A mind is a terrible thing to waste they say. With that in mind, I wander around a few "sciency" blogs, websites and fora in an attempt to knock some of the cobwebs out of the corners of my mind. Sometimes visits lead me to believe that there may not be any intelligent life left on Earth. One recent example is a wild, completely irrelevant discussion on a suggestion in a new textbook. The suggestion was that Bose-Einstein Statistics might be useful when attempting to describe cloud formation at low temperatures. Clouds tend to be a beautiful PITA at times since they appear to have their own personal drummer. On Earth most clouds are made of water in its various stages, solid, liquid and gas with the solid and liquid being the parts we generally see. When water vapor becomes liquid, it is considered to condense. When water vapor becomes ice it is considered to nucleate. When ice directly changes to water vapor it is considered to sublimate. When water is well below its freezing point it is consider super cooled and when water vapor is present in greater amount that it should be based on saturation pressure it is considered super saturated. Predicting the path that water vapor will take in a cloud based on just temperature and/or energy gets to be a bit difficult. If you can't predict what path it will follow, you may be able to determine a probability that it will follow a particular path which will give you some idea how likely you can pick the right path. If the way you try to predict tends to be useless or close to useless, you might want to consider a different approach.

To better understand why you might want to try a different approach, it would be nice to understand a few approaches. So I went looking for an fairly simple description of applicable statistics and found this:

where I used the Boltzmann distribution. However, the probabilities that the number of particles in the given one-particle state is equal to

These conditions are obviously solved by

which implies that the expectation value of

The calculation for bosons is analogous except that the Pauli exclusion principle doesn't restrict

and

These conditions are solved by

Note that the ratio of the adjacent

because the number of particles, an integer, must be weighted by the probability of each such possibility. The denominator is still inherited from the denominator of

Don't forget that

This result's denominator has a second power. One of the copies gets cancelled with the denominator before and the result is therefore

which is the Bose-Einstein distribution.

I made the whole explanation a link to the comment of Luboš Motl who could be described as a quantum physics junkies go to dealer.

Given the tools Lubos describe, how could one possibly use Bose-Einstein Statistics for water vapor?

One simple example would be to consider the limits of T as they relate to water. At -43 C degrees, water vapor is super cooled to the point that it will change to ice, but there is a fairly large time window of hours. So if you replace T with (T-T(-43C)) you would be indicating that the probability that water will be in its solid state is 100% at -43C degrees. However, since that isn't really true because of the time window, you could pick a lower temperature that makes the probability more likely for a smaller time window. Say minus 50 C for example. That could be useful even though it is not completely true.

The suggestion boils down to if the "accepted" methods don't provide enough accuracy consider options like Bose-Einstein, which created a tempest in a teacup. Personally, I found the suggestion interesting and the controversy inspired me to review tidbits lurking behind some of the cobwebs. i

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