Is the Canonical Ensemble Rule Derived Ad Hoc in Statistical Mechanics?

In summary, the rule of maximum entropy comes from the assumption that all microstates are equally likely.
  • #1
intervoxel
195
1
In Statistical Mechanics, the key step in the derivation of the Canonical Ensemble is that the probability of S being in the m-th state, P_m , is proportional to the corresponding number of microstates available to the reservoir when S is in the m-th state. That is

[itex]P_m=c\Omega(E_0-E_m)[/itex],

where E_0 is the total energy.

Where does this rule come from? It seems to be inserted ad hoc in my textbook, and even in Wikipedia.
 
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  • #2
One justification for this comes from the idea of maximum entropy. Given a system about which you have limited knowledge, say only the total energy E, you can ask what probabilities you should assign to various microstates. The distribution [itex] p(n) [/itex] (n labels microstates at energy E) which maximizes the entropy [itex] S = - \sum_n p(n) \log{p(n)} [/itex] is the flat distribution [itex] p = 1/N(E) [/itex] which gives an entropy of [itex] \log{N(E)} [/itex]. N(E) is the total number of states at energy E.

A similar calculations gives the Boltzmann distribution with temperature T interpreted as a Lagrange multiplier that enforces the constraint that the average energy be E.
 
  • #3
To me the rule of maximum entropy arises from the assumption that all microstates are equally likely and not the other way around.

The idea is simply that ALL microstates are equally likely. This is a key assumption of statistical mechanics, which sounds wrong when you consider QM etc., but actually turns out to give surprisingly good answers in the correct thermodynamic limit. Thus, the probability of S in the m-th state is then the total number of microstates that correspond to S in the m-th state divided by the total number of microstates there are total (which is just a constant, if we keep the energy of the whole system constant).

The number of microstates with S in the m-th state is simply equal to what you stated above as "the corresponding number of microstates available to the reservoir when S is in the m-th state". This is obvious because there is exactly 1 state that the sub-system S is in.
 
  • #4
Think I've got it.

When the system is in equilibrium, T_R=T_S, S is maximized and all microstates are equally probable. Then, for instance:

Total number of microstates=100
E1'+E1=E0
E2'+E2=E0
E3'+E3=E0

Code:
    R   |    S
------+-------
E1' 18 |
E2' 27 |
E3' 45 |
         |
         .
         .
         |
         | E3 5
         | E2 3
         | E1 2
--------------
     90 |     10
finally, c=1/90

Is it correct?
 
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FAQ: Is the Canonical Ensemble Rule Derived Ad Hoc in Statistical Mechanics?

What is the Canonical Ensemble?

The Canonical Ensemble is a statistical mechanical ensemble used to describe a system in thermal equilibrium with a heat bath at a fixed temperature.

What is the importance of the Canonical Ensemble?

The Canonical Ensemble helps us understand the behavior of a system at a specific temperature, which is crucial in many physical and chemical processes. It allows us to calculate the average values of thermodynamic quantities and predict the probability of a system being in a certain state.

How is the Canonical Ensemble derived?

The Canonical Ensemble is derived from the fundamental assumptions of statistical mechanics, such as the postulate of equal a priori probabilities and the ergodic hypothesis. It also uses the concept of microstates and macrostates to describe the behavior of a system.

What is the difference between the Canonical Ensemble and other ensembles?

The Canonical Ensemble differs from other ensembles, such as the Microcanonical and Grand Canonical Ensembles, in the way it considers the system's energy to be fixed and the heat bath to be at a constant temperature. This allows for the calculation of thermodynamic quantities at a specific temperature.

How is the Canonical Ensemble related to thermodynamics?

The Canonical Ensemble is closely related to thermodynamics as it provides a statistical interpretation of thermodynamic quantities, such as energy, entropy, and temperature. It also allows for the calculation of thermodynamic properties of a system, such as heat capacity and free energy, which are crucial in understanding the behavior of a system at a specific temperature.

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