Lecture 5 Group actions

Size: px
Start display at page:

Download "Lecture 5 Group actions"

Transcription

1 Lecture 5 Group actions

2 From last time: 1. A subset H of a group G which is itself a group under the same operation is a subgroup of G. Two ways of identifying if H is a subgroup or not: (a) Check that H = H. (b) Check that xy 1 H for all x, y H.

3 From last time: 1. A subset H of a group G which is itself a group under the same operation is a subgroup of G. Two ways of identifying if H is a subgroup or not: (a) Check that H = H. (b) Check that xy 1 H for all x, y H. 2. A homomorphism is a map of groups ϕ : G H satisfying ϕ(g 1 g 2 ) = ϕ(g 1 )ϕ(g 2 ). Example: ϕ : (R, +) (R >0, ) by ϕ(x) = e x. Non-example: ϕ : (R >0, ) (R, +) by ϕ(x) = x (inclusion).

4 Mathematical aside: morphisms in general (Not in D & F, but for our own betterment) In general in math, a (homo)morphism is just a map from one mathematical object to another of its own kind, which obeys the right rules ( structure-preserving ). (Look up category theory if you ever want to feel like you re doing all math, ever, all at once)

5 Mathematical aside: morphisms in general (Not in D & F, but for our own betterment) In general in math, a (homo)morphism is just a map from one mathematical object to another of its own kind, which obeys the right rules ( structure-preserving ). (Look up category theory if you ever want to feel like you re doing all math, ever, all at once) Examples: 1. We just defined homomorphisms of groups 2. Linear transformations are morphisms of vector spaces 3. Any map from one set to another is a morphism of sets (no rules!)

6 Mathematical aside: morphisms in general (Not in D & F, but for our own betterment) In general in math, a (homo)morphism is just a map from one mathematical object to another of its own kind, which obeys the right rules ( structure-preserving ). (Look up category theory if you ever want to feel like you re doing all math, ever, all at once) Examples: 1. We just defined homomorphisms of groups 2. Linear transformations are morphisms of vector spaces 3. Any map from one set to another is a morphism of sets (no rules!) Endomorphisms are morphisms from something to itself. Isomorphisms are bijective morphisms. Automorphisms are bijective endomorphisms.

7 Mathematical aside: morphisms in general (Not in D & F, but for our own betterment) In general in math, a (homo)morphism is just a map from one mathematical object to another of its own kind, which obeys the right rules ( structure-preserving ). (Look up category theory if you ever want to feel like you re doing all math, ever, all at once) Examples: 1. We just defined homomorphisms of groups 2. Linear transformations are morphisms of vector spaces 3. Any map from one set to another is a morphism of sets (no rules!) Hom(X, Y ) = {ϕ : X Y ϕ is structure-preserving} Endomorphisms are morphisms from something to itself. End(X) = Hom(X, X) = {ϕ : X X} Isomorphisms are bijective morphisms. Automorphisms are bijective endomorphisms. Aut(X) = {ϕ : X X}

8 Group actions Goal: Build automorphisms of sets (permutations) by using groups.

9 Group actions Goal: Build automorphisms of sets (permutations) by using groups. Fact: Aut(A) = S A for a set A.

10 Group actions Goal: Build automorphisms of sets (permutations) by using groups. Fact: Aut(A) = S A for a set A. Examples we already know: 1. The dihedral group permutes the set of symmetric states a regular n-gon can occupy. 2. The symmetric group S X permutes the objects of X. 3. The invertible matrices move vectors around in a vector space. 4. The symmetric group S n can also move vectors in R n around when you map its elements to permutation matrices.

11 Group actions Goal: Build automorphisms of sets (permutations) by using groups. Fact: Aut(A) = S A for a set A. Examples we already know: 1. The dihedral group permutes the set of symmetric states a regular n-gon can occupy. 2. The symmetric group S X permutes the objects of X. 3. The invertible matrices move vectors around in a vector space. 4. The symmetric group S n can also move vectors in R n around when you map its elements to permutation matrices. Basically, if A is the set we re permuting, then the goal is to find homomorphisms from G into S A.

12 Group actions: new language, same idea. Definition A group action of a group G on a set A is a map from G A (g, a) A g a which satisfies g (h a) = (gh) a and 1 a = a for all g, h G, a A. We say G acts on A.

13 Group actions: new language, same idea. Definition A group action of a group G on a set A is a map from G A (g, a) A g a which satisfies g (h a) = (gh) a and 1 a = a for all g, h G, a A. We say G acts on A. Theorem A group action is equivalent to a homomorphism G S A g σ g defined by σ g (a) = g a. In other words, given a homomorphism, you get an action, and vice versa.

14 Back to the same examples from before: 1. The dihedral group acts on the set of symmetric states a regular n-gon can occupy by rotations and flips. 2. The symmetric group S X acts on X by permutation. 3. The invertible matrices act on vector spaces. 4. The symmetric group S n also acts on R n by permutation matrices.

15 Back to the same examples from before: 1. The dihedral group acts on the set of symmetric states a regular n-gon can occupy by rotations and flips. 2. The symmetric group S X acts on X by permutation. 3. The invertible matrices act on vector spaces. 4. The symmetric group S n also acts on R n by permutation matrices. Any action of a group on a vector space (which is the same thing as a homomorphism of G into GL n ) is called a representation of G. In particular, the map G S A is called the permutation representation associated to the given action because you re pretending that A is a basis for a vector space. Thought of this way, σ g is just one of those permutation matrices (exactly one 1 in each row and column).

16 Some vocabulary: The trivial action is g a = a, i.e σ g = 1 for all g G.

17 Some vocabulary: The trivial action is g a = a, i.e σ g = 1 for all g G. If the map g σ g is injective, we say the action is faithful.

18 Some vocabulary: The trivial action is g a = a, i.e σ g = 1 for all g G. If the map g σ g is injective, we say the action is faithful. The kernel of an action is the set {g G g a = a a A}.

19 Some vocabulary: The trivial action is g a = a, i.e σ g = 1 for all g G. If the map g σ g is injective, we say the action is faithful. The kernel of an action is the set {g G g a = a a A}. The way we ve been writing the action is called a left action. Sometimes it s better to write a g means g is acting from the right.

20 Some vocabulary: The trivial action is g a = a, i.e σ g = 1 for all g G. If the map g σ g is injective, we say the action is faithful. The kernel of an action is the set {g G g a = a a A}. The way we ve been writing the action is called a left action. Sometimes it s better to write a g means g is acting from the right. More examples: 1. R acts on R n by scaling: x (v 1, v 2,..., v n ) = (xv 1, xv 2,..., xv n ).

21 Some vocabulary: The trivial action is g a = a, i.e σ g = 1 for all g G. If the map g σ g is injective, we say the action is faithful. The kernel of an action is the set {g G g a = a a A}. The way we ve been writing the action is called a left action. Sometimes it s better to write a g means g is acting from the right. More examples: 1. R acts on R n by scaling: x (v 1, v 2,..., v n ) = (xv 1, xv 2,..., xv n ). 2. Any group G acts on itself (let A = G) in several ways: left regular action: g a = ga right multiplication: g a = ag 1 conjugation: g a = gag 1

Introduction to Modern Algebra

Introduction to Modern Algebra Introduction to Modern Algebra David Joyce Clark University Version 0.0.6, 3 Oct 2008 1 1 Copyright (C) 2008. ii I dedicate this book to my friend and colleague Arthur Chou. Arthur encouraged me to write

More information

G = G 0 > G 1 > > G k = {e}

G = G 0 > G 1 > > G k = {e} Proposition 49. 1. A group G is nilpotent if and only if G appears as an element of its upper central series. 2. If G is nilpotent, then the upper central series and the lower central series have the same

More information

I. GROUPS: BASIC DEFINITIONS AND EXAMPLES

I. GROUPS: BASIC DEFINITIONS AND EXAMPLES I GROUPS: BASIC DEFINITIONS AND EXAMPLES Definition 1: An operation on a set G is a function : G G G Definition 2: A group is a set G which is equipped with an operation and a special element e G, called

More information

Computing the Symmetry Groups of the Platonic Solids With the Help of Maple

Computing the Symmetry Groups of the Platonic Solids With the Help of Maple Computing the Symmetry Groups of the Platonic Solids With the Help of Maple Patrick J. Morandi Department of Mathematical Sciences New Mexico State University Las Cruces NM 88003 USA pmorandi@nmsu.edu

More information

University of Lille I PC first year list of exercises n 7. Review

University of Lille I PC first year list of exercises n 7. Review University of Lille I PC first year list of exercises n 7 Review Exercise Solve the following systems in 4 different ways (by substitution, by the Gauss method, by inverting the matrix of coefficients

More information

GROUP ACTIONS KEITH CONRAD

GROUP ACTIONS KEITH CONRAD GROUP ACTIONS KEITH CONRAD 1. Introduction The symmetric groups S n, alternating groups A n, and (for n 3) dihedral groups D n behave, by their very definition, as permutations on certain sets. The groups

More information

Abstract Algebra Cheat Sheet

Abstract Algebra Cheat Sheet Abstract Algebra Cheat Sheet 16 December 2002 By Brendan Kidwell, based on Dr. Ward Heilman s notes for his Abstract Algebra class. Notes: Where applicable, page numbers are listed in parentheses at the

More information

S on n elements. A good way to think about permutations is the following. Consider the A = 1,2,3, 4 whose elements we permute with the P =

S on n elements. A good way to think about permutations is the following. Consider the A = 1,2,3, 4 whose elements we permute with the P = Section 6. 1 Section 6. Groups of Permutations: : The Symmetric Group Purpose of Section: To introduce the idea of a permutation and show how the set of all permutations of a set of n elements, equipped

More information

Chapter 13: Basic ring theory

Chapter 13: Basic ring theory Chapter 3: Basic ring theory Matthew Macauley Department of Mathematical Sciences Clemson University http://www.math.clemson.edu/~macaule/ Math 42, Spring 24 M. Macauley (Clemson) Chapter 3: Basic ring

More information

Group Theory. Contents

Group Theory. Contents Group Theory Contents Chapter 1: Review... 2 Chapter 2: Permutation Groups and Group Actions... 3 Orbits and Transitivity... 6 Specific Actions The Right regular and coset actions... 8 The Conjugation

More information

9. Quotient Groups Given a group G and a subgroup H, under what circumstances can we find a homomorphism φ: G G ', such that H is the kernel of φ?

9. Quotient Groups Given a group G and a subgroup H, under what circumstances can we find a homomorphism φ: G G ', such that H is the kernel of φ? 9. Quotient Groups Given a group G and a subgroup H, under what circumstances can we find a homomorphism φ: G G ', such that H is the kernel of φ? Clearly a necessary condition is that H is normal in G.

More information

1 Symmetries of regular polyhedra

1 Symmetries of regular polyhedra 1230, notes 5 1 Symmetries of regular polyhedra Symmetry groups Recall: Group axioms: Suppose that (G, ) is a group and a, b, c are elements of G. Then (i) a b G (ii) (a b) c = a (b c) (iii) There is an

More information

NOTES ON GROUP THEORY

NOTES ON GROUP THEORY NOTES ON GROUP THEORY Abstract. These are the notes prepared for the course MTH 751 to be offered to the PhD students at IIT Kanpur. Contents 1. Binary Structure 2 2. Group Structure 5 3. Group Actions

More information

Linear Maps. Isaiah Lankham, Bruno Nachtergaele, Anne Schilling (February 5, 2007)

Linear Maps. Isaiah Lankham, Bruno Nachtergaele, Anne Schilling (February 5, 2007) MAT067 University of California, Davis Winter 2007 Linear Maps Isaiah Lankham, Bruno Nachtergaele, Anne Schilling (February 5, 2007) As we have discussed in the lecture on What is Linear Algebra? one of

More information

Mathematics Course 111: Algebra I Part IV: Vector Spaces

Mathematics Course 111: Algebra I Part IV: Vector Spaces Mathematics Course 111: Algebra I Part IV: Vector Spaces D. R. Wilkins Academic Year 1996-7 9 Vector Spaces A vector space over some field K is an algebraic structure consisting of a set V on which are

More information

GROUPS ACTING ON A SET

GROUPS ACTING ON A SET GROUPS ACTING ON A SET MATH 435 SPRING 2012 NOTES FROM FEBRUARY 27TH, 2012 1. Left group actions Definition 1.1. Suppose that G is a group and S is a set. A left (group) action of G on S is a rule for

More information

GROUP ALGEBRAS. ANDREI YAFAEV

GROUP ALGEBRAS. ANDREI YAFAEV GROUP ALGEBRAS. ANDREI YAFAEV We will associate a certain algebra to a finite group and prove that it is semisimple. Then we will apply Wedderburn s theory to its study. Definition 0.1. Let G be a finite

More information

Group Fundamentals. Chapter 1. 1.1 Groups and Subgroups. 1.1.1 Definition

Group Fundamentals. Chapter 1. 1.1 Groups and Subgroups. 1.1.1 Definition Chapter 1 Group Fundamentals 1.1 Groups and Subgroups 1.1.1 Definition A group is a nonempty set G on which there is defined a binary operation (a, b) ab satisfying the following properties. Closure: If

More information

The cover SU(2) SO(3) and related topics

The cover SU(2) SO(3) and related topics The cover SU(2) SO(3) and related topics Iordan Ganev December 2011 Abstract The subgroup U of unit quaternions is isomorphic to SU(2) and is a double cover of SO(3). This allows a simple computation of

More information

Matrix Representations of Linear Transformations and Changes of Coordinates

Matrix Representations of Linear Transformations and Changes of Coordinates Matrix Representations of Linear Transformations and Changes of Coordinates 01 Subspaces and Bases 011 Definitions A subspace V of R n is a subset of R n that contains the zero element and is closed under

More information

Assignment 8: Selected Solutions

Assignment 8: Selected Solutions Section 4.1 Assignment 8: Selected Solutions 1. and 2. Express each permutation as a product of disjoint cycles, and identify their parity. (1) (1,9,2,3)(1,9,6,5)(1,4,8,7)=(1,4,8,7,2,3)(5,9,6), odd; (2)

More information

( ) which must be a vector

( ) which must be a vector MATH 37 Linear Transformations from Rn to Rm Dr. Neal, WKU Let T : R n R m be a function which maps vectors from R n to R m. Then T is called a linear transformation if the following two properties are

More information

(Q, ), (R, ), (C, ), where the star means without 0, (Q +, ), (R +, ), where the plus-sign means just positive numbers, and (U, ),

(Q, ), (R, ), (C, ), where the star means without 0, (Q +, ), (R +, ), where the plus-sign means just positive numbers, and (U, ), 2 Examples of Groups 21 Some infinite abelian groups It is easy to see that the following are infinite abelian groups: Z, +), Q, +), R, +), C, +), where R is the set of real numbers and C is the set of

More information

Chapter 7. Permutation Groups

Chapter 7. Permutation Groups Chapter 7 Permutation Groups () We started the study of groups by considering planar isometries In the previous chapter, we learnt that finite groups of planar isometries can only be cyclic or dihedral

More information

4.1 Modules, Homomorphisms, and Exact Sequences

4.1 Modules, Homomorphisms, and Exact Sequences Chapter 4 Modules We always assume that R is a ring with unity 1 R. 4.1 Modules, Homomorphisms, and Exact Sequences A fundamental example of groups is the symmetric group S Ω on a set Ω. By Cayley s Theorem,

More information

Notes on finite group theory. Peter J. Cameron

Notes on finite group theory. Peter J. Cameron Notes on finite group theory Peter J. Cameron October 2013 2 Preface Group theory is a central part of modern mathematics. Its origins lie in geometry (where groups describe in a very detailed way the

More information

On an algorithm for classification of binary self-dual codes with minimum distance four

On an algorithm for classification of binary self-dual codes with minimum distance four Thirteenth International Workshop on Algebraic and Combinatorial Coding Theory June 15-21, 2012, Pomorie, Bulgaria pp. 105 110 On an algorithm for classification of binary self-dual codes with minimum

More information

GENERATING SETS KEITH CONRAD

GENERATING SETS KEITH CONRAD GENERATING SETS KEITH CONRAD 1 Introduction In R n, every vector can be written as a unique linear combination of the standard basis e 1,, e n A notion weaker than a basis is a spanning set: a set of vectors

More information

MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS. + + x 2. x n. a 11 a 12 a 1n b 1 a 21 a 22 a 2n b 2 a 31 a 32 a 3n b 3. a m1 a m2 a mn b m

MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS. + + x 2. x n. a 11 a 12 a 1n b 1 a 21 a 22 a 2n b 2 a 31 a 32 a 3n b 3. a m1 a m2 a mn b m MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS 1. SYSTEMS OF EQUATIONS AND MATRICES 1.1. Representation of a linear system. The general system of m equations in n unknowns can be written a 11 x 1 + a 12 x 2 +

More information

Chapter 7: Products and quotients

Chapter 7: Products and quotients Chapter 7: Products and quotients Matthew Macauley Department of Mathematical Sciences Clemson University http://www.math.clemson.edu/~macaule/ Math 42, Spring 24 M. Macauley (Clemson) Chapter 7: Products

More information

= 2 + 1 2 2 = 3 4, Now assume that P (k) is true for some fixed k 2. This means that

= 2 + 1 2 2 = 3 4, Now assume that P (k) is true for some fixed k 2. This means that Instructions. Answer each of the questions on your own paper, and be sure to show your work so that partial credit can be adequately assessed. Credit will not be given for answers (even correct ones) without

More information

Linearly Independent Sets and Linearly Dependent Sets

Linearly Independent Sets and Linearly Dependent Sets These notes closely follow the presentation of the material given in David C. Lay s textbook Linear Algebra and its Applications (3rd edition). These notes are intended primarily for in-class presentation

More information

Orthogonal Diagonalization of Symmetric Matrices

Orthogonal Diagonalization of Symmetric Matrices MATH10212 Linear Algebra Brief lecture notes 57 Gram Schmidt Process enables us to find an orthogonal basis of a subspace. Let u 1,..., u k be a basis of a subspace V of R n. We begin the process of finding

More information

CONSEQUENCES OF THE SYLOW THEOREMS

CONSEQUENCES OF THE SYLOW THEOREMS CONSEQUENCES OF THE SYLOW THEOREMS KEITH CONRAD For a group theorist, Sylow s Theorem is such a basic tool, and so fundamental, that it is used almost without thinking, like breathing. Geoff Robinson 1.

More information

Chapter 6. Orthogonality

Chapter 6. Orthogonality 6.3 Orthogonal Matrices 1 Chapter 6. Orthogonality 6.3 Orthogonal Matrices Definition 6.4. An n n matrix A is orthogonal if A T A = I. Note. We will see that the columns of an orthogonal matrix must be

More information

COHOMOLOGY OF GROUPS

COHOMOLOGY OF GROUPS Actes, Congrès intern. Math., 1970. Tome 2, p. 47 à 51. COHOMOLOGY OF GROUPS by Daniel QUILLEN * This is a report of research done at the Institute for Advanced Study the past year. It includes some general

More information

Galois representations with open image

Galois representations with open image Galois representations with open image Ralph Greenberg University of Washington Seattle, Washington, USA May 7th, 2011 Introduction This talk will be about representations of the absolute Galois group

More information

NOTES ON CATEGORIES AND FUNCTORS

NOTES ON CATEGORIES AND FUNCTORS NOTES ON CATEGORIES AND FUNCTORS These notes collect basic definitions and facts about categories and functors that have been mentioned in the Homological Algebra course. For further reading about category

More information

Outline 2.1 Graph Isomorphism 2.2 Automorphisms and Symmetry 2.3 Subgraphs, part 1

Outline 2.1 Graph Isomorphism 2.2 Automorphisms and Symmetry 2.3 Subgraphs, part 1 GRAPH THEORY LECTURE STRUCTURE AND REPRESENTATION PART A Abstract. Chapter focuses on the question of when two graphs are to be regarded as the same, on symmetries, and on subgraphs.. discusses the concept

More information

MATH 304 Linear Algebra Lecture 9: Subspaces of vector spaces (continued). Span. Spanning set.

MATH 304 Linear Algebra Lecture 9: Subspaces of vector spaces (continued). Span. Spanning set. MATH 304 Linear Algebra Lecture 9: Subspaces of vector spaces (continued). Span. Spanning set. Vector space A vector space is a set V equipped with two operations, addition V V (x,y) x + y V and scalar

More information

THE SIGN OF A PERMUTATION

THE SIGN OF A PERMUTATION THE SIGN OF A PERMUTATION KEITH CONRAD 1. Introduction Throughout this discussion, n 2. Any cycle in S n is a product of transpositions: the identity (1) is (12)(12), and a k-cycle with k 2 can be written

More information

Chapter 3. Distribution Problems. 3.1 The idea of a distribution. 3.1.1 The twenty-fold way

Chapter 3. Distribution Problems. 3.1 The idea of a distribution. 3.1.1 The twenty-fold way Chapter 3 Distribution Problems 3.1 The idea of a distribution Many of the problems we solved in Chapter 1 may be thought of as problems of distributing objects (such as pieces of fruit or ping-pong balls)

More information

5. Linear algebra I: dimension

5. Linear algebra I: dimension 5. Linear algebra I: dimension 5.1 Some simple results 5.2 Bases and dimension 5.3 Homomorphisms and dimension 1. Some simple results Several observations should be made. Once stated explicitly, the proofs

More information

Name: Section Registered In:

Name: Section Registered In: Name: Section Registered In: Math 125 Exam 3 Version 1 April 24, 2006 60 total points possible 1. (5pts) Use Cramer s Rule to solve 3x + 4y = 30 x 2y = 8. Be sure to show enough detail that shows you are

More information

On the structure of C -algebra generated by a family of partial isometries and multipliers

On the structure of C -algebra generated by a family of partial isometries and multipliers Armenian Journal of Mathematics Volume 7, Number 1, 2015, 50 58 On the structure of C -algebra generated by a family of partial isometries and multipliers A. Yu. Kuznetsova and Ye. V. Patrin Kazan Federal

More information

Notes on Group Theory

Notes on Group Theory Notes on Group Theory Mark Reeder March 7, 2014 Contents 1 Notation for sets and functions 4 2 Basic group theory 4 2.1 The definition of a group................................. 4 2.2 Group homomorphisms..................................

More information

Similarity and Diagonalization. Similar Matrices

Similarity and Diagonalization. Similar Matrices MATH022 Linear Algebra Brief lecture notes 48 Similarity and Diagonalization Similar Matrices Let A and B be n n matrices. We say that A is similar to B if there is an invertible n n matrix P such that

More information

MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS

MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS Systems of Equations and Matrices Representation of a linear system The general system of m equations in n unknowns can be written a x + a 2 x 2 + + a n x n b a

More information

Group Theory. Chapter 1

Group Theory. Chapter 1 Chapter 1 Group Theory Most lectures on group theory actually start with the definition of what is a group. It may be worth though spending a few lines to mention how mathematicians came up with such a

More information

CLUSTER ALGEBRAS AND CATEGORIFICATION TALKS: QUIVERS AND AUSLANDER-REITEN THEORY

CLUSTER ALGEBRAS AND CATEGORIFICATION TALKS: QUIVERS AND AUSLANDER-REITEN THEORY CLUSTER ALGEBRAS AND CATEGORIFICATION TALKS: QUIVERS AND AUSLANDER-REITEN THEORY ANDREW T. CARROLL Notes for this talk come primarily from two sources: M. Barot, ICTP Notes Representations of Quivers,

More information

Geometric Transformations

Geometric Transformations Geometric Transformations Definitions Def: f is a mapping (function) of a set A into a set B if for every element a of A there exists a unique element b of B that is paired with a; this pairing is denoted

More information

Elements of Abstract Group Theory

Elements of Abstract Group Theory Chapter 2 Elements of Abstract Group Theory Mathematics is a game played according to certain simple rules with meaningless marks on paper. David Hilbert The importance of symmetry in physics, and for

More information

8 Square matrices continued: Determinants

8 Square matrices continued: Determinants 8 Square matrices continued: Determinants 8. Introduction Determinants give us important information about square matrices, and, as we ll soon see, are essential for the computation of eigenvalues. You

More information

Integer Sequences and Matrices Over Finite Fields

Integer Sequences and Matrices Over Finite Fields Integer Sequences and Matrices Over Finite Fields arxiv:math/0606056v [mathco] 2 Jun 2006 Kent E Morrison Department of Mathematics California Polytechnic State University San Luis Obispo, CA 93407 kmorriso@calpolyedu

More information

4. FIRST STEPS IN THE THEORY 4.1. A

4. FIRST STEPS IN THE THEORY 4.1. A 4. FIRST STEPS IN THE THEORY 4.1. A Catalogue of All Groups: The Impossible Dream The fundamental problem of group theory is to systematically explore the landscape and to chart what lies out there. We

More information

Each copy of any part of a JSTOR transmission must contain the same copyright notice that appears on the screen or printed page of such transmission.

Each copy of any part of a JSTOR transmission must contain the same copyright notice that appears on the screen or printed page of such transmission. Degrees of Sums in a Separable Field Extension Author(s): I. M. Isaacs Source: Proceedings of the American Mathematical Society, Vol. 25, No. 3 (Jul., 1970), pp. 638-641 Published by: American Mathematical

More information

Lecture 5 Principal Minors and the Hessian

Lecture 5 Principal Minors and the Hessian Lecture 5 Principal Minors and the Hessian Eivind Eriksen BI Norwegian School of Management Department of Economics October 01, 2010 Eivind Eriksen (BI Dept of Economics) Lecture 5 Principal Minors and

More information

EXERCISES FOR THE COURSE MATH 570, FALL 2010

EXERCISES FOR THE COURSE MATH 570, FALL 2010 EXERCISES FOR THE COURSE MATH 570, FALL 2010 EYAL Z. GOREN (1) Let G be a group and H Z(G) a subgroup such that G/H is cyclic. Prove that G is abelian. Conclude that every group of order p 2 (p a prime

More information

ON GENERALIZED RELATIVE COMMUTATIVITY DEGREE OF A FINITE GROUP. A. K. Das and R. K. Nath

ON GENERALIZED RELATIVE COMMUTATIVITY DEGREE OF A FINITE GROUP. A. K. Das and R. K. Nath International Electronic Journal of Algebra Volume 7 (2010) 140-151 ON GENERALIZED RELATIVE COMMUTATIVITY DEGREE OF A FINITE GROUP A. K. Das and R. K. Nath Received: 12 October 2009; Revised: 15 December

More information

Universitext. Springer. S. Axler F.W. Gehring K.A. Ribet. Editorial Board (North America): New York Berlin Heidelberg Hong Kong London Milan Paris

Universitext. Springer. S. Axler F.W. Gehring K.A. Ribet. Editorial Board (North America): New York Berlin Heidelberg Hong Kong London Milan Paris Universitext Editorial Board (North America): S. Axler F.W. Gehring K.A. Ribet Springer New York Berlin Heidelberg Hong Kong London Milan Paris Tokyo This page intentionally left blank Hans Kurzweil Bernd

More information

Linear Algebra Notes

Linear Algebra Notes Linear Algebra Notes Chapter 19 KERNEL AND IMAGE OF A MATRIX Take an n m matrix a 11 a 12 a 1m a 21 a 22 a 2m a n1 a n2 a nm and think of it as a function A : R m R n The kernel of A is defined as Note

More information

5. Orthogonal matrices

5. Orthogonal matrices L Vandenberghe EE133A (Spring 2016) 5 Orthogonal matrices matrices with orthonormal columns orthogonal matrices tall matrices with orthonormal columns complex matrices with orthonormal columns 5-1 Orthonormal

More information

Symmetries in Physics

Symmetries in Physics Symmetries in Physics J.Pearson June 4, 2009 Abstract These are a set of notes I have made, based on lectures given by M.Dasgupta at the University of Manchester Jan-May 09. Please e-mail me with any comments/corrections:

More information

FINITE GROUP THEORY. FOR COMBINATORISTS Volume one. Jin Ho Kwak. Department of Mathematics POSTECH Pohang, 790 784 Korea jinkwak@postech.ac.

FINITE GROUP THEORY. FOR COMBINATORISTS Volume one. Jin Ho Kwak. Department of Mathematics POSTECH Pohang, 790 784 Korea jinkwak@postech.ac. FINITE GROUP THEORY FOR COMBINATORISTS Volume one Jin Ho Kwak Department of Mathematics POSTECH Pohang, 790 784 Korea jinkwak@postech.ac.kr Ming Yao Xu Department of Mathematics Peking University Beijing

More information

THE AVERAGE DEGREE OF AN IRREDUCIBLE CHARACTER OF A FINITE GROUP

THE AVERAGE DEGREE OF AN IRREDUCIBLE CHARACTER OF A FINITE GROUP THE AVERAGE DEGREE OF AN IRREDUCIBLE CHARACTER OF A FINITE GROUP by I. M. Isaacs Mathematics Department University of Wisconsin 480 Lincoln Dr. Madison, WI 53706 USA E-Mail: isaacs@math.wisc.edu Maria

More information

SMALL SKEW FIELDS CÉDRIC MILLIET

SMALL SKEW FIELDS CÉDRIC MILLIET SMALL SKEW FIELDS CÉDRIC MILLIET Abstract A division ring of positive characteristic with countably many pure types is a field Wedderburn showed in 1905 that finite fields are commutative As for infinite

More information

[1] Diagonal factorization

[1] Diagonal factorization 8.03 LA.6: Diagonalization and Orthogonal Matrices [ Diagonal factorization [2 Solving systems of first order differential equations [3 Symmetric and Orthonormal Matrices [ Diagonal factorization Recall:

More information

Math 223 Abstract Algebra Lecture Notes

Math 223 Abstract Algebra Lecture Notes Math 223 Abstract Algebra Lecture Notes Steven Tschantz Spring 2001 (Apr. 23 version) Preamble These notes are intended to supplement the lectures and make up for the lack of a textbook for the course

More information

Basic Algebra (only a draft)

Basic Algebra (only a draft) Basic Algebra (only a draft) Ali Nesin Mathematics Department Istanbul Bilgi University Kuştepe Şişli Istanbul Turkey anesin@bilgi.edu.tr February 12, 2004 2 Contents I Basic Group Theory 7 1 Definition

More information

Lecture 2 Matrix Operations

Lecture 2 Matrix Operations Lecture 2 Matrix Operations transpose, sum & difference, scalar multiplication matrix multiplication, matrix-vector product matrix inverse 2 1 Matrix transpose transpose of m n matrix A, denoted A T or

More information

Algebra of the 2x2x2 Rubik s Cube

Algebra of the 2x2x2 Rubik s Cube Algebra of the 2x2x2 Rubik s Cube Under the direction of Dr. John S. Caughman William Brad Benjamin. Introduction As children, many of us spent countless hours playing with Rubiks Cube. At the time it

More information

1 Homework 1. [p 0 q i+j +... + p i 1 q j+1 ] + [p i q j ] + [p i+1 q j 1 +... + p i+j q 0 ]

1 Homework 1. [p 0 q i+j +... + p i 1 q j+1 ] + [p i q j ] + [p i+1 q j 1 +... + p i+j q 0 ] 1 Homework 1 (1) Prove the ideal (3,x) is a maximal ideal in Z[x]. SOLUTION: Suppose we expand this ideal by including another generator polynomial, P / (3, x). Write P = n + x Q with n an integer not

More information

SOME PROPERTIES OF FIBER PRODUCT PRESERVING BUNDLE FUNCTORS

SOME PROPERTIES OF FIBER PRODUCT PRESERVING BUNDLE FUNCTORS SOME PROPERTIES OF FIBER PRODUCT PRESERVING BUNDLE FUNCTORS Ivan Kolář Abstract. Let F be a fiber product preserving bundle functor on the category FM m of the proper base order r. We deduce that the r-th

More information

Notes on Algebraic Structures. Peter J. Cameron

Notes on Algebraic Structures. Peter J. Cameron Notes on Algebraic Structures Peter J. Cameron ii Preface These are the notes of the second-year course Algebraic Structures I at Queen Mary, University of London, as I taught it in the second semester

More information

Spherical representations and the Satake isomorphism

Spherical representations and the Satake isomorphism Spherical representations and the Satake isomorphism Last updated: December 10, 2013. Topics: otivation for the study of spherical representations; Satake isomorphism stated for the general case of a connected

More information

Linear Algebra Review. Vectors

Linear Algebra Review. Vectors Linear Algebra Review By Tim K. Marks UCSD Borrows heavily from: Jana Kosecka kosecka@cs.gmu.edu http://cs.gmu.edu/~kosecka/cs682.html Virginia de Sa Cogsci 8F Linear Algebra review UCSD Vectors The length

More information

Elasticity Theory Basics

Elasticity Theory Basics G22.3033-002: Topics in Computer Graphics: Lecture #7 Geometric Modeling New York University Elasticity Theory Basics Lecture #7: 20 October 2003 Lecturer: Denis Zorin Scribe: Adrian Secord, Yotam Gingold

More information

Arkansas Tech University MATH 4033: Elementary Modern Algebra Dr. Marcel B. Finan

Arkansas Tech University MATH 4033: Elementary Modern Algebra Dr. Marcel B. Finan Arkansas Tech University MATH 4033: Elementary Modern Algebra Dr. Marcel B. Finan 6 Permutation Groups Let S be a nonempty set and M(S be the collection of all mappings from S into S. In this section,

More information

MATH 304 Linear Algebra Lecture 18: Rank and nullity of a matrix.

MATH 304 Linear Algebra Lecture 18: Rank and nullity of a matrix. MATH 304 Linear Algebra Lecture 18: Rank and nullity of a matrix. Nullspace Let A = (a ij ) be an m n matrix. Definition. The nullspace of the matrix A, denoted N(A), is the set of all n-dimensional column

More information

T ( a i x i ) = a i T (x i ).

T ( a i x i ) = a i T (x i ). Chapter 2 Defn 1. (p. 65) Let V and W be vector spaces (over F ). We call a function T : V W a linear transformation form V to W if, for all x, y V and c F, we have (a) T (x + y) = T (x) + T (y) and (b)

More information

Classification of Cartan matrices

Classification of Cartan matrices Chapter 7 Classification of Cartan matrices In this chapter we describe a classification of generalised Cartan matrices This classification can be compared as the rough classification of varieties in terms

More information

Notes on Determinant

Notes on Determinant ENGG2012B Advanced Engineering Mathematics Notes on Determinant Lecturer: Kenneth Shum Lecture 9-18/02/2013 The determinant of a system of linear equations determines whether the solution is unique, without

More information

Group Theory and the Rubik s Cube. Janet Chen

Group Theory and the Rubik s Cube. Janet Chen Group Theory and the Rubik s Cube Janet Chen A Note to the Reader These notes are based on a 2-week course that I taught for high school students at the Texas State Honors Summer Math Camp. All of the

More information

How To Understand The Relation Between Quadratic And Binary Forms

How To Understand The Relation Between Quadratic And Binary Forms 8430 HANDOUT 3: ELEMENTARY THEORY OF QUADRATIC FORMS PETE L. CLARK 1. Basic definitions An integral binary quadratic form is just a polynomial f = ax 2 + bxy + cy 2 with a, b, c Z. We define the discriminant

More information

Math 2270 - Lecture 33 : Positive Definite Matrices

Math 2270 - Lecture 33 : Positive Definite Matrices Math 2270 - Lecture 33 : Positive Definite Matrices Dylan Zwick Fall 2012 This lecture covers section 6.5 of the textbook. Today we re going to talk about a special type of symmetric matrix, called a positive

More information

Logic, Combinatorics and Topological Dynamics, II

Logic, Combinatorics and Topological Dynamics, II Logic, Combinatorics and Topological Dynamics, II Alexander S. Kechris January 9, 2009 Part II. Generic symmetries Generic properties Let X be a topological space and P X a subset of X viewed as a property

More information

MATH10212 Linear Algebra. Systems of Linear Equations. Definition. An n-dimensional vector is a row or a column of n numbers (or letters): a 1.

MATH10212 Linear Algebra. Systems of Linear Equations. Definition. An n-dimensional vector is a row or a column of n numbers (or letters): a 1. MATH10212 Linear Algebra Textbook: D. Poole, Linear Algebra: A Modern Introduction. Thompson, 2006. ISBN 0-534-40596-7. Systems of Linear Equations Definition. An n-dimensional vector is a row or a column

More information

it is easy to see that α = a

it is easy to see that α = a 21. Polynomial rings Let us now turn out attention to determining the prime elements of a polynomial ring, where the coefficient ring is a field. We already know that such a polynomial ring is a UF. Therefore

More information

Math 250A: Groups, rings, and fields. H. W. Lenstra jr. 1. Prerequisites

Math 250A: Groups, rings, and fields. H. W. Lenstra jr. 1. Prerequisites Math 250A: Groups, rings, and fields. H. W. Lenstra jr. 1. Prerequisites This section consists of an enumeration of terms from elementary set theory and algebra. You are supposed to be familiar with their

More information

Math 231b Lecture 35. G. Quick

Math 231b Lecture 35. G. Quick Math 231b Lecture 35 G. Quick 35. Lecture 35: Sphere bundles and the Adams conjecture 35.1. Sphere bundles. Let X be a connected finite cell complex. We saw that the J-homomorphism could be defined by

More information

Department of Pure Mathematics and Mathematical Statistics University of Cambridge GEOMETRY AND GROUPS

Department of Pure Mathematics and Mathematical Statistics University of Cambridge GEOMETRY AND GROUPS Department of Pure Mathematics and Mathematical Statistics University of Cambridge GEOMETRY AND GROUPS Albrecht Dürer s engraving Melencolia I (1514) Notes Michaelmas 2012 T. K. Carne. t.k.carne@dpmms.cam.ac.uk

More information

Question 2: How do you solve a matrix equation using the matrix inverse?

Question 2: How do you solve a matrix equation using the matrix inverse? Question : How do you solve a matrix equation using the matrix inverse? In the previous question, we wrote systems of equations as a matrix equation AX B. In this format, the matrix A contains the coefficients

More information

A numerable cover of a topological space X is one which possesses a partition of unity.

A numerable cover of a topological space X is one which possesses a partition of unity. Chapter 1 I. Fibre Bundles 1.1 Definitions Definition 1.1.1 Let X be a topological space and let {U j } j J be an open cover of X. A partition of unity relative to the cover {U j } j J consists of a set

More information

How To Solve The Group Theory

How To Solve The Group Theory Chapter 5 Some Basic Techniques of Group Theory 5.1 Groups Acting on Sets In this chapter we are going to analyze and classify groups, and, if possible, break down complicated groups into simpler components.

More information

Transfer of the Ramsey Property between Classes

Transfer of the Ramsey Property between Classes 1 / 20 Transfer of the Ramsey Property between Classes Lynn Scow Vassar College BLAST 2015 @ UNT 2 / 20 Classes We consider classes of finite structures such as K < = {(V,

More information

Probabilistic Strategies: Solutions

Probabilistic Strategies: Solutions Probability Victor Xu Probabilistic Strategies: Solutions Western PA ARML Practice April 3, 2016 1 Problems 1. You roll two 6-sided dice. What s the probability of rolling at least one 6? There is a 1

More information

DECOMPOSING SL 2 (R)

DECOMPOSING SL 2 (R) DECOMPOSING SL 2 R KEITH CONRAD Introduction The group SL 2 R is not easy to visualize: it naturally lies in M 2 R, which is 4- dimensional the entries of a variable 2 2 real matrix are 4 free parameters

More information

Solutions to TOPICS IN ALGEBRA I.N. HERSTEIN. Part II: Group Theory

Solutions to TOPICS IN ALGEBRA I.N. HERSTEIN. Part II: Group Theory Solutions to TOPICS IN ALGEBRA I.N. HERSTEIN Part II: Group Theory No rights reserved. Any part of this work can be reproduced or transmitted in any form or by any means. Version: 1.1 Release: Jan 2013

More information

6. LECTURE 6. Objectives

6. LECTURE 6. Objectives 6. LECTURE 6 Objectives I understand how to use vectors to understand displacement. I can find the magnitude of a vector. I can sketch a vector. I can add and subtract vector. I can multiply a vector by

More information

Inner Product Spaces and Orthogonality

Inner Product Spaces and Orthogonality Inner Product Spaces and Orthogonality week 3-4 Fall 2006 Dot product of R n The inner product or dot product of R n is a function, defined by u, v a b + a 2 b 2 + + a n b n for u a, a 2,, a n T, v b,

More information