Matrices Lie: An introduction to matrix Lie groups and matrix Lie algebras By Max Lloyd A Journal submitted in partial fulfillment of the requirements for graduation in Mathematics. Abstract: This paper is an introduction to Lie theory and matrix Lie groups. In working with familiar transformations on real, complex and quaternion vector spaces this paper will define many well studied matrix Lie groups and their associated Lie algebras. In doing so it will introduce the types of vectors being transformed, types of transformations, what groups of these transformations look like, tangent spaces of specific groups and the structure of their Lie algebras. Whitman College 2015 1 Contents 1 Acknowledgments 3 2 Introduction 3 3 Types of Numbers and Their Representations 3 3.1 Real (R)................................4 3.2 Complex (C).............................4 3.3 Quaternion (H)............................5 4 Transformations and General Geometric Groups 8 4.1 Linear Transformations . .8 4.2 Geometric Matrix Groups . .9 4.3 Defining SO(2)............................9 5 Conditions for Matrix Elements of General Geometric Groups 11 5.1 SO(n) and O(n)........................... 11 5.2 U(n) and SU(n)........................... 14 5.3 Sp(n)................................. 16 6 Tangent Spaces and Lie Algebras 18 6.1 Introductions . 18 6.1.1 Tangent Space of SO(2) . 18 6.1.2 Formal Definition of the Tangent Space . 18 6.1.3 Tangent space of Sp(1) and introduction to Lie Algebras . 19 6.2 Tangent Vectors of O(n), U(n) and Sp(n)............. 21 6.3 Tangent Space and Lie algebra of SO(n).............. 22 6.4 Tangent Space and Lie algebras of U(n), SU(n) and Sp(n)... 24 6.5 Dimensions of Tangent Spaces . 26 6.6 Non-Geometric Lie Goups and Their Lie Algebras . 28 6.6.1 GL(n; C) and gl(n; C).................... 28 6.6.2 SL(n; C) and sl(n; C).................... 28 7 Lie Algebra Structure 29 7.1 Algebra Topics . 29 7.2 Normal Subgroups, Ideals and Simplicity . 29 7.3 Homomorphisms . 31 7.4 Non-simple Lie Algebras . 32 7.4.1 gl(n; C)............................ 32 7.4.2 so(4).............................. 33 7.4.3 Constructing gl(n; C) From Simple Algebras . 33 2 1 Acknowledgments A special thank you to Barry Balof, Moira Gresham and Patrick Keef for provid- ing a guiding hand throughout the project, Alex Porter for editing my papers and John Stillwell, whose book Naive Lie Theory is the basis of this paper. Without your support and instruction this would not have been possible. 2 Introduction Lie theory was developed by mathematician Sophus Lie in the late 19th century. In essence it rests on the theory of continuous groups or groups with a continuous operation. In this paper we specifically discuss groups of matrices corresponding to linear transformations on different spaces. In order to do this we will utilize the conventions and structure presented in [1]. In general Lie theory is strongly rooted in topology and the group structure of smooth differentiable manifolds. This, however, is beyond the scope of this paper. Since we only aim to introduce the fundamental concepts of Lie theory we choose to narrow our focus onto matrix Lie groups or Lie groups whose elements are all matrices. What makes a group \Lie" is that it has an associated vector algebra or Lie algebra. This algebra can be found by exploiting the continuous nature of a Lie group and bestowing upon it the structure of a Lie Bracket. This algebra can be far easier to work in so operations can be made here before moving back to the group through a process called exponentiation. Though we do not talk explicitly about exponentiation the purpose of this paper is to get the reader to become antiquated with what a matrix Lie group is and how it generates an algebra. To help the reader understand this process the paper will focus specifically on the general geometric groups which are groups of matrices corresponding to rotations and isometries of real, complex and quaternion vector spaces. This is done by slowly constructing the definitions of each group before finding their Lie algebras. Specifically, in section 3 we will introduce what real, complex and quaternion elements look like and learn how we represent them. In section 4 we will explicitly define the types of transformations we are interested in and the conditions for matrices in each geometric group. In section 5 we will define the actual elements in each general geometric group. In section 6 we will use the explicit elements in each geometric group to define their Lie algebra and in section 7 we will dive into the structure of each Lie algebra. 3 Types of Numbers and Their Representations To begin we will discuss and use of specific numbers and their representations. Specifically we will examine the reals (R), complexes (C) and quaternions (H). Usually when one thinks about something real or complex they imagine a num- ber like 2 or 3 + 4i. This, however, is just a representation of an element in either set. For the purposes of this paper we will define each element of our three sets using a point in a real vector field and choose to express it as either 3 a number or a matrix. In this way we say that a real number characterizes a one dimensional point, a complex number characterizes an ordered pair, and a quaternion characterizes an ordered quadruple. The explicit form of for each is outlined in the table in Figure 1. Each number will now be discussed in greater detail. 3.1 Real (R) We should be familiar with the real numbers. Let's start with some real number a. This characterizes a point that is at the location a on a number line and can be represented as either the number a or the 1 × 1 matrix [a]. The difference between these two representations is trivial. Clearly all algebraic operations behave exactly the same between the numerical and matrix representations. The only other operation worth note is that det([a]) = a which the distance from a to the origin. 3.2 Complex (C) Now consider some complex number z = a + ib. This characterizes the ordered pair (a; b) 2 R2 and can be represented as the 2 × 2 real matrix a −b Z = : b a We want to explore this matrix a bit farther. Notice that we can decompose z into a −b 1 0 0 −1 Z = = a + b : b a 0 1 1 0 From now on we will call any n × n identity matrix unity and denote it 1. Now let us explore the second matrix in the term a bit further. Notice that 2 0 −1 −1 0 = = −1: 1 0 0 −1 This means that 0 −1 p = -1 1 0 Type Characterizes As a Number As a Matrix \Real" (R) (a) 2 R a [a] a −b \Complex" ( ) (a; b) 2 2 a + bi C R b a a + bi −c − di \Quaternion" ( ) (a; b; c; d) 2 4 a + bi + cj + dk H R c − di a − bi Figure 1: Numerical and matrix representations of reals, complexes and quater- nions 4 and therefore behaves just likep the imaginary number i. Thus, we can rewrite our matrix form as Z = a1 + b -1 which looks strikingly similar to our numer- ical form for a complex number. This offers a linear algebra explanation as a rationale behind the behavior of complex numbers. Now we want to explore the matrix form a bit further. First notice that a −b 2 2 det(Z) = = a + b b a which is the distance between (a; b) and the origin. Now lets explore some more properties of the matrix form. a −b c −d Let Z = and Z = be two complex number in matrix 1 b a 2 c d from. First notice that a −b c −d ac − bd −(ad + bc) Z Z = = = Z Z 1 2 b a d c ad + dc ac − bd 2 1 which is the matrix form of the complex number ad − dc + i(ac − bd) = (a + bi)(c + di): This is an expected result and shows that multiplication between representations is isomorphic which includes the abelian nature of complex multiplication. For the remainder of the paper we will definep the conjugate of any complex numberp z = a + ib as z = a − ib and Z = a1 − b -1 for any complex Z = a1 + b -1 in matrix form. 3.3 Quaternion (H) To begin our discussion of quaternions first examine some complex number z. Notice that we associate it with the ordered pair (a; b) 2 R2 and number a + ib under the condition that i2 = −1. We can do the same for ordered quadruples. Start with the ordered quadruple (a; b; c; d) 2 R4 we can now associate it with the quaternion q = a + bi + cj + dk: under the condition that i2 = j2 = k2 = -1, ij = −ji = k, ki = −ik = j and jk = −kj = i. Or more succinctly ijk = i2 = j2 = k2 = −1: This is the numerical representation of a quaternion. We will call the ladder equation the Hamilton Relation. A note on quaternions is that they are non- commutative; that is for any two quaternions q1 and q2 it is not usually the case that q1q2 = q2q1. This is a critical feature of quaternions and is what sets them apart from most other types of numbers. 5 Now let us discuss the matrix form of a quaternion. Any quaternion q = a + bi + cj + dk has the matrix form a + id −b − ic α −β q = = b − ic a − id β∗ α∗ if we let α = a + id and β = b + ic.