Minimizing angular momentum uncertainties

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Homework Help Overview

The discussion revolves around minimizing uncertainties in angular momentum, specifically focusing on the expression for the total angular momentum uncertainties in the x, y, and z components. The subject area is quantum mechanics, particularly the properties of angular momentum operators and their eigenstates.

Discussion Character

  • Exploratory, Mathematical reasoning, Assumption checking

Approaches and Questions Raised

  • Participants explore various mathematical expressions related to angular momentum uncertainties and discuss the implications of maximizing certain quantities. There are attempts to relate the minimization of uncertainties to maximizing the expectation values of angular momentum components. Some participants question the assumptions underlying the expressions and the conditions for minimizing uncertainties.

Discussion Status

The discussion is active, with participants offering different approaches and hints. Some suggest using the method of Lagrange multipliers, while others explore the implications of specific states like |l,l⟩. There is recognition of the need to prove the global nature of the maximum found through variations.

Contextual Notes

Participants note the constraints of working within the angular momentum subspace and the normalization conditions for the states being considered. There is also mention of the need to verify the global maximum of the derived expressions.

mrbetadine
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Homework Statement
Consider a physical system of fixed angular momentum ##l##. The state of the system is in the subspace spanned by ##2l+1## eigenvectors ##|l,m\rangle## of ##L_z## (##-l\leq m\leq +l##). Find the state ##|\psi_0\rangle## of the system for which ##(\Delta L_x)^2+(\Delta L_y)^2+(\Delta L_z)^2## is minimal.
Relevant Equations
n/a
\begin{align*}
&(\Delta L_x)^2+(\Delta L_y)^2+(\Delta L_z)^2\\
={}&\langle L_x^2\rangle-\langle L_x \rangle^2+\langle L_y^2\rangle-\langle L_y \rangle^2+\langle L_z^2\rangle-\langle L_z \rangle^2\\
={}&\langle L_x^2+L_y^2+L_z^2 \rangle-(\langle L_x \rangle^2+\langle L_y \rangle^2+\langle L_z \rangle^2)\\
={}&l(l+1)\hbar^2-(\langle L_x \rangle^2+\langle L_y \rangle^2+\langle L_z \rangle^2).
\end{align*}
To minimize ##(\Delta L_x)^2+(\Delta L_y)^2+(\Delta L_z)^2## is equivalent to maximizing
$$ \langle L_x \rangle^2+\langle L_y \rangle^2+\langle L_z \rangle^2$$

How should I proceed?
I have also obtained an alternative expression
$$\langle L_x \rangle^2+\langle L_y \rangle^2+\langle L_z \rangle^2=\langle L_+\rangle\langle L_-\rangle+\langle L_z\rangle^2 $$
where
$$ L_\pm=L_x\pm i L_y$$
but it does not help much. It would be easy if we restrict ourselves to finding states of the form ##|l,m\rangle##.

*The hint I got indicates that ##|\psi_0\rangle## is the solution to the equations
\begin{align*}
(L_x+iL_y)|\psi_0\rangle&=0\\
L_z|\psi_0\rangle&=l\hbar|\psi_0\rangle.
\end{align*}
 
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By the hint
$$<L_x>=<L_y>=0$$
$$<L_z>=l\hbar$$
 
There may be a simple and elegant solution to the problem, but I can't see it currently. So I'll suggest a brute force approach.

Note that if ##~|\psi_0\rangle~## minimizes the uncertainty, then any state derived from it by a rotation is just as good.

Any normalized state in the ##l## subspace can be spanned as$$|\psi\rangle=\sum^l_{m=-l}\left(\alpha_m+i\beta_m\right)|l,m\rangle\quad,$$where ##~\{\alpha_m,\beta_m\}~## are ##~4l+2~## real coefficients.
As you concluded in post #1, minimizing the uncertainty is the same as maximizing$$f:=\langle L_+\rangle\langle L_-\rangle+\langle L_z\rangle^2 $$(which can now be expressed explicitly as a real function of the real ##~\{\alpha_m,\beta_m\}~##), subjected to the normalization constraint$$\chi:=\langle\psi|\psi\rangle-1=\sum\left(\alpha_m^2+\beta_m^2\right)-1=0\quad.$$The method of Lagrange multipliers is usually applicable in cases like this.
 
We wish to maximise ##\langle L_x \rangle^2 + \langle L_y \rangle^2 + \langle L_z \rangle^2##. Write

\begin{align*}
| \psi_0 \rangle = \sum_{m=-l}^l a_m |l,m\rangle
\end{align*}

I get

\begin{align*}
& | \langle L_+\rangle |^2 + \langle L_z\rangle^2 =
\nonumber \\
& = \hbar^2\, \left| \sum_{m=-l}^{l-1} a_{m+1}^* a_m \sqrt{l(l+1)-m(m+1)} \right|^2 + \hbar^2\, (\sum_{m=-l}^l |a_m|^2m)^2
\end{align*}

We want to maximise this subject to ##\sum_{m=-l}^l |a_m|^2 = 1##.

The value of the first sum is maximised when all terms have the same phase. Choose ##a_m = |a_m| e^{-i m \phi - i \phi_0}##, then

\begin{align*}
& | \langle L_+\rangle |^2 + \langle L_z\rangle^2 =
\nonumber \\
& = \hbar^2\, \left( \sum_{m=-l}^{l-1} x_{m+1} x_m \sqrt{l(l+1)-m(m+1)} \right)^2 + \hbar^2\, (\sum_{m=-l}^l x_m^2m)^2
\end{align*}

where ##x_m = |a_m|##. We want to maximise this subject to ##\sum_{m=-l}^l x_m^2 = 1##.

Let us maximise ##f(x_m) = \hbar \sqrt{S^2+M^2}##, where

\begin{align*}
S = \sum_{m=-l}^{l-1} x_{m+1} x_m \sqrt{l(l+1)-m(m+1)} , \quad M = \sum_{m=-l}^l x_m^2m
\end{align*}

Method of Lagrange multipliers gives the eigenvector equation

\begin{align*}
\frac{\partial}{\partial x_m} f (x_m) - \lambda \frac{\partial}{\partial x_m} (\sum_{m=-l}^l x_m^2 - 1) = 0
\end{align*}

Thus

\begin{align*}
\hbar\, \frac{S}{\sqrt{S^2+M^2}} \frac{\partial S}{\partial x_m} + \hbar\, \frac{M}{\sqrt{S^2+M^2}} \frac{\partial M}{\partial x_m} - \lambda 2 x_m = 0
\end{align*}

Define

\begin{align*}
\sin \alpha = \frac{S}{\sqrt{S^2+M^2}} , \quad \cos \alpha = \frac{M}{\sqrt{S^2+M^2}} ,
\end{align*}

then the eigenvector equation becomes

\begin{align*}
\hbar\, \sin \alpha \frac{\partial S}{\partial x_m} + \hbar\, \cos \alpha \frac{\partial M}{\partial x_m} - \lambda 2 x_m = 0
\end{align*}

Perform ##\frac{\partial S}{\partial x_m}## and ##\frac{\partial M}{\partial x_m}##.

Calculate ##\langle l,m | \, e^{-i \phi L_z/\hbar} L_{x} e^{i \phi L_z/\hbar} | \psi_0 \rangle##.

Use ##e^{-i \phi L_z/\hbar} L_{x} e^{i \phi L_z/\hbar} = \cos \phi L_{x} + \sin \phi L_{y}##. Substituting into the eigenvector equation, we obtain

\begin{align*}
\sin \alpha (\cos \phi L_{x} + \sin \phi L_{y}) \,|\psi_0 \rangle + \cos \alpha L_{z} \,|\psi_0 \rangle = \lambda |\psi_0 \rangle
\end{align*}

or

\begin{align*}
\vec{L} \cdot \vec{n} |\psi_0 \rangle = \lambda |\psi_0 \rangle
\end{align*}

where ##\vec{n} = (\sin \alpha \cos \phi , \sin \alpha \sin \phi, \cos \alpha)##. Without loss of generality, you can consider

\begin{align*}
L_z |\psi_0 \rangle = \lambda |\psi_0 \rangle
\end{align*}

and find the eigenvector and eigenvalue that maximises ##\langle L_x \rangle^2 + \langle L_y \rangle^2 + \langle L_z \rangle^2##. For eigenstates of ##L_{z}##, ##\langle l,m |L_x | l,m \rangle = \langle l,m | L_y | l,m \rangle = 0## and ##\langle l,m | L_z | l,m \rangle^2 = m^2##. Obviously the states ##| l,l \rangle## and ##| l,-l \rangle## maximises ##\langle L_x \rangle^2 + \langle L_y \rangle^2 + \langle L_z \rangle^2##.

States that also maximises ##\langle L_x \rangle^2 + \langle L_y \rangle^2 + \langle L_z \rangle^2##, are obtained from the state ##| l,l \rangle## by rotation.
 
Last edited:
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Very nice. Thanks, @julian.

Actually, it is easier to show by variation that ##~|l,l\rangle~## (or its rotations) yield a maximum for$$f:=\langle L_+\rangle\langle L_-\rangle+\langle L_z\rangle^2\quad.$$The shortcoming of this variation approach is that we still have to prove that this maximum is global.

Consider the variation$$|\psi\rangle=\left(1-\varepsilon^2\sum^{l-1}_{m=-l}\left|a_m\right|^2\right)^{1/2}|l,l\rangle+\varepsilon\sum^{l-1}_{m=-l}a_m|l,m\rangle\quad,$$where ##~\varepsilon\ll 1~##. Then
1. The lowest order correction to ##f## is proportional to ##~\varepsilon^2~##.
2. The contribution of the left term of ##f## to the ##~a_{l-1}##-dependence of the ##~\varepsilon^2~## correction, is canceled by the contribution of the right term.
3. For ##~m\le l-2~##, only the (diagonal) right term of ##f## contributes to the ##~\varepsilon^2~## correction, and these contributions are either zero (rotation) or negative.
 
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