What is the Matrix of a Non-Degenerate Non-Symmetric Bilinear Form?

In summary, the conversation discusses the proof of a lemma regarding non-degenerate non-symmetric bilinear forms. The lemma states that for such forms, there exists a basis in which the form has one of three specific matrices. The proof involves decomposing the form into a symmetric and skew symmetric form and making the assumption that the dimension of the kernel of the skew symmetric form is 1. The conversation also considers the possibility of the dimension being 2 and asks for alternative proofs of the lemma.
  • #1
Dmak
15
0
Hello I was reading through some research and I came across the proof of a lemma which I did not wholly understand. The problem statement is as follows:

Let F be a non-degenerate non-symmetic bilinear form in V. Then there exists a basis in V with respect to which F has one of the following matrices:

[tex] H_{\phi} =
\[ \left( \begin{array}{ccc}
cos \phi & sin \phi & 0 \\
-sin \phi & cos \phi & 0 \\
0 & 0 & 1 \end{array} \right)\], J = \[ \left( \begin{array}{ccc} 1& 1 & 0 \\ -1 & 0 & 0 \\ 0 & 0 & 1 \end{array} \right)\], K = \[ \left( \begin{array}{ccc}
1 & 1 & 0 \\
-1 & 0 & 1 \\
0 & 1 & 0 \end{array} \right)\]
[/tex].

First we decompose F into the sum of a symmetric and a skew symmetric form, [tex]F = F_{+} + F_{-} [/tex]. The proof then makes the assumption that [tex]dim \; ker \; F_{-}= 1[/tex]. It seems that the dimension could equally be 2. Any ideas why this is the case? Or better yet can anyone offer another proof of this lemma? Thank you for your help.
 
Physics news on Phys.org
  • #2
I guess ##\dim V =3##. In this case, if ##\dim \ker F_->1##, then ##F## will be symmetric, which is excluded.

Let ##\{\,u,v,w\,\}## be a basis with ##v,w \in \ker F_-##. Then ##u^\tau Fv=u^\tau F_+v=v^\tau Fu## and similar for ##w##. If all three are in the kernel, or for ##v^\tau Fw## we have zero anyway.
 

Related to What is the Matrix of a Non-Degenerate Non-Symmetric Bilinear Form?

What is a matrix of bilinear form?

A matrix of bilinear form is a square matrix that represents a bilinear form, which is a function that takes two vectors as inputs and produces a scalar as output. This matrix contains the coefficients of the bilinear form in its entries.

How is a matrix of bilinear form constructed?

To construct a matrix of bilinear form, the bilinear form must first be represented as a linear combination of basis elements. The coefficients of the linear combination are then arranged in a square matrix, with the basis elements as the rows and columns.

What is the relationship between a matrix of bilinear form and its corresponding bilinear form?

The entries of a matrix of bilinear form represent the coefficients of the corresponding bilinear form. The values in the matrix can be used to evaluate the bilinear form for any two given vectors. Additionally, the matrix can be used to find the change of basis matrix for the bilinear form.

How is a matrix of bilinear form used in linear algebra?

A matrix of bilinear form is used to represent and manipulate bilinear forms in linear algebra. It can be used to perform operations such as matrix multiplication, finding eigenvalues and eigenvectors, and determining the rank and nullity of the bilinear form.

Can a matrix of bilinear form be diagonalized?

Yes, a matrix of bilinear form can be diagonalized if it is symmetric. This means that it has real eigenvalues and orthogonal eigenvectors, which can be used to construct the change of basis matrix for the bilinear form. Diagonalization can simplify calculations involving the bilinear form and make its properties more apparent.

Similar threads

  • Linear and Abstract Algebra
Replies
5
Views
1K
Replies
7
Views
1K
  • Linear and Abstract Algebra
Replies
7
Views
1K
  • Linear and Abstract Algebra
Replies
7
Views
914
Replies
2
Views
828
  • Linear and Abstract Algebra
Replies
3
Views
880
  • Linear and Abstract Algebra
Replies
2
Views
1K
  • Linear and Abstract Algebra
Replies
2
Views
749
  • Linear and Abstract Algebra
Replies
1
Views
1K
  • Linear and Abstract Algebra
Replies
19
Views
2K
Back
Top