Invertible Matrix Theorem: Multiple Solutions for Ax=b?

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Homework Help Overview

The discussion revolves around the Invertible Matrix Theorem and its implications for the equation Ax = b, particularly focusing on the uniqueness and existence of solutions for different vectors b in the context of an n x n invertible matrix.

Discussion Character

  • Conceptual clarification, Assumption checking

Approaches and Questions Raised

  • Participants explore the wording of the theorem regarding the existence and uniqueness of solutions, questioning whether it states "at least one" or "exactly one" solution for each b. Some participants discuss the implications of invertibility on the nature of solutions, while others raise concerns about the validity of certain statements regarding the consistency and uniqueness of solutions.

Discussion Status

The conversation is ongoing, with participants clarifying the statements of the theorem and discussing the implications of invertibility. There is a recognition that both existence and uniqueness of solutions are true for invertible matrices, but the exact phrasing in different sources is causing some confusion.

Contextual Notes

Some participants express urgency in seeking proofs for related theorems, while others caution against deviating from the original topic. There is mention of specific cases, such as the zero matrix, that illustrate the conditions under which solutions may or may not exist.

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General question regarding the Inv. Matrix Thm:

One part of the theorem states that for an nxn invertible matrix, then there exists at least one solution for each b in Ax=b. Why wouldn't it be "there exists at MOST one solution for each b" since every column/row has a pivot. How would there exist more than one solution for each b if the columns span R_n?
 
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Are you sure that's what the theorem says? My book doesn't say "at least one". It says "exactly one". Here's what Wikipedia says:

[PLAIN]http://en.wikipedia.org/wiki/Invertible_matrix_theorem said:
Let[/PLAIN] A be a square n by n matrix over a field K (for example the field R of real numbers). Then the following statements are equivalent:

A is invertible.
A is row-equivalent to the n-by-n identity matrix In.
A is column-equivalent to the n-by-n identity matrix In.
A has n pivot positions.
det A ≠ 0.
rank A = n.
The equation Ax = 0 has only the trivial solution x = 0 (i.e., Null A = {0})
The equation Ax = b has exactly one solution for each b in Rn.
The columns of A are linearly independent.
The columns of A span Rn (i.e. Col A = Rn).
The columns of A form a basis of Rn.
The linear transformation mapping x to Ax is a bijection from Rn to Rn.
There is an n by n matrix B such that AB = In.
The transpose AT is an invertible matrix.
The matrix times its transpose, AT × A is an invertible matrix.
The number 0 is not an eigenvalue of A.
 
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Oh, weird. Yeah my book does say "at least one solution". Thanks for showing me the wiki entry though.
 
Well, the statement is still true: if a matrix is invertible, then the equation Ax= b has exactly one solution so it is certainly true that there is at least one solution.

If A is not invertible then Ax= b may have no solutions or an infinite number of solutions.

You book may have some reason for emphasizing "the solution exists" right now rather than "the solution is unique"- both of which are true for A invertible.
 
Pyae said:
Does anyone know how to prove the following theorems:

1) Ax = b is consistent for every n x 1 matrix b

2) Ax = b has exactly one solution for every n x 1 matrix b

3) Ax = b has exactly one solution for at least one n x 1 matrix b

Pls... I need help. It's urgent!
First, don't "hijack" someone else's thread for your own question- that's rude. Use the "new topic" button to start your own thread.

Second, go back and reread the question. You can't prove any of those, they are all false. For example, if A is the 0 matrix, "Ax= b" has NO soution for b non-zero and has an infinite number of solutions if b is 0.
 

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