A3.14
(i) The pressure and mass density , at distance from the centre of a spherically-symmetric star, obey the pressure-support equation
where , and the prime indicates differentiation with respect to . Let be the total volume of the star, and its average pressure. Use the pressure-support equation to derive the "virial theorem"
where is the total gravitational potential energy [Hint: multiply by ]. If a star is assumed to be a self-gravitating ball of a non-relativistic ideal gas then it can be shown that
where is the total kinetic energy. Use this result to show that the total energy is negative. When nuclear reactions have converted the hydrogen in a star's core to helium the core contracts until the helium is converted to heavier elements, thereby increasing the total energy of the star. Explain briefly why this converts the star into a "Red Giant". (ii) Write down the first law of thermodynamics for the change in energy of a system at temperature , pressure and chemical potential as a result of small changes in the entropy , volume and particle number . Use this to show that
The microcanonical ensemble is the set of all accessible microstates of a system at fixed . Define the canonical and grand-canonical ensembles. Why are the properties of a macroscopic system independent of the choice of thermodynamic ensemble?
The Gibbs "grand potential" can be defined as
Use the first law to find expressions for as partial derivatives of . A system with variable particle number has non-degenerate energy eigenstates labeled by , for each , with energy eigenvalues . If the system is in equilibrium at temperature and chemical potential then the probability that it will be found in a particular -particle state is given by the Gibbs probability distribution
where is Boltzmann's constant. Deduce an expression for the normalization factor as a function of and , and hence find expressions for the partial derivatives
in terms of .
Why does also depend on the volume ? Given that a change in at fixed leaves unchanged the Gibbs probability distribution, deduce that
Use your results to show that
for some constant .