How Probable is the Most Probable Distribution in Statistical Mechanics?

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Discussion Overview

The discussion revolves around the concept of the most probable distribution in statistical mechanics, exploring its implications, the existence of other distributions, and the conditions under which these distributions can be understood. Participants examine theoretical aspects, mathematical derivations, and the foundational laws of physics that govern these distributions.

Discussion Character

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

Main Points Raised

  • Some participants note that while the most probable distribution is derived in statistical mechanics, it does not inherently exclude the existence of other, less probable distributions.
  • Others argue that the most probable distribution may be the best representation of a system, despite uncertainties regarding the exact states of particles, suggesting that this uncertainty is a limitation of our knowledge rather than a flaw in the model.
  • One participant emphasizes that to obtain a different distribution, a different set of physical laws would be necessary, indicating a strong connection between the laws of physics and the derived distributions.
  • Another participant discusses the probability being proportional to the number of ways a distribution can be realized, highlighting a mathematical perspective on the most probable distribution.
  • A detailed example involving an ensemble of 3-level systems is presented, illustrating how the most probable distribution can be shown to dominate as the number of systems increases, using Stirling's formula and Taylor expansion.
  • Concerns are raised about the lack of thorough explanations in introductory texts regarding the relationship between the binomial distribution and the most probable distribution, suggesting a need for deeper understanding.

Areas of Agreement / Disagreement

Participants express a mix of agreement and disagreement regarding the implications of the most probable distribution and the existence of other distributions. While some acknowledge the dominance of the most probable distribution, others question the clarity and completeness of explanations provided in educational resources.

Contextual Notes

Limitations in understanding arise from the dependence on specific assumptions about the physical laws and the mathematical frameworks used. The discussion also reflects varying levels of clarity in foundational concepts, particularly regarding the binomial distribution's relevance.

Who May Find This Useful

This discussion may be useful for students and researchers in statistical mechanics, those interested in the foundations of probability distributions in physics, and individuals seeking clarification on the relationship between physical laws and statistical distributions.

Gayle
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in stat mechanics we derive most probable distribution .but this does not say any thing about existence of other less probable distributions. is there a way to find out how probable is the most probable
 
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I come to question about these things a lot and I totally agree with what you say and there is a way to find the most propable propability, even though we aren't aware of where stuff is and we don't know their state for sure, we don't know that no matter what they wouldn't (and shouldn't) smash a bunch of laws of physics and the distribution that applies this MIGHT bd the best propability distribution, but for the best not so sure because we cannot know pricesly the state and properly describe the microstates of each little particle (example) this is an artefact of our ignorance !
 
The distribution is derived from the laws of physics. To get a different distribution you need to get a different set of physics laws.
 
Gayle said:
in stat mechanics we derive most probable distribution .but this does not say any thing about existence of other less probable distributions. is there a way to find out how probable is the most probable
It is a probability question. The probability is proportional to number of ways distribution can be realized.
 
Most introductory SM books state without much back-up that the most probable distribution of energy states in a large ensemble of systems is so overwhelmingly the most probable that we can forget about the others. More precisely, they say that for a very large number of systems the logarithm of the number of ways of achieving the most probable distribution is the same as the logarithm of the sum of the numbers of ways of achieving every distribution!

Usually they refer to the binomial distribution for back-up, without properly explaining why the binomial distribution is related to the matter in hand.

I've found the following elementary example useful for clarifying what's going on…

Take an ensemble of N 3-level systems. Let the levels be non-degenerate with energies 0, E, 2E. Let the total ensemble energy be \frac{4}{7}NE. Suppose n1 systems are on the lowest level, n2 systems are on the middle level, n3 systems are on the top level. It's easy to express n1 and n2 in terms of n3 (and the constant, N). So there's only one free variable, n3.
For this simple system it's possible to show by quite elementary means (using Stirling's formula and second order Taylor expansion) that, as N approaches infinity, the most probable distribution is the only one that carries any weight.

There's nothing special about the choice of \frac{4}{7}NE for the total ensemble energy; it just makes the arithmetic slightly neater then many other choices. For example, in the most probable distribution n2 turns out be half n1 and twice n3.
 
Last edited:
Gayle. It would be nice to know if any of the responses to your question were of any use. If any were impossible to understand, or didn't go far enough towards answering your question, you can ask for clarification.
 

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