An eigenstates, eigenvectors and eigenvalues question

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Discussion Overview

The discussion revolves around eigenstates, eigenvectors, and eigenvalues in the context of quantum mechanics, specifically related to the operators associated with spin states. Participants are addressing a problem from past exam papers, exploring the mathematical relationships between state vectors and their corresponding operators.

Discussion Character

  • Homework-related
  • Mathematical reasoning
  • Technical explanation
  • Debate/contested

Main Points Raised

  • One participant describes the process of showing that specific state vectors are eigenvectors of a given operator using the characteristic equation and simultaneous equations.
  • Another participant suggests an alternative approach to demonstrate that the state vectors are eigenvectors by directly applying the operator to the states, arguing it is a more efficient method.
  • A later reply proposes that the second part of the question can be approached similarly by applying the operator to the combined state and setting up an eigenvalue equation.
  • There is a discussion about the relative difficulty of solving the characteristic equation versus applying the operator to the vectors, with differing opinions on which method is easier or faster.
  • Some participants express uncertainty about the correctness of their suggestions, indicating a lack of confidence in their proposed solutions.

Areas of Agreement / Disagreement

Participants do not reach a consensus on the best approach to solve the problem. There are competing views on the efficiency of different methods for demonstrating the eigenvector relationships.

Contextual Notes

Some participants note that the complexity of the matrix or operator could affect the ease of solving the eigenvalue equation, suggesting that the discussion is context-dependent.

pigletbear
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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+> = \frac{1}{\sqrt{}2} times a 2x1 matrix (1,1) and |Sy+> = \frac{1}{\sqrt{}2} 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...

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 two... Of what operator is the state \frac{1}{sqrt{}2}[/itex]/(|S<sub>x</sub>+&gt; + |S<sub>y</sub>+&gt;) and eigenstate, and with what eigenvalue...<br /> <br /> Any help would be great and much appreciated
 
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pigletbear said:
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+> = \frac{1}{\sqrt{}2} times a 2x1 matrix (1,1) and |Sy+> = \frac{1}{\sqrt{}2} 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...

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 two... Of what operator is the state \frac{1}{sqrt{}2}[/itex]/(|S<sub>x</sub>+&gt; + |S<sub>y</sub>+&gt;) and eigenstate, and with what eigenvalue...<br /> <br /> Any help would be great and much appreciated
<br /> <br /> Hello!<br /> My suggestion is to try to explicitly add up the two states in matrix notation... <br /> The answer should then be obvious to you :)<br /> <br /> Edit:<br /> The answer you gave to the first question is right. Nevertheless it is more time consuming then it was necessary and time is precious during exams :) <br /> You have to <i>show</i> that those are egenvectors with given eigenvalue, so you could simply show that <br /> <br /> S_x |S_x ± \rangle = ± \frac{h}{2}|S_x ± \rangle, <br /> <br /> without solving the egenvalue equation <br /> <br /> |S_x-\lambda I|=0.<br /> <br /> Ilm
 
Last edited:
Ilmrak said:
Hello!
My suggestion is to try to explicitly add up the two states in matrix notation...
The answer should then be obvious to you :)

Edit:
The answer you gave to the first question is right. Nevertheless it is more time consuming then it was necessary and time is precious during exams :)
You have to show that those are egenvectors with given eigenvalue, so you could simply show that

S_x |S_x ± \rangle = ± \frac{h}{2}|S_x ± \rangle,

without solving the egenvalue equation
Ilm

|S_x-\lambda I|=0. is a lot easier and faster to solve ;)

about the second question, it works in the same way:

A(|Sx+> + |Sy+>) = λ (|Sx+> + |Sy+>)

=> (A-λI)(|Sx+> + |Sy+>) = 0

A-λI = 0; Fill in λ = 1/sqrt(2) and the matrix will be (1/sqrt(2) 0; 0 1/sqrt(2) )

It's been a while since I did this, I could be wrong ofcourse.. (and it looks a bit to easy, but hey?)edit: I think I'm wrong...
 
Dreak said:
|S_x-\lambda I|=0. is a lot easier and faster to solve ;)[...]

Yes it is easy but no, it isn't faster.
And if it were a bigger matrix (or worst a differential operator) it wouldn't be so easy to solve that equation while it would still be easy to let a matrix (or a differential operator) act on a vector (or a function).
To solve an equation is (almost) always more difficult than checking one solution ^^

Ilm
 

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