S_z matrix in s_y basis: three methods and three results

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Homework Help Overview

The discussion revolves around the representation of the \( s_z \) matrix in the \( s_y \) basis using different methods, including unitary transformations and rotations. Participants express confusion over obtaining different results from these methods, specifically whether \( s_z \) in the \( s_y \) basis corresponds to \( s_y \) or \( s_x \).

Discussion Character

  • Mixed

Approaches and Questions Raised

  • Participants explore various methods for transforming the \( s_z \) matrix into the \( s_y \) basis, questioning the correctness of angles used in rotations and the implications of cyclic permutations. There is a focus on the differences in results obtained from unitary transformations versus rotation methods.

Discussion Status

The discussion is ongoing with participants offering different interpretations of the transformation methods. Some suggest that the choice of rotation angle may affect the outcome, while others highlight the importance of cyclic permutations in determining the correct representation. There is no explicit consensus on which result is correct, as multiple interpretations are being explored.

Contextual Notes

Participants reference specific problems and solutions from textbooks and external resources, indicating that there may be differing conventions or interpretations regarding the transformations involved. The discussion also touches on the freedom in choosing eigenstates in the \( s_y \) basis, which may contribute to the confusion over results.

the_doors
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Hello guys. when i write s_z matrix in s_y basis with unitary transformation i get s_y but in second method when i rotate s_z about x-axis ( - pi/2 ) to get s_z in s_y basis , i get -s_y ! and if we consider cyclic permutation, s_z becomes s_x. i am totally confused! three methods and three results !

thank you .
 
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Hi.
In your second method, use the right hand rule to see if you need a rotation of ( - pi/2 ) or ( pi/2 )?
In the third method, see that for the 3 coordinates you have 3 cyclic permutations: one of them is the one you mention (x–>y, y–>z, z–>x), another one gives you the identity, then what's the third one?
 
It's the coordinates system you're rotating here (passive transformation), so the angle is +pi/2.
For third method: yes, this is the other permutation: (x–>z, y–>x, z–>y).
 
but in this sulotion set i attached , he consider -pi/2 . and in the third method , we get s_x , so finally which is correct ? s_x or s_y ?


Thank you
 

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Well it looks to me that he's getting –s_y which is not what you want to get, so i'll keep saying that since we're rotating a coordinates system pi/2 makes sense to me..
cyclic permutation (x–>z, y–>x, z–>y) gets you from s_z to s_y, and (x–>y, y–>z, z–>x) from s_y to s_z; pick the one you need!
 
the problem is exactly here, with permutation : s_z in s_y basis : s_x but with unitary transformation or rotating method s_z in s_y basis : s_y . i mean why we have 2 results ? at last which of the results are correct ?
 
Put it this way: if you have a vector in real space pointing along the +y-direction with a set of equations involving positions, and want to call this direction your new z+ while keeping all equations you may have intact, it's fine as long as you perform the cyclic permutation (x–>y, y–>z, z–>x) in your coordinate system and in the equations. The same is true with spin matrices in the sense that it leaves the commutation relations unchanged... the other cyclic permutation would make you relabel the y-direction as x and apart from the identity transformation that's all the cyclic permutations you have.
 
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the_doors said:
Hello guys. when i write s_z matrix in s_y basis with unitary transformation i get s_y

There is some freedom in choosing the ##s_y## eigenstates. For example, in the z-basis, the ##s_y## eigenstates are often taken to be $$\frac{1}{\sqrt{2}} \binom {1} {i},\;\;\frac{1}{\sqrt{2}} \binom {1} {-i}$$

Or, you can choose $$\frac{1}{\sqrt{2}} \binom {1} {i},\;\;\frac{1}{\sqrt{2}} \binom {i} {1}$$

See what you get if you take the first set of y-eigenstates as a basis for expressing the ##s_z## matrix.

Repeat for the second set of y-eigenstates.
 

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