Understanding the Linearity of Determinants: Exploring the Identity Property

In summary, the conversation discusses the linearity of determinants and how the two matrices on the right side of the equation can be identical. The explanation is that the last determinant is zero due to two equal rows. The conversation also touches on the property of determinants and how it is generally not true that det(A) = det(B) + det(C). Finally, the conversation ends with the understanding that the expression for the determinant of the matrix on the left side can be split into two equal determinants, leading to the equality shown in the equation.
  • #1
twoflower
368
0
Hi all,

I don't understand one thing about linearity of determinants. In the book I have:

[tex]
\det \left( \begin{array}{ccc} . & . & . \\ . & . & . \\ \mbox{} \\ . & . & . \\ . & . & . \\ . & . & . \\ \mbox{[j]} \end{array} \right) = \det \left( \begin{array}{ccc} . & . & . \\ . & . & . \\ \mbox{} \\ . & . & . \\ . & . & . \\ . & . & . \\ \mbox{[j+i]} \end{array} \right)
[/tex]

And the explanation is:

[tex]
\det \left( \begin{array}{ccc} . & . & . \\ . & . & . \\ \mbox{} \\ . & . & . \\ . & . & . \\ . & . & . \\ \mbox{[j+i]} \end{array} \right) = \det \left( \begin{array}{ccc} . & . & . \\ . & . & . \\ \mbox{} \\ . & . & . \\ . & . & . \\ . & . & . \\ \mbox{[j]} \end{array} \right) + \det \left( \begin{array}{ccc} . & . & . \\ . & . & . \\ \mbox{} \\ . & . & . \\ . & . & . \\ . & . & . \\ \mbox{} \end{array} \right)
[/tex]

But I can't see how these two matrixes (I mean now left and right side of the bottom equation) can be identical, because when I sum the two matrixes on the right, I won't get the matrix on the left...

Thank you for the explanation.
 
Physics news on Phys.org
  • #2
You shouldn't add the bottom right matrices, since they are determinants. The last determinant is zero because two rows are equal.
To see why the equality is true, expand the first along the last row.
 
  • #3
Galileo said:
You shouldn't add the bottom right matrices, since they are determinants. The last determinant is zero because two rows are equal.
To see why the equality is true, expand the first along the last row.

This property of determinant is before expaning along rows/columns, so I think it should be possible to see it even simplier.

I know they are determinants, but I suppose that if

A = B + C
then det(A) = det(B) + det(C)
 
  • #4
Here's a special case that might help:

[tex]\vec A\times (\vec B +\vec A) = \vec A\times\vec B +\vec A\times \vec A= \vec A\times\vec B[/tex]

twoflower said:
I know they are determinants, but I suppose that if

A = B + C
then det(A) = det(B) + det(C)

This is generally false.
Let [tex]B=\left(\begin{array}{cc} 1 & 0 \\ 0 &0 \end{array} \right) [/tex] and [tex]C=\left(\begin{array}{cc} 0& 0 \\ 0 &1 \end{array} \right) [/tex]. These have zero determinant... so the sum of the determinants is zero. However, the matrix sum has determinant 1.
 
  • #5
Thank you, I think I have it. I just have to write the expression for the determinant of the matrix on the left side and I can split it into two determinants equal to the ones on the right side. Thanks.
 

Question 1: What is the definition of linearity of determinant?

The linearity of determinant refers to the property of a determinant where it changes sign when two rows or columns are exchanged, and it remains the same when multiplied by a constant or added to another determinant.

Question 2: How does linearity of determinant affect the calculation of determinants?

The linearity of determinant allows for easier calculation of determinants as it allows for the use of row operations to simplify the matrix before calculating the determinant. This property also allows for the use of properties such as expansion by minors and cofactors to calculate determinants of larger matrices.

Question 3: What is the significance of linearity of determinant in linear algebra?

The linearity of determinant is significant in linear algebra as it is a key property used in solving systems of linear equations. It also plays a crucial role in the invertibility of matrices and in the calculation of eigenvalues and eigenvectors.

Question 4: Can the linearity of determinant be used to simplify the calculation of determinants of non-square matrices?

Yes, the linearity of determinant can be used to simplify the calculation of determinants of non-square matrices by reducing the matrix to a square matrix using row and column operations. This allows for the use of properties such as expansion by minors and cofactors to calculate the determinant of the resulting square matrix.

Question 5: Is the linearity of determinant specific to determinants of matrices?

Yes, the linearity of determinant is specific to determinants of matrices and does not apply to other mathematical operations. However, similar properties of linearity can be found in other mathematical concepts such as linearity of functions in calculus.

Similar threads

  • Linear and Abstract Algebra
Replies
5
Views
944
  • Linear and Abstract Algebra
Replies
2
Views
1K
  • Linear and Abstract Algebra
Replies
3
Views
819
  • Linear and Abstract Algebra
Replies
4
Views
2K
  • Linear and Abstract Algebra
Replies
3
Views
1K
  • Linear and Abstract Algebra
Replies
7
Views
927
  • Linear and Abstract Algebra
Replies
1
Views
1K
  • Linear and Abstract Algebra
Replies
1
Views
857
  • Linear and Abstract Algebra
Replies
3
Views
2K
  • Linear and Abstract Algebra
Replies
5
Views
1K
Back
Top