Taken from Hopf Algebras by Abe. This is not even nearly finished however I pressed publish instead of save draft… oh well.
In this section, we give the definition of Hopf algebras and present some examples. We begin by defining coalgebras, which are in a dual relationship with algebras., then bialgebras and Hopf algebras as algebraic systems in which the structures of algebras and coalgebras are interrelated by certain laws.
1.1 Coalgebras
We define a coalgebra dually to an algebra. Given an algebra and algebra homomorphisms
and
, we call
or just
a coalgebra when we have:
,
(the coassociative law).
,
(the counitary property)
The maps and
are called the comultiplication map and the counit map of
, and together they are said to be the structure maps of the coalgebra
.
Now suppose we are given two coalgebras and
. A linear map
satisfying the conditions
,
is called a coalgebra morphism.
For algebras and
we define a linear map
by
for
,
. If a coalgebra satisfies
,
then is said to be cocommutative. If
and
are two coalgebras, the tensor product
becomes a coalgebra with structure maps
,
,
which we call the tensor product of and
. If
are cocommutative, then
is a direct product of cocommutative coalgebras where the canonical projections
,
are respectively given by
and
for
,
.
When a subalgebra of a coalgebra
satisfies the condition
, then
becomes a coalgebra with the restrictions of
to
as the structure maps. Such a
is called a subcoalgebra of
.
For algebras and
, if we define a map
by
,
where ,
,
and
, then
is an injective linear map (Suppose that
. That is to say that for all
,
.
and by the no divisors theorem or
for all
,
. Hence
or
and
.). Given a coalgebra
, let
denote the dual of
.
,
,
becomes an algebra, which we call the dual algebra of
.
I’m not sure exactly what and
are here. I’m supposing that they are the adjoints of the linear maps
and
but I haven’t ever gone through the construction via the inducement of a map
from a linear map
— which is an approach mentioned here. The only natural inducement I can think of is follows. Let
be a linear map between vector spaces
and
. Now define a linear map
by
.
Now let be a bilinear form. A bilinear form
induces linear maps
and
:
,
where
,
and similarly for .
If and
are inner product spaces, I can also define a bilinear maps
using the inner product of
and
:
.
By fixing , I could define a linear functional on
and hence we have a map
given by:
.
I’m happy enough here to invoke Riesz representation theorem and the existence of such that
,
where I define in the obvious way. So what I have is
,
but I really want to identify
with a
and this will hopefully tell me what
and
are. Let
and define
, by
.
I think this is the identification I need. For example, take . In this construction,
so that
,
where is the inner product adjoint of
. Similarly
.
In general, is not necessarily an isomorphism. Thus we cannot define a coalgebra structure on the dual space
of an algebra
in a similar fashion. However, if
is a finite dimensional vector space, then
turns out to be a vector space isomorphism; if
,
are the structure maps of
, then by setting
,
, we see that
becomes a coalgebra.
Firstly, I can’t see how can be a comultiplication for
. We require
, yet
doesn’t act on
— it acts on
. I’m going to try
— at least
. Let
and
. We know that
.
We might want to show that so that
is the inverse of
when we restrict to
. This is equivalent to
or
and even further
. From here we may be able to identify elements of
with elements of
uniquely and hopefully pull the coassociativity of
from this via
. I don’t know if this is necessarily true but I can still look at statements about
and turn them into statements about
— which has coassociativity. If we note that
, then
so we need to show that
, for all
.
Could we express in terms of
alone? We start by noting that
by
.
While this is indeed progress and I’m getting better at visualising what’s going on I’ll leave it there for now…
This is called the dual coalgebra of .
Example 2.1 (Modified)
Let be a vector space with an orthonormal basis
. Define linear maps:
,
for by
,
, then
becomes a coalgebra (
). The dual space
can be identified with
where the dual algebra structure of
is given by
,
,
for ,
and
.
First let us examine . Take an element
. Now
and
. So if I can show that
we are done as this will yield
. Now, for all
we have
,
,
.
Now and from this it is clear that
so we are done.
Now looking at the map . Now let
so that we want
.
The only way this makes any kind of sense is if , where
is the constant function on
.
Example 2.2
Let be a vector space with a countable orthonormal basis
and define
,
.
to obtain the coalgebra (
). We will briefly look at the structure of the dual algebra of
. If we let
be defined by
,
.
then can be written
, where
.
With regard to multiplication on , we have
.
Thus the relation holds, and we get
for
. Therefore we see that
is isomorphic to the ring
.
Example 2.3
Let be a natural number and set
and
the vector space with basis
. Defining
,
,
we obtain a coalgebra (
). The dual space
of
is a vector space of dimension
and if we define
by
,
then is a basis for
. By identifying
with the
square matrix
,
becomes the algebra
of all
square matrices with complex entries.
Notation for Coalgebra Operations
In general, the notation used for operations of coalgebras is not as concise as that for operations of algebras. The following notation is effective in simplifying various types of operations. Given a colalgebra and
, we can write
, for
.
We write this formally as
,
and for linear operators (or functionals) , we write
.
Moreover, since the associative law holds, we have
,
and in general we define , and
,
for , and write
.
Using this method of notation, the counitary property may be expressed as
.
Exercise 2.1
Prove the following equalities
,
,
.
Solution : First write
.
Now we note that, using the counitary property, we can write
.
But
.
Now use the counitary and coassociativity to write
.
This yields:
.
After we make the identifications , this is the first set of equalities.
By applying coassociativity we have
.
A quick calculation shows the first of the second set of equalities. A calculation shows that
.
By coassociativity:
.
Now hit with this:
by the first of the equality above.
For the third equality, the right-hand side is given by:
.
Now by using coassociativity and the counitary propery twice:
.
So all three sets of inequalities are proven.
Theorem 2.1.1
Given a vector space , suppose that there are linear maps
,
,
,
such that is an algebra and
is a coalgebra. Then the following are equivalent.
and
are coalgebra morphisms.
and
are algebra morphisms.
,
,
,
.
Proof : The conditions under which is an algebra morphism are (see here):
(a)
(b)
The conditions under which is an algebra morphism are
(c)
(d) .
On the other hand, is a coalgebra morphism exactly when it satisfies conditions (a) and (c) (
); and
is a coalgebra morphism if it satisfies conditions (b) and (d) (
). This fact allows us to conclude that 1.
2.
Now assume (2). The equation
implies that .
The equation we get that
.
The equation yields
.
Finally the equation yields
. Clearly (iii)
(ii) and we are done
When a vector space together with linear maps
satisfies one of the equivalent conditions of Theorem 2.1.1, then
, or simply
, is called a bialgebra. Given two bialgebras
and
, when a linear map
is an algebra morphism and is also a coalgebra morphism, then
is called a bilalgebra morphism.
If a subspace of a bialgebra
is a subalgebra as well as a subcoalgebra, then
becomes a bialgebra, and is called a sub-bialgebra of
. Moreover, if a bialgebra
is finite dimensional, then a bialgebra structure may be defined on its dual
, which we call the dual bialgebra of
.
Example 2.4
Let be a semigroup with identity, and let
be the free complex vector space generated by
. In the sense of example 2.1,
has a coalgebra structure when we consider
as a basis for
. With regard to these two structures,
admits a bialgebra structure. Such a bialgebra is called a semigroup bialgebra. In particular, when
is a group, it is called a group bialgebra. The dual space
can be identified with
, and in particular, when
is finite, then
becomes a dual bialgebra of
. The algebra structure of
is the one described in Example 1.5, and its coalgebra structure is given for
,
, and the identity element
by
,
.
I’m not one hundred percent what these are — do they just mean:
and
.
When an element of a coalgebra
is such that
and
, then
is said to be a group-like element. We denote the set of all group-like elements by
.
Theorem 2.1.2
Let be a coalgebra.
(i) The elements of are linearly independent. Thus
may be regarded as a subcoalgebra of
.
(ii) When is a bialgebra,
is a semigroup with respect to multiplication, and the subspace of
generated by
is a sub-bialgebra of
isomorphic to the semigroup bialgebra
of
.
Proof : Suppose that the elements in are linearly dependent, and let
be the least value for a set of elements of
to be linearly dependent. Then there exist
such that
are linearly independent and
can be written
,
and
.
Since
, and also
.
Hence we may write
.
Since is a set of linearly independent elements of
(
), this implies that all of the
or
— and also that the mixed terms
all vanish. Hence
and
, which contradicts the choice of
(i.e.
is a set of
linearly dependent elements. We also have no problem when
). Hence the elements of
are linearly independent. It is apparent that
is a subcoalgebra of
.
To prove part (ii), the first thing is to show that . Note that associativity is clear as
. Using the equation
,
we can show that for all
, as required
An element of a bialgebra
(resp a coalgebra
which has only one group-like element, i.e.
) which satisfies
(resp.
) is called a primitive element. The set of all primitive elements of
is denoted by
. Now we have the following.
Theorem 2.1.3
If is a bialgebra, then
is a subspace of
, and for
, we have
. Thus
has the structure of a Lie Algebra. Moreover, if
,
.
Proof : If , then
.
Thus . For
we have
.
Hence
Example 2.6
Let , and let
be the coalgebra defined in Example 2.2. Defining a multiplication by
,
becomes an algebra. With respect to these two structures,
becomes a bialgebra. By setting
,
we obtain , which implies
for
. Thus as an algebra,
is isomorphic to the polynomial ring
in one variable. In this situation,
.
1.2 Hopf Algebras
Given a coalgebra and an algebra
. If
,
is said to be the convolution of and
. If
, then
, which is simply the definition of the product of two functions on
via multiplication on
.
becomes an algebra with structure maps
,
.
Given a bialgebra , let
and
respectively denote
regarded simply as an algebra and a coalgebra, and view
as an algebra via convolution as defined above. When the identity map
of
is an invertible element of
with respect to multiplication on
, the inverse
of
is called the antipode of
. The antipode
is the element which satisfies one of the following equivalent conditions
A bialgebra with antipode is called a Hopf algebra. Let be Hopf algebras and let
be the antipodes of
respectively. When a bialgebra morphism
satisfies the condition
,
is called a Hopf algebra morphism.
Example 2.7
Denote by the group bialgebra of a group
(see Example 2.4). We define a linear map
by
for
. Then
,
.
Thus is the antipode of
, so that
becomes a Hopf algebra.
is an anti-automorphism of
as an algebra and
is the identity map of
.
Theorem 2.1.4
The following properties hold for an antipode of a Hopf algebra
.
, for all
.
; namely
.
.
; in other words.
- The following conditions are equivalent
implies
.
implies
.
.
Remark
1. and 2. imply that is an anti-algebra morphism; 3. and 4. imply that
is an anti-coalgebra morphism.
Proof : 1. Define elements of in the following manner. For
, we write
,
,
.
Now, if we show that , then we get
, which would prove 1.
I can show that
, and
,
but can’t see how this implies that — which is the technique Abe uses. To show
is just a calculation.
2. Since ,
, we have
.
3. From the fact that and…
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