1 Group representations Consider the group C 4v ElementMatrix E1 0 0 0 1 0 0 0 1 C 4 0 1 0 -1 0 0 0 0 1 C 2 -1 0 0 0 -1 0 0 0 1 C 4 0 -1 0 1 0 0 0 0 1.

Slides:



Advertisements
Similar presentations
2.3 Modeling Real World Data with Matrices
Advertisements

Group Theory II.
Identity and Inverse Matrices
Matrices A matrix is a rectangular array of quantities (numbers, expressions or function), arranged in m rows and n columns x 3y.
Part 2.4: Rules that Govern Symmetry 1. Define Group Theory The Rules for Groups Combination Tables Additional Rules/Definitions – Subgroups – Representations.
Linear Algebra.
Mathematics. Matrices and Determinants-1 Session.
Maths for Computer Graphics
ECIV 301 Programming & Graphics Numerical Methods for Engineers Lecture 12 System of Linear Equations.
CHEM 515 Spectroscopy Lecture # 10 Matrix Representation of Symmetry Groups.
Chapter 3 Determinants and Matrices
Lecture # 9 Matrix Representation of Symmetry Groups
Lecture 3.
Chapter 2 Matrices Definition of a matrix.
Ch 7.2: Review of Matrices For theoretical and computation reasons, we review results of matrix theory in this section and the next. A matrix A is an m.
1 Neural Nets Applications Vectors and Matrices. 2/27 Outline 1. Definition of Vectors 2. Operations on Vectors 3. Linear Dependence of Vectors 4. Definition.
Section 9.6 Determinants and Inverses Objectives To understand how to find a determinant of a 2x2 matrix. To understand the identity matrix. Do define.
Part 2.5: Character Tables
Matrices MSU CSE 260.
Intro to Matrices Don’t be scared….
CE 311 K - Introduction to Computer Methods Daene C. McKinney
Section 10.3 – The Inverse of a Matrix No Calculator.
Lecture 10 REPRESENTATIONS OF SYMMETRY POINT GROUPS 1) Basis functions, characters and representations Each symmetry operation in a group can be represented.
UnB - Financial Econometrics I Otavio Medeiros 1 The Matrix Otavio R. de Medeiros UnB Programa de Pós-Graduação em Administração Programa Multiinstitucional.
Symmetry and Group Theory
Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley 7.1 Solving Systems of Two Equations.
Graphics CSE 581 – Interactive Computer Graphics Mathematics for Computer Graphics CSE 581 – Roger Crawfis (slides developed from Korea University slides)
8.1 Vector spaces A set of vector is said to form a linear vector space V Chapter 8 Matrices and vector spaces.
Symplectic Group.  The orthogonal groups were based on a symmetric metric. Symmetric matrices Determinant of 1  An antisymmetric metric can also exist.
Copyright © 2011 Pearson, Inc. 7.2 Matrix Algebra.
Matrices Addition & Subtraction Scalar Multiplication & Multiplication Determinants Inverses Solving Systems – 2x2 & 3x3 Cramer’s Rule.
Matrices. Definitions  A matrix is an m x n array of scalars, arranged conceptually as m rows and n columns.  m is referred to as the row dimension.
Matrix Algebra and Regression a matrix is a rectangular array of elements m=#rows, n=#columns  m x n a single value is called a ‘scalar’ a single row.
General Introduction to Symmetry in Crystallography A. Daoud-Aladine (ISIS)
Matrices A matrix is a table or array of numbers arranged in rows and columns The order of a matrix is given by stating its dimensions. This is known as.
Linear Algebra 1.Basic concepts 2.Matrix operations.
17. Group Theory 1.Introduction to Group Theory 2.Representation of Groups 3.Symmetry & Physics 4.Discrete Groups 5.Direct Products 6.Symmetric Groups.
4.4 Identify and Inverse Matrices Algebra 2. Learning Target I can find and use inverse matrix.
Notes 7.2 – Matrices I. Matrices A.) Def. – A rectangular array of numbers. An m x n matrix is a matrix consisting of m rows and n columns. The element.
Meeting 18 Matrix Operations. Matrix If A is an m x n matrix - that is, a matrix with m rows and n columns – then the scalar entry in the i th row and.
Matrices and Determinants
2.5 Determinants and Multiplicative Inverses of Matrices. Objectives: 1.Evaluate determinants. 2.Find the inverses of matrices. 3.Solve systems of equations.
MATRICES Operations with Matrices Properties of Matrix Operations
2.5 – Determinants and Multiplicative Inverses of Matrices.
LEARNING OUTCOMES At the end of this topic, student should be able to :  D efination of matrix  Identify the different types of matrices such as rectangular,
CS 450: COMPUTER GRAPHICS TRANSFORMATIONS SPRING 2015 DR. MICHAEL J. REALE.
Linear System of Simultaneous Equations Warm UP First precinct: 6 arrests last week equally divided between felonies and misdemeanors. Second precinct:
Matrix Algebra Basics Chapter 3 Section 5. Algebra.
Matrices. Variety of engineering problems lead to the need to solve systems of linear equations matrixcolumn vectors.
Graphics Graphics Korea University kucg.korea.ac.kr Mathematics for Computer Graphics 고려대학교 컴퓨터 그래픽스 연구실.
Introduction Types of Matrices Operations
A very brief introduction to Matrix (Section 2.7) Definitions Some properties Basic matrix operations Zero-One (Boolean) matrices.
2.1 Matrix Operations 2. Matrix Algebra. j -th column i -th row Diagonal entries Diagonal matrix : a square matrix whose nondiagonal entries are zero.
1 Matrix Math ©Anthony Steed Overview n To revise Vectors Matrices.
MTH108 Business Math I Lecture 20.
Matrices and Vector Concepts
Matrices and vector spaces
Finding the Inverse of a Matrix
Matrix Operations Add and Subtract Matrices Multiply Matrices
Multiplication of Matrices
Warm-up a. Solve for k: 13 −5
2. Matrix Algebra 2.1 Matrix Operations.
Derivative of scalar forms
Section 3.3 – The Inverse of a Matrix
Matrices Introduction.
MATRICES Operations with Matrices Properties of Matrix Operations
PHY 752 Solid State Physics
Multiplication of Matrices
L4-5/L4-6 Objective: Students will be able to evaluate determinants of matrices.
Matrices and Determinants
Presentation transcript:

1 Group representations Consider the group C 4v ElementMatrix E C C C Example molecule: SF 5 Cl S F F F F Cl F x y z 3

2 Group representations Consider the group C 4v ElementMatrix E C C C Example molecule: SF 5 Cl S F F F F Cl F x y z (xyz) (yxz) 3

3 Group representations Consider the group C 4v Element Matrix E C C  v  v C  d  d Example molecule: SF 5 Cl S F F F F Cl F x y z 3 ' '

4 Group representations These matrices obey all rules for a group when combination rule is matrix multiplication: Identity exists - E Products in group =  v C 4  d '

5 Group representations These matrices obey all rules for a group when combination rule is matrix multiplication: Identity exists - E Products in group =  v C 4  d Inverses in group Transpose matrix; determine co-factor matrix of transposed matrix; divide by determinant of original matrix '

6 Group representations These matrices obey all rules for a group when combination rule is matrix multiplication: Inverses in group Transpose matrix; determine co-factor matrix of transposed matrix ; divide by determinant of original matrix C 4 transpose co-factor matrix det = 1 3

7 Group representations These matrices obey all rules for a group when combination rule is matrix multiplication: Inverses in group Transpose matrix; determine co-factor matrix of transposed matrix ; divide by determinant of original matrix C 4 transpose inverse = C 4 All matrices listed show these properties 3

8 Group representations These matrices obey all rules for a group when combination rule is matrix multiplication: Inverses in group Transpose matrix; determine co-factor matrix of transposed matrix ; divide by determinant of original matrix C 4 transpose inverse = C 4 The matrices represent the group Each individual matrix represents an operation 3

9 Group representations Set of representation matrices that can be block diagonalized termed a reducible representation Ex: trace = trace = 1

10 Group representations Set of representation matrices that can be block diagonalized termed a reducible representation Ex: trace = trace = 1 Character  of matrix is its trace (sum of diagonal elements)

11 Group representations Consider the group C 4v Element Matrix E1 0 0all matrices can be block diagonalized - all are reducible C C  v  v C  d  d ' '

12 Irreducible Representations 1. Sum of squares of dimensions d i of the irreducible representations of a group = order of group 2. Sum of squares of characters  i in any irreducible representation = order of group 3. Any two irreducible representations are orthogonal (sum of products of characters representing each operation = 0) 4. No. of irreducible representations of group = no. of classes in group (class = set of conjugate elements)

13 Irreducible Representations Ex: C 2h (E, C 2, i,  h ) Each operation constitutes a class C 2 – E -1 C 2 E = C 2 (C 2 ) -1 C 2 C 2 = C 2 i -1 C 2 i = C 2 (  h ) -1 C 2  h = C 2 Other elements behave similarly C 2h

14 Irreducible Representations Ex: C 2h (E, C 2, i,  h ) Each operation constitutes a class Must be 4 irreducible representations Order of group = 4: d d d d 4 2 = 4 All d i = ±1 All  i = ±1

15 Irreducible Representations Ex: C 2h (E, C 2, i,  h ) Each operation constitutes a class Thus, must be 4 irreducible representations Order of group = 4: d d d d 4 2 = 4 All d i = ±1 All  i = ±1 Let  1 = Array  1 of matrices represents the group – thus exhibits all group props. & has same mult. table E = 1 E -1 = = = 1

16 Irreducible Representations Ex: C 2h (E, C 2, i,  h ) Thus, must be 4 irreducible representations Order of group = 4: d d d d 4 2 = 4 All d i = ±1 All  i = ±1 4 representations: E C 2 i  h   –1 –1  3 1 –1 –1 1  4 1 –1 1 –1

17 Irreducible Representations Ex: C 2h (E, C 2, i,  h ) 4 representations: E C 2 i  h   –1 –1  3 1 –1 –1 1  4 1 –1 1 –1 These irreducible representations are orthogonal Ex: (-1) + 1 (-1) = 0 E C i  h

18 Irreducible Representations Ex: C 3v ([E], [C 3, C 3 ], [  v,  v,  v,]) 3 classes, 3 representations: Order of group = 6 Dimensions given by d d d 3 2 = 6 ––> E 2C 3 3  v   –1  3 2 –1 0 '“

19 Irreducible Representations Ex: C 3v ([E], [C 3, C 3 ], [  v,  v,  v,]) 3 classes, 3 representations: Order of group = 6 Dimensions given by d d d 3 2 = 6 ––> E 2C 3 3  v   –1  3 2 –1 0 '“

20 Irreducible Representations Ex: C 3v ([E], [C 3, C 3 ], [  v,  v,  v,]) 3 classes, 3 representations: Order of group = 6 Dimensions given by d d d 3 2 = 6 ––> E 2C 3 3  v   –1  3 2 –1 0 '“ /2 3/2 - 3/2 -1/2

21 Irreducible Representations Ex: C 2h (E, C 2, i,  h ) C 2h E C 2 i  h A g R z B g 1 –1 1 –1 R x R y A u 1 1 –1 –1 z B u 1 –1 –1 1 x y 1-D representations called A (+), B(–) 2-D representations called E 2-D representations called T Subscript 1 - symmetric wrt C 2 perpend to rotation axis g, u – character wrt i