Solving the Eigenvalue Problem: Proving \ e ^ A \psi=\ e ^\lambda\psi

Therefore, the statement 0 = 1 is true.In summary, the conversation discusses a proof for the equation e^Apsi=e^lambdapsi, and the concept of canceling matrices. The speaker also mentions their understanding of the definition of e^A and provides a counterexample to the flawed proof presented.
  • #1
neelakash
511
1

Homework Statement



Consider the following problem:

if [tex]\ A [/tex][tex]\psi=[/tex][tex]\lambda[/tex][tex]\psi[/tex],prove that

[tex]\ e ^ A [/tex][tex]\psi=[/tex][tex]\ e ^\lambda[/tex][tex]\psi[/tex]

Homework Equations





The Attempt at a Solution



This is my attempt.Please check if I am correct.

If
[tex]\ e ^ A [/tex][tex]\psi=[/tex][tex]\ e ^\lambda[/tex][tex]\psi[/tex]

is correct, we should have:

[tex]\ ln [/tex][tex]\ e^ A [/tex][tex]\psi=[/tex][tex]\ ln [/tex][tex]\ e ^\lambda[/tex][tex]\psi[/tex]

or, [tex]\ ln \{e^A} + [/tex][tex]\ ln \psi=[/tex][tex]\ ln \{e^\lambda} + [/tex][tex]\ ln \psi[/tex]

Now cancel [tex]\ ln \psi[/tex] from both sides and post-multiply the resulting equation by [tex]\psi[/tex]

That is---

[tex]\ ln \{e^A} =[/tex][tex]\ ln \{e^\lambda}[/tex]

or, [tex]\ [ln \{e ^ A}][/tex][tex]\psi=[/tex][tex]\ [ln \{e ^\lambda}][/tex][tex]\psi[/tex]

Alternatively,

[tex]\ A [/tex][tex]\psi=[/tex][tex]\lambda[/tex][tex]\psi[/tex]

So, we got the given equation from the equation to be proved.
 
Last edited:
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  • #2
The LaTeX image is not coming good.But I think everyone will understand my procedure.
 
  • #3
neelakash said:
...
Now cancel [tex]\ ln \psi[/tex] from both sides and post-multiply the resulting equation by [tex]\psi[/tex] You cannot "cancel". [tex]\ln \psi[/tex] is a matrix.

Do you know the definition of the matrix [itex]e^A[/itex]?
 
  • #4
I know the definition of e^A

Let A,B and C be three matrices.

If I have A+C=B+C

what is wrong if I cancel C from both sides?

ln (psi) is a matrix if you consider psi as matrix.I am usimg psi as a complex function like psi=M+iN
 
  • #5
I did according to your hint.That works well, but still I am having problem to see why the logaritm of a matrix/operator will not work.
 
  • #6
Also, your way of setting up the proof is flawed, as the following direct analogy shows

Theorem: If 1 = 1, prove that 0 = 1.

Proof:
If 0 = 1 is correct, then we obviously also have 1 = 0. Adding the two equations gives
Code:
0 = 1
1 = 0  + 
--------
1 = 1
which is the assumption given.
 

Related to Solving the Eigenvalue Problem: Proving \ e ^ A \psi=\ e ^\lambda\psi

1. What is the Eigenvalue Problem?

The Eigenvalue Problem is a mathematical problem that involves finding the eigenvalues and eigenvectors of a given matrix. Eigenvalues are special numbers that represent the scaling factor for their corresponding eigenvectors.

2. Why is solving the Eigenvalue Problem important?

Solving the Eigenvalue Problem has many practical applications in various fields such as physics, engineering, and computer science. It allows us to understand the behavior and properties of a system described by a matrix, and can help us make predictions and solve complex problems.

3. How is the Eigenvalue Problem solved?

The Eigenvalue Problem is solved by finding the characteristic polynomial of the given matrix, which is a polynomial equation that has the eigenvalues as its roots. The eigenvalues can then be found by solving this polynomial equation. Once the eigenvalues are known, the corresponding eigenvectors can be found by solving a system of equations.

4. What is the relationship between eigenvalues and eigenvectors?

The eigenvalues and eigenvectors of a matrix are closely related. Each eigenvalue corresponds to a unique eigenvector, and vice versa. The eigenvalue represents the scaling factor for its corresponding eigenvector, and the eigenvector represents the direction of the transformation performed by the matrix.

5. How is the formula e^AΨ = e^λΨ used in solving the Eigenvalue Problem?

The formula e^AΨ = e^λΨ is used to solve the Eigenvalue Problem by expressing the matrix in terms of its eigenvalues and eigenvectors. By substituting the eigenvalue and eigenvector values into the equation, we can prove that it holds true for the given matrix. This formula is also useful in finding the solution to differential equations, where A represents the derivative operator.

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