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If Heisenberg uncertainty principle involves the standard deviation of quantities then why do we use it in a different way as here?

Physics Asked on December 24, 2020

Heisenberg uncertainty principle is mathematically given as

$$sigma_x cdot sigma_p ge {{hbar} over {2}}$$

The two terms on the left being the standard deviations of position and momentum.

But on many places the HUP is as

$$Delta x Delta pgeq frac{h}{4π}$$ and used as in this example( as in beisers modern Physics):

If a particle can be anywhere in a sphere of radius $Delta R$ and can have momentum in a range $Delta p$ then we have have
$Delta R$. $Delta p geq frac{hbar}{2}$

How does this example follow from the definition given on the top?

3 Answers

The first formula is more precise. For a gaussian wave package the standard deviations in x and p are related by this expression.

A wave function that is uniform over a spherical volume and zero outside it has high momentum components due to its sharp edges. This causes he product of x and p standard deviations to be larger than $hbar/2 = h/4pi$.

Answered by my2cts on December 24, 2020

The idea is that if a particle can be anywhere in the sphere of radius $Delta R$, then $sigma_xsimDelta R$ (you can try to calculate the standard deviation of the position of a particle that can be anywhere on a sphere of radius $Delta R$ and it will be proportional to $Delta R$). It is a bit like the Fermi Problem (https://en.wikipedia.org/wiki/Fermi_problem), in which you are only interested in estimating the order-of-magnitude of something.

This kind of "estimates" are not rigorous but common. However, this is usually enough. Notice that, independently of the rigor of the inequality, the physical interpretation will remain the same: if the radius of this sphere to which the particle is confined decreases, the uncertainty of the momentum increases (i.e. it is very hard to confine particles to very small spaces).

Answered by Jonhy on December 24, 2020

This answer is a comment really.

The standard deviation has a strict statistical meaning

The root-mean-square deviation of x from its average is called the standard deviation. For a set of discrete measurements, the standard deviation takes the form

estdevdiscr

for continuous:

stdevcont ....

Determining the average or mean in the above expression involves the distribution function for the variable.

stdev

The distribution function is also statistically defined, for example:

distrfun , Poisson

That is why the $σ$ symbol is usually confined to standard deviation.

The Heisenberg uncertainty(HUP) is usually given as

HUP

with the $Δ$ symbol instead of the $σ$ to keep clear that the distribution function is not one of the statistical ones, but given by the quantum mechanical solution of the equations and boundary conditions of the problem, $Ψ^*Ψ$, a probability distribution, but not a statistical one.

Answered by anna v on December 24, 2020

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