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MSC Classification: 22 (Topological groups, Lie groups) |
Prerequisites: Abstract Algebra I, Abstract Algebra II
Getting Oriented
Page to be included nav:lietheory can not be found!
Using mathematical formalism, a group G may be "represented'' by transformations on a vector space.
Representations
The Basics
A representation of a group
is a vector space
for which one can view each
as a transformation
.
- Representation
- a pair
, where
is a finite dimensional vector space over
, and
is a continuous homomorphism
into the Lie group
of invertible linear transformations.
We will write
for an element of
and
for its corresponding transformation. The dimension of the representation is the dimension of the vector space
. Simple examples of representations include:
- The trivial representation with
or
for all
. - The standard representation for
with
for all
. - A group action
provides a representation with
and
. Thus,
takes the map
to the map
.
Reducible and Unitary Representations
Given an invariant subspace
of a representation
, meaning
for all
, one may restrict
to the subspace representation
with
. The existence of invariant subspaces allows one to break up a representation into smaller pieces. Those without invariant subspaces are:
- Irreducible representation
- a
with no nontrivial invariant subspaces.
As a simple example, a 1-dimensional representation must be irreducible.
Irreducible representations form the building blocks for all others, just as primes do for integers. And as we ask how to decompose a given integer into primes, it is natural to ask when and how we can write
where the
are all irreducible invariant subspaces. Here are some things to consider:
- By extending a basis for an invariant subspace
to a basis for
, we can write all
in block-upper diagonal form
. - If we can write
, we can similarly write
in block-diagonal form
. - Not every invariant subspace provides such a decomposition. Letting
with the standard representation, we have invariant subspace
but its complement
clearly not.
It turns out that a representation
is completely reducible, meaning it can be broken down into irreducible invariant subspace representations, when it finite-dimensional and invariant under a certain inner product:
- Unitary representation
- a representation
for which
for some positive-definite Hermitian inner product
. To be Hermitian, it must satisfy
and
. This is equivalent to requiring the matrices
to be unitary
or
.
The finite-dimensional unitary representations are completely reducible for the following simple fact:
- if
is an invariant subspace, then
is also invariant.
Thus, an algorithm for finding invariant subspaces provides an algorithm for finding the irreducible ones, but only in the finite-dimensional case.
Some Completely Reducible Representations
In order to show that a representation is completely reducible, it suffices to show that it is unitary. In the case of a finite group
, this is easy: take any positive-definite Hermitian inner product
on
and average it over the group by defining:

It is simple to show that
is again positive-definite and Hermitian and it is obvious from the definition that it is invariant under
for
.
This averaging trick also works for any compact group
, although we must now integrate. Again, assuming the existence of a non-degenerate Hermitian inner product
on
, we define

The catch is that the measure
must satisfy certain conditions for this new inner product to be
-invariant. The appropriate notion is: :
(Right) Haar measure : a measure
on a locally compact topological group
defined on the Borel subsets
and satisfying (1) finiteness
for
compact, (2) non-degeneracy
for
non-empty and open, and (3) translation invariance
for
and
.
For such a measure, we have
, making the above inner product invariant under
.
Actually, a Haar measure is unique up to a constant factor, usually chosen so that
. In the finite case, we have
, and this process gives the same inner product as above.
Dual and Tensor Representations
An arbitrary representation
of
gives rise to a dual representation
with
the dual vector space to
and
the contragradient defined by
. Note that
and
, so this inner product is given by
. In terms of matrices (using a given basis and the dual basis), we have
. Also, an invariant subspace
corresponds to an invariant subspace
where
.
Two representations
of
and
of
give a tensor representation
of
defined in the obvious manner by
. In the case that
, we also have a representation on
with
. A major question of interest in representation theory is:
- Given (irreducible) representations
and
, how does one decompose
in terms of irreducible invariant subspaces?
Equivalence of Representations
A map between representations
and
must respect the structure of
, and thus is called a
-map, meaning a linear map
such that
. These maps form the group
. This also provides the notion of equivalence:
- Equivalent Representations
- those for which there exists a
-map
which is also a vector space isomorphism (a
-isomorphism). In this case, the matrix of
with respect to basis
and that of
with respect to basis
coincide. This brings up another major problem in representation theory:
- Find all irreducible representations of a given group
up to equivalence.
A first step in solving this problem is the following intuitive theorem:
- Schur's Lemma
- Let a group
and a
-map
between irreducible representations
and
be given. We have:
- If
, then
for some
; * If
(just an equivalence), then
; - Otherwise,
, and all such
vanish, so that
.
The proof relies on the fact that
-maps preserve invariant subspaces, such as
,
, and
-eigenspaces. This lemma is a simple but powerful tool in representation theory and will be widely used. It follows, for example, that all irreducible representations of abelian groups are 1-dimensional, since all 1-dimensional subspaces are invariant.
Following abelian groups, the next simplest case is that of finite groups. Representations in this case are also easily classified, and are a good model for the general theory. Before we turn to such taxonomical questions, however, we will look at classifying only pieces of representations… specifically class functions… in the Peter-Weyl Theorem.
The Peter-Weyl Theorem
The Peter-Weyl Theorem is really just a generalization of Fourier series:
- Fourier: any function
from the circle to the complex numbers can be approximated by a finite sum of exponentials. - Peter-Weyl Theorem: any class function on a compact group
(those with
) can be approximated by a sum of characters (a character is the trace of a representation).
There are actually many ways to write the Peter-Weyl Theorem, and the classical statement says nothing about class functions and characters. Rather, this result will arise as a corollary.
Fourier Series
We can reinterpret Fourier series in the language of representation theory. First, our group is
, which is abelian. Hence, all representations are 1-dimensional and of the form
with
for
.
We can identify the representation
with the vector space
, which is invariant under translation:
. Then, Fourier theory states that

where
is the space of square-integrable functions on
with respect to the standard Haar measure
. Moreover,
is a complete orthonormal basis for
.
As we have said, this example is a prototype for the Peter-Weyl Theorem, the stated form of which will mimic the
decomposition.
Preliminary Results
In general, we will assume that
is a compact group. This compactness implies that left and right Haar measures on
are equivalent; thus, all Haar measures are invariant under both left
and right
translations.
We now give a slew of results which lead up to the Peter-Weyl Theorem, and can be thought of as extensions of Schur's Lemma:
- (Lemma) For irreducible representations
and
of a compact group
, and
a
-map, set
for a normalized Haar measure. Then,
if
, but
if
.
The map
is a sort of average of
between the two representations. The proof is straightforward: one must show that
is a
-map, so Schur's Lemma can be applied. Then one must show how the lemma's claims for the
-map
extend to
.
- (Corollary) If
and
, then
equals 0 if
but
if
.
This result follows from the previous lemma using the map
. A slight change in language for unitary representations gives the next result.
- (Corollary) Likewise, for unitary representations and Hermitian inner product
, we may take
and obtain
equals 0 if
but
if
.
- (Schur Orthogonality Relation) Here we restrict to matrix elements: if
and
are matrix elements of
and
with respect to orthonormal bases of
and
, then
equals 0 if
or
if
.
This follows from the above by noting that for basis elements
and
, the matrix element is given by
.
The Theorem
We are finally ready for the main result:
- Peter-Weyl Theorem
- Let
be a compact group, and
a complete set of inequivalent unitary representations of
. Given an orthonormal basis
for
, define
. Then,
where
is a complete orthonormal set in
, and
must be countable.
For the proof, first note that
is clearly orthonormal by the Schur Orthogonality Relation given above. It remains to show completeness and countability. In a separable Hilbert space, every orthonormal set is countable, and
is separable since the set of rational polynomials in
forms a countable dense subset.
Actually, all polynomials are matrix coefficients: if
is a polynomial of degree
, then
where
is right translation
and
is the set of polynomials of degree
is a representation. Moreover, selecting
such that
gives
meaning
is a matrix coefficient. So the matrix coefficients are dense in
since the polynomials are, and this verifies completeness.
The Peter-Weyl Theorem allows us to decompose
into subspaces invariant under
. Specifically, we can write

where
is spanned by the matrix coefficients of the representation
. Note that
is invariant under the action of
by left/right translation.
Characters and Class Functions
Basics
The Peter-Weyl Theorem also has consequences for characters and class functions. Characters are functions in
given by the trace of a representation, while a class function is any function invariant under conjugation:
- Character
- given a finite-dimensional representation
, it is the function
given by
. - Class Function
- a function
such that
.
Thus, a class function is really a function on the conjugacy classes of the group. Of course, all characters are class functions since
. Characters have the following properties:
- Equivalent representations have the same character:
implies
. Actually, the reverse implication also holds. - For direct sum and tensor product representations:
and
. - For the dual representation:
; for unitary representations,
. - (Schur Orthogonality for Characters) Given irreducible representations
and
of
, the characters satisfy
: 1 if
and 0 if
.
Characters for Counting
The Schur Orthogonality relation above implies that a lot of information about a representation can be read directly from its character. For example, if a representation
has irreducible direct summands
, and
is an irreducible character of
, then

the number of pieces of
equivalent to
. Thus, we could write
Note that this implies that
is irreducible iff
, or more generally
.
Characters are especially useful because they form a complete orthonormal basis for
class functions. This is perhaps the most important consequence of the Peter-Weyl Theorem. We present the justification in a number of steps:
- Given
, let
be given by
, meaning
This essentially gives a representation over
. - Given a class function
and
irreducible, then
, where
. This follows based on a result prior to the Peter-Weyl Theorem for the matrix
, noting that
. - Given an orthonormal basis
of
with
, then
. A straightforward evaluation demonstrates this, noting that
.
These results give an easy demonstration of:
- Theorem
- Given a class function
and an irreducible representation
of
, we can write
, where
is the set of all representations on
. Hence,
is a complete orthonormal basis for
class functions.
We can also decompose a representation uniquely in terms of its
-isotypic subspace, the direct summand of all irreducible components equivalent to
. Thus,

Uniqueness does not hold for the decomposition into irreducible subspaces however.
Characters can be used to show that the representation
of
is irreducible iff
and
are, and a given irreducible representation
of
can be decomposed
into irreducibles.
Finally, given
, one can write (i)
where
,
, (ii)
where
or
is a matrix coefficient of
. The proof relies on the fact that
is irreducible, where
. One must show that the subspaces generated by functions of the forms given in (i) and (ii) are both invariant, hence all of
.
Representations of Finite Groups
Representation theory for finite groups contains a surprisingly large amount of the theory used in the more general case. We have already seen that all finite representations are unitary using the averaging technique
(7)
a fact which will bring us to several more formula allowing us to completely classify the irreducible representations of a finite group.
Representations via the Group Algebra
Classifying the Representations of Permutation Groups
The methods used to classify the representations of the symmetric groups
are surprisingly adaptable to the case of general Lie groups. In particular, we introduce Young Tableau and the Young Symmetrizer, which will come in again with the classification of general
Lie groups.
The Young Tableau
The irreducible representations of
are in one-to-one correspondence with the conjugacy classes of
, which may be described in terms of partitions:
- Young Diagrams/Tableaus
- A Young Diagram is a graphical representation of a partition of the integer
, that is a set of integers
such that
and
. One may represent this as several rows of boxes, with
boxes on the [[$i$th row. If in addition the boxes are numbered, the diagram is called a Young Tableau.
Each partition has a conjugate partition
where
is the number of boxes in the
of 10 is conjugate to
.
The Young Symmetrizer
The numbering in a Tableau allows the definition of%
(8)

These sets will be very important for classifying the irreducible representations. In terms of the group algebra
these give rise to the elements:%

If
acts on
by permuting its tensor powers (
is any vector space), then these elements can be viewed as functions, and have images:%


Thus,
produces a tensor product of symmetric powers of
and can be thought of as a symmetrizer function, while
produces a tensor product of alternating powers of
and can be thought of as an anti-symmetrizer.
Combining these functions gives:%
- Young Symmetrizer
- the group ring element (or function)%

The images of these functions give essentially all irreducible representations of
. Indeed,
for some scalar
, and if
acts on
by right multiplication (so
), then the image
is a unique irreducible representation of
. All irreps may be obtained in this way.
The element
is therefore an idempotent, meaning
. It is also sometimes called a projector, since it may be interpreted as a map from
to
.
Some Specific Examples
As examples, consider the first few permutation groups.
has just two partitions:
and
which produce representations
, the trivial representation, and
, the alternating representation. Here, the representations are given as
-modules.
Note that the correspondence between a representation
with
and a
-module is essentially given by looking for the basis. In particular, the trivial representation is the one with
for all
. Because
has basis
, we have
, which is of course fixed by left multiplication of any
. Similarly,
, so that the second module is just the alternating representation.
Moving to
, we have three partitions,
and
. Just as above, we see that
is the trivial representation, and
is the alternating representation. For
, we have%
![V_{(2,1)}=\mathbb{C}S_3[a_\lambda\cdot b_\lambda]=\mathbb{C}S_3[(e_1+e_{12})\cdot(e_1-e_{13})]=\mathbb{C}S_3[e_1+e_{12}-e_{13}-e_{132}]=\mathbb{C}S_3[v].](/local--math/eqs/6a7a9757b7f70926ab4cac03ef7d71af.png)
Since the permutation
fixes
, we can reduce this to
, where the last step follows since
. Thus,
is the representation with basis

with
acting on these basis elements in the only manner possible. This is called the standard representation, which for general
is an irreducible quotient of
by an invariant subspace (the sum of basis elements
), where
acts on
by permuting coordinates.
For general
, it is clear that
is the trivial representation and
is the alternating representation. It is actually also true that
is the standard representation. As above we compute
:
![V_{(d-1,1)}=\mathbb{C}S_d [(e_1+e_{12}+\cdots+e_{123\cdots (d-1)})\cdot(e_1-e_{1d})]=\mathbb{C}S_d[v],](/local--math/eqs/a18cfe68457e4b874cc27fd2b0cfaa34.png)
which has basis
, if I had to guess.
What about the conjugate representation
, since tensoring with the alternating representation
corresponds to switching the signs of all odd permutations in the expression
, so that
becomes
, where
is the partition conjugate to
. But it is not too hard to show that
For the exact same reason, it is true in general that
, where
is the conjugate representation to
, and
is the alternating representation.
The above discussion shows that the irreps of
are
(the trivial, alternating, standard, and standard conjugate representations), plus
. This last is 2-dimensional, with basis computed to be
(wild guess) with

As a last example,
has irreps
. How do we show that
, although I'm not sure at this point why.
Projectors and the Character Table
There is a nice correspondence between the character table of a given representation and the projectors
. The permutations in
may be partitioned via their conjugacy class. The character table can be used to write down the projector
: its coefficient for a given permutation is just the entry in the character table for that permutation. These projectors can then be written in terms of symmetrizers and anti-symmetrizers.
For example, the standard representation
of
has character values 2 on the identity element, 0 on swaps, and
on the
conjugacy class. Thus,
![c_{12}=\frac13[2(1)-(123)-(132)],](/local--math/eqs/e919a3bc08bb47ea50f712ce8ce79e84.png)
where the numbers in parentheses are permutations. Incredibly, this also works for any representation
of any permutation group
. Diagrams can be used to greatly simplify the representations of these projectors.
Diagrams for Class Theory
In the general formula for the projector
, there are 2 important components: the symmetrizer pieces
, and the anti-symmetrizer pieces
. We now show how to write these two pieces down in terms of diagrams.
Computational Examples
We now turn to representations of non-finite groups, and illustrate a few cases which will be especially demonstrative of the general classification theory.
Representations of 
The representations of
are a very important case because they indicate the fundamental structure behind every representation of a Lie algebra. The eigenvalues of any irreducible representation form a neat structure. In the case of
, these eigenvalues are colinear and occur on the nice integer lattice, while in the more general case they also have a very nice structure on a (higher-dimensional) lattice.
The best part about the irreducible representations of
is that there is one, and only one, for each integer
, and we can describe how to write down every one of them. Our basic strategy involves three steps:
- Find a suitable abelian subspace
of the Lie algebra. Break the Lie algebra into pieces corresponding to this
. Check that all these pieces preserve the given decomposition. - Decompose
in terms of the eigenspaces of
. Check that this decomposition is preserved by the other pieces of the Lie algebra. - Determine the possible configuration of the eigenspaces by examining their eigenvalues.
Actually, these are the three steps used to write down the representations of any Lie algebra, although it certainly becomes more complicated. This is especially true since
will be cyclic for the case at hand, but not in general.
Step 1:
For our first task, we write down the following basis of
:

Our abelian subspace
consists of the diagonal elements and is generated by
. Note that we have
, and
.
Step 2:
The action of
on our representation
is diagonalizable (a Jordan decomposition argument), so we may decompose
where
for all
.
Step 3:
Now, the question is how the rest of
acts on
; specifically, we must consider
and
. We have for 
=X(\alpha\cdot v)+2X(v)=(\alpha+2)X(v),](/local--math/eqs/0682b81eb8fb7acc1a7bd240803939bd.png)
and so
. Likewise, for
we have
.
Finite-dimensionality and irreducibility combine to give the existence of a vector
such that
spans
. Here, we let
, the largest nonzero eigenspace. This is a finite-dimensional vector space, and invariant under the actions of
,
, and
, hence under all of
. Therefore, it must be all of
.
This means that all eigenspaces are 1-dimensional, and that
is the direct sum of
. Now, if
, then
but
, and so
. Thus,
is an integer, and an irreducible representation
looks like:

We can actually show that
is isomorphic to the representation
by analyzing eigenvalues. It is clear that a representation is uniquely defined by its set of eigenvalues. This fact allows us to solve the Clebsch-Gordon Problem: write down formulae for various products of representations in terms of the irreducibles. In particular, since the eigenvalues of
are just the sum of those in
and those in
, we have:

We also have
One could also obtain these formulae through algebraic geometry…
Representations of 
As might be expected, raising the dimension greatly complicates the problem of writing down the irreducible representations. It is still quite possible, however, and still involves the same three basic steps. The approach must be generalized somewhat, however, and also streamlined. We will introduce a few new terms here which occur in the general theory.
Step 1:
The first difficulty to overcome is that the abelian subspace
from above is no longer generated by a single element. Thus, we must redefine our notions of eigenvector, eigenvalue, and eigenspace to accommodate several generators. Given an abelian subspace
, an eigenvector will satisfy the equation
for all
. Of course, now
depends on
, and thus can be viewed as a element
; so the eigenvalues are now elements of the dual space rather than scalars.
Remarkably, for a suitable choice of
in a general Lie algebra, the action of
on the Lie algebra
and all its representations is simultaneously diagonalizable. What this means is that we can decompose
, where
is an eigenspace for the adjoint action of
: whenever
,
we have
.
Our choice of
will (again) be the set of diagonal matrices. Finding the
is not difficult; the only elements
with
for all diagonal matrices
are those only one nonzero entry. Hence, the subspaces
are generated by the matrix
whose only nonzero entry is
. Letting
, the eigenvectors are elements of the space
generated by
. Since
, we see that
generates the space
. In particular, we have:

Clearly,
preserves this eigenspace decomposition, but it is also true that each
preserves it. In fact, by considering elements of the given subspaces, one can show that
.
Step 2:
Now, we consider an arbitrary representation
of
, and break it up into eigenspaces
, so that whenever
and
we have
. When
is outside
, we have
, and so the action of
on the representation carries
to
. In particular, we see that the eigenvalues of the representation are all in some translate of the lattice
in
generated by
.
Now for some terminology. The eigenvalues
of the adjoint action on
are called roots, with the corresponding
root spaces. The lattice formed by the roots is called the weight lattice, and denote
. For an arbitrary representation, the eigenvalues
are called weights, and the
weight spaces. So, the roots determine how we decompose the Lie algebra, while the weights determine how we decompose the representation.
Step 3:
To finish the proof requires a generalization of an ‘extremal’ vector. In one dimension, the notion is trivial, but here we must choose a linear functional which is positive on half the roots and negative on the other half. The mechanism used to define an extreme vector is not so important, however. What is important is that there is a vector
which is killed by each of
, and
. This corresponds to the case for
when
was the extremal vector killed by
.
Given this, we see as before that
is generated by the images of
under the opposite elements
, and
. This restricts us to a sort of ‘corner region’ of
. There are a few more key observations to make:
- The eigenspaces on the boundaries of the region correspond to irreducible representations on
. - There is a symmetry about the three lines
.
This implies that the weights (eigenvalues) of the representations are contained in either a hexagon or a triangle (with
symmetry). It is clear that the interior must be filled out, and the interior weights must have multiplicity 1. This completes the
case.
The General Case
In order to classify all (irreducible/finite-dimensional) representations for an arbitrary (semisimple) Lie algebra, one must take steps analogous to those above for
and
. The theory is extremely practical, and provides a mechanical calculation of possibilities. We will go through the steps in detail here.
The Cartan Decomposition (Step 1)
We need to find a suitable abelian subspace, analogous to the set of diagonal matrices for
. Our choice is restricted to maximal abelian subalgebras which act diagonally on the adjoint representation. This is called a Cartan subalgebra, and is a well-defined piece of every semisimple Lie algebra.
The Cartan subalgebra
is used to define the Cartan decomposition of the Lie algebra:
. There will be a finite number of eigenvalues
called roots, with corresponding subspaces
called root spaces. As we saw before, the roots comprise a subset
of the dual space and their configuration therein is a useful depiction of the structure of
. Note that the adjoint action of
takes
to
, so that the decomposition is preserved by the action of
.
We note a few facts regarding this decomposition. First, each root space
is one-dimensional. Second,
generates a lattice
with rank equal to
, meaning the roots span
. Last,
is a root iff
is also a root.
Decomposing the Representation (Step 2)
We now turn our attention to an arbitrary representation
, and note that the action of
on
gives the decomposition
. The eigenvalues are now called weights and the
are called weight spaces. The dimension of
is called the multiplicity of the weight. A simple diagram in
suffices to depict the weights and their dimensions.
Note that the weights are all congruent modulo the root lattice, meaning they differ by linear combinations of the roots of the Lie algebra. This is related to the fact that a piece
of the Cartan decomposition takes
into
.
Analyzing the Configuration of Eigenvalues/Weights (Step 3)
This third step is by far the most detailed, although it is really not much harder than the previous two. It basically amounts to finding an extremal piece of the representation (which turns out to be an
representation, and using it to fill in the eigenvalues for the rest of the representation.
First, note that for any root space
, we have a corresponding subalgebra
which is, in fact, isomorphic to
. To see this, one can choose elements
,
, and
which will act exactly like
. Thus, when we restrict to
we obtain a representation of
. In particular, all eigenvalues
of the representation must be
-valued on all elements
.
We can say more than that about the eigenvalues of
, however: they are symmetric about the hyperplane
. Letting
be the reflection in this hyperplane, we see that
-equivalence classes of
such as
are all invariant under the action of
, and so fixed by the
involution. Moreover, from the structure of
representations, one sees that each equivalence class can be written
.
The set of such hyperplane reflections
forms a group called the Weyl Group. In general, the set of weights, and the multiplicities of the weights, of any representation of
is invariant under the action of the Weyl group. One can see this by noting that it is true for each equivalence class
. Here is another fact: every element of the Weyl group is induced by an automorphism of
which fixes
.





