Why Does a Rank One Matrix with a=1 Still Have Solutions?

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Discussion Overview

The discussion revolves around the properties of a rank one matrix when the parameter \( a \) is set to 1, specifically exploring the existence of solutions in this context. The conversation includes mathematical reasoning and technical explanations related to matrix determinants and specific matrix forms.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • One participant suggests using a permutation matrix to express the left-hand side (LHS) of an equation as \( \mathbf{11}^T + (a-1)\mathbf{I} \) and claims that for \( a \neq 1, -2 \), the matrix is invertible.
  • Another participant questions the origin of the \( \mathbf{11}^T \) expression, seeking clarification on its use.
  • A participant explains that \( \mathbf{11}^T \) represents the ones matrix, which simplifies calculations, and notes that the right-hand side (RHS) is naturally represented as \( 1, a, a^2 \), referring to it as the moment curve.
  • One participant asserts that a solution does not exist when the determinant of the matrix is zero.
  • Another participant counters this claim, stating that when \( a = 1 \), the matrix is rank one but still has positive solutions, citing standard basis vectors as examples.

Areas of Agreement / Disagreement

Participants express disagreement regarding the existence of solutions when the determinant is zero, with some asserting that solutions exist for \( a = 1 \) while others maintain that no solutions can occur under certain conditions.

Contextual Notes

The discussion includes assumptions about the properties of matrices and their determinants, but these assumptions are not fully explored or resolved. The implications of the rank of the matrix and the specific values of \( a \) remain under debate.

Carbon273
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TL;DR
What conditions will there be no solutions, a unique solution and a p-parameter of solutions? If possible may you express in particular and homogenous vectors. I'm a bit rusty so bear with me, trying to reestablish my understanding here.
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I'd strongly suggest multiplying by a permutation matrix ##\mathbf P## so that the LHS matrix is

##\mathbf {11}^T + (a-1)\mathbf I##
and the RHS has the natural progression of ##1, a, a^2 ##

assuming this is in reals, you should be able to confirm that any ##a \neq 1, -2## implies an invertible matrix. And ##a=1## still has (at least one) solution because... and as for ##a=-2## well...
 
Hmm why is that you used that expression for the LHS. I am curious, where does the 11^T comes from?
 
Carbon273 said:
Hmm why is that you used that expression for the LHS. I am curious, where does the 11^T comes from?
because ##\mathbf {11}^T## is the ones matrix and it is easy to work with. The (scaled) Identity matrix is even easier to work with.

and the RHS is most natural as ##1, a, a^2## -- this is called the moment curve.
 
No solution when the determinant of the matrix is 0.
 
mathman said:
No solution when the determinant of the matrix is 0.
This is not correct.

The matrix is rank one when ##a=1## and yet there are ##\gt 0## solutions. e.g. any of the standard basis vectors will do for x here.

I was trying to get OP to come to this conclusion when I said

StoneTemplePython said:
And ##a=1## still has (at least one) solution because...
 

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