Bilinear forms & Symmetric bilinear forms

In summary: I am assuming that you want to diagonalize the form f using the basis vectors in R^3, right? If so, then the expression for f would just be (P^T)AP.
  • #1
kingwinner
1,270
0
1) Let f: V x V -> F be a symmetric bilinear form on V, where F is a field.
Suppose B={v1,...,vn} is an orthogonal basis for V
This implies f(vi,vj)=0 for all i not=j
=>A=diag{a1,...,an} and we say that f is diagonalized.


============
Now I don't understand the red part, i.e. how does orthongality imply f(vi,vj)=0 for all i not=j?

============

2) For the following symmetric matrix A,
A=[1 -1 -1
-1 1 -1
-1 -1 1]
a) find an orthogonal matrix P such that (P^T)AP is diagonal.
b) Let f be the bilinear form on R^3 that has matrix A relative to the basis B={(1,1,1),(1,0,1),(0,1,-1)}. Use the matrix P from part a to find a basis of R^3 relative to which f is represented by a diagonal matrix. Also write out the corresponding diagonalized expression for f.


I got part a),
P= [1/sqrt3 1/sqrt2 1/sqrt6
1/sqrt3 -1/sqrt2 1/sqrt6
1/sqrt3 0 -2/sqrt6]
is orthogonal such that (P^T)AP=diag{-1,2,2} is diagonal.
Now part b is the headache, I don't even know how to start, can someone please help me? It seems really challenging, but I am sure someone here knows how to solve it.


Thanks a million!
 
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  • #2
Can someone please help me?
 
  • #3
kingwinner said:
1) Let f: V x V -> F be a symmetric bilinear form on V, where F is a field.
Suppose B={v1,...,vn} is an orthogonal basis for V
This implies f(vi,vj)=0 for all i not=j
=>A=diag{a1,...,an} and we say that f is diagonalized.


============
Now I don't understand the red part, i.e. how does orthongality imply f(vi,vj)=0 for all i not=j?

============
It doesn't- there certainly exist symmetric bilinear forms that are not "diagonalized" just because we pick an orthonormal basis. Perhaps you have misunderstood or miscopied something. A symmetric bilinear operator can always be written as a symmetric matrix in any basis and it is always possible to choose an orthonormal basis so that matrix is diagonal. But it must be chosen carefully, it is not true for every orthonormal basis.

2) For the following symmetric matrix A,
A=[1 -1 -1
-1 1 -1
-1 -1 1]
a) find an orthogonal matrix P such that (P^T)AP is diagonal.
b) Let f be the bilinear form on R^3 that has matrix A relative to the basis B={(1,1,1),(1,0,1),(0,1,-1)}. Use the matrix P from part a to find a basis of R^3 relative to which f is represented by a diagonal matrix. Also write out the corresponding diagonalized expression for f.
In fact, this problem wouldn't make sense if the forgoing were true! If a symmetric bilinear form is diagonal in any orthonormal basis, they wouldn't be asking you to find such a basis!

I got part a),
P= [1/sqrt3 1/sqrt2 1/sqrt6
1/sqrt3 -1/sqrt2 1/sqrt6
1/sqrt3 0 -2/sqrt6]
is orthogonal such that (P^T)AP=diag{-1,2,2} is diagonal.
Now part b is the headache, I don't even know how to start, can someone please help me? It seems really challenging, but I am sure someone here knows how to solve it.


Thanks a million!
Okay, I presume that you found that A has a double eigenvalue of 2 and a single eigenvalue of 1 and have found 3 independent vectors corresponding to those eigenvalues and used those vectors as columns to construct the matrix P. Well, that's the whole point isn't it! You've already done all the work. If you use THOSE eigenvectors as basis vectors, then A is diagonal with the eigenvalues on the diagonal. The columns of the matrix P are the basis vectors sought in b and D is just the diagonal matrix with the eigenvalues of A, 2, 2, -1, on the diagonal.
 
  • #4
HallsofIvy said:
Okay, I presume that you found that A has a double eigenvalue of 2 and a single eigenvalue of 1 and have found 3 independent vectors corresponding to those eigenvalues and used those vectors as columns to construct the matrix P. Well, that's the whole point isn't it! You've already done all the work. If you use THOSE eigenvectors as basis vectors, then A is diagonal with the eigenvalues on the diagonal. The columns of the matrix P are the basis vectors sought in b and D is just the diagonal matrix with the eigenvalues of A, 2, 2, -1, on the diagonal.


2b) So is the answer to this part going to be the columns of P?
But isn't there a difference between diagonalizing A and diagonalizing the bilinear form f? I don't get why the answer is true...
Also, what would the diagonalized expression for f look like?

By the way, the question says "Let f be the bilinear form on R^3...", so f is not necessarily a symmetric bilinear form, right?
Theorem: A bilinear form f is symmetric if and only if EVERY matrix that represents f is symmetric.
So using this theorem, ONE matrix (i.e. the matrix A) that represents f is symmetric doesn't imply that f is symmetric.

I am so confused, please help me...
 
Last edited:

1. What is a bilinear form?

A bilinear form is a mathematical function that takes in two vectors and outputs a scalar. It is linear in each of its arguments, meaning that when one argument is held constant, the function behaves like a linear function in the other argument.

2. What is the difference between a bilinear form and a symmetric bilinear form?

A symmetric bilinear form is a type of bilinear form in which the order of the arguments does not matter. This means that if we swap the two vectors in the function, the output remains the same. In contrast, a general bilinear form may have different outputs depending on the order of the arguments.

3. How are bilinear forms used in mathematics?

Bilinear forms are used in various areas of mathematics, such as linear algebra, differential geometry, and functional analysis. They are useful for defining and studying multilinear functions, quadratic forms, and inner products. They also have applications in physics, engineering, and computer science.

4. What are some properties of bilinear forms?

Some properties of bilinear forms include linearity, symmetry (for symmetric bilinear forms), and non-degeneracy. Non-degeneracy means that the function is not constantly zero and has a non-trivial kernel, which is important for defining inverse operations and studying other properties.

5. How are symmetric bilinear forms related to quadratic forms?

A quadratic form is a function that takes in a vector and outputs a scalar by squaring each component of the vector and summing them. A symmetric bilinear form can be used to define a quadratic form by setting one argument of the bilinear form to be the same vector, and the other argument to be a variable vector. This connection allows us to study quadratic forms using the properties and techniques of symmetric bilinear forms.

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