Definitions of vector space and subspace

Click For Summary
The discussion focuses on the definitions and significance of vector spaces and subspaces as outlined in Axler's "Linear Algebra Done Right." A vector space is defined as a set with operations of addition and multiplication that adhere to specific algebraic properties, including the presence of an additive identity. Subspaces are subsets of vector spaces that maintain these properties, which are crucial for understanding linear algebra concepts. The conversation highlights the challenge of applying these definitions to non-numeric sets, such as polynomials, and emphasizes the importance of subspaces in the broader context of linear transformations. The participants suggest that the significance of these concepts will become clearer with further study, particularly in relation to bases and linear transformations.
elementbrdr
Messages
43
Reaction score
0
I am using Axler's Linear Algebra Done Right as a text for independent study of linear algebra. Axler basically defined a vector space to be a set which has defined operations of addition and multiplication (and which comports with certain algebraic properties) and that contains an additive identity (which I understand to mean essentially {0}). As I understand it, a subspace is simply a subset of a vector space that has the same properties.

I am having trouble understanding what this all means for sets other than F^n I find vector space and subspace to be intuitive concepts when applied to complex number sets (particularly so with respect to real number sets). But I have trouble understanding what vector space and subspace actually means when applied to sets containing non-numeric elements. For example, Axler discusses subspaces in the context of the set P(F), which is the set of all polynomials with coefficients in F, and the function p(x), which is a polynomial function. The example he provides is that the set \{\rho \in P(F) : \rho(3) = 0\} is a subspace of P(F)
This makes a bit of sense to me, but I'm having trouble understanding its significance. I don't get why the concept of subspace is useful for anything other than vector space having ordered n-tuples as elements. I'm having similar difficulty with the concept of direct sum, but I'll save that until after I've cleared up my current confusion.

Thanks.
 
Physics news on Phys.org
Hi elementbrdr! :smile:

It seems that you understand quite well what a subspace is, so you're only asking yourself what the use is of subspaces?

Well, subspaces are just a formulation of some handy properties. That is, it's just saying that it's a vector space in it's own right (with operations that coincide with that of the larger vector space). You will see the term subspace used time after time in linear algebra, so you will soon see it's importance.

Also, if you understand the vector space Fn, then you actually understand them all because all vector spaces have this form!
 
P(F) is a little special, because it is an infinite-dimensional vector space.

Have you studied bases of vector spaces yet? Do you agree that every vector in an n-dimensional vactor space, given a basis, is in one-to-one correspendance with its coordinate vector? This relationship let's us represent any n-dimensional vector space as an ordered n-tuple in a basis.

I think the significance of subspaces and direct sums will become evident when you study linear transformations.
 
Thanks for the responses!

espen180, I have not yet studied bases of vector spaces. As of now, I have only advanced as far as learning span.

I think the takeaway here is that I should be patient and this will all make sense in due time :)
 
Axler basically defined a vector space to be a set which has defined operations of addition and multiplication (and which comports with certain algebraic properties)

I don't know Axler, but I doubt he says that a vector space is only a single set.
You actually need two sets to define scalar multiplication, which I presume you mean since scalar multiplication is fundamental to all vector spaces, whilst vector multiplication is not.

You have your field set - the scalars and your vector set - the vectors.
Together they make the vector space.
 
I am studying the mathematical formalism behind non-commutative geometry approach to quantum gravity. I was reading about Hopf algebras and their Drinfeld twist with a specific example of the Moyal-Weyl twist defined as F=exp(-iλ/2θ^(μν)∂_μ⊗∂_ν) where λ is a constant parametar and θ antisymmetric constant tensor. {∂_μ} is the basis of the tangent vector space over the underlying spacetime Now, from my understanding the enveloping algebra which appears in the definition of the Hopf algebra...

Similar threads

  • · Replies 6 ·
Replies
6
Views
3K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 18 ·
Replies
18
Views
4K
  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 3 ·
Replies
3
Views
3K
  • · Replies 3 ·
Replies
3
Views
5K
  • · Replies 8 ·
Replies
8
Views
2K
  • · Replies 19 ·
Replies
19
Views
5K
  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 8 ·
Replies
8
Views
3K