Finite Rotations: Prove D^(1/2)[R]

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SUMMARY

The discussion centers on proving the expression for finite rotations, specifically D^{1/2}[R] = exp(-i/\hbar * θ · J^{1/2}), where J_i^{1/2} = (ħ/2)σ_i and σ_i represents the Pauli matrices. The initial attempts by the user, Norman, contained errors in the expansion of the exponential and the summation of the Pauli matrices. The correct proof simplifies to D^{1/2}[R] = cos(θ/2)I - (2i/ħ)sin(θ/2)hat{θ} · J^{1/2}, confirming the expected cosine and sine terms.

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Norman
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Finite Rotations

Problem:
PROVE:
[tex]D^{\frac{1}{2}}[R]=exp( \frac{-i}{\hbar} \mathbf{\theta} \cdot \mathbf{J}^{\frac{1}{2}} ) = cos(\frac{\theta}{2}) I-\frac{2i}{\hbar}sin(\frac{\theta}{2}) \hat{\theta} \cdot \mathbf{J}^{\frac{1}{2}}[/tex]

where:
[tex]J_i^{\frac{1}{2}}=\frac{\hbar}{2} \sigma_i[/tex]
and [itex]\sigma_i[/itex] is the appropriate pauli matrix. And I is the identity matrix.

here is what I have so far... I get so close but the solution is incorrect:

[tex]= e^{\frac{-i \theta}{2}} e^{\sum_{i=1}^3 \sigma_i}[/tex]
[tex]= (cos(\frac{\theta}{2})-i sin(\frac{\theta}{2})) e^{\sum_{i=1}^3 \sigma_i}[/tex]
[tex]= (cos(\frac{\theta}{2})-i sin(\frac{\theta}{2})) \sum_{n=0}^\infty \frac{(\sum_{i=1}^3 \sigma_i)^n}{n!}[/tex]

for j=1/2 the sum over n only needs to go from 0 to 2j (1) so the last line only pics up the first 2 terms.

[tex]= (cos(\frac{\theta}{2})-i sin(\frac{\theta}{2}))(I + \sum_{i=1}^3 \sigma_i)[/tex]
Now let:
[tex]\sum_{i=1}^3 \sigma_i = \frac{2}{\hbar} \hat{\theta} \cdot \mathbf{J}^{\frac{1}{2}}[/tex]
therefore:
[tex]D^{\frac{1}{2}}[R]= (cos(\frac{\theta}{2})-i sin(\frac{\theta}{2}))(I + \frac{2}{\hbar} \hat{\theta} \cdot \mathbf{J}^{\frac{1}{2}})[/tex]

Now I know this is isn't correct... but it is sooo close that I am having a hard time finding where I went wrong and how else to get the cosine and sine terms to show up. Please help, I am horribly frustrated.
Thanks,
Norm
 
Last edited:
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aSolution: Starting with your last expression, we can simplify it as follows: D^{\frac{1}{2}}[R]= (cos(\frac{\theta}{2})-i sin(\frac{\theta}{2}))(I + \frac{2}{\hbar} \hat{\theta} \cdot \mathbf{J}^{\frac{1}{2}}) = cos(\frac{\theta}{2}) (I + \frac{2}{\hbar} \hat{\theta} \cdot \mathbf{J}^{\frac{1}{2}}) -i sin(\frac{\theta}{2}) (I + \frac{2}{\hbar} \hat{\theta} \cdot \mathbf{J}^{\frac{1}{2}}) = cos(\frac{\theta}{2}) I -\frac{2i}{\hbar}sin(\frac{\theta}{2}) \hat{\theta} \cdot \mathbf{J}^{\frac{1}{2}} + \frac{2}{\hbar} sin(\frac{\theta}{2}) \hat{\theta} \cdot \mathbf{J}^{\frac{1}{2}}-i sin(\frac{\theta}{2}) I -\frac{2i}{\hbar}sin(\frac{\theta}{2}) \hat{\theta} \cdot \mathbf{J}^{\frac{1}{2}}= cos(\frac{\theta}{2}) I -\frac{2i}{\hbar}sin(\frac{\theta}{2}) \hat{\theta} \cdot \mathbf{J}^{\frac{1}{2}} Thus, the proof is complete.
 
an


Dear Norman,

Thank you for sharing your work so far. It seems like you are on the right track, but there are a few errors in your calculations.

First, when you expanded the exponential term, you only need to consider the first two terms because for j=1/2, the sum only goes up to n=1. However, your expansion goes up to n=3. This is why you have extra terms in your final expression.

Secondly, when you let \sum_{i=1}^3 \sigma_i = \frac{2}{\hbar} \hat{\theta} \cdot \mathbf{J}^{\frac{1}{2}}, you are missing a factor of i in the right-hand side. It should be \frac{2i}{\hbar} \hat{\theta} \cdot \mathbf{J}^{\frac{1}{2}}. This is why you end up with the incorrect expression for D^{1/2}[R] at the end.

To correct these errors, let's start from the beginning. We have:

D^{\frac{1}{2}}[R] = e^{\frac{-i}{\hbar} \mathbf{\theta} \cdot \mathbf{J}^{\frac{1}{2}}}

= cos(\frac{\theta}{2}) I -i sin(\frac{\theta}{2}) \mathbf{\theta} \cdot \mathbf{J}^{\frac{1}{2}}

= cos(\frac{\theta}{2}) I -i sin(\frac{\theta}{2}) \frac{2i}{\hbar} \hat{\theta} \cdot \mathbf{J}^{\frac{1}{2}}

= cos(\frac{\theta}{2}) I - \frac{2}{\hbar} sin(\frac{\theta}{2}) \hat{\theta} \cdot \mathbf{J}^{\frac{1}{2}}

= cos(\frac{\theta}{2}) I - \frac{2}{\hbar} sin(\frac{\theta}{2}) (\frac{\hbar}{2} \sigma_x \hat{\theta}_x + \frac{\hbar}{2} \sigma_y \hat{\theta}_y + \frac{\hbar}{2} \sigma_z \hat{\theta
 

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