Linear algebra: determinants and eigenvalues

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Discussion Overview

The discussion revolves around properties of skew-symmetric matrices and their determinants, as well as the relationship between eigenvalues and the inverse of a matrix. Participants explore theoretical aspects of linear algebra, specifically focusing on two problems related to skew-symmetric matrices and eigenvalues.

Discussion Character

  • Exploratory
  • Technical explanation
  • Mathematical reasoning

Main Points Raised

  • One participant states that a skew-symmetric matrix is singular when its order is odd, suggesting that the determinant must be zero.
  • Another participant proposes that the relationship between the characteristic polynomial of a matrix and its inverse can explain the second problem regarding eigenvalues.
  • Some participants express confusion about why the determinant of a skew-symmetric matrix of odd order must be zero, questioning the implications of the determinant being equal to its negative.
  • There is a discussion about the relationship between the determinants of a matrix and its transpose, with a participant noting that they are equal.
  • One participant highlights that the determinant of a skew-symmetric matrix of even order is not necessarily zero, using the zero matrix as an example.
  • Another participant attempts to clarify the reasoning behind the determinant being zero by relating it to the equation D = -D.

Areas of Agreement / Disagreement

Participants generally agree on the properties of determinants and eigenvalues, but there is ongoing confusion and disagreement regarding the implications of skew-symmetry, particularly for odd versus even orders of matrices. The discussion remains unresolved on some points, particularly the necessity of the determinant being zero for skew-symmetric matrices of odd order.

Contextual Notes

Participants express uncertainty regarding the assumptions underlying the properties of skew-symmetric matrices and their determinants, as well as the implications of the characteristic polynomial for eigenvalues. There are also unresolved mathematical steps in the reasoning presented.

jhson114
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i'm reading and doing some work in introduction to linear algebra fifth edition, and i came across some problems that i had no clue.

1. An (n x n) matrix A is a skew symmetric (A(transposed) = -A). Argue that an (n x n) skew-symmetrix matrix is singular when n is an odd integer.

2. Prove that if A is nonsingular, then 1/(eigenvalue symbol) is an eigenvalue of A^-1

can someone explain some of these for me. thank you
 
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The second follows from considering the characteristic polynomial (as does the first now I imagine).
 
can you please explain it in more details?
 
For the first, you can show that det(A) is zero. Just use what you know about determinants and A.
 
Yep, that seems better.

But the second is the char poly. e-values are the roots of... relate the char poly of A to that of A^{-1}
 
i don't understand why det(A) has to be zero for the skew symmetric matrix. i know that if n is odd then det(-A)=-det(A) but i don't get why it has to equal zero. and why can't it be zero if n is even??
 
Last edited:
You're almost there. You haven't used the fact that A is skew symmetric yet.
 
and why can't it be zero if n is even??

Eh? Nothing written in this thread implies that a skew-symmetric matrix of even order is always invertible (consider the zero matrix...).
 
arg.. this is confusing. so since its skew-symmetric matrix det(-A)=-det(A)=det(A(transposed)). but why must it be zero :(
 
  • #10
Forget about skew-symmetric matrices for a while. In general, how are det(A') and det(A) related (A is any square matrix, A' the transpose of A)?
 
  • #11
det(A') and det(A) are equal. so that means the two determinants are zero?? man i suck
 
  • #12
Right:

det(A') = det(A).

But as already noted, for a skew-symmetric matrix of odd order, we also have that

det(A') = -det(A).

Hence...?
 
  • #13
Hopefully that's that cleared up for that one.

How about the other: if Av=tv (where t is the eigenvalue and v is the eigenvector) then v=A^{-1}tv=tA^{-1}v

can you complete that from there?
 
  • #14
i know that det(A') = det(A) = -det(A). i think i also mentioned this in the earlier post. But i still don't get why all the determinants are zero.

oh yeah. i figured out number 2. thanks
 
  • #15
Oh let D bet Det(A), you know D, a number, is equal to minus D. How many real (or complex) numbers satisfy D=-D? Or 2D=0?
 
  • #16
ah ha! that makes more sense. and that's so simple too. thanks a lot!
 

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