The Grand Canonical Ensemble
When a system exchanges both energy and particles with a reservoir, the reservoir fixes its temperature and its chemical potential. Expanding the reservoir entropy to first order in the exchanged energy and particle number gives the Gibbs factor , and summing it over every microstate of every particle number gives the grand partition function .
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The canonical ensemble fixes the particle number and lets the energy fluctuate. Many systems fix neither. A region of a gas open to the rest of the container, a metal surface adsorbing molecules from a vapor, a single quantum mode that any number of bosons may occupy — each exchanges particles as freely as energy with its surroundings. The grand canonical ensemble describes a system in contact with a reservoir that fixes the temperature and the chemical potential while both the energy and the particle number of the system fluctuate. Its central object is the grand partition function, from which the whole thermodynamics follows exactly as the canonical thermodynamics follows from .
A system open to a particle reservoir
Consider a small system in contact with a large reservoir , the two together forming an isolated compound with fixed total energy and fixed total particle number . The wall between them passes both energy and particles. A microstate of is now labeled by two quantities: its energy and its particle number . When is in a definite microstate , the reservoir holds the remainder and , and it does so in ways.
By the postulate of equal a priori probabilities applied to the isolated compound, the probability of the system microstate is proportional to the number of reservoir microstates consistent with it,
The system energies and particle numbers are tiny against the reservoir totals, so expand the reservoir entropy to first order in both and :
These two reservoir derivatives coincide with the statistical definitions of temperature and chemical potential established for the microcanonical ensemble,1
Both are properties of the reservoir alone, hence constants that the reservoir imposes on the system. Writing , the reservoir count reduces to a weight on the system microstate,
The Gibbs factor
The exponential weight is the two-variable analogue of the Boltzmann factor.
The Gibbs factor differs from the Boltzmann factor by the extra weight . Raising multiplies the weight of every particle-carrying state, favoring microstates with more particles; lowering it favors emptier states. The chemical potential is the reservoir's control knob on the system's population, precisely as the temperature is its knob on the energy. For a fixed particle number the Gibbs factor collapses to the Boltzmann factor, so the canonical ensemble is the -fixed section of the grand ensemble.
The grand partition function
Normalizing the Gibbs factor requires summing it over every microstate the system can occupy — over all particle numbers, and for each particle number over all microstates of that many particles.
The double sum factorizes the counting cleanly. The inner sum over the -particle microstates is the canonical partition function studied in the previous module,2 so the grand partition function is a -weighted sum of canonical partition functions,
This makes a generating function: it packages the canonical partition functions of every particle number into one object, with marking the particle number as a bookkeeping variable. Fixing selects a distribution over rather than a single value, which is the whole point of opening the system to particle exchange.
Fugacity
The weight appears once per particle, so it is convenient to name it.
Written this way is a polynomial (or power series) in whose coefficient of is the -particle canonical partition function. The fugacity runs from (the empty limit , where only the term survives) upward; marks . For the classical gases of the next lesson stays small, and the low-order terms of the series dominate; for the quantum gases of the following module is the natural expansion variable in which the Bose and Fermi occupation functions are written. The fugacity is the same control knob as , rescaled to enter as a simple multiplicative activity per particle.
The grand potential
The bridge to thermodynamics is the logarithm of the grand partition function, exactly as bridges the canonical ensemble.
To connect to the potentials already in hand, start from the Helmholtz free energy and subtract the particle term. The grand potential is the double Legendre transform of the energy that trades for and for ,
Its differential follows from the fundamental relation . Substituting and cancelling gives
The natural variables are read off the differential: is a function of , , and , and its three first derivatives return the entropy, pressure, and particle number,
The grand potential is
The three natural variables of are , , and , of which only is extensive. Doubling the system at fixed and doubles and doubles , so must be proportional to with a coefficient built from the intensive variables alone.
The relation is the grand-ensemble counterpart of and is often the fastest route to an equation of state: compute , read off the pressure directly, and obtain the density from .
Mean energy and particle number
The averages come from derivatives of , mirroring the canonical construction. Treat as a function of and the product ; each derivative pulls down the corresponding quantity from the Gibbs exponent. The mean particle number is the derivative with respect to at fixed temperature,
This agrees with once is inserted. The mean energy is obtained by differentiating in at fixed fugacity, which isolates the energy exponent,
The combination is the quantity conjugate to in the Gibbs exponent, so it emerges most naturally from the -derivative; the separate mean energy then follows by adding . The entropy closes the set through , giving
When the grand ensemble is the right choice
The three ensembles predict the same thermodynamics for a macroscopic system, so the choice among them is a matter of which calculation is easiest. The grand canonical ensemble is the convenient one whenever the constraint of fixed particle number obstructs the sum.
- Quantum ideal gases. Counting configurations of indistinguishable bosons or fermions at fixed total ties the single-particle occupation numbers together through . Releasing decouples the modes: the grand partition function factorizes over single-particle states, and each mode is summed independently. This is the derivation of the Bose-Einstein and Fermi-Dirac distributions in the next module.
- Adsorption and chemical equilibrium. Surfaces, binding sites, and reacting species exchange particles with a bath at fixed ; the equilibrium occupation follows directly from the Gibbs factor.
- Open subvolumes and fluctuations. A region of a fluid with imaginary walls exchanges particles with the surrounding fluid; the grand ensemble is the natural setting for density fluctuations, taken up in the next lesson.
Summary
- A system exchanging energy and particles with a reservoir at fixed and has microstate probability set by the Gibbs factor, obtained by expanding the reservoir entropy to first order in and with and .
- The grand partition function normalizes the Gibbs factor; it is a generating function in the fugacity whose coefficient is the canonical partition function of particles.
- The grand potential has differential , so , , and follow by differentiation. Because is its only extensive variable, , giving .
- Averages come from derivatives of : and . The grand ensemble is the tool of choice when fixed obstructs the sum, above all for the quantum ideal gases.
Footnotes
- Reif, Fundamentals of Statistical and Thermal Physics, §9.1–9.3, and the microcanonical definitions and established in the thermal, mechanical, and diffusive equilibrium lesson. ↩
- The canonical partition function and the bridge are developed in the partition function and Helmholtz free energy lesson. Schroeder, An Introduction to Thermal Physics, §7.1; companion material at https://physics.weber.edu/schroeder/thermal/. Kardar, Statistical Physics of Particles, §4.9; MIT OCW 8.333, https://ocw.mit.edu/courses/8-333-statistical-mechanics-i-statistical-mechanics-of-particles-fall-2013/. Pathria & Beale, Statistical Mechanics (4th ed.), §4.1–4.4. ↩
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