Can Vector Spaces be Considered Spans?

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Discussion Overview

The discussion revolves around the relationship between vector spaces and spans, particularly whether vector spaces can be considered spans of their elements. Participants explore definitions, properties, and axioms related to vector spaces and spans, with a focus on foundational concepts in linear algebra.

Discussion Character

  • Conceptual clarification
  • Technical explanation
  • Debate/contested

Main Points Raised

  • One participant questions if vector spaces can be considered spans, noting that spans are defined as sets of all linear combinations of vectors within subspaces.
  • Another participant clarifies that "span" refers specifically to the span of a set of vectors and asserts that the span of a set is itself a linear space.
  • A participant explains the "ten axioms" that determine if a set of vectors is part of a vector space, mentioning properties like closure under addition and the existence of a zero vector.
  • Further elaboration on the ten axioms is provided, detailing the properties of addition and scalar multiplication that define vector spaces.
  • Another participant states that every vector space has a basis, which consists of linearly independent vectors that can generate the entire vector space through linear combinations.

Areas of Agreement / Disagreement

Participants express differing views on the terminology and definitions related to spans and vector spaces. There is no consensus on whether vector spaces can be considered spans, and the discussion remains unresolved regarding the implications of the definitions and axioms presented.

Contextual Notes

Participants reference specific properties and axioms without fully resolving the implications of these definitions. The discussion highlights a potential misunderstanding of terminology and the foundational concepts of linear algebra.

evilpostingmong
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Hello, very new to vector spaces, it seems like they take some getting used
to. Anyway, since spans are sets of all the linear combinations of vectors
contained within subspaces, I wonder whether or not vector spaces
which contain elements (or vectors) that follow the ten axioms can be
considered spans.
 
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You seem to be mixed up in your terminology.

"Span" by itself doesn't really mean anything. You always talk about the span of a set of vectors.

The span of a set of vectors is the set of all vectors that can be made from linear combinations of those vectors. This is the definition. It is easy to prove that a span of a set of vectors is a linear space itself.

I'm not sure what "ten axioms" you're talking about.
 
Oh so it doesn't just apply to subspaces. Yeah those ten axioms are
rules that determine whether or not a set of vectors are contained
within a vector space such as wheter or not they are closd under
addition. Thank you for the response, very informative!:smile:
 
evilpostingmong said:
Oh so it doesn't just apply to subspaces. Yeah those ten axioms are
rules that determine whether or not a set of vectors are contained
within a vector space such as wheter or not they are closd under
addition. Thank you for the response, very informative!:smile:

I believe that you are referring to these ten:

Addition:

1. u + v is in V. (Closure under addition)
2. u + v = v + u (Commutative property)
3. u + (v + w) = (u + v) + w (Associative property)
4. V has a zero vector 0 such that for every u in V, u = 0 = u (Additive identity)
5. For every u in V, there is a vector in V denoted by -u such that u + (-u) = 0 (Additive inverse)

Scalar Multiplication
6. cu is in V. (Closure under scalar multiplication)
7. c(u + v) = cu + cv (Distributive Property)
8. (c + d)u= cu + du (Distributive Property)
9. c(du) = (cd) u (Associative Property)
10. 1(u) = u (Scalar Identity)



^From Elementary Linear Algebra by Larson, Edwards, and Falvo 5th edition.
 
Yes, every vector space has a basis, i.e. a set of linearly independent vectors such that every element of the vector space is a linear combination of the set of basis vectors. This is true also for infinite dimensional vector spaces. There always exists a so-called Hamel basis which is a set of vectors such that every element of the vector space is a finite linear combination of the basis vectors.
 

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