I don't understand partition function

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Discussion Overview

The discussion revolves around the concept of the partition function in statistical mechanics, particularly its role in connecting the Boltzmann factor to the probabilities of different states in a system. Participants seek qualitative explanations and interpretations of the partition function, exploring its implications in the context of thermal equilibrium and probability theory.

Discussion Character

  • Exploratory
  • Technical explanation
  • Conceptual clarification
  • Debate/contested

Main Points Raised

  • One participant asks for a qualitative explanation of the partition function, expressing difficulty in understanding its physical interpretation despite familiarity with its mathematical use.
  • Another participant explains that the partition function acts as a normalization constant for probabilities, ensuring they sum to one, and relates it to the Boltzmann factor.
  • A different participant reiterates that the partition function is the normalization constant, providing a mathematical expression for probabilities in the canonical ensemble.
  • One participant shares notes and an image related to the derivation of the partition function, questioning whether it can be equal to one under certain conditions.
  • Another participant challenges the assumption that certain terms in the derivation are equal, emphasizing the need for careful consideration of mathematical implications.
  • Further discussion includes a clarification that the ratio of probabilities does not imply direct equality of probabilities, highlighting nuances in the mathematical relationships involved.
  • One participant shares a PDF resource on Boltzmann statistics, noting that while the partition function is convenient, it is not strictly necessary for deriving probabilities.
  • A participant outlines a detailed derivation of probabilities based on the number of states in a reservoir, connecting it to the partition function through entropy and temperature definitions.

Areas of Agreement / Disagreement

Participants express varying interpretations of the partition function and its implications, with some agreeing on its role as a normalization constant while others contest specific mathematical relationships. The discussion remains unresolved regarding the equality of certain terms and the implications of the partition function in different contexts.

Contextual Notes

Some participants highlight the importance of understanding the assumptions behind the mathematical derivations and the definitions of terms like entropy and temperature, indicating that the discussion may depend on these underlying concepts.

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is the Boltzmann factor the probability of a particular state of a system?

can someone explain the partition function to me (qualitatively please!), we've been using it in class and i don't get it. we derived what the partition function was for a general system. usually when learning physics and i don't understand something it's because I'm looking at the math and i don't understand the physical interpretation of something, what something "is" physically. but in this case, we're rather studying physical phenomena using statistics, and so i have to be able to look at things and understand what's going on statistically (statistics is a class which i haven't taken yet). So, statistically, i don't understand what the partition function "is". What does it tell me?
all i know is what i can do with it, kind of... i can convert between the Boltzmann factor of a particular state and the probability of that state, and that's all i know. could someone give me a better feel for what the partition function is?

i've looked on wikipedia and google searched it but i didn't really get much..
 
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The partition function in particular, and the Boltzmann statistics in general come straight out of probability theory; once I figured out just how this worked, it made a lot more sense for me.

The situation is that you have two objects, a "system" and a "reservoir", which together form a larger system, which we'll call the kaboodle.

The system and reservoir each can exchange energy with each other, and do so back and forth, the net effect one way or the other being zero when the system and reservoir are in thermal equailibrium (when they have the same temperature). The kaboodle we treat as a closed system, so that energy can flow in between each part of the kaboodle, but no energy can flow in or out of the kaboodle.

Probability comes into play when we say that the energy of the system can have different values so long as the total energy of the kaboodle remains constant. The question we ask then, is:
" What is the probability that the system has energy U, given that the system plus reservoir has total energy E?"
Working it out, you can show that the probability that the system has total energy U is equal to its Boltzmann factor divided by the partition function.

The partition function conceptually is just a normalization constant so all the probabilities add up to one.
 
Yep. The partition function is the normalization constant for the probabilities. (or that's how I like to think of it, anyway). For the canonical ensemble, we know the probability of observing the system having energy ##E_i## must be proportional to
\exp(-\beta E_i)
So, if we say ##1/Z## is the constant of proportionality, then we have
P_i = 1/Z \exp(-\beta E_i)
And when we sum over all states ##i##, we get:
\sum_i P_i = 1/Z \sum_i \exp(-\beta E_i)
and we know that (since probabilities must add to 1)
\sum_i P_i = 1
so therefore:
Z = \sum_i \exp(-\beta E_i)
 
Last edited:
The partition function conceptually is just a normalization constant so all the probabilities add up to one.


----------------------------

http://i.imgur.com/H9RF6s5.jpg

here is an image of my notes about the derivation of the partition function. all the terms circled in yellow are terms that are all equal to each other (but not all terms that are equal to each other have been circled)

the bottom most yellow circle: above that is P(S2) which i forgot to circle, but those two terms are equal to one another, and are the terms on the right hand side; ie on the RHS the numerator and demoninator are both equal to one another, so could i say that Z is ultimately equal to 1?
 
Not all the stuff inside the yellow circles is equal. ##S_R(S_2) - S_R(S_1) = -\frac{1}{T}((U_{sys}(S_2)-U_{sys}(S_1))## does not imply that ##S_R(S_2)=-\frac{1}{T} U_{sys}(S_2)##
 
how not? for the case where we ignore any volumetric changes due to energy exchange, and if there are no particles being exchanged, how is what you wrote not true? if you'd like you could replace the equal sign to a ≈, but aside from this, in this context, why does it not imply that

the SR(S2) corresponds to the -(1/T)Usys(S2) and the the SR(S1) corresponds to the -(1/T)Usys(S1) i thought.
 
nope. If you think about it, mathematically, you can add whatever you want to both ##S_R(S_2)## and ##S_R(S_1)## and the left hand side of the equation doesn't change. So mathematically, that equation does not imply that ##S_R(S_2)=-\frac{1}{T} U_{sys}(S_2)##.
 
Also, it is true that
\frac{P(S_2)}{P(S_1)} = \exp((S_R(S_2)-S_R(S_1))/k)
But this does not mean that
P(S_2) = \exp(S_R(S_2)/k)
for similar reasons.
 
I wrote a series of notes on Boltzmann statistics, but the conversion to pdf shredded my handwriting for some reason.

http://i.imgur.com/SnpZVsF.jpg?2

In it, I show how to get the Boltzmann factors, and how they relate to the total probabilities, along with a lot of other general knowledge. If you find it's useful, then that's great.
You don't actually have to use the partition function to get the probabilities to come out right. It's just a very convenient way of doing things.

Also, it covers how to deal with multiple states of the same energy (degenerate states)
 
  • #10
i found this pdf very helpful
 

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  • #11
This probably repeats what everybody else says, but it's short.

Assume that you have a small system that can exist in a number of discrete states of energy \mathcal{E}_j. This system is in thermal contact with a much, much huger system, say, a reservoir of water, which has vastly more possible states.

Let W(E) be the number of states of the reservoir with energy E. Now, suppose we place the small system into the reservoir, and allow it to exchange energy with the reservoir. The basic assumption is that all states (of the composite small system + reservoir) having the same total energy E are equally likely. So the probability of the small system being in state j is just the fraction of all states of small system + reservoir such that the reservoir has energy E - \mathcal{E}_j. This is given by:

P_j = \dfrac{W(E - \mathcal{E}_j)}{\sum_{i} W(E - \mathcal{E}_{i})}

The final steps are to define the entropy of the reservoir, S(E), to be

S(E) = k ln(W(E))

or W(E) = e^\frac{S(E)}{k} where k is Boltzmann's constant.

and we define temperature via:

\frac{dS}{dE} = \frac{1}{T}

With these definitions,

W(E - \mathcal{E}_{i}) = e^\frac{S(E - \mathcal{E}_i)}{k} \approx e^\frac{S(E) - \mathcal{E}_i \frac{dS}{dE}}{k} = e^\frac{S(E) T - \mathcal{E}_i }{kT}

where we used a Taylor series to approximate S

So the probability becomes:

P_j = \dfrac{e^\frac{S(E) T - \mathcal{E}_j }{kT}}{\sum_i e^\frac{S(E) T - \mathcal{E}_i }{kT}}

The factor of e^\frac{S(E) T}{kT} cancels from numerator and denominator, leaving:

P_j = \dfrac{e^\frac{ - \mathcal{E}_j }{kT}}{\sum_i e^\frac{ - \mathcal{E}_i }{kT}}

Okay, so it wasn't that short. It seemed simpler when I started.
 

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