Skew Symmetry: Inner Product of Rows & Determinant

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In summary, the determinant of a matrix is its diagonals. If the determinant is even, then it is similar to the levi-civita symbol. If the determinant is odd, then it is a set of permutations.
  • #1
Tenshou
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I am entranced. I mean There are so many thing which seem to deal with skew symmetry, like the skew anti-symmetric matrices of Electromagnetic 4-tensor, I have this thing, a question. And it is stated as: " if you take the inner product of the rows of a skew symmetric matrix would it be equal to 0" because I remember hearing, or reading some where that the determinant of a matrix is its diagonals
 
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  • #2
No but the determinant itself is an alternating form meaning the determinant of a matrix with two identical columns will vanish; you might have seen in say relativity textbooks the determinant is defined using the levi-civita symbol so the above property of the determinant is immediately apparent when cast in such form (in LA books like Friedberg you would see the determinant characterized as the unique n-linear alternating map that sends the identity matrix to 1).
 
  • #3
That actually helps! But, the levi-civita symbols are a little confusing @_@ I mean just in general I don't understand why that is a reason for skew anti-symmetry
 
  • #4
Why what is a reason?
 
  • #5
D: maybe I asked the question wrong, I was asking, or trying to ask why does the determinant function hold to be skew anti-symmetric n-linear function phi from one vector space to another. In the book the determinant function is defined as ## \Delta = \sum_{\sigma} \epsilon_{\sigma}\left(\sigma\Phi\right) ## and ##\forall\sigma\in S_{n}## which is a set of permutations and epsilon is a homomorphism from ##S_{n}## to the multiplicative set {1,-1} and when ##\epsilon_{\sigma}## is even (when ##\epsilon_{\sigma}## is odd respectively) < that right there is similar to the levi-civita but I don't understand why it makes it skew anti-symmetric, is it because phi is skew symmetric?
 
  • #7
D: but I am not looking for a basis free definition, thank you for the resource but that hasn't settled this problem D:
 
  • #8
bump D:
please help?
 

What is skew symmetry?

Skew symmetry is a mathematical property that describes a relationship between two matrices, where the inner product of the rows of one matrix is equal to the negative of the determinant of the other matrix.

What is an inner product?

An inner product is a mathematical operation that takes two vectors and produces a scalar value. It is often denoted as ⟨x,y⟩ and can be thought of as a measure of the similarity or angle between two vectors.

What is the determinant of a matrix?

The determinant of a matrix is a scalar value that is calculated from the elements of the matrix. It describes the volume of a parallelepiped formed by the column vectors of the matrix and is used to solve various linear algebra problems.

What is the significance of skew symmetry?

Skew symmetry is important in linear algebra and matrix theory as it helps to identify relationships between matrices and can be used to simplify calculations and proofs. It is also useful in applications such as physics and engineering.

How can skew symmetry be applied in real life?

Skew symmetry has applications in areas such as physics, engineering, and computer science. It is used in the study of electromagnetism, mechanics, and quantum mechanics. It is also used in computer graphics and computer vision algorithms for tasks such as image recognition and 3D reconstruction.

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