Proving det(A) = lambda_1 * lambda_2 * ... * lambda_n for Eigenvalue A

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Discussion Overview

The discussion revolves around proving the relationship between the determinant of a matrix \( A \) and its eigenvalues, specifically the equation \( \text{det}(A) = \lambda_1 \cdot \lambda_2 \cdots \lambda_n \), where \( \lambda_i \) represents the eigenvalues of \( A \). The scope includes theoretical aspects of linear algebra and eigenvalue properties.

Discussion Character

  • Debate/contested
  • Technical explanation
  • Mathematical reasoning

Main Points Raised

  • One participant questions the validity of the statement, suggesting it is not true without careful examination of the conditions.
  • Another participant asserts that for the equation to hold, certain assumptions must be made, particularly that \( A \) is a square matrix. They provide conditions for both real and complex matrices that can be diagonalized.
  • A participant mentions that the statement is true for square, symmetric matrices but may not hold for non-symmetric cases.
  • There is a discussion about the importance of distinguishing between algebraic and geometric multiplicity in the context of eigenvalues.
  • A later post provides a hint involving the characteristic polynomial and suggests that the determinant can be expressed as a product of eigenvalues under specific conditions.

Areas of Agreement / Disagreement

Participants express differing views on the validity of the determinant-eigenvalue relationship, with some asserting it is true under specific conditions while others caution against assuming it holds universally. The discussion remains unresolved regarding the general applicability of the statement.

Contextual Notes

Limitations include the dependence on the matrix being square and the potential differences in behavior for symmetric versus non-symmetric matrices. The discussion also touches on the distinction between algebraic and geometric multiplicities, which may affect the interpretation of eigenvalues.

Niels
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How do you prove that [itex]det(A) = \lambda_1*\lambda_2*...*\lambda_n[/itex], where [itex]\lambda_i[/itex] is the eigenvalues of A? I'm stuck :cry:
 
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It isn't true, so you can't prove it. You should examine the question carefully.
 
Last edited:
Niels said:
How do you prove that [itex]det(A) = \lambda_1*\lambda_2*...*\lambda_n[/itex], where [itex]\lambda_i[/itex] is the eigenvalues of A? I'm stuck :cry:

For that to happen,u must make certain assumptions on the matrix 'A'.
The most important is that the matrix 'A' is of square form.If it is symmetrical,then:
a)if A has real elements,then exists a nonsingular orthogonal matrix M which can bring A to diagonal form:
[tex]\exists M\in O_{n}(R)[/tex],so that [tex]MAM^{T}=A_{diag}[/tex]
Then it's easy to show that det A=det A_{diag}=product of eigenvalues.
b)if A has complex elements,then exists a unitary matrix Z which can bring A to diagonal form
[tex]\exists Z\in U_{n}(C)[/tex],so that [tex]ZAZ^{\dagger}=A_{diag}[/tex]
Again,it's easy to show that the eigenvalues are on the diagonal and hence the det.is the product of eigenvalues.

Daniel.
 
Well,Matt,if u're right and I'm wrong,then I'm going to kill my QFT teacher since he graduated both physics and maths. :mad: For a square,symmetrical matrix it has to be true.For other cases (meaning square form and nonsymetry),probably not.

Daniel.
 
No, we're both correct, I said you should be careful, and you showed something inthe special case the matrix is diagonalizable, which is in some sense the notion I meant when I said that you should be careful. This depends upon how we dsitinguish between algebraic and geometric multiplicity.
 
Ok,sorry here's the whole text:
Let A be an nxn matrix, and suppose A har n real eigenvalues [itex]\lambda_1 ... \lambda_n[/itex] repeated accordingly to multiplicities, so that
[tex]det(A - \lambda I) = (\lambda_1 - \lambda)*(\lambda_2 - \lambda)*...*(\lambda_n - \lambda)[/tex]
Explain why det(A) is the product of the n eigenvalues of A.
(Hint: the equation holds for all [itex]\lambda[/itex])
 
let lambda = 0
 
Thanks! I know now that I'm stupied :)
 

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