentiation with respect to the variable z. 3.1 Finite subgroups of PGL(2, C) Any Fuchsian differential equation with a basis of algebraic solutions has a finite monodromy group, (and vice versa, see Theorem 2.1.8). In particular this is the case for second order Fuchsian equations, to which we restrict ourselves for now. The monodromy group for such an equation is contained in GL(2, C). Any subgroup G ⊂ GL(2, C) acts on the Riemann sphere P1. More specifically, a matrix γ ∈ GL(2, C)with ab γ := cd has an action on C defined as at + b γ ∗ t := . (3.1) ct + d for all appropriate t ∈ C. The action is extended to P1 by γ ∗∞ = a/c in the case of ac =0and γ ∗ (−d/c)=∞ when c is non-zero. The action of G on P1 factors through to the projective group PG ⊂ PGL(2, C). In other words we have the well-defined action PG : P1 → P1 γ · ΛI2 : t → γ ∗ t. 39 40 Chapter 3. Equations of order 2 PG name |PG| Cm Cyclic group m Dm Dihedral group 2m A4 Tetrahedral group 12 (Alternating group on 4 elements) S4 Octahedral group 24 (Symmetric group on 4 elements) A5 Icosahedral group 60 (Alternating group on 5 elements) Table 3.1: The finite subgroups of PGL(2, C). -
Enhancing Self-Reflection and Mathematics Achievement of At-Risk Urban Technical College Students
Psychological Test and Assessment Modeling, Volume 53, 2011 (1), 108-127 Enhancing self-reflection and mathematics achievement of at-risk urban technical college students Barry J. Zimmerman1, Adam Moylan2, John Hudesman3, Niesha White3, & Bert Flugman3 Abstract A classroom-based intervention study sought to help struggling learners respond to their academic grades in math as sources of self-regulated learning (SRL) rather than as indices of personal limita- tion. Technical college students (N = 496) in developmental (remedial) math or introductory col- lege-level math courses were randomly assigned to receive SRL instruction or conventional in- struction (control) in their respective courses. SRL instruction was hypothesized to improve stu- dents’ math achievement by showing them how to self-reflect (i.e., self-assess and adapt to aca- demic quiz outcomes) more effectively. The results indicated that students receiving self-reflection training outperformed students in the control group on instructor-developed examinations and were better calibrated in their task-specific self-efficacy beliefs before solving problems and in their self- evaluative judgments after solving problems. Self-reflection training also increased students’ pass- rate on a national gateway examination in mathematics by 25% in comparison to that of control students. Key words: self-regulation, self-reflection, math instruction 1 Correspondence concerning this article should be addressed to: Barry Zimmerman, PhD, Graduate Center of the City University of New York and Center for Advanced Study in Education, 365 Fifth Ave- nue, New York, NY 10016, USA; email: [email protected] 2 Now affiliated with the University of California, San Francisco, School of Medicine 3 Graduate Center of the City University of New York and Center for Advanced Study in Education Enhancing self-reflection and math achievement 109 Across America, faculty and policy makers at two-year and technical colleges have been deeply troubled by the low academic achievement and high attrition rate of at-risk stu- dents. -
Reflection Invariant and Symmetry Detection
1 Reflection Invariant and Symmetry Detection Erbo Li and Hua Li Abstract—Symmetry detection and discrimination are of fundamental meaning in science, technology, and engineering. This paper introduces reflection invariants and defines the directional moments(DMs) to detect symmetry for shape analysis and object recognition. And it demonstrates that detection of reflection symmetry can be done in a simple way by solving a trigonometric system derived from the DMs, and discrimination of reflection symmetry can be achieved by application of the reflection invariants in 2D and 3D. Rotation symmetry can also be determined based on that. Also, if none of reflection invariants is equal to zero, then there is no symmetry. And the experiments in 2D and 3D show that all the reflection lines or planes can be deterministically found using DMs up to order six. This result can be used to simplify the efforts of symmetry detection in research areas,such as protein structure, model retrieval, reverse engineering, and machine vision etc. Index Terms—symmetry detection, shape analysis, object recognition, directional moment, moment invariant, isometry, congruent, reflection, chirality, rotation F 1 INTRODUCTION Kazhdan et al. [1] developed a continuous measure and dis- The essence of geometric symmetry is self-evident, which cussed the properties of the reflective symmetry descriptor, can be found everywhere in nature and social lives, as which was expanded to 3D by [2] and was augmented in shown in Figure 1. It is true that we are living in a spatial distribution of the objects asymmetry by [3] . For symmetric world. Pursuing the explanation of symmetry symmetry discrimination [4] defined a symmetry distance will provide better understanding to the surrounding world of shapes. -
The Magic Square of Reflections and Rotations
THE MAGIC SQUARE OF REFLECTIONS AND ROTATIONS RAGNAR-OLAF BUCHWEITZ†, ELEONORE FABER, AND COLIN INGALLS Dedicated to the memories of two great geometers, H.M.S. Coxeter and Peter Slodowy ABSTRACT. We show how Coxeter’s work implies a bijection between complex reflection groups of rank two and real reflection groups in O(3). We also consider this magic square of reflections and rotations in the framework of Clifford algebras: we give an interpretation using (s)pin groups and explore these groups in small dimensions. CONTENTS 1. Introduction 2 2. Prelude: the groups 2 3. The Magic Square of Rotations and Reflections 4 Reflections, Take One 4 The Magic Square 4 Historical Note 8 4. Quaternions 10 5. The Clifford Algebra of Euclidean 3–Space 12 6. The Pin Groups for Euclidean 3–Space 13 7. Reflections 15 8. General Clifford algebras 15 Quadratic Spaces 16 Reflections, Take two 17 Clifford Algebras 18 Real Clifford Algebras 23 Cl0,1 23 Cl1,0 24 Cl0,2 24 Cl2,0 25 Cl0,3 25 9. Acknowledgements 25 References 25 Date: October 22, 2018. 2010 Mathematics Subject Classification. 20F55, 15A66, 11E88, 51F15 14E16 . Key words and phrases. Finite reflection groups, Clifford algebras, Quaternions, Pin groups, McKay correspondence. R.-O.B. and C.I. were partially supported by their respective NSERC Discovery grants, and E.F. acknowl- edges support of the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 789580. All three authors were supported by the Mathematisches Forschungsinstitut Oberwolfach through the Leibniz fellowship program in 2017, and E.F and C.I. -
3 Bilinear Forms & Euclidean/Hermitian Spaces
3 Bilinear Forms & Euclidean/Hermitian Spaces Bilinear forms are a natural generalisation of linear forms and appear in many areas of mathematics. Just as linear algebra can be considered as the study of `degree one' mathematics, bilinear forms arise when we are considering `degree two' (or quadratic) mathematics. For example, an inner product is an example of a bilinear form and it is through inner products that we define the notion of length in n p 2 2 analytic geometry - recall that the length of a vector x 2 R is defined to be x1 + ... + xn and that this formula holds as a consequence of Pythagoras' Theorem. In addition, the `Hessian' matrix that is introduced in multivariable calculus can be considered as defining a bilinear form on tangent spaces and allows us to give well-defined notions of length and angle in tangent spaces to geometric objects. Through considering the properties of this bilinear form we are able to deduce geometric information - for example, the local nature of critical points of a geometric surface. In this final chapter we will give an introduction to arbitrary bilinear forms on K-vector spaces and then specialise to the case K 2 fR, Cg. By restricting our attention to thse number fields we can deduce some particularly nice classification theorems. We will also give an introduction to Euclidean spaces: these are R-vector spaces that are equipped with an inner product and for which we can `do Euclidean geometry', that is, all of the geometric Theorems of Euclid will hold true in any arbitrary Euclidean space. -
Notes on Symmetric Bilinear Forms
Symmetric bilinear forms Joel Kamnitzer March 14, 2011 1 Symmetric bilinear forms We will now assume that the characteristic of our field is not 2 (so 1 + 1 6= 0). 1.1 Quadratic forms Let H be a symmetric bilinear form on a vector space V . Then H gives us a function Q : V → F defined by Q(v) = H(v,v). Q is called a quadratic form. We can recover H from Q via the equation 1 H(v, w) = (Q(v + w) − Q(v) − Q(w)) 2 Quadratic forms are actually quite familiar objects. Proposition 1.1. Let V = Fn. Let Q be a quadratic form on Fn. Then Q(x1,...,xn) is a polynomial in n variables where each term has degree 2. Con- versely, every such polynomial is a quadratic form. Proof. Let Q be a quadratic form. Then x1 . Q(x1,...,xn) = [x1 · · · xn]A . x n for some symmetric matrix A. Expanding this out, we see that Q(x1,...,xn) = Aij xixj 1 Xi,j n ≤ ≤ and so it is a polynomial with each term of degree 2. Conversely, any polynomial of degree 2 can be written in this form. Example 1.2. Consider the polynomial x2 + 4xy + 3y2. This the quadratic 1 2 form coming from the bilinear form HA defined by the matrix A = . 2 3 1 We can use this knowledge to understand the graph of solutions to x2 + 2 1 0 4xy + 3y = 1. Note that HA has a diagonal matrix with respect to 0 −1 the basis (1, 0), (−2, 1). -
Isometries and the Plane
Chapter 1 Isometries of the Plane \For geometry, you know, is the gate of science, and the gate is so low and small that one can only enter it as a little child. (W. K. Clifford) The focus of this first chapter is the 2-dimensional real plane R2, in which a point P can be described by its coordinates: 2 P 2 R ;P = (x; y); x 2 R; y 2 R: Alternatively, we can describe P as a complex number by writing P = (x; y) = x + iy 2 C: 2 The plane R comes with a usual distance. If P1 = (x1; y1);P2 = (x2; y2) 2 R2 are two points in the plane, then p 2 2 d(P1;P2) = (x2 − x1) + (y2 − y1) : Note that this is consistent withp the complex notation. For P = x + iy 2 C, p 2 2 recall that jP j = x + y = P P , thus for two complex points P1 = x1 + iy1;P2 = x2 + iy2 2 C, we have q d(P1;P2) = jP2 − P1j = (P2 − P1)(P2 − P1) p 2 2 = j(x2 − x1) + i(y2 − y1)j = (x2 − x1) + (y2 − y1) ; where ( ) denotes the complex conjugation, i.e. x + iy = x − iy. We are now interested in planar transformations (that is, maps from R2 to R2) that preserve distances. 1 2 CHAPTER 1. ISOMETRIES OF THE PLANE Points in the Plane • A point P in the plane is a pair of real numbers P=(x,y). d(0,P)2 = x2+y2. • A point P=(x,y) in the plane can be seen as a complex number x+iy. -
Reflection Groups 3
Lecture Notes Reflection Groups Dr Dmitriy Rumynin Anna Lena Winstel Autumn Term 2010 Contents 1 Finite Reflection Groups 3 2 Root systems 6 3 Generators and Relations 14 4 Coxeter group 16 5 Geometric representation of W (mij) 21 6 Fundamental chamber 28 7 Classification 34 8 Crystallographic Coxeter groups 43 9 Polynomial invariants 46 10 Fundamental degrees 54 11 Coxeter elements 57 1 Finite Reflection Groups V = (V; h ; i) - Euclidean Vector space where V is a finite dimensional vector space over R and h ; i : V × V −! R is bilinear, symmetric and positiv definit. n n P Example: (R ; ·): h(αi); (βi)i = αiβi i=1 Gram-Schmidt theory tells that for all Euclidean vector spaces, there exists an isometry (linear n bijective and 8 x; y 2 V : T (x) · T (y) = hx; yi) T : V −! R . In (V; h ; i) you can • measure length: jjxjj = phx; xi hx;yi • measure angles: xyc = arccos jjx||·||yjj • talk about orthogonal transformations O(V ) = fT 2 GL(V ): 8 x; y 2 V : hT x; T yi = hx; yig ≤ GL(V ) T 2 GL(V ). Let V T = fv 2 V : T v = vg the fixed points of T or the 1-eigenspace. Definition. T 2 GL(V ) is a reflection if T 2 O(V ) and dim V T = dim V − 1. Lemma 1.1. Let T be a reflection, x 2 (V T )? = fv : 8 w 2 V T : hv; wi = 0g; x 6= 0. Then 1. T (x) = −x hx;zi 2. 8 z 2 V : T (z) = z − 2 hx;xi · x Proof. -
Mathematicians Fleeing from Nazi Germany
Mathematicians Fleeing from Nazi Germany Mathematicians Fleeing from Nazi Germany Individual Fates and Global Impact Reinhard Siegmund-Schultze princeton university press princeton and oxford Copyright 2009 © by Princeton University Press Published by Princeton University Press, 41 William Street, Princeton, New Jersey 08540 In the United Kingdom: Princeton University Press, 6 Oxford Street, Woodstock, Oxfordshire OX20 1TW All Rights Reserved Library of Congress Cataloging-in-Publication Data Siegmund-Schultze, R. (Reinhard) Mathematicians fleeing from Nazi Germany: individual fates and global impact / Reinhard Siegmund-Schultze. p. cm. Includes bibliographical references and index. ISBN 978-0-691-12593-0 (cloth) — ISBN 978-0-691-14041-4 (pbk.) 1. Mathematicians—Germany—History—20th century. 2. Mathematicians— United States—History—20th century. 3. Mathematicians—Germany—Biography. 4. Mathematicians—United States—Biography. 5. World War, 1939–1945— Refuges—Germany. 6. Germany—Emigration and immigration—History—1933–1945. 7. Germans—United States—History—20th century. 8. Immigrants—United States—History—20th century. 9. Mathematics—Germany—History—20th century. 10. Mathematics—United States—History—20th century. I. Title. QA27.G4S53 2008 510.09'04—dc22 2008048855 British Library Cataloging-in-Publication Data is available This book has been composed in Sabon Printed on acid-free paper. ∞ press.princeton.edu Printed in the United States of America 10 987654321 Contents List of Figures and Tables xiii Preface xvii Chapter 1 The Terms “German-Speaking Mathematician,” “Forced,” and“Voluntary Emigration” 1 Chapter 2 The Notion of “Mathematician” Plus Quantitative Figures on Persecution 13 Chapter 3 Early Emigration 30 3.1. The Push-Factor 32 3.2. The Pull-Factor 36 3.D. -
Regular Elements of Finite Reflection Groups
Inventiones math. 25, 159-198 (1974) by Springer-Veriag 1974 Regular Elements of Finite Reflection Groups T.A. Springer (Utrecht) Introduction If G is a finite reflection group in a finite dimensional vector space V then ve V is called regular if no nonidentity element of G fixes v. An element ge G is regular if it has a regular eigenvector (a familiar example of such an element is a Coxeter element in a Weyl group). The main theme of this paper is the study of the properties and applications of the regular elements. A review of the contents follows. In w 1 we recall some known facts about the invariant theory of finite linear groups. Then we discuss in w2 some, more or less familiar, facts about finite reflection groups and their invariant theory. w3 deals with the problem of finding the eigenvalues of the elements of a given finite linear group G. It turns out that the explicit knowledge of the algebra R of invariants of G implies a solution to this problem. If G is a reflection group, R has a very simple structure, which enables one to obtain precise results about the eigenvalues and their multiplicities (see 3.4). These results are established by using some standard facts from algebraic geometry. They can also be used to give a proof of the formula for the order of finite Chevalley groups. We shall not go into this here. In the case of eigenvalues of regular elements one can go further, this is discussed in w4. One obtains, for example, a formula for the order of the centralizer of a regular element (see 4.2) and a formula for the eigenvalues of a regular element in an irreducible representation (see 4.5). -
From Singularities to Graphs
FROM SINGULARITIES TO GRAPHS PATRICK POPESCU-PAMPU Abstract. In this paper I analyze the problems which led to the introduction of graphs as tools for studying surface singularities. I explain how such graphs were initially only described using words, but that several questions made it necessary to draw them, leading to the elaboration of a special calculus with graphs. This is a non-technical paper intended to be readable both by mathematicians and philosophers or historians of mathematics. Contents 1. Introduction 1 2. What is the meaning of those graphs?3 3. What does it mean to resolve a surface singularity?4 4. Representations of surface singularities around 19008 5. Du Val's singularities, Coxeter's diagrams and the birth of dual graphs 10 6. Mumford's paper on the links of surface singularities 14 7. Waldhausen's graph manifolds and Neumann's calculus on graphs 17 8. Conclusion 19 References 20 1. Introduction Nowadays, graphs are common tools in singularity theory. They mainly serve to represent morpholog- ical aspects of surface singularities. Three examples of such graphs may be seen in Figures1,2,3. They are extracted from the papers [57], [61] and [14], respectively. Comparing those figures we see that the vertices are diversely depicted by small stars or by little circles, which are either full or empty. These drawing conventions are not important. What matters is that all vertices are decorated with numbers. We will explain their meaning later. My aim in this paper is to understand which kinds of problems forced mathematicians to associate graphs to surface singularities.