Vector Space Basis: Standard or Odd?

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Discussion Overview

The discussion revolves around the concept of "standard" bases in vector spaces, exploring whether every vector space has such a basis and what constitutes a standard basis for various types of vector spaces, including finite-dimensional spaces and spaces of linear transformations.

Discussion Character

  • Debate/contested
  • Conceptual clarification
  • Mathematical reasoning

Main Points Raised

  • Some participants question whether every vector space has a "standard" basis, suggesting that many vector spaces may not have been explored or defined.
  • One participant proposes that a "standard" basis is simply a basis that has been designated as such, implying subjectivity in its definition.
  • A related inquiry is made about what constitutes a basis for the space of linear transformations from R^2 to R^2, with suggestions including any 2x2 matrix or a set of arbitrary 2x2 matrices.
  • Another participant defines the "standard" basis for the space of linear transformations L(U,V) as matrices Ekl, which are constructed using the unit of the scalar field, and notes that every vector space has a basis of this type, termed a Hamel basis.
  • It is mentioned that the standard basis for the vector space of 2 by 2 matrices consists of four specific matrices, allowing any 2x2 matrix to be expressed as a linear combination of these basis matrices.

Areas of Agreement / Disagreement

Participants express differing views on the existence and definition of "standard" bases, indicating that multiple competing perspectives remain unresolved regarding what constitutes a standard basis in various contexts.

Contextual Notes

There is an acknowledgment of the complexity surrounding the definition of bases in infinite-dimensional spaces, where Hamel bases are noted to be uncomputable and unenumerable, adding to the discussion's nuance.

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In short: does every vector space have a "standard" basis in the sense as it is usually defined i.e. the set {(0,1),(1,0)} for R2? And another example is the standard basis for P3 which is the set {1,t,t2}. But for more abstract or odd vector spaces such as the space of linear transformations (automorphisms?) what would the standard basis be?
 
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No, not every vector space has a "standard" basis because there are many vector spaces no one has every looked at! There are, after all, an infinite number of vector spaces! A "standard" basis is simply a basis that has been declared "standard".
 
This makes sense. But a related question: What then would be any basis for the space of linear transformations of R^2 onto R^2? Any 2x2 matrix? or perhaps 4 arbitrary 2x2 matrices?
 
The space of Linear transformations L(U,V), where U and V are finite dimensional linear spaces, with dimensions m and n, is itself a linear space with dimension mn; its "standard" basis is the set of matrices Ekl, defined by:

[tex][Ekl]_{ij}[/tex] = [tex]\delta_{kilj}[/tex]

These basis are called "standard", because they are built using only the unit (1) of the scalar field; therefore, given a representation of the vector relative to this basis, its coordinates are, in a sense, immediate.

Regarding the general question, every vector space, finite or infinite dimensional, has indeed a basis of this type, called an Hamel basis, and also because they are completely classified by their dimension (vector spaces with the same dimension are isomorphic); of course, in infinite dimensional spaces, the Hamel basis is uncomputable (and unenumerable); in finite dimensions, it coincides with the usual canonical (or "standard basis").
 
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The "standard basis" for the vector space of 2 by 2 matrices (while not every vector space has a "standard" basis, simple one like this do) consists of the four matrices
[tex]\begin{bmatrix}1 & 0 \\ 0 & 0\end{bmatrix}[/tex]
[tex]\begin{bmatrix}0 & 1 \\ 0 & 0\end{bmatrix}[/tex]
[tex]\begin{bmatrix}0 & 0 \\ 1 & 0\end{bmatrix}[/tex]
and
[tex]\begin{bmatrix}0 & 0 \\ 0 & 1\end{bmatrix}[/tex]

So that any matrix can be written as
[tex]\begin{bmatrix}a & b \\ c & d\end{bmatrix}= a\begin{bmatrix}1 & 0 \\ 0 & 0\end{bmatrix}+ b\begin{bmatrix}0 & 1 \\ 0 & 0\end{bmatrix}+ c\begin{bmatrix}0 & 0 \\ 1 & 0\end{bmatrix}+ d\begin{bmatrix}0 & 0 \\ 0 & 1\end{bmatrix}[/tex]
 

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