Statistical definition of temperature

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Discussion Overview

The discussion revolves around the statistical definition of temperature, particularly focusing on the relationship between the number of microstates (Ω) and energy (E). Participants explore the calculus involved in deriving the expression d(lnΩ)/dE = 1/kbT, and the implications of this relationship in statistical mechanics.

Discussion Character

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

Main Points Raised

  • One participant seeks clarification on the derivation of the expression d(lnΩ)/dE = 1/kbT, questioning the calculus involved and its implications for maximizing microstates.
  • Another participant notes that the quantity kblnΩ is known as Entropy, suggesting a connection to the broader context of the discussion.
  • A participant explains that energy tends to move from higher to lower temperatures, which increases the total number of microstates, linking this behavior to the statistical mechanics definition of temperature.
  • Concerns are raised about taking derivatives of discrete quantities, emphasizing that the statistical mechanics definition is valid primarily for large systems where states can be approximated smoothly.
  • A later reply discusses the concept of density of states, indicating that a rigorous mathematical definition requires considering a small region of energy that overlaps many states.

Areas of Agreement / Disagreement

Participants express varying levels of understanding regarding the calculus involved in the statistical definition of temperature. There is no consensus on the derivation or the mathematical rigor required, indicating ongoing debate and exploration of the topic.

Contextual Notes

Participants highlight limitations in understanding the relationship between microstates and energy, particularly regarding the assumptions necessary for applying statistical mechanics to large systems. The discussion reflects uncertainty about the mathematical treatment of discrete quantities in this context.

WrongMan
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hello everyone. i need help understanding this statement:
d(lnΩ)/dE = 1/kbT
so Ω are the posible microstates for energy E, and the derivative of Ω w.r.t E is 1/kbT.
why?
what i understand so far is: looking at the division of energy of two "connected" systems the energy will divide itself in a way that maximizes the total possible microstates, and since the total number of microstates is: Ω1(E1)*Ω2(E2)
(where "Ω1(E1)" means posible microstates at E1 for system 1) this would mean:
Et=E1+E2 and
Ωt(Et)=Ω1(E1)*Ω2(E2)
and since i want to maximize this i say:
t/dEt=0
so now what? i feel that I am close but i can't get there
 
Last edited:
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Hi, I want remember you that ##k_{b}\ln{\Omega}## is a well know quantity called Entropy...

Ssnow
 
Energy wants to move from a higher temperature to a lower temperature, until the temperatures are equal.
The statistical mechanics definition of temperature tells you that by moving energy from a higher temperature to a lower temperature, the total number of microstates is increased.
 
i understand the theory part of it, i just don't understand the calculus part of it, where does the 1/kbT comes from? what is meant by "d(lnΩ)/dE" is the rate at which lnΩ chages w.r.t E right? but i was never given an expression that relates mictostates with energy, i just sort of "count" ( or calculate using combinatory "formulas").
 
Ok, how do you take the derivative of a discrete quantity? Well, you can't. The statistical mechanics definition of temperature is really only valid for large systems where you can smooth over the quantum steps. You need to imagine a system with a whole bunch of closely spaced states. Then you imagine a small region of energy which overlaps many states. You have to calculate a density of states, which is a function that tells you how many states are in a small region of energy around any particular energy. Your small region has to be much bigger than the distance between adjacent states, or it fails. I'm not sure if there's a more mathematically rigorous way to define it.
 
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