Eigenvalues, eigenvectors, eigenstates and operators

In summary, the conversation discusses a question about finding the eigenvalues and eigenvectors of a given matrix, and asks for help with a specific part. The solution involves verifying that the given vector is an eigenvector of the matrix and finding the corresponding eigenvalue. It also discusses the notation used for the given vectors.
  • #1
pigletbear
2
0

Homework Statement



Good evening :-)

I have an exam on Wednesday and am working through some past papers. My uni doesn't give the model answers out, and I have come a bit stuck with one question. I have done part one, but not sure where to go from here, would be great if someone could point me in the right direction:

S2) Show that the state vectors |Sx+> = [itex]\frac{1}{\sqrt{}2}[/itex] times a 2x1 matrix (1,1) and |Sy+> = [itex]\frac{1}{\sqrt{}2}[/itex] times a 2x1 matrix (1,-1) are eigenvectors of Sx = h/2 times a 2x2 matrix (0 1, 1 0) with respective eigenvalues plus and minus h/2...


Part two... Of what operator is the state [itex]\frac{1}{\sqrt{}2}[/itex](|Sx+> + |Sy+>) and eigenstate, and with what eigenvalue...

Any help would be great and much appreciated

Homework Equations



All in question

The Attempt at a Solution



Part 1: This I can do by using |A - λI| = 0, finding the eigenvalues, then using A.v=λv and setting up simutaneous quations to find the eigenvalues.

Part 2... this is where I need help please :-)
 
Physics news on Phys.org
  • #2
Hello.

For part (1) you don't need to go through solving for the eigenvalues and eigenvectors. You just want to verify that |Sx+>, say, is an eigenvector of the given matrix. So, just multiply the matrix times the 2x1 vector representing |Sx+> and verify that you get a constant factor times |Sx+>. The constant factor is your eigenvalue.

For part (2), what 2x1 vector do you get when you add [itex]\frac{1}{\sqrt{}2}[/itex](|Sx+> + |Sy+>) ? Can you recognize it?

[Aside: The notation|Sy+> for the second given vector is a bit odd. It seems like |Sx-> would be more appropriate.]
 

1. What are eigenvalues and eigenvectors?

Eigenvalues and eigenvectors are important concepts in linear algebra, specifically in the study of matrices. Eigenvalues are scalars (numbers) that represent the scaling factor of the eigenvectors when a linear transformation is applied. Eigenvectors are non-zero vectors that do not change direction when a linear transformation is applied, but may be scaled by the eigenvalue.

2. How are eigenvalues and eigenvectors calculated?

To calculate eigenvalues and eigenvectors, we first need to have a square matrix. Then, we solve the characteristic equation, which is det(A-λI)=0, where A is the matrix, λ is the eigenvalue, and I is the identity matrix. The solutions to this equation are the eigenvalues. To find the corresponding eigenvectors, we substitute the eigenvalues back into the equation (A-λI)x=0 and solve for the vector x. This process can also be done using computer software such as MATLAB or Python.

3. What is the significance of eigenvalues and eigenvectors?

Eigenvalues and eigenvectors are important in many areas of mathematics and physics. They are used to solve systems of differential equations, analyze the stability of dynamical systems, and in quantum mechanics, they represent the possible states of a quantum system. They also have applications in data analysis and image processing.

4. What are eigenstates and how are they related to eigenvalues and eigenvectors?

Eigenstates are states of a quantum system that correspond to specific eigenvalues and eigenvectors. In quantum mechanics, the eigenvalues represent the possible values that can be measured for a physical quantity, while the eigenvectors represent the corresponding states of the system. For example, in the case of an electron in an atom, the eigenstates represent the different energy levels that the electron can occupy, and the eigenvalues represent the corresponding energy values.

5. What is the role of operators in eigenvalue and eigenvector calculations?

Operators are mathematical objects that represent transformations or operations in linear algebra. In the context of eigenvalues and eigenvectors, operators are used to represent linear transformations on a vector space. In quantum mechanics, operators are used to represent physical observables, such as position or momentum, and they act on the eigenstates to give the corresponding eigenvalues as measurement outcomes.

Similar threads

  • Advanced Physics Homework Help
Replies
13
Views
1K
  • Advanced Physics Homework Help
Replies
6
Views
928
  • Advanced Physics Homework Help
Replies
14
Views
1K
  • Advanced Physics Homework Help
Replies
3
Views
969
  • Advanced Physics Homework Help
Replies
9
Views
1K
  • Advanced Physics Homework Help
Replies
1
Views
1K
  • Advanced Physics Homework Help
Replies
7
Views
2K
Replies
1
Views
995
  • Advanced Physics Homework Help
Replies
1
Views
2K
  • Advanced Physics Homework Help
Replies
3
Views
1K
Back
Top