Estimate for root-mean-square uncertainty

In summary, classical mechanics states that the lowest possible energy accessible to any system is the minimum potential energy, while quantum mechanics reveals the existence of a non-zero minimum energy due to the uncertainty principle. To estimate the root-mean-square uncertainty in position, one can look at the range of x allowed classically for a given energy. This can be done by sketching a graph of potential energy as a function of x and finding the turning points where the potential energy meets the energy line. The length of the region between these two points can then be used as an estimate for the root-mean-square uncertainty in position.
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terp.asessed
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Homework Statement


In classical mechanism, the lowest possible energy accessible to any system is the minimum potential energy, in this case 0. However, quantum mechanically, one finds that there is a zero-point energy (where ground state energy > classical minimum). Fundamentally, zero-point energy comes from the uncertainty principle, so it is possible to estimate for root-mean square uncertainty in position, by looking at the range of x allowed classically for a given energy. Remember that in the classical mechanics, the total energy is given by:

E = p2/(2mu) + V(x)

so that V(x) > E. Therefore, sketch a a graph of potential energy as a function of x. Estimate root-mean square uncertainty as a function of Energy (E), mu and w.

Homework Equations



E = p2/(2mu) + V(x)

The Attempt at a Solution


I drew a graph, V(x) vs. x, and drew a line (Energy) horizontally through the curve, for V(x) = mu*w2x2/2. There are TWO intersecting points where V(x) meets Energy lines--which I set as boundaries. However, I am stuck as how to move from here...any suggestion would be welcome...I've been thinking about using root-mean square2 = <x2> - <x>2, but the question wants ESTIMATE of root-mean-square by LOOKING at the range...
 
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  • #2
You found the turning points. Classically, the particle is confined to the region between those two points. How long is that region? That's what you use as an estimate for ##\Delta x##.
 
  • #3
Gotcha!
 

Related to Estimate for root-mean-square uncertainty

1. What is root-mean-square uncertainty?

Root-mean-square uncertainty is a measure of the average deviation of a set of values from their mean. It is used to estimate the overall uncertainty of a measurement or calculation.

2. How is root-mean-square uncertainty calculated?

The root-mean-square uncertainty is calculated by taking the square root of the sum of the squared deviations of each value from the mean, divided by the number of values in the set.

3. Why is root-mean-square uncertainty important?

Root-mean-square uncertainty is important because it provides a more accurate representation of the overall uncertainty in a measurement or calculation compared to other methods such as average deviation. It takes into account all values in the set, not just the ones that are closest to the mean.

4. Can root-mean-square uncertainty be used for any type of measurement?

Yes, root-mean-square uncertainty can be used for any type of measurement, as long as there is a set of values to calculate it from. It is commonly used in scientific experiments and engineering calculations.

5. How can root-mean-square uncertainty be reduced?

Root-mean-square uncertainty can be reduced by increasing the precision and accuracy of the measurements, and by increasing the number of values in the set. It is also important to use appropriate statistical methods to calculate the uncertainty.

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