| > Which we don’t know precisely. Entropy is about not knowing. No, it is not about not knowing. This is an instance of the intuition from Shannon’s entropy does not translate to statistical Physics. It is about the number of possible microstates, which is completely different. In Physics, entropy is a property of a bit of matter, it is not related to the observer or their knowledge. We can measure the enthalpy change of a material sample and work out its entropy without knowing a thing about its structure. > Minus infinity. Entropy in classical statistical mechanics is proportional to the logarithm of the volume in phase space. No, 0. In this case, there is a single state with p=1 and and S = - k Σ p ln(p) = 0. This is the same if you consider the phase space because then it is reduced to a single point (you need a bit of distribution theory to prove it rigorously but it is somewhat intuitive). The probability p of an microstate is always between 0 and 1, therefore p ln(p) is always negative and S is always positive. You get the same using Boltzmann’s approach, in which case Ω = 1 and S = k ln(Ω) is also 0. > (You need an appropriate extension of Shannon’s entropy to continuous distributions.) Gibbs’ entropy. > Or you may study statistical mechanics Indeed. |
>> Entropy in classical statistical mechanics is proportional to the logarithm of the volume in phase space [and diverges to minus infinity if you define precisely the position and momentum of the particles and the volume in phase sphere goes to zero]
> [It's zero also] if you consider the phase space because then it is reduced to a single point (you need a bit of distribution theory to prove it rigorously but it is somewhat intuitive).
> The probability p of an microstate is always between 0 and 1, therefore p ln(p) is always negative and S is always positive.
The points in the phase space are not "microstates" with probability between 0 and 1. It's a continuous distribution and if it collapses to a point (i.e. you somehow learned the exact positions and momentums) the density at that point is unbounded. The entropy is also unbounded and goes to minus infinity as the volume in phase space collapses to zero.
You can avoid the divergence by dividing the continuous phase space into discrete "microstates" but having a well-defined "microstate" corresponding to some finite volume in phase space is not the same as what was written above about "particles having a defined position and momentum" that is "somehow learned". The microstates do not have precisely defined positions and momentums. The phase space is not reduced to a single point in that case.
If the phase space is reduced to a single point I'd like to see your proof that S(ρ) = −k ∫ ρ(x) log ρ(x) dx = 0