Prove the 3 definitions of entropy are equivalent (stat. mechanics)

In summary, the conversation discusses the equivalence of three expressions for entropy, S(E,V) = kln(\Gamma(E)), S(E,V) = kln(\omega(E)), and S(E,V) = kln(\Sigma(E)), up to an additive constant. The equations \Gamma(E) = \int_{E<H<E+\Delta}^{'}dpdq, \Gamma(E)=\omega\Delta, and \Sigma(E) = \int_{H<E}^{'}dpdq are used to define these expressions, with \omega = \frac{\partial \Sigma}{\partial E}. The conversation also mentions the system's Hamiltonian, H, and an arbitrary energy, E, and integration over all p and q variables
  • #1
Tosh5457
134
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Homework Statement



[tex]
S(E,V) = kln(\Gamma(E) )\\
S(E,V) = kln(\omega(E) )\\
S(E,V) = kln(\Sigma(E) )\\
[/tex]

S entropy, k Boltzmann's constant. Prove these 3 are equivalent up to an additive constant.

Homework Equations



[tex]
\Gamma(E) = \int_{E<H<E+\Delta}^{'}dpdq\\
\Gamma(E)=\omega\Delta \\
\Delta << E\\

\Sigma(E) = \int_{H<E}^{'}dpdq\\
\omega = \frac{\partial \Sigma}{\partial E}\\
[/tex]

H is the system's Hamiltonian and E is an arbitrary energy. These are integrations over all the p and q's, I wrote them like that to abbreviate.

The Attempt at a Solution



Using the 1st definition I can get to the 2nd one, but I can't reach at sigma's definition.
[tex]

kln(\Gamma(E)) = kln(\omega\Delta) = kln(\omega) + kln(\Delta)\\
ln(\Delta) << ln(\omega) => S = kln(\omega)\\
[/tex]
 
Last edited:
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  • #2
I'm sorry you are not generating any responses at the moment. Is there any additional information you can share with us? Any new findings?
 
  • #3
I would say ##\Gamma (E)=\Sigma (E+\Delta) -\Sigma (E)=\Delta \frac{\partial \Sigma}{\partial E}+...##
 

Related to Prove the 3 definitions of entropy are equivalent (stat. mechanics)

1. What is entropy?

Entropy is a measure of the disorder or randomness in a system. It is a fundamental concept in thermodynamics and statistical mechanics.

2. What are the 3 definitions of entropy?

The three definitions of entropy are the thermodynamic definition, the statistical definition, and the information-theoretic definition. These definitions all describe entropy in different ways but are equivalent to each other.

3. How is entropy related to statistical mechanics?

In statistical mechanics, entropy is defined as the logarithm of the number of microstates available to a system at a given energy. It is a measure of the uncertainty or randomness in the distribution of particles within a system.

4. How do the 3 definitions of entropy relate to each other?

The thermodynamic definition of entropy is based on the change in heat and temperature in a system, while the statistical definition is based on the distribution of particles within a system. The information-theoretic definition is based on the amount of information needed to describe a system. These definitions are equivalent because they all describe the same underlying concept of disorder or randomness.

5. Why is it important to prove the equivalence of the 3 definitions of entropy?

Proving the equivalence of the 3 definitions of entropy provides a deeper understanding of the concept and its applications. It also allows for the use of different approaches to calculate entropy in different systems, making it a more versatile and useful tool in scientific research and applications.

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