Eigenvalues of linear operators

In summary: The operator C is the identity operator, which means it simply maps every function to itself. The eigenvalue for this operator is 1, since Cf=f for any value of f.
  • #1
LocationX
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Let V be the vector space of all real integrable functions on [0,1] with inner product [tex]<f,g>=\int_0^1 f(t)g(t)dt[/tex]

Three linear operators defined on this space are [tex] A=d/dt [/tex] and [tex]B=t[/tex] and [tex]C=1[/tex] so that [tex]Af=df/dt[/tex] and [tex]Bf=tf[/tex] and [tex]Cf=f[/tex]

I need to find the eigenvalues of these operators:

For A:
[tex]\frac{df}{dt} = \lambdaf[/tex]
[tex]\frac{d ln(f)}{dt} = \lambda [/tex]
[tex]d(ln(f))=\lambda dt+c[/tex]
[tex]f=ce^{\lambda t}[/tex]

So the eigenvalues for A are continuous and can be any real number.

For B:
[tex]tf=\lambda f[/tex]
[tex]\lambda =t [/tex]

The eigenvalues are the variable t?

For B;
[tex]Cf=f=\lambda f[/tex]
The eigenvalue is 1.

Confused about B.
 
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  • #2


LocationX said:
Let V be the vector space of all real integrable functions on [0,1] with inner product [tex]<f,g>=\int_0^1 f(t)g(t)dt[/tex]

Three linear operators defined on this space are [tex] A=d/dt [/tex] and [tex]B=t[/tex] and [tex]C=1[/tex] so that [tex]Af=df/dt[/tex] and [tex]Bf=tf[/tex] and [tex]Cf=f[/tex]

I need to find the eigenvalues of these operators:

For A:
[tex]\frac{df}{dt} = \lambdaf[/tex]
[tex]\frac{d ln(f)}{dt} = \lambda [/tex]
[tex]d(ln(f))=\lambda dt+c[/tex]
[tex]f=ce^{\lambda t}[/tex]

So the eigenvalues for A are continuous and can be any real number.
I'm not sure I like the statement "the eigenvalues of A are continuous". What does it mean for a number to be "continuous"? But, yes, every real number is an eigenvalue- the set of eigenvalues is a continuous interval rather than discreet.

For B:
[tex]tf=\lambda f[/tex]
[tex]\lambda =t [/tex]

The eigenvalues are the variable t?
No, eigenvalues are NUMBERS, not variables. [itex]tf= \lambda f[/itex] if and only if f(t)= 0 for all t, the "zero vector". This operator has NO eigenvalues.

For B;
[tex]Cf=f=\lambda f[/tex]
The eigenvalue is 1.

Confused about B.
 

Related to Eigenvalues of linear operators

1. What are eigenvalues of linear operators?

Eigenvalues of linear operators are the special values that satisfy the equation Ax = λx, where A is a square matrix and x is a non-zero vector. They represent the scaling factor by which the vector x is multiplied when acted upon by the linear operator A.

2. How do you calculate eigenvalues of linear operators?

Eigenvalues can be calculated by finding the roots of the characteristic polynomial of the matrix A. This polynomial is obtained by subtracting λ from the diagonal elements of A and taking the determinant of the resulting matrix.

3. What is the significance of eigenvalues in linear algebra?

The eigenvalues of a linear operator provide important information about the behavior of the system. They determine the stability, convergence, and oscillation of a system and are used in various applications such as differential equations, signal processing, and quantum mechanics.

4. Can a linear operator have complex eigenvalues?

Yes, a linear operator can have complex eigenvalues. This occurs when the matrix A has complex elements. In this case, the eigenvalues will be complex numbers and the eigenvectors will also have complex elements.

5. What is the relationship between eigenvalues and eigenvectors of a linear operator?

Eigenvectors are the corresponding vectors to each eigenvalue of a linear operator. They represent the direction of the vector that remains unchanged when acted upon by the linear operator. The eigenvalues and eigenvectors are related through the equation Ax = λx, where λ is the eigenvalue and x is the eigenvector.

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