Definitions of vector space and subspace

Click For Summary

Discussion Overview

The discussion revolves around the definitions and significance of vector spaces and subspaces, particularly in the context of linear algebra as presented in Axler's "Linear Algebra Done Right." Participants explore the implications of these concepts beyond finite-dimensional spaces, including their application to polynomial sets and the nature of infinite-dimensional vector spaces.

Discussion Character

  • Conceptual clarification
  • Debate/contested
  • Exploratory

Main Points Raised

  • One participant describes a vector space as a set with defined operations of addition and multiplication, containing an additive identity, and defines a subspace as a subset of a vector space with similar properties.
  • Another participant suggests that subspaces represent useful properties and indicate that they are vector spaces in their own right, emphasizing their recurring importance in linear algebra.
  • A participant notes that P(F) is an infinite-dimensional vector space and questions the relationship between vectors and their coordinate representations in n-dimensional spaces.
  • One participant expresses uncertainty about the significance of subspaces and direct sums, indicating a need for further study to understand these concepts fully.
  • Another participant challenges the interpretation of Axler's definition, suggesting that a vector space requires two sets: the field of scalars and the set of vectors.

Areas of Agreement / Disagreement

Participants generally agree on the basic definitions of vector spaces and subspaces but express differing views on their significance and implications, particularly in relation to infinite-dimensional spaces and the necessity of multiple sets in defining a vector space. The discussion remains unresolved regarding the broader utility of these concepts.

Contextual Notes

Some participants have not yet studied bases of vector spaces, which may limit their understanding of the significance of subspaces and direct sums. There is also a lack of consensus on the interpretation of scalar multiplication in the context of vector spaces.

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.
 

Similar threads

  • · Replies 15 ·
Replies
15
Views
5K
  • · Replies 6 ·
Replies
6
Views
4K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 18 ·
Replies
18
Views
4K
  • · Replies 8 ·
Replies
8
Views
3K
  • · Replies 32 ·
2
Replies
32
Views
6K
  • · Replies 8 ·
Replies
8
Views
3K
  • · Replies 8 ·
Replies
8
Views
3K
  • · Replies 8 ·
Replies
8
Views
2K
  • · Replies 3 ·
Replies
3
Views
2K