What are the implications of calculating the determinant of a matrix?

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    Determinant Matrix
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Discussion Overview

The discussion revolves around the implications of calculating the determinant of a matrix, exploring both theoretical and practical aspects. Participants examine the relationships between the determinant and properties such as linear dependence, invertibility, and geometric interpretations.

Discussion Character

  • Technical explanation
  • Conceptual clarification
  • Debate/contested

Main Points Raised

  • Some participants assert that if det A=0, it indicates linear dependence, infinitely many solutions, and that the matrix is non-invertible or singular.
  • Others argue that if det A != 0, it implies linear independence, a unique solution, and that the matrix is invertible.
  • A participant questions the interpretation of "parallel vectors," suggesting that in larger matrices, at least one row is in the span of the others.
  • Another participant highlights that the determinant corresponds to the volume of the parallelepiped spanned by the matrix's rows or columns, linking this to the concept of singular matrices.
  • One participant points out that a determinant of zero does not necessarily mean there are infinitely many solutions, as it can also indicate no solutions in certain cases.
  • It is noted that numerical algorithms can encounter significant issues when the determinant is close to zero, affecting stability in matrix inversion.

Areas of Agreement / Disagreement

Participants express differing views on the implications of the determinant, particularly regarding the conditions under which solutions exist or do not exist. The discussion remains unresolved with multiple competing interpretations and no consensus reached.

Contextual Notes

Some claims depend on the dimensions of the matrix and the definitions used, which may not be universally agreed upon. The implications of the determinant in numerical algorithms also introduce practical considerations that are not fully explored.

knightmetal
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Hello,

I'd like to know if the following two paragraphs regarding the determinant of a matrix are correct and also, am I missing any other important implications by calculating the determinant? any other important things I can find from with that value? thanks.

1. If det A=0 <=> Linear Dependence <=> Infinitely many solutions (hence non trivial solution) <=> non invertible (or singular) matrix <=> vectors are parallel.

2. If det A != 0 <=> L.I <=> unique solution <=> invertible (also nonsingular or regular) matrix
 
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knightmetal said:
Hello,

I'd like to know if the following two paragraphs regarding the determinant of a matrix are correct and also, am I missing any other important implications by calculating the determinant? any other important things I can find from with that value? thanks.

1. If det A=0 <=> Linear Dependence <=> Infinitely many solutions (hence non trivial solution) <=> non invertible (or singular) matrix <=> vectors are parallel.

2. If det A != 0 <=> L.I <=> unique solution <=> invertible (also nonsingular or regular) matrix


It's hard to be certain about what you mean: what "vectors" are parallel? Do you mean the matrix's rows (columns)? Then this is false

if the matrix is n x n , n > 2, as what is actually true is that at least one row is in the span of the other ones.

This determinant-not-zero thing is one of the basic mathematics ideas with more equivalent formulations: you could also say that det A = 0

iff ker A = 0 iff A is onto (when seen as linear operator) iff zero is NOT one of its eigenvalues iff for any non-zero b, the system Ax = b has one single solutions...

DonAntonio
 
Aside from what DonAntonio mentioned, one important fact you missed is that the determinant is equal to the volume of the parallelepiped spanned by the columns (or the rows). See http://en.wikipedia.org/wiki/Determinant#Volume_and_Jacobian_determinant and scroll down to the colorful pictures.

This explains (geometrically) why a determinant of zero corresponds to a singular matrix. It also goes a long way toward explaining the rule for changing variables in multiple integrals.
 
the opposite of one solution is zero or at least two.

if det A=0, it is possible to have no solution. for instance 0x=0 has many solutions, while 0x=1 has none.

In other words, if det A =0, then A is not injective nor surjectinve.
 
Hey guys thanks a lot for your replies, it helped :)
 
knightmetal said:
am I missing any other important implications by calculating the determinant? any other important things I can find from with that value?

Another useful thing to know: many numerical algorithms run into horrible problems whenever ##\textrm{Det}[\hat{M}] \approx 0##. (E.g. matrix inversion is unstable.)

There's also a fairly comprehensive list of singular-matrix implications on Wikipedia:
http://en.wikipedia.org/wiki/Singular_matrix#Properties
 
heres all there is to know about determinants.
 

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