Teaching Quantum Mechanics

THE HEISENBERG PRINCIPLE

'Close Encounters' Approach


Lorenzo Galante

Heisenberg main page

H2 - DISTRIBUTIONS AND DISPERSIONS

So far we have worked with pure tones (Section H1), two tones sounds (H2) and vowels spoken by a person (H3). In all this cases, sounds were composed by a complex of frequencies. Each one having a different distribution in f. The shape of the distribution tells us what frequencies are composing our sound and their importance (the intensity I(f) ) in forming the complex.


As already mentioned (H1a) an important feature is the dispersion of a distribution. Without moving into mathematical details we can say that the dispersion of a distribution is the length of the frequency range in which the distribution is significantly high.

Dispersion may be represented by the symbol Δf.

The dispersion gives and idea of the spread of the distribution along the variable represented along the x-axis.

Any physical system is dispersed in many different domains. A sound may be dispersed in time, t, or in frequency, f, as we have deeply discussed. A body may be dispersed in space, x. For example, think to a string fixed at both ends. It is made of many parts distributed along a spatial dimension. If the string vibrates, its parts have different speeds: zero at the ends, maximum at the center (if the first vibrational mode is active). Therefore the system is distributed even in the speed domain, v. A gas at temperature T is distributed in the speeds of the molecules (Maxwell distribution) and, for example, this is extremely important for the fusion processes in our Sun.




Rough estimation of the Dispersion

In case of peaked shapes of the distribution, a rough calculation of the dispersion may be achieved evaluating the distance along the x-axis (in Hz in our case) between the peak and a point x dB below (see figure on the left).

If we want to compare dispersions of different distributions we may use this method, always keeping in mind that the amount of decibels (x dB) has to be the same for every distribution we want to compare.