This set is due Friday, March 12.
It is common in algebraic settings to build new structures by taking quotients of old ones. This occurs in topology (building quotient spaces), in abstract algebra when building field extensions, or in the homomorphism theorems. Here we explore quotients in vector spaces.
First we briefly consider an example from differential equations.
Let be the space
consisting of all continuously differentiable functions
and let
be the space
of all continuous functions
Let
be the linear transformation
Show that is a real vector space of dimension 1, by showing that
iff
is a constant. This means, of course, that
Show that by finding a particular solution
to the equation
One way of doing this is by looking for such a function
of the form
for some constant
Find the form of an arbitrary function
such that
by noting that if
then
More generally, show that is surjective, by finding for any
the explicit form of the solutions
to the equation
It may help you solve this equation if you first multiply both sides by
For another example, denote by the space of all
matrices with real entries. Define a map
by
Show explicitly that
has dimension 6 and that
is surjective.
Now we abstract certain features of these examples to a general setting:
Suppose is a field and
is a linear transformation between two
-vector spaces
and
It is not necessary to assume that
or
are finite dimensional.
Let and let
be any preimage, i.e.,
Show that the set
of all preimages of
is precisely
Define a relation in
by setting
iff
Show that
is an equivalence relation. Denote by
the equivalence class of the vector
Let be the quotient of
by
i.e., the collection of equivalence classes of the relation
We want to give
the structure of an
-vector space. In order to do this, we define
and
for all
and
Show that this is well-defined and satisfies the axioms of an
-vector space. What is the usual name we give to the 0 vector of this space?
It is standard to denote by
Define two functions
and
as follows:
is given by
Also,
is given by
Show that
is well-defined and that both
and
are linear.
Show that that
is a surjection, and that
is an isomorphism between
and
In particular, any surjective image of a vector space
by a linear map can be identified with a quotient of
In the second example, where T maps the real 3×3 matrices to R^3, you ask us to show explicitly that the dimension of null(T) is 6. By explicitly, do you mean that you actually want us to find a basis for null(T), or would it suffice to reference an appropriate theorem?
Thanks,
Nick
I would prefer an actual basis, I’ve been seen some difficulties carrying out explicit computations in the previous homework sets.
When we define an equivalence relation, what is required to show that it is an equivalence relation? The book doesn’t discuss them, so from google I found three properties: a~a, a~b then b~a, and finally a~b and b~c then a~c. Is this all that’s required to show it is one?
Thanks, Amy
Yes, that’s all that is needed. To be precise: You need to show that
holds for all vectors
. (This is called the reflexive property.) Similarly, you need to show that, for any vectors
, if it is the case that
, then also
(symmetry), and that if it is the case that
and
, then also
(transitivity).
I had a question referring to what I have called Show #7: “Show that this is well-defined and satisfies the axioms of an
-vector space.”
I’m not sure what you mean by “show that this is well-defined”? What exactly do I need to show? I tried to look this up and I found things that said well defined meant the mapping was one-to-one, is this what we are talking about here?
Thanks,
Summer
Hi Summer,
We are defining a map on a quotient. Whenever we do this, we typically run into the following problem:
I am defining
However, if
and
then
and
right? This is potentially a problem, because we are defining
But we had already said that
So, there is the risk that the definition of sum we gave makes no sense: Which one is it:
or
?
The answer ought to be that both expressions are the same, i.e., that no matter what elements of
and
are chosen, when we add them, we always land in the same equivalence class. This is usually expressed by saying that the definition of sum that we gave is independent of the specific representatives
and
that we choose in order to compute
from which we then obtain ![{}[v_1+v_2].](https://s0.wp.com/latex.php?latex=%7B%7D%5Bv_1%2Bv_2%5D.&bg=ffffff&fg=333333&s=0&c=20201002)
Then you have to argue that, similarly, if
then
for any
so the definition of scalar multiplication we are giving is also independent of the specific representatives of the equivalence classes that we choose in order to compute it.
(The point is that when somebody hands you two equivalence classes
and
and asks you to add them, you are not given
and
, only their classes. You have to pick an element of the first class, and one of the second, and then you add these 2 elements, and form the class of the result that you obtain, and that’s your answer. Of course, you want that your answer does not change if you pick different elements of the first and second classes to begin with.)