Why are probabilities distribution of thermodynamic variables tend to Gaussian?

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SUMMARY

The probability distribution of thermodynamic variables tends to a Gaussian form due to the Taylor series expansion of the availability function A(x) around equilibrium conditions. The distribution is expressed as P = N e^{-A(x)/KT}, where A(x) can be represented by Helmholtz free energy F or Gibbs free energy G. The mean of the Gaussian distribution is x_{0}, and the standard deviation is given by √(KT / (∂²A/∂x²)_{x=x_{0}}). The truncation of the series is justified when the deviation |x - x_{0}| is small, particularly in systems with a large number of particles N.

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  • Knowledge of Helmholtz and Gibbs free energies
  • Basic principles of statistical mechanics
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dd331
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The probability distribution for some thermodynamic variable x is given by

P = N e^{-A(x)/KT}

where A(x) is the availability, which can be replaced by Hemlholtz free energy F, Gibb's free energy G, etc depending on the conditions imposed. N is just some normalization constant. A(x) can be expanded in a taylor series about the equilibrium conditions,

A(x) = A(x_{0}) + (x - x_{0})(\frac {\partial A} {\partial x})_{x = x_{0}} + \frac{1} {2} (x - x_{0})^{2} (\frac {\partial^2 A} {\partial x^2})_{x = x_{0}} + ...

The second term is 0 since dA/dx = 0 at equilibrium. If we truncate all the other terms, clearly we see that P will be a Gaussian distribution with mean of x_{0} and standard deviation of

\sqrt {\frac {K T} {(\frac {\partial^2 A} {\partial x^2})_{x = x_{0}}}}

What is the justification for truncating this series? This is justified if (x - x0) is small. But why will it be small for big N?
 
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I am not familiar with the details of the physics. However such truncation would be based on the assumption |x-x0| is small.
 

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