Determinant of a symmetric matrix

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Discussion Overview

The discussion revolves around finding a simplification for the determinant of a symmetric matrix, specifically focusing on a 3x3 matrix defined in terms of a function f(x) and other variable elements. Participants explore the implications of this determinant in the context of finding its roots.

Discussion Character

  • Exploratory, Technical explanation, Mathematical reasoning

Main Points Raised

  • One participant, Krindik, inquires about simplifications for the determinant of a symmetric matrix and provides a specific example with a 3x3 matrix.
  • Another participant suggests that the determinant can be expressed as f(x)³ - B2f(x), where B is a vector defined in terms of the matrix elements.
  • A later reply questions how this determinant simplification can be generalized to nxn matrices.

Areas of Agreement / Disagreement

There is no consensus on the generalization of the determinant simplification to nxn matrices, as the discussion remains open with questions posed about broader applications.

Contextual Notes

The discussion does not address potential limitations or assumptions regarding the definitions of the matrix elements or the function f(x), nor does it resolve the mathematical steps involved in generalizing the determinant.

krindik
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Hi,

Is there a simplification for the determinant of a symmetric matrix? For example, I need to find the roots of \det [A(x)]
where
<br /> A(x) = \[ \left( \begin{array}{ccc}<br /> f(x) &amp; a_{12}(x) &amp; a_{13}(x) \\<br /> a_{12}(x) &amp; f(x) &amp; a_{23}(x) \\<br /> a_{13}(x) &amp; a_{23}(x) &amp; f(x) \end{array} \right)\]<br />

Really appreciate if you could point me in the correct directions. Thanks in advance,

Krindik
 
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Hi Krindik! :smile:

If we define a vector B = (B1, B2, B3) = (a23, a31, a12),

then the determinant is f(x)3 - B2f(x) :wink:
 
Thanks :)
 
tiny-tim said:
Hi Krindik! :smile:

If we define a vector B = (B1, B2, B3) = (a23, a31, a12),

then the determinant is f(x)3 - B2f(x) :wink:

How is this generalized to nxn matrices?
 

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