The concept of prime ideal in a commutative ring with
is one of several natural generalisations of the concept of prime integer number.
An ideal
is called prime if for any
the following holds:
implies that at least one of these elements,
and
is in
![]()
E.g. the principal ideal is prime if and only if
is prime.
A maximal ideal
is prime.
Indeed, let Assume that
We need to show that then
If this were not the case then
and
are two non-zero elements in the ring
such that
But this is not possible, as
is a field. Thus
as claimed.
Analysing this proof, one can easily see that
If
is prime then
has no zero-divisors, i.e. it is an integral domain.
Further important property of prime ideals is that they are radical, i.e.
where the radical
of the ideal
ideal is
Indeed,
implies that either
or
is in
and we derive
by applying this reduction.
Yet another interesting observation is that is multiplicatively closed.
Rings of fractions
A subset
is called multiplicatively closed (or multiplicative) if
![]()
and
for any
![]()
Given a multiplicatively closed set one defines
a relation on as follows:
It is not hard to show that is an equivalence relation.
To simplify the notation, write its equivalence class with representative as
We define
is the ring of fractions of
w.r.t.
with addition and multiplication given by the rules
![]()
![]()
It is easy to check that this is well-defined. We also have
so that
is a ring homomorphism.
Note that need not be injective, i.e.
need not hold. Indeed, if
is a zero-divisor such that
for
then
and so
The most well-known example is the case being an integral domain, and
Then
is a field, called the field of fractions of
Examples:
is the field of fractions of
- for the ring of polynomials
over a field
the field
is the field of rational functions over
- Let
be non-nilpotent. Then
isa multiplicative set. Moreover, then
(it is not completely trivial to prove this, though). Intuitively, we make the variable
behave like the inverse of
as
in this ring.
Now let us look at the case for
a nonzero prime ideal. In this case
is denoted by
and called the localisation of
at
Example: Let be the ring of polynomials over a field
and
Then
is prime, and
is equal to
The ring
has unique maximal ideal
![]()
It suffices to show that is invertible in
iff
Indeed, if
then
On the other hand, if
then there exists
such that
Thus
and so
(if it was,
would be in
as
is an ideal).
There is one glaring omission in our Linear Algebra curriculum – it avoids talking about the dual space of a vector space. This makes talking about relationship between subspaces and equations that define them exceedingly difficult. Better late than never, so here it comes.
Let be a vector space over a field
Denote by
the set of linear functions
Examples
Let the space of continuous functions on
Then the function
given by
is linear on
Let be the vector space of polynomials with real coefficients.
Then the function given by
is linear on
Note that as is linear, one has
for any
Thus we have
defined by
so that
To simplify notation, we will write
instead
As well, we can define
for any
and more generally,
And there is the zero function
for any
Thus we have all the ingredients of a vector space, as can be easily checked.
is a vector space over
It is called the dual space of
![]()
So far, we haven’t used the linearity of our functions at all (we actually did not need the fact that ). Indeed, any closed under addition and multiplication set of functions
would form a vector space.
What makes the dual space so special is that to define it suffices to define
on a basis
of
Indeed,
so we can compute
for any
once we know the
’s.
Thus for a finite-dimensional vector space one sees a (dependent upon the choice of a basis in
) bijection between
and
This bijection, that is even an isomorphism of vector spaces, is defined by the dual basis of
given by coordinate functions
where
’s are the coefficients of
is the decomposition of
in the basis
Finite-dimensionality is crucial here. E.g. let us consider the vector space of polynomials It is a countable space: one can view it as the set of infinite 0-1 strings, with only finitely many 1’s occurring in each string. On the other hand,
can be viewed as the set of all the infinite 0-1 strings, which is uncountable, so there cannot be a bijection between
and
Given one can define a function
as follows:
It is linear, as
Here we do not see any dependence on the choice of a basis in
and we have
The vector space
of linear functions on
is (canonically) isomorphic to
via the mapping
![]()
Indeed, we see immediately that and so we need only to check that this mapping is bijective. Let
be a basis in
and
its dual basis in
Then
if
and 0 otherwise. Thus
is the basis of
which is dual to the basis
of
and the mapping
sends the vector with coordinates
to the vector with the same coordinates in
the basis of
Hence the latter is bijective.
In view of the latter, we can identify with
and write
instead
The set of
such that
is a subspace, called annihilator of
of dimension
More generally, the following holds.
Let
be a subspace of
and
Then the annihilator
of
is a subspace of
of dimension
![]()
Indeed, we can choose a basis in
so that
is a basis of
where
Then we have the dual basis
of
and
is the subspace with the basis
In view of this, each can be obtained as the set of solutions of a system of homogeneous linear equations
for
of rank
Dual spaces and annihilators under a basis change
Let be a linear transformation of
and
a subspace of
Then
is a subspace. How can one look at
By writing out
in a basis
for any
in the dual basis
we get equation
Thus, considering
as a matrix, we get
where
denotes the action of
on
It follows that
i.e.
We have, considering that
acts on
by right multiplication, and not by left ones, to take the transpose, too.
acts on
as
![]()
An example.
Let We work in the standard basis
of
Then the dual basis of
is
, so that
Let be the group of matrices
It fixes, in its left action on
by multiplication, the vector
. Let
be the 1-dimensional subspace of
generated by
Then
is generated by
and
The group
preserves
in its action on
As
is 2-dimensional, there should be a nontrivial kernel in this action, and indeed, it consists of the elements of the form
A particularly simple case is Then
is isomorphic to
the symmetric group on 4 letters, as can be seen in its action on the 4 elements of
outside
On the other hand, it acts on the 3 nonzero elements of
as

Excercises in algebra
One application of actions of finite groups is in combinatorics, more precisely, counting objects that possess particular symmetries.
A classical example are -necklaces and
-bracelets. These are words of length
in a
-letter alphabet, with beginnings and ends of the words glued together and made invisible (so one can visualise them as regular
with letters from the alphabet placed at the vertices). Two necklaces are identical when one is obtained from another by rotations; two bracelets are identical when one can be obtained from another by rotation and a “flip”. One can view counting of necklaces and bracelets as counting of orbits of certain groups on the sets of “labelled” necklaces (resp. bracelets). For the necklace case, the group is
and for the bracelet case it is the dihedral group of order
The set of labelled necklaces/bracelets is just the set of words of length
in a
-letter alphabet; so one has
Orbit counting is often simplified by the following result, often attrubuted to Burnside, although it was certainly known to Frobenius.
Let a finite group
act on a finite set
Denote by
for
the set of elements of
fixed by
Then the number
of orbits of
on
is the average, over
of
i.e.
![]()
The proof involves counting of edges in the bipartite graph, with one part being and the other being
a pair
for
and
is an edge iff
Thus the total number of edges in this graph is
On the other hand, a pair is an edge iff
the stabiliser of
in
Thus, for a
-orbit
one has the total number of edges leaving
equal to
Summing over all the
-orbits, one obtains the total number of edges
completing the proof.
Often it is easier to sum over distinctive representatives of the conjugacy classes
as
So one has
where denoting the centraliser of
in
Let us see how this can be applied to counting bracelets. For simplicity, let us assume that is prime. We consider natural the action of the dihedral group
on the set of
words of a
-letter alphabet.
We know that is generated by the cyclic permutation
and an order two “flip” permutation
The group can be decomposed into the union of cosets
The only words fixed by a nonidentity element of the subgroup
are the “constant” ones, i.e. words consisting of a single letter, and so
The coset
equals
(an unusual coincidence), and so it suffices to find
For a word
to be in the latter set, it must have
…
so there are
possibilites.
Thus we count
E.g. for
one obtains
We have already seen abstract groups as permutation groups, or, more generally, as groups of bijections, in a number of contexts:
acting on itself by (left) multiplication, when we associated with each
a bijection
by
acting on itself by conjugation, when we associated with each
a bijection
by
-
acting on the set of (left) cosets
of a subgroup
when we associated with each
a bijection
by
We have also seen matrix groups at work as permutation groups (e.g. on the set of subspaces), permutation groups becoming matrix groups (e.g. represented by
permutation matrices), etc.
What unites all these examples is the concept of a group action.
Let
be a group and
be a set, with a group of bijections
An action of
on
is a homomorphism
![]()
There are many different types of actions, e.g. permutation actions when is a finite set and
the symmetric group (of all permutations of
linear actions, when is a vector space, and
a group of its linear transformations (i.e. matrix groups), etc.
By the homomorphism theorem, An action satisfying
is called faithful (or effective).
For instance, the action of on itself by (left) multiplication is always faithful, but the action on cosets of an
need not be faithful. E.g. it will not be faithful if
is commutative and
Orbits and point stabilisers
An action of
on
defines an equivalence relation
on
as follows:
iff there exists
such that
The equivalence classes of
are called orbits (more precisely, orbits of
on
).
Let and
Then
is called the stabiliser of
in
and denoted
Let for some
What can be said about
Indeed, the coset consists of the elements of
that map
to
Thus any
fixes
and any
that fixes
belongs to
as
When we consider the action of
on itself by conjugation, the orbits are called conjugacy classes.
For instance, the conjugacy classes of the symmetric group on
letters, can be shown to be in 1-to-1 correspondence with the unordered partitions of
into parts
where
as follows:
Let a permutation be written in the cyclic notation. Then for any
one has
and so we can transform to any permutation with cycles of the same lengths
Equivalent actions
When do two actions and
of a group
on, respectively, sets
and
can be viewed as “the same”? Obviously we need a bijection
to exist, that also “respects”
in the sense that
for all
and
Such an
is called a
-equivariant bijection, and is said to define an isomorphism of actions.
An action that has just one orbit is called transitive.
Let
be a transitive action of
on
Then
is isomorphic to the action on
for any
where we denoted by
the preimage of
in
![]()
This isomorphism of actions is given by such that
where
Indeed,
-
is obviously a bijection
-
iff
iff
iff
-
is
-equivariant. Indeed, let
Then for any
one has
as claimed.
Finally, for an action of
on
we can characterise
as
for an
Actions of matrix groups (a.k.a. linear actions)
Subgroups of the group, with respect to matrix multiplication, of invertible
matrices with entries in a field
have a number of natural actions, that all come one way or another from the vectorspace
Indeed, each
provides a bijection
by
for any
Moreover, such a bijection is even an automorphism of the vectorspace
(Automorphisms of vectorspaces are defined just as these for groups and rings: these are bijections preserving the corresponding algebraic structure (i.e. operations, etc)).
Apart from the action on the vectors of
(called the natural action (by left multiplication)) there is another action on the vectors, namely, by
(which one can equivalently writen as
). It is called contragradient action.
(Note that the map given by
is not always an action, as
and so
is not a homomorphism, unless we have a commutative group.)
Natural and contragradient actions give a simple example of two non-equivalent faithful (i.e. with trivial kernel) actions of one group, say, , with
on the same set
Indeed, if
were an equivalence of these actions, then
for all
and
Let and $f(v)=u$ so that
and
are linearly independent. In the basis
, take
Then
We see that
a contradiction.
If, on the other hand, and
are always linearly dependent,
we take the same in the standard basis
and see that
for some
again a contradiction. The argument showing non-equivalence in the case
is similar. For
these two actions are isomorphic, as
is commutative.
Another important class of actions is the action on on subspaces of
For simplicity, let us consider the action on the set
of subspaces of dimension
Given a
-dimensional subspace
and
we define
Then
is a
-dimensional subspace, as can be seen by choosing a basis
of
and observing that
is a basis of
Thus
induces a bijection on
When fixes a
we can choose a basis in such a way, that
becomes a group of
block matrices, discussed earlier here.In this case
has a normal subgroup acting trivially on
that is the kernel of the action of
on the quotient space
The centre of
acts trivially on
as it preserves every 1-dimensional subspace (indeed, any
equals
with
).
Projective line.
The simplest nontrivial is
when
This set is called projective line and denoted
and can be viewed as the set of pairs
as follows: every 1-dimensional subspace
of
can be described by equation
or by equation
To understand the action of an element of
on
consider
and
just as if we multiply a vector by
and then normalize either to
or to
depending upon whether or not
A generalised quadrangle with lines of size and with
points on each line (a
, for short) has a lot of “regularity” – and as we learned from a previous post, any finite “non-degenerate” GQ is a
for some
This regularity allows for the use of quite a bit of linear algebra and algebraic graph theory in investigating them.
One considers the collinearity graph of the GQ
The collinearity graph of a GQ
is the graph with the vertex set
two vertices
are adajcent iff they are collinear, i.e. if there exists
such that
![]()
For a such a graph is strongly regular, see wikipedia for a good short intro.
Basically, a graph is strongly regular if it is
- regular, i.e. each vertex is adjacent to
other vertices;
- for each edge
there are exactly
vertices
such that
- for each non-edge
there are exactly
vertices
such that
One says that when is as above, one has an
One famous example of a srg is the Petersen graph. It is an
Exercise.
- Prove that the collinearity graph of an
![]()
is an
- Compute
as a function of
and
(namely, it is
)
An important tool in studying srg’s, and graphs in general, is the
Adjacency matrix of a graph
is the
matrix
that has
for each
and otherwise
![]()
In particular and the
-th row sum is the number of vertices adjacent to
This means that the all-1 vector is an eigenvector of
with eigenvalue
In fact, this is the largest eigenvalue, and for the connected graphs it has 1-dimensional eigenspace. For srgs, much more can be said.
For a connected
an
the adjacency matrix
has at most 3 distinct eigenvalues, namely
and
![]()
This follows from the fact that multiplication of 0-1 matrices boils down to computing certain combinatorial parameters of underlying graphs. E.g. is the number of length 2 walks from
to
In our case we have
where is the identity matrix and
the all-1 matrix. Any eigenvector
with eigenvalue
must be orthogonal to the
-eigenvector, in particular
Thus
and this translates into
a quadratic equation! It remains to compute its solutions to establish the claim.
Moreover, one can compute the multiplicities of the eigenvalues of
Indeed, we know that has multiplicity
and so the other two eigenvalues have multiplicities
and
that satisfy
-
(by just discussed) and
-
(as the trace of
is 0.)
We can solve these two linear equations to obtain
These are powerful conditions that rule out large sets of tuples as
must be nonnegative integers!
For an srg arising from a one can compute that the eigenvalues of
are
and
This gives one, by computing the multiplicities, that for one has
With more work (one needs e.g. the Krein bound) the case
can be ruled out.
Just as in the case of abelian groups, each subgroup gives rise to a coset decomposition of
or, more precisely, to two decompositions, into left cosets i.e.
and right cosets, i.e.
It is proved by the same argument as in the case of abelian groups that one indeed has decompositions of in this way.
Unlike in the case of abelian groups, these two decompositions need not be the same: an example is given by
The following is an important and elementary implication of the fact that all the cosets of have the same cardianlity:
Let
and
Then
divides
![]()
An extremely important case (and, in fact, the only case) when these two decompositions are the same is when where
is a group homomorphism. (Just as in the case of abelian groups, one can show that
and
)
We need to show that for any and
one has
for some
We compute
Hence
A subgroup
satisfying
for all
is called normal (notation:
or
when
)
Often it is more convenient to work with the equivalent condition for normality, namely that for all
Examples of normal subgroups.
- The subgroup generated by
in
is normal.
defined by
is normal.
of index 2 (i.e. the one that has exactly 2 left cosets in
) is normal.
The 1st is easy to establish directly (it also follows from the 3rd).The 2nd follows from the identity
The 3rd follows from the equality and an observation that
so
Cosets play an important role in constructing “easier” groups from “complicated” ones, by the quotient group construction. The difference with the case of abelian groups is that only normal subgroups can be kernels of homomorphism.
Let
Then
is a group with operation
and
a group homomorphism
with the kernel
![]()
We need to use to establish that the multiplication in
is well-defined:
Then is a group with the identity element
as associativity in
follows from the associativity in
and
It can be readily checked that is a homomorphism, and that
Indeed,
Also,
for
and so
On the other hand if
then
and so
Matrix groups
Subgroups of the group, with respect to matrix multiplication, of invertible
matrices with entries in a field
provide a rich playground for various examples of normal subgroups and quotient groups. To this end, we will work with block matrices, i.e. we will partition our matrices into rectangular blocks of appropriate size, so that this block decomposition is preserved under the matrix multiplication. The simplest case is the following partition into 4 blocks (i.e.
block matrices).
Given an matrix
and positive integer
we can view
as
where
is a
matrix,
a
matrix (and certainly
and
being of size
).
Let us fix and
First, we need to convince ourselves (an easy exercise in matrix multiplication) that the following multiplication law works for two block matrices and
:
It should of course look very familiar, as this is exactly how two matrices are multiplied.
When we see that the shape is preserved, i.e.
More precisely
We see that the blocks with indices 11 and 22 behave as if “nothing around them matters”, as if they sit in their own groups and
(that is, assuming the matrices we talk about are invertible). We can formalise this observation as follows.
Let
be a subgroup of
block matrices, with diagonal blocks of sizes
and
and such that
for all
Then
- the maps
and
are group homomorphisms.for
The reader is encouraged to provide a proof.
More generally, this result can be interpreted in terms of the actions of on the
dimensional vectorspace
over
Exercise. Prove that the intersection of two normal subgroups of a group is a normal subgroup. Based on this, describe and derive that
is a normal subgroup of
Note that (where
or
) cannot be obtained by simply setting the remaining off-diagonal block of
to 0, and the remaining diagonal block to the identity matrix. For instance, let
be generated by the matrix
where
Then
is a cyclic group of order 4, and it satisfies the conditions of the above lemma with
It is easy to see that
is an isomorphism, and
is a homomorphism with the kernel generated by
Let us denote and
As by the usual argument involving decomposition of
into the cosets of
computing
for
for
prime, can be accomplished by computing
and
separately. In turn,
so we can simplify the task of computing
too.
To illustrate this principle, let us compute the order of
First we derive the following:
where
is prime.
Indeed, we can fill in the 1st row of an matrix in
way (everything goes, except all zeros). Fixing this 1st row vector
we can again fill in the 2nd row with entries of any vector
which is linearly independent (to get an invertible matrix) of
i.e. lies outside of the subspace
spanned by
As
we get
ways to choose
Now we fix
as well, and fill in the 3rd row with entries of any vector
which is linearly independent of
and
i.e. lies outside of the subspace
spanned by
and
As
we get
ways to choose
So when filling the -th row, we have
choices, giving us the formula above.
Now, we claim that Indeed,
consists of
such that
whereas we can fill the entries of
without any strings attached – the result will be invertible. Thus we have
Excercise. Compute for
and
as in (1).
(Hint: use the fact that is a group homomorphism.)