How to prove the Gibbs-Bogoliubov inequality

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TlnQ1 ≥ -kTlnQ2 + <H1-H2>.3. Simplifying, we get: lnQ1/Q2 ≥ β<H1-H2>.4. Finally, using the definition of β, we get: -β<H1-H2> = -<H1-H2>/kT which proves the second part of the Gibbs-Bogoliubov inequality.In summary, the Gibbs-Bogoliubov inequality can be proven in two stages. First, using the ritz variational principle, we can show that the partition function for a canonical ensemble is always greater than or equal to the trial partition function. Then, using this result, we can prove that the
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evantop
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Hi

I need to prove the Gibbs-Bogoliubov inequality in two stages.
First I need to prove that if I have a canonical partition function so:

Q(N,V,T)>=Sigma(exp(-beta*<fi|H|fi>) by using the ritz variational principle
fi = set of orthonormal functions in the hilbert space.
Then... by using this inequality I need to prove that:
A1=< A2+<H1-H2> which is the Gibbs-Bogoliubov inequality. (A is the free helmholtz energy, and H is hamiltonian)

Anyone can help me or give me a link to a paper with the solution?

Thanks

Evan
 
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Hello Evan,

The Gibbs-Bogoliubov inequality is a fundamental result in statistical mechanics, which relates the free energy and the expectation value of the Hamiltonian in a canonical ensemble. I will provide an outline of the proof for you to follow:

Part 1: Proving the inequality using the ritz variational principle

1. Begin by writing the partition function for a canonical ensemble as: Q(N,V,T) = Tr(exp(-βH)) where β = 1/kT, k is the Boltzmann constant, and H is the Hamiltonian.

2. Using the ritz variational principle, we can write the partition function as a minimum of the trial partition function, Q_T(N,V,T) = Tr(exp(-βH_T)), over a set of orthonormal functions {ϕ_i} in the Hilbert space.

3. By definition, the trial partition function is always greater than or equal to the true partition function, i.e. Q_T(N,V,T) ≥ Q(N,V,T). This is because the trial partition function is a minimum of the true partition function over a restricted set of functions.

4. Now, we can expand the trial partition function using the orthonormality of the trial functions: Q_T(N,V,T) = Σ_i exp(-βE_i) <ϕ_i|ϕ_i> where E_i is the energy corresponding to the state ϕ_i.

5. Using the inequality from step 3, we can write: Σ_i exp(-βE_i) <ϕ_i|ϕ_i> ≥ Σ_i exp(-βE_i).

6. Since the true partition function is the sum of all possible energy states, we can write: Q(N,V,T) = Σ_i exp(-βE_i).

7. Combining steps 5 and 6, we get: Q_T(N,V,T) ≥ Q(N,V,T) which proves the first part of the Gibbs-Bogoliubov inequality.

Part 2: Proving A1 = A2 + <H1-H2> using the Gibbs-Bogoliubov inequality

1. The free energy can be written as: A = -kTlnQ. Using this, we can write the Gibbs-Bogoliubov inequality as: A1 ≥ A2 + <H1-H2>.

2. Substituting for the partition function, we get
 

1. What is the Gibbs-Bogoliubov inequality?

The Gibbs-Bogoliubov inequality is a mathematical expression that relates the partition function of a system to the free energy, entropy, and internal energy. It is used in statistical mechanics to determine the stability and equilibrium of a system.

2. How is the Gibbs-Bogoliubov inequality derived?

The inequality is derived from the Gibbs-Bogoliubov-Kubo formula, which relates the partition function to the correlation functions of a system. The inequality is then obtained by using the Cauchy-Schwarz inequality on these correlation functions.

3. What is the significance of the Gibbs-Bogoliubov inequality?

The inequality provides a lower bound on the free energy of a system, which is important in determining the stability and equilibrium of a system. It also allows for the calculation of thermodynamic quantities such as entropy and internal energy.

4. What are the conditions for the validity of the Gibbs-Bogoliubov inequality?

The inequality is valid for systems in thermal equilibrium with a fixed number of particles. It also requires that the interactions between particles are weak, and that the system is not close to a phase transition.

5. How can the Gibbs-Bogoliubov inequality be used to study real-world systems?

The inequality can be applied to a wide range of systems, from simple gases to complex liquids and solids. It is a powerful tool for understanding the thermodynamic properties of these systems and can be used to make predictions about their behavior under different conditions.

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