Prove Rank & Similarity of Matrices A & B

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Discussion Overview

The discussion revolves around proving the similarity of two n x n matrices A and B, given that both are idempotent (i.e., A^2 = A and B^2 = B). Participants explore the relationship between the rank of these matrices and their similarity, considering eigenvalues and complementary subspaces.

Discussion Character

  • Exploratory
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • Some participants propose that A and B are similar if and only if they have the same rank.
  • One participant questions whether the eigenvalues can be used to establish a connection to the rank of the matrices.
  • Another participant discusses the decomposition of vectors into complementary subspaces related to the idempotent property of A and B.
  • There is a suggestion that proving similarity involves showing that A and B have the same eigenvalues.
  • Some participants mention the implications of eigenvalues on the null space and rank, referencing the dimension theorem.
  • One participant warns against assuming similarity based solely on eigenvalues, citing examples of matrices with the same eigenvalues that are not similar.
  • Another participant notes that the trace of an idempotent matrix relates to its rank, suggesting a potential direction for proving similarity.

Areas of Agreement / Disagreement

Participants express differing views on the sufficiency of eigenvalues for establishing similarity. While some argue that the same rank implies similarity, others caution that matrices can share eigenvalues without being similar. The discussion remains unresolved regarding the definitive criteria for similarity.

Contextual Notes

Participants reference the need for proofs regarding the disjoint complementary subspaces and the implications of eigenvalues on rank and nullity. There are unresolved mathematical steps related to the connection between eigenvalues and similarity.

Bachelier
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let A and B be n x n matrices over a field F. Suppose that A^2 = A and B^2 = B. Prove that A and B are similar if and only if they have the same rank.
 
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Can I use the same eigenvalues argument?
They have +1,-1 as eigenvalue, but how do I make the connection to the rank?

Thank you
 
Perhaps this will help: Every vector x can be written as x=(I-A)x+Ax. If [tex]A^2=A[/tex] then the range of (I-A) and the range of A are disjoint complementary subspaces (needs a proof). A vanishes on the first subspace while the second one consists of vectors of eigenvalues 1. Similarly for B.
 
arkajad said:
Perhaps this will help: Every vector x can be written as x=(I-A)x+Ax. If [tex]A^2=A[/tex] then the range of (I-A) and the range of A are disjoint complementary subspaces (needs a proof). A vanishes on the first subspace while the second one consists of vectors of eigenvalues 1. Similarly for B.

So basically to prove similarity of A and B, I am proving they have the same eigenvalues. Am I wrong?
we have
[tex]A^2 -A =0[/tex]
[tex]A( A - I) =0[/tex]
A( A - I) is not invertible.
To say A is not invertible is to say A has eigenvalue of 0.
and A - I is not invertible , means A has eigenvalue of 1. Similarly for B.
What do you think?
 
Bachelier said:
Can I use the same eigenvalues argument?
They have +1,-1 as eigenvalue, but how do I make the connection to the rank?

Thank you
If you know the eigenvalues, what can you tell about the null space and therefore the nullity? Using the nullity, what can you tell about rank given that they have the same dimensions?
 
Anonymous217 said:
If you know the eigenvalues, what can you tell about the null space and therefore the nullity? Using the nullity, what can you tell about rank given that they have the same dimensions?

Using the Nullity, I can find the rank of A by the dimension theorem. n-r.
If I know the eigenvalues, then rank A = [tex]n - rank (A- \lambda*I)[/tex]I) For all eigenvalues.

Note that Null space of A alone equals the eigenspace of its eigenvalue 0.
 
Equality of the ranks should tell you that the two complementary subspaces have the same dimension for A i B. Therefore you can find ... what?
 
Be careful, you have [tex]\begin{pmatrix}1&0\\0&1\end{pmatrix}, \begin{pmatrix}1&1\\0&1\end{pmatrix}[/tex] which are not similar but have the same eigenvalues. Better check for a similarity matrix between two idempotent matrix and use trace(P) = rank(P) for an idempotent matrix P. I did not check it myself but that was the first thing came to my mind.

EDIT : Actually this proves the [itex](\Longrightarrow)[/itex] direction since if they are similar, their trace equals to the number of "1" eigenvalues which is their corresponding matrix rank.

Note: Idempotent matrix eigenvalues are either 1 or zero.
 
Last edited:

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