Chapter 3 Group Theory p. 1 - Remark: This is only a brief summary of most important results of groups theory with respect

Similar documents
v a 1 b 1 i, a 2 b 2 i,..., a n b n i.

where the coordinates are related to those in the old frame as follows.

Recurrence. 1 Definitions and main statements

8.5 UNITARY AND HERMITIAN MATRICES. The conjugate transpose of a complex matrix A, denoted by A*, is given by

This circuit than can be reduced to a planar circuit

Linear Circuits Analysis. Superposition, Thevenin /Norton Equivalent circuits

Chapter 7 Symmetry and Spectroscopy Molecular Vibrations p. 1 -

We are now ready to answer the question: What are the possible cardinalities for finite fields?

Face Verification Problem. Face Recognition Problem. Application: Access Control. Biometric Authentication. Face Verification (1:1 matching)

Conversion between the vector and raster data structures using Fuzzy Geographical Entities

BERNSTEIN POLYNOMIALS

1 Example 1: Axis-aligned rectangles

What is Candidate Sampling

PERRON FROBENIUS THEOREM

1. Fundamentals of probability theory 2. Emergence of communication traffic 3. Stochastic & Markovian Processes (SP & MP)

21 Vectors: The Cross Product & Torque

Module 2 LOSSLESS IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur

Ring structure of splines on triangulations

An Alternative Way to Measure Private Equity Performance

Efficient Project Portfolio as a tool for Enterprise Risk Management

Support Vector Machines

Loop Parallelization

IT09 - Identity Management Policy

n + d + q = 24 and.05n +.1d +.25q = 2 { n + d + q = 24 (3) n + 2d + 5q = 40 (2)

The OC Curve of Attribute Acceptance Plans

L10: Linear discriminants analysis

Brigid Mullany, Ph.D University of North Carolina, Charlotte

Extending Probabilistic Dynamic Epistemic Logic

Traffic State Estimation in the Traffic Management Center of Berlin

Institute of Informatics, Faculty of Business and Management, Brno University of Technology,Czech Republic

Product-Form Stationary Distributions for Deficiency Zero Chemical Reaction Networks

Politecnico di Torino. Porto Institutional Repository

Comparison of Control Strategies for Shunt Active Power Filter under Different Load Conditions

The Full-Wave Rectifier

Feature selection for intrusion detection. Slobodan Petrović NISlab, Gjøvik University College

A Simple Approach to Clustering in Excel

A Performance Analysis of View Maintenance Techniques for Data Warehouses

Production. 2. Y is closed A set is closed if it contains its boundary. We need this for the solution existence in the profit maximization problem.

Implementation of Deutsch's Algorithm Using Mathcad

How To Assemble The Tangent Spaces Of A Manfold Nto A Coherent Whole

Study on Model of Risks Assessment of Standard Operation in Rural Power Network

A Novel Methodology of Working Capital Management for Large. Public Constructions by Using Fuzzy S-curve Regression

HÜCKEL MOLECULAR ORBITAL THEORY

Causal, Explanatory Forecasting. Analysis. Regression Analysis. Simple Linear Regression. Which is Independent? Forecasting

QUESTIONS, How can quantum computers do the amazing things that they are able to do, such. cryptography quantum computers

Luby s Alg. for Maximal Independent Sets using Pairwise Independence

The descriptive complexity of the family of Banach spaces with the π-property

Small pots lump sum payment instruction

Forecasting the Direction and Strength of Stock Market Movement

A Probabilistic Theory of Coherence

Performance Analysis and Coding Strategy of ECOC SVMs

The Greedy Method. Introduction. 0/1 Knapsack Problem

MONITORING METHODOLOGY TO ASSESS THE PERFORMANCE OF GSM NETWORKS

How To Calculate The Accountng Perod Of Nequalty

THE METHOD OF LEAST SQUARES THE METHOD OF LEAST SQUARES

Can Auto Liability Insurance Purchases Signal Risk Attitude?

DEFINING %COMPLETE IN MICROSOFT PROJECT

SPEE Recommended Evaluation Practice #6 Definition of Decline Curve Parameters Background:

Rate Monotonic (RM) Disadvantages of cyclic. TDDB47 Real Time Systems. Lecture 2: RM & EDF. Priority-based scheduling. States of a process

REGULAR MULTILINEAR OPERATORS ON C(K) SPACES

PSYCHOLOGICAL RESEARCH (PYC 304-C) Lecture 12

Multiplication Algorithms for Radix-2 RN-Codings and Two s Complement Numbers

Matrix Multiplication I

Least Squares Fitting of Data

I. INTRODUCTION. 1 IRCCyN: UMR CNRS 6596, Ecole Centrale de Nantes, Université de Nantes, Ecole des Mines de Nantes

Fisher Markets and Convex Programs

copyright 1997 Bruce A. McCarl and Thomas H. Spreen.

Reporting Forms ARF 113.0A, ARF 113.0B, ARF 113.0C and ARF 113.0D FIRB Corporate (including SME Corporate), Sovereign and Bank Instruction Guide

An Integrated Semantically Correct 2.5D Object Oriented TIN. Andreas Koch

Hollinger Canadian Publishing Holdings Co. ( HCPH ) proceeding under the Companies Creditors Arrangement Act ( CCAA )

FREQUENCY OF OCCURRENCE OF CERTAIN CHEMICAL CLASSES OF GSR FROM VARIOUS AMMUNITION TYPES

The Development of Web Log Mining Based on Improve-K-Means Clustering Analysis

TENSOR GAUGE FIELDS OF DEGREE THREE

"Research Note" APPLICATION OF CHARGE SIMULATION METHOD TO ELECTRIC FIELD CALCULATION IN THE POWER CABLES *

Lecture 3: Force of Interest, Real Interest Rate, Annuity

BRNO UNIVERSITY OF TECHNOLOGY

Calculation of Sampling Weights

A Secure Password-Authenticated Key Agreement Using Smart Cards

Rotation Kinematics, Moment of Inertia, and Torque

Copulas. Modeling dependencies in Financial Risk Management. BMI Master Thesis

Nonlinear Time Series Analysis in a Nutshell

Allocating Collaborative Profit in Less-than-Truckload Carrier Alliance

Generalizing the degree sequence problem

POLYSA: A Polynomial Algorithm for Non-binary Constraint Satisfaction Problems with and

The Mathematical Derivation of Least Squares

RESEARCH ON DUAL-SHAKER SINE VIBRATION CONTROL. Yaoqi FENG 1, Hanping QIU 1. China Academy of Space Technology (CAST)

How To Understand The Results Of The German Meris Cloud And Water Vapour Product

HALL EFFECT SENSORS AND COMMUTATION

Peak Inverse Voltage

The Distribution of Eigenvalues of Covariance Matrices of Residuals in Analysis of Variance

GRAVITY DATA VALIDATION AND OUTLIER DETECTION USING L 1 -NORM

Logistic Regression. Lecture 4: More classifiers and classes. Logistic regression. Adaboost. Optimization. Multiple class classification

An Interest-Oriented Network Evolution Mechanism for Online Communities

Research of Network System Reconfigurable Model Based on the Finite State Automation

Parallel Algorithms for Big Data Optimization

Power-of-Two Policies for Single- Warehouse Multi-Retailer Inventory Systems with Order Frequency Discounts

On Lockett pairs and Lockett conjecture for π-soluble Fitting classes

Damage detection in composite laminates using coin-tap method

Software project management with GAs

Fixed income risk attribution

Transcription:

Chapter 3 Group Theory p. - 3. Compact Course: Groups Theory emark: Ths s only a bref summary of most mportant results of groups theory wth respect to the applcatons dscussed n the followng chapters. For a more detaled descrpton see references. 3. Defnton of a group We assume a set of elements G {A, B, C,...}. Furthermore, we assume that there s a defnton of a combnaton of two elements AB, whch we denote as the product of two elements. G s a group f the followng condtons are satsfed:. Closure: AB G The product of two elements of the group s also an element of the group.. Identty element: The s an element E G, such that AE EA A for all A G. A neutral element exsts, whch has no effect on the other elements f the group. 3. Assocate law: A ( BC ) ( AB ) C for all A, B, C G. 4. Inerse element: The s an element A G, such that A A E for all A G. In nerse element exsts for all elements of the group, whch nerts the acton of a gen element. For some, but not for all groups, the commutate law holds (commutate law: AB BA for all A G ). These groups are called Abelan groups. Wthout proof (see e.g. F. A. Cotton): C ( ABC ) A B. (3.: Example for a group) 3. rder of a group The number of elements of a group s called the order of the group.

Chapter 3 Group Theory p. - 3.3. ultplcaton table For any group, we can set up a multplcaton table, whch tabulates the results of the products of two elements. Wthout proof: Eery lne and column contans eery group element exactly once. No lne or column s dentcal to another one. (3.: How many types of groups are there wth three elements? Dere the multplcaton tables.) 3.4 Cyclc groups In a cyclc group all n elements are generated by powers of the frst element n n G {E( A ), A, A,...A }. (3.3: Example of a cyclc group) An mportant property of cyclc groups s that they are Abelan (as n m n+ m A A A A m A n ). 3.5 Subgroups A subset of the elements of the group G can tself form a group U. We call U a subgroup of G. (3.4: Example of a subgroup) 3.6 Symmetry groups The complete set of symmetry elements of a molecule, surface or crystal has the mathematc structure of a group. The set s called the symmetry group. (3.5: Example of a symmetry group. H molecule: show that the symmetry elements behae lke a group). 3.7 Classes We defne a smlarty transformaton B X AX

Chapter 3 Group Theory p. 3 - whch transform some element A by means of another element X nto some other element B. If A and X are elements of the group G, the elements are called conugated elements. A complete set of elements, whch s conugated to one another s called a class of elements of the group. The classes hae a fgurate meanng: Those symmetry operatons belong to the same class, whch can be reached by a transformaton of the coordnate system, whch s part of the symmetry group. (3.6: Example: Dde the elements of the symmetry group C 4 nto classes). (The defnton of classes wll greatly smplfy the work wth symmetry groups). 3.8 epresentaton of symmetry operatons by matrces We can represent all symmetry operatons dscussed so far n the form of a matrx. In the smplest case, these matrces act on ponts X r n three-dmensonal space and assgn a new poston bass coordnated r r X X (Note: f nstead we consder a bass transformaton defnng the new B r n terms of the old one as X r are r r - X A X ): (3.7: Examples for matrx representatons of symmetry operatons). r r B AB, the coordnates of the pont n the new 3.9 epresentatons of a group A set of matrces whch upon multplcaton behaes analogous to the elements of a group s called a representaton of the group. Example: We consder the transformaton of a pont X r n three dmensonal space accordng to the symmetry operatons of group C V.

Chapter 3 Group Theory p. 4 - E ; C ; ; Wth respect to matrx multplcaton, these matrces follow the multplcaton table of group C V. 3. educble and rreducble representatons As specfc case of matrces are so called block-dagonal matrces. Block-dagonal matrces are multpled accordng to the scheme,.e. the multplcaton can be reduced to the multplcatons of the sub-matrces of lower dmenson: y b x a y x b a For the specfc example consdered, the matrces are completely dagonal,.e. all blocks are of dmenson. Accordngly we can reduce the three dmensonal representaton gen aboe nto three one-dmensonal representatons, whch agan are representatons of the symmetry group C V : E E E ; C C C ; ; We consder a representaton of a group by a set of matrces of dmenson n. Addtonally, we consder a bass transformaton to a new coordnate system B B r r A, wth the coordnates of a ector n the new bass n terms of the old coordnates X X r - A. The representaton of the group n the new bass s A A A -. For any representaton, we can search for the bass transformaton, whch yelds a set of representatons wth lowest possble dmenson. We

Chapter 3 Group Theory p. 5 - denote a representaton wth the lowest possble dmenson as an rreducble representaton and a representaton wth hgher than mnmum dmenson as a reducble representaton. The example shows that there are rreducble representatons (bref: rreps) of dfferent type,.e. behang dfferently wth respect to the symmetry operatons contaned n the group. 3. Character of a matrx We defne the character χ of a matrx Γ as the sum oer the dagonal elements: Γ χ Γ. Γ (3.8: Character of matrces). The character of a matrx has an mportant property: It s narant upon a transformaton of the bass. (3.9: Character of matrces). Ths s qute handy, as n the followng t allows us to work wth characters nstead of the full representaton matrces, rrespecte of a specfc choce of the bass. 3. Propertes of rreducble representatons: GT great orthogonalty theorem (for proof see textbooks) Γ ( ) mnγ ( ) m n * δ δ δ mm nn h l l wth h : order of the group : symmetry operaton of the group Γ ( ) : matrx representaton for operaton of the rreducble representaton of type l : dmenson of the -th type of rreducble representaton

Chapter 3 Group Theory p. 6 - The ectors consstng of correspondng elements of the representaton matrces are orthogonal and normalzed. There are a number of smpler conclusons followng from the GT, whch can be easly proen (see e.g. A. F. Cotton), e.g: l χ ( E) h ; sum oer the dmenson squares of the rreps (sum oer the character squares of the dentty element) s equal to the order of the group. χ ( ) h ; sum oer character sqares oer all symmetry operaton for a gen type of representaton s equal to the order of the group. ( ) ( ) χ χ hδ : Character ectors of dfferent rreps are orthogonal. The characters of representaton matrces for a gen type of rrep for operatons belongng to a common class are dentcal. The number of classes s equal to the number of rreps. (3.: Deelop the characters and representaton matrces for the symmetry group C V from the aboe statements). 3.3 Analyss of reducble representatons The followng dea s a key pont for a large number of applcatons n the next chapters of ths course. We assume that Γ ( ) s a reducble representaton of the symmetry group G wth the correspondng characters χ ( ). We would lke to know, how many rreducble representatons of symmetry type are contaned n Γ ( ). For ths reason we assume that we hae transformed Γ ( ) to ts blockdagonal form ( ) As the characters are narant wth respect to ths transformaton, we obtan: χ ( ) χ ( ) a χ ( ) wth ( ) χ : character of -th rrep of group Γ. a : number of tmes that -th rrep s contaned n Γ ( ) By multplyng wth χ ( ) and summng oer all operatons of the group:

χ ( ) χ ( ) a χ ( ) χ ( ) a a χ ha h χ ( ) χ ( ) ( ) χ ( ) 443 4 hδ a χ( ) χ ( ) Chapter 3 Group Theory p. 7 - Here, all we need as an nput s the characters of the rreps of the group. These are lsted n the so called character tables. 3.4 Character tables ost mportant nformaton whch s requred to work wth a gen symmetry group s summarzed n the co called character table. Example: C 4V group name (Schoenfless) symmetry operatons ordered by classes symmetry propertes of some functons and ther classfcaton by rreps C 4V E C 4 C d A z x +y, z A - - z B - - x -y B - - (x, y) xy E - ( x, y ) (xz, yz)

Chapter 3 Group Theory p. 8 - st of rreducble representatons: ullken notaton: () dm. rreps: A, B dm. rreps: E 3 dm. rreps: T 4 dm. rreps: G 5 dm. rreps: H () A/B: symmetrc / antsymmetrc wth respect to rotaton by π/n around prncple axs C n. (3) Index /: symmetrc / antsymmetrc wth respect to rotaton by π around C axs (perpendcular to C n ). (4) or : symmetrc / antsymmetrc wth respect to h. (5) g/u: symmetrc / antsymmetrc wth respect to.