Undergrad Proof of Column Extraction Theorem for Finding a Basis for Col(A)

Click For Summary
The discussion centers on the Proof of the Column Extraction Theorem, which states that the columns of a matrix A corresponding to leading ones in its reduced row echelon form (RREF) form a basis for Col(A), with the dimension of Col(A) equal to the rank of A. It explains that a linear map α from vector space V to W, when applied to a basis B of V, spans α(V) due to the linearity of α. The RREF definition indicates that columns without leading ones can be expressed as linear combinations of the basis columns. An example illustrates this by showing how non-basis columns can be constructed from basis columns in a specific RREF matrix. The discussion emphasizes the relationship between leading ones and the basis of the column space.
mattTch
Messages
2
Reaction score
0
TL;DR
Let A be an m×n matrix. I am not sure why it's immediately obvious that the set B containing all and only the column vectors of R = RREF(A) which have leading ones, forms a basis for R. In particular, why is it the case that Span(B) = Col(R)? FYI: The linear independence of B is obvious to me.
Theorem: The columns of A which correspond to leading ones in the reduced row echelon form of A form a basis for Col(A). Moreover, dimCol(A)=rank(A).
 
Physics news on Phys.org
Consider:

1. If \alpha : V \to W is a linear map and B = \{b_i\} is a basis for V, then \alpha(B) spans \alpha(V). This follows from linearity of \alpha: If v \in V then v = \sum_i a_ib_i and <br /> \alpha(v) = \alpha\left(\sum _ia_i b_i\right) = \sum_i a_i \alpha(b_i).

2. The ith column of a matrix is the image of the ith standard basis vector.

3. It follows from the definition of RREF that columns which don't have a leading 1 are linear combinations of the columns which do.
 
Why does 3 follow from the definition of RREF?
 
mattTch said:
Why does 3 follow from the definition of RREF?
Can chip in? If I've understood your question this might help.

Consider an example RREF matrix:

##\begin{bmatrix}
1 & 0 & 2 & 0 & 8\\
0 & 1 & 7 & 0 & 3\\
0 & 0 & 0 & 1 & 2\\
0 & 0 & 0 & 0 & 0
\end{bmatrix} ##

Some columns contain a leading '1' (with zeroes for all other elements). These are the basis columns.

Other columns do not contain a leading '1'. These are non-basis columns.

The basis columns here are ##C_1 = \begin{bmatrix}
1\\
0\\
0\\
0
\end{bmatrix}##, ##C_2 = \begin{bmatrix}
0\\
1\\
0\\
0
\end{bmatrix}## and ##C_4 = \begin{bmatrix}
0\\
0\\
1\\
0
\end{bmatrix}##.

From inspection it should be clear that any non-basis column can be constructed as a linear combination of the basis columns, e.g. ##C_5 = 8C_1 + 3C_2 + 2C_4##.

That’s because every non-zero coefficient in a non-basis column is a simple multiple of the ‘1’ in a basis column.
 
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 4 ·
Replies
4
Views
2K
  • · Replies 4 ·
Replies
4
Views
3K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 8 ·
Replies
8
Views
3K
  • · Replies 3 ·
Replies
3
Views
3K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 7 ·
Replies
7
Views
2K
  • · Replies 3 ·
Replies
3
Views
3K
  • · Replies 2 ·
Replies
2
Views
3K