Why Does Matrix B & C Result in Matrix A?

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Discussion Overview

The discussion revolves around the relationship between matrices A, B, and C, particularly focusing on how matrix C can represent the row reduced echelon form (RREF) of matrix A when multiplied by matrix B to yield A. Participants explore the implications of linear independence, row operations, and matrix dimensions in this context.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • Some participants propose that the rows of matrix C correspond to the rows of matrix A in RREF, questioning the underlying reason for this relationship.
  • Others argue that the columns of matrix B are linearly independent, which is essential for the decomposition BC=A to hold.
  • A participant expresses confusion about how the rows of C are determined, noting that C was introduced to facilitate the multiplication with B, yet its rows seem to reflect those of A in RREF.
  • Another participant mentions that the rank of the row space equals the rank of the column space, suggesting a connection but acknowledging that the bases can differ significantly.
  • One participant points out a potential issue with dimensions, arguing that if A has rank less than its number of rows, then the dimensions of C would not match those of A, raising questions about the validity of C being the RREF of A.
  • Another participant clarifies that the RREF of A will contain zero rows beneath the non-zero rows of C, which aligns with the rank of A.
  • Some participants discuss the process of row reduction and its implications for understanding the relationship between A, B, and C, suggesting that a concrete example might clarify the concepts further.
  • A later reply introduces the idea of multiple decompositions of A, questioning whether different matrices can yield the same result and how to ascertain their equivalence.

Areas of Agreement / Disagreement

Participants express various viewpoints regarding the relationship between matrices A, B, and C, with some agreeing on the linear independence of B's columns while others raise concerns about dimensionality and the nature of the decompositions. The discussion remains unresolved, with multiple competing views on the implications of these relationships.

Contextual Notes

Participants note limitations regarding the assumptions about matrix dimensions and ranks, as well as the implications of row operations on the relationships between the matrices. These aspects remain unresolved within the discussion.

SmilingDave
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Cullen in a question seems to say this;

You have a matrix A of any size. Make a matrix B consisting of only the linearly independent columns of A, choosing them by going from left to right through the columns of A. Then make a matrix C such that BC=A [The q was to prove this is always possible. But I'm not asking about that]

He then says that the rows of C are exactly the rows of A in row reduced echelon form. I tried an example, and it works.

My q is, why is this so? I assume it's not just coincidence, so what is going on?
 
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Because the columns of B are linearly independent.
i.e. what does it mean to reduce to row echelon form?
 
To have the rows interact until they produce a basis for the row space of A.

What I don't see is how did C get to have exactly those same rows. I mean, C was introduced into the picture to have its columns operate on the columns in B so as to produce from B the whole of A. Its rows were never given a thought and didn't play a part. So how did they magically become the rows of A in RREF?
 
Are the rows, then, not related to the columns?
 
What I know is that the rank of the row space is always equal to the rank of the column space, but I don't know of any other connection between them. The bases can be very different. For example, if A is 3x5, the rows are elements of a five dimensional space, and the columns of a three dimensional one.
 
SmilingDave said:
Cullen in a question seems to say this;

You have a matrix A of any size. Make a matrix B consisting of only the linearly independent columns of A, choosing them by going from left to right through the columns of A. Then make a matrix C such that BC=A [The q was to prove this is always possible. But I'm not asking about that]

He then says that the rows of C are exactly the rows of A in row reduced echelon form. I tried an example, and it works.

My q is, why is this so? I assume it's not just coincidence, so what is going on?
Something is wrong here. If A has type m x n, and rank(A)=k<m, then B has type m x k, so if C satifies BC=A, then C has type k x n, which is not the same as the type of A. But then, C is not the reduced row echolon form of A, sice A and C have different types.
 
Erland,

The RREF of A will have a bunch of zero rows underneath the rows of C [which are all nonzero].
 
The other way of seeing this is that you take your matrix A, row reduce it (to reduced row echelon form), call this C, then find the matrix B: BC=A.

Perhaps if you picked a simple case and treated it as a system of simultaneous equations it would help you see what is happening at each stage: what you are doing to the equations.

Note: when you row-reduce A like that, you are finding a particular basis, not just any old basis.
It should come as no surprise that this basis should have a special relationship with A.
 
I see some light. Let R be the matrix that represents all the row operations used to row reduce A. Then RA=C

Thus A=BC, where B is R-inverse.

Let A have rank r.

Since C is also of rank r, it is just rows of zeros beyond row r, and thus it will only use the first r columns of B to build A from B.

So we can get the same effect, meaning get A, by using a matrix consisting of just the first r columns of B, and multiplying by the first r rows of C, and we will get A.

[If A is mxn, modified B will be mxr, and modified C will be rxn, so the dimension are OK].

But I'm still a bit in the dark. We have shown that there is a decomposition of A into R-inverse [modified] and C [modified].

Also, that there is a decomposition using the first lin ind columns of A [call it A modified] and some other matrix, call it D. So that A= R-inverse-modified times C-modified and also = A-modified times D.

But maybe A has two decompositions, using completely different matrices. How do we know A-modified equals R-inverse modified, and that C-modified equals D?

Still working on it. Will try your suggestion of a concrete example.

Thanks for all the help.
 
  • #10
Are there more than one decomposition that fits all the conditions?
Have you covered LU and LDU decomposition yet?
 

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