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Canonical ensemble

In statistical mechanics, the canonical ensemble is a theoretical construct representing a large number of identical systems, each with a fixed number of particles N, fixed volume V, and in thermal equilibrium with an external heat reservoir at a fixed temperature T, allowing energy to fluctuate while volume and particle number remain constant.^[1]^[2] This ensemble models closed systems that exchange heat but not matter or work, providing a framework to compute thermodynamic properties such as internal energy, entropy, and heat capacity from microscopic states via statistical averaging.^[1]^[2] The probability of a system occupying a particular microstate with energy E_i follows the Boltzmann distribution, given by p_i = \frac{e^{-\beta E_i}}{Z}, where \beta = 1/(kT) with k as Boltzmann's constant, and Z is the canonical partition function Z = \sum_i e^{-\beta E_i} (for discrete states) or the integral equivalent for continuous phase space.^[1]^[2] The partition function Z(T, V, N) serves as a central quantity, linking statistical mechanics to thermodynamics through relations like the Helmholtz free energy F = -kT \ln Z, from which other potentials derive.^[2] For classical systems, Z integrates over phase space: Z = \frac{1}{N! h^{3N}} \int e^{-\beta H(\mathbf{p}, \mathbf{q})} d\mathbf{p} d\mathbf{q}, where H is the Hamiltonian, h is Planck's constant, and the N! accounts for indistinguishability.^[1] Historically, the canonical ensemble was first outlined by Ludwig Boltzmann in 1884 as a "holode" for systems in thermal contact,^[3] but it was rigorously formalized by J. Willard Gibbs in his 1902 treatise Elementary Principles in Statistical Mechanics, where he introduced ensembles as a method to average over accessible states under constraints.^[4] Gibbs' approach derives the ensemble from the microcanonical ensemble by considering a small system coupled to a large reservoir, yielding the exponential energy weighting and establishing the foundation for modern equilibrium statistical mechanics.^[2]^[4] This framework applies widely to ideal gases, quantum systems, and phase transitions, enabling predictions like the equipartition theorem, where each quadratic degree of freedom contributes \frac{1}{2} kT to the average energy.^[1]

Fundamentals

Definition

The canonical ensemble is a fundamental concept in statistical mechanics that models a closed system with a fixed number of particles N, fixed volume V, and fixed temperature T, where the system exchanges energy but not particles with an external heat bath to maintain thermal equilibrium./03%3A_Classical_Ensembles/3.03%3A_Canonical_Ensemble) In this framework, the heat bath is assumed to be much larger than the system, ensuring that its temperature remains effectively constant despite energy fluctuations transferred to or from the system.^[5] This setup allows for the statistical description of thermodynamic properties through the distribution of possible microstates, focusing on systems where temperature control is the primary constraint. The canonical ensemble was introduced by J. Willard Gibbs in his 1902 work Elementary Principles in Statistical Mechanics as one of the three principal ensembles in statistical mechanics, alongside the microcanonical and grand canonical ensembles.^[6] Gibbs developed it to bridge classical thermodynamics with probabilistic descriptions of mechanical systems, emphasizing ensembles as collections of hypothetical replicas to represent equilibrium states.^[7] It differs from the microcanonical ensemble, which applies to isolated systems with fixed energy E, N, and V (no energy exchange), and the grand canonical ensemble, which allows particle exchange with a reservoir at fixed chemical potential \mu, T, and V.^[8] In the canonical ensemble, the probability P of the system occupying a particular microstate with energy E is given by P \propto \exp(-\beta E), where \beta = 1/(kT) and k is Boltzmann's constant; this distribution is normalized by the partition function, introduced later.^[9]

Applicability

The canonical ensemble is applicable to thermodynamic systems that are in weak thermal contact with a large heat bath, allowing energy exchange while maintaining a fixed temperature T, fixed particle number N, and fixed volume V. This setup assumes the heat bath is sufficiently large such that its temperature remains essentially constant despite energy fluctuations in the system, with the interaction between the system and bath being weak to avoid significant perturbation of the bath's state.^[10]^[2] The formulation further relies on the ergodicity hypothesis, which posits that over sufficiently long times, the system explores all accessible microstates equally, equating time averages to ensemble averages.^[10]^[2] Additionally, it presupposes a separation of time scales, where the relaxation time of the bath is much shorter than that of the system, ensuring the bath quickly restores equilibrium after energy transfers. The ensemble is valid when energy fluctuations \Delta E are small relative to the average energy E, specifically \Delta E \ll E, which holds for macroscopic systems where \Delta E / E \propto 1/\sqrt{N}.^[10] This condition is typically satisfied in the thermodynamic limit, where the number of particles N \to \infty and volume V \to \infty with N/V fixed, rendering fluctuations negligible and extensive properties well-defined.^[10] However, the canonical ensemble is not suitable for isolated systems with fixed total energy, for which the microcanonical ensemble is appropriate instead.^[10] It also requires modifications in cases of strong quantum coherence effects, as standard free energy relations fail to fully capture coherence in thermodynamic processes.^[11] In the thermodynamic limit, the canonical ensemble recovers classical thermodynamics, with quantities like the Helmholtz free energy F providing the bridge to macroscopic thermodynamic potentials.^[10]

Mathematical Formulation

Classical Formulation

In the classical formulation of the canonical ensemble, the system is described using continuous phase space variables, encompassing the positions \mathbf{q} and momenta \mathbf{p} of N particles in three dimensions, resulting in a $6N-dimensional phase space. The probability density for a microstate specified by \Gamma = (\mathbf{q}, \mathbf{p}) is proportional to \exp(-\beta H(\Gamma)), where H(\mathbf{q}, \mathbf{p}) is the classical Hamiltonian of the system and \beta = 1/(k_B T) with k_B Boltzmann's constant and T the temperature. This representation assumes the high-temperature limit where quantum effects are negligible, allowing the use of continuous integrals rather than discrete sums over states.^[12] The canonical partition function in the classical limit is given by

Z_\text{class}(T, V, N) = \frac{1}{N! \, h^{3N}} \int \exp\left[-\beta H(\mathbf{q}, \mathbf{p})\right] \, d^{3N}q \, d^{3N}p,

where the integral extends over the configuration space volume V and all momenta, h is Planck's constant, and the prefactor ensures dimensional consistency and accounts for quantum-to-classical correspondence. This expression normalizes the probability distribution, such that the average of any phase function A(\Gamma) is \langle A \rangle = Z_\text{class}^{-1} \int A(\Gamma) \exp[-\beta H(\Gamma)] \, d^{3N}q \, d^{3N}p / (N! \, h^{3N}). The formulation originates from the foundational work on statistical ensembles, adapted to classical mechanics for systems like ideal gases or liquids where wavefunction overlaps are minimal.^[6]^[12]^[13] This classical partition function can be derived from the microcanonical ensemble through a limiting procedure involving a large heat bath. Consider a small system of interest in thermal contact with a much larger reservoir at fixed temperature T, forming an isolated composite with total energy E_\text{total}. In the microcanonical ensemble for the composite, the probability of the system having energy E is proportional to the reservoir's phase space volume \Omega_R(E_\text{total} - E). For E \ll E_\text{total}, a Taylor expansion of the reservoir entropy S_R(E_\text{total} - E) \approx S_R(E_\text{total}) - E/T yields \Omega_R \propto \exp(-E/(k_B T)), leading to the Boltzmann factor \exp(-\beta H) upon averaging over the thin energy shell. In the classical limit, this transitions the uniform microcanonical density on the energy hypersurface to the canonical exponential weighting over the full phase space.^[5]^[12] The factor $1/N! corrects for the indistinguishability of identical particles, preventing overcounting of permutations in the phase space integral. Without it, the partition function would treat particles as distinguishable, leading to N! identical configurations for the same physical state and an unphysical entropy increase upon mixing identical gases (Gibbs paradox). This correction is exact in the classical ideal gas limit where particle separations exceed the thermal de Broglie wavelength, ensuring the sackur-tetrode entropy expression matches experimental values. The h^{3N} term provides the quantum scale for phase space cells, with each cell volume h^3 per particle corresponding to one quantum state in the semiclassical approximation.^[14]^[15]^[12] For Hamiltonians separable as H(\mathbf{q}, \mathbf{p}) = [K(\mathbf{p})](/page/Kinetic_energy) + U(\mathbf{q}), where kinetic energy K depends only on momenta and potential U only on positions, the partition function factors into independent configurational and momentum parts: Z_\text{class} = Z_\text{momentum} \, Z_\text{config}. The momentum integral yields Z_\text{momentum} = (2\pi m k_B T)^{3N/2} / h^{3N} for quadratic kinetic terms (as in ideal gases, with m the particle mass), while Z_\text{config} = \frac{1}{N!} \int \exp[-\beta U(\mathbf{q})] \, d^{3N}q captures interactions via the configuration integral. This separation simplifies computations for many-body systems, highlighting how temperature scales the momentum contributions independently of interactions.^[13]^[16]

Quantum Formulation

In quantum mechanics, the canonical ensemble is formulated using the density operator, which describes the statistical state of a system in thermal equilibrium with a heat reservoir at temperature T. The density operator \hat{\rho} for the canonical ensemble is given by

\hat{\rho} = \frac{e^{-\beta \hat{H}}}{Z},

where \hat{H} is the Hamiltonian operator of the system, \beta = 1/(k_B T) with k_B Boltzmann's constant, and Z is the quantum partition function serving as the normalization factor. This formulation, introduced by John von Neumann, generalizes the classical probability distribution to account for quantum superpositions and entanglement in the ensemble average.^[17] The quantum partition function is defined as the trace over the Hilbert space of the system:

Z = \mathrm{Tr}\left[e^{-\beta \hat{H}}\right] = \sum_i e^{-\beta E_i},

where the sum runs over all eigenstates |i\rangle of the Hamiltonian, satisfying the time-independent Schrödinger equation \hat{H} |i\rangle = E_i |i\rangle, and E_i are the corresponding energy eigenvalues. The probability of finding the system in eigenstate |i\rangle is then P_i = e^{-\beta E_i}/Z, ensuring that the ensemble averages of observables \langle \hat{A} \rangle = \mathrm{Tr}(\hat{\rho} \hat{A}) yield the thermal expectation values. This discrete summation over energy levels contrasts with the continuous phase-space integral of the classical case and becomes essential for capturing quantum effects at low temperatures or high densities. For systems of identical particles, the trace in the partition function inherently incorporates the required symmetry under Bose-Einstein or Fermi-Dirac statistics, as the Hilbert space is constructed from symmetrized or antisymmetrized wave functions, respectively. This ensures compliance with the Pauli exclusion principle for fermions or Bose condensation for bosons without additional modifications to the formalism. In the classical limit as \hbar \to 0, where quantum effects diminish, the quantum partition function Z reduces to the classical phase-space integral, bridging the two descriptions for high-temperature regimes.

Key Quantities and Relations

Partition Function

In the canonical ensemble, the partition function Z serves as the central mathematical object, defined for a discrete set of microstates as

Z = \sum_i \exp(-\beta E_i),

where \beta = 1/(k_B T), k_B is Boltzmann's constant, T is the temperature, and E_i is the energy of the i-th microstate.^[18] For classical systems with continuous phase space, this generalizes to an integral over coordinates and momenta:

Z = \frac{1}{h^{3N} N!} \int \exp(-\beta H(\mathbf{q}, \mathbf{p})) \, d\mathbf{q} \, d\mathbf{p},

where H is the Hamiltonian, h is Planck's constant, N is the number of particles, and the prefactor accounts for indistinguishability and phase space units.^[19] This formulation ensures the normalization of the probability distribution in the ensemble, with the probability of microstate i given by p_i = \exp(-\beta E_i)/Z, such that \sum_i p_i = 1.^[18] The partition function thus encodes the statistical weight of all accessible states at fixed temperature, volume, and particle number, providing a bridge between microscopic energies and macroscopic thermodynamics.^[19] A key property arises from the logarithmic form of Z, where the Helmholtz free energy F is related by F = -k_B T \ln Z. This connection follows directly from the normalization, as the average energy and entropy can be expressed in terms of \ln Z and its derivatives, yielding F as the appropriate thermodynamic potential.^[19] The partition function acts as a generating function for all thermodynamic averages in the canonical ensemble, with quantities like the average energy \langle E \rangle = - \partial \ln Z / \partial \beta and heat capacity C_V = \partial \langle E \rangle / \partial T obtained via logarithmic derivatives. The ensemble average of an observable A can be obtained by modifying the Hamiltonian to H \to H - \lambda A and computing \langle A \rangle = \frac{1}{\beta} \frac{\partial \ln Z}{\partial \lambda} \bigg|_{\lambda=0}.^[19] Exact computation of Z is feasible only for simple systems with few particles or non-interacting degrees of freedom, such as the ideal gas or harmonic oscillators, where the sum or integral factorizes. For complex interacting systems, approximations are essential; the mean-field approach, for instance, replaces interactions with an average field, simplifying the partition function to a product over single-particle states, as applied to the Ising model. Series expansions provide another route, expanding Z in powers of interaction strength or inverse temperature for perturbative insights.^[19] High- and low-temperature expansions offer analytic tools for probing limits: at high temperatures (small \beta), Z expands as a series in \beta, capturing classical behavior and weak correlations via virial coefficients; at low temperatures (large \beta), the expansion focuses on ground-state dominance, revealing quantum effects and excitation gaps. These series, often in powers of \beta J for interaction energy J, yield insights into phase transitions and critical phenomena.^[20]

Helmholtz Free Energy

In the canonical ensemble, the Helmholtz free energy F serves as the central thermodynamic potential, defined as F = -k_B T \ln Z, where Z is the partition function, k_B is Boltzmann's constant, and T is the temperature.^[10] This expression connects the microscopic statistical description of the system to macroscopic thermodynamics, with F achieving a minimum value at thermal equilibrium for fixed temperature T, volume V, and particle number N.^[21] Equivalently, F can be expressed as F = \langle E \rangle - T S, where \langle E \rangle is the average internal energy and S is the entropy, highlighting its role in balancing energetic and entropic contributions.^[22] The differential form of the Helmholtz free energy is given by

dF = -S \, dT - P \, dV + \mu \, dN,

where P is the pressure and \mu is the chemical potential, confirming that F = F(T, V, N) is an exact differential with natural variables T, V, and N.^[22] From this, key relations follow: the entropy S = -\left( \frac{\partial F}{\partial T} \right)_{V,N}, the pressure P = -\left( \frac{\partial F}{\partial V} \right)_{T,N}, and the chemical potential \mu = \left( \frac{\partial F}{\partial N} \right)_{T,V}.^[10] These partial derivatives enable the derivation of equations of state and response functions directly from F.^[21] Physically, the Helmholtz free energy quantifies the maximum useful work extractable from a system at constant temperature and volume, excluding work due to volume changes.^[22] It arises as the Legendre transform of the internal energy U(S, V, N) with respect to entropy, F(T, V, N) = U - T S, shifting the emphasis from fixed entropy to fixed temperature.^[21] Further Legendre transforms connect F to other potentials, such as the Gibbs free energy G = F + P V, which is appropriate for constant pressure processes.^[10] For thermodynamic stability, the Helmholtz free energy exhibits mixed convexity properties in its natural variables: it is concave in temperature T and convex in volume V and particle number N, ensuring positive heat capacities and compressibilities, and that small perturbations do not lead to instability with the equilibrium state corresponding to a global minimum.^[21]^[10]

Ensemble Averages

In the canonical ensemble, the ensemble average of a dynamical observable A is computed as the expectation value weighted by the Boltzmann probabilities over all accessible microstates. For a discrete set of states labeled by i with energies E_i, this is given by

\langle A \rangle = \frac{1}{Z} \sum_i A_i \, e^{-\beta E_i},

where Z = \sum_i e^{-\beta E_i} is the partition function and \beta = 1/(k_B T) with k_B Boltzmann's constant and T the temperature.^[18] This formula, introduced by Gibbs, represents the thermal average under fixed temperature, volume, and particle number.^[23] In the classical limit, for a system of N particles, the average becomes an integral over phase space:

\langle A \rangle = \frac{1}{Z} \int A(\mathbf{q}, \mathbf{p}) \, e^{-\beta H(\mathbf{q}, \mathbf{p})} \frac{d\mathbf{q} \, d\mathbf{p}}{h^{3N} N!},

where H is the Hamiltonian, \mathbf{q} and \mathbf{p} are the coordinates and momenta, and h is Planck's constant.^[24] The partition function Z normalizes the integral, ensuring the probabilities sum to unity.^[25] Key thermodynamic quantities can be obtained directly from derivatives of the partition function. The average internal energy is

\langle E \rangle = -\frac{\partial \ln Z}{\partial \beta} \Big|_{V,N},

which connects statistical mechanics to macroscopic thermodynamics.^[25] Similarly, the average PV term, related to pressure via the equation of state, satisfies

\langle PV \rangle = k_B T \frac{\partial \ln Z}{\partial \ln V} \Big|_{T,N}.

^[24] These relations follow from the logarithmic derivative of Z, leveraging its dependence on thermodynamic variables.^[18] The average energy \langle E \rangle relates to the Helmholtz free energy F = -k_B T \ln Z through \langle E \rangle = F + T S, where S is the entropy.^[1] The variance of an observable A, quantifying fluctuations, is \operatorname{Var}(A) = \langle A^2 \rangle - \langle A \rangle^2. To compute it using the partition function, introduce a parameter \lambda into the Hamiltonian as H \to H - \lambda A; then,

\operatorname{Var}(A) = \frac{1}{\beta^2} \frac{\partial^2 \ln Z}{\partial \lambda^2} \Big|_{\lambda=0}.

^[23] This second derivative form arises from expanding the modified partition function and reflects the response to perturbations.^[25] For the energy itself, the variance yields the heat capacity via \operatorname{Var}(E) = k_B T^2 C_V.^[24] The ergodic hypothesis underpins the practical utility of ensemble averages by positing that, for an isolated stationary system in equilibrium, the time average of an observable along a single trajectory equals its ensemble average over the canonical distribution.^[18] This equivalence, originally discussed by Gibbs in the context of phase space exploration, justifies using ensemble methods for real systems observed over finite times.^[26] For a system composed of independent, non-interacting subsystems, the total partition function factorizes as Z = Z_1 Z_2 \cdots Z_M, where Z_j is the partition function of the j-th subsystem.^[18] Consequently, the ensemble average of an additive observable separates additively, \langle A \rangle = \langle A_1 \rangle + \langle A_2 \rangle + \cdots + \langle A_M \rangle, simplifying computations for composite systems like ideal gases.^[24]

Properties

Thermodynamic Consistency

The canonical ensemble ensures consistency with the zeroth law of thermodynamics by modeling the system as weakly coupled to a large heat bath at fixed temperature T, allowing the system to reach thermal equilibrium where its temperature equals that of the bath, as defined by the transitive property of thermal equilibrium. Regarding the first law of thermodynamics, the ensemble maintains energy conservation on average, with the internal energy \langle E \rangle = -\frac{\partial \ln Z}{\partial \beta} (where Z is the partition function and \beta = 1/kT) remaining constant in equilibrium, such that \frac{d \langle E \rangle}{dt} = 0 for the isolated total system comprising the small system and large bath.^[25] The second law is reproduced through the Helmholtz free energy F = -kT \ln Z, from which the entropy follows as S = -\left( \frac{\partial F}{\partial T} \right)_{V,N}, yielding a non-negative entropy increase in irreversible processes; in the classical limit, this aligns with H-theorem analogs demonstrating approach to maximum entropy equilibrium.^[27] Consistency with the third law emerges in the low-temperature limit, where F \to E_0 (the ground-state energy) as T \to 0, implying S \to 0 for systems with a unique ground state, unattainable by finite processes.^[28] In the thermodynamic limit as the number of particles N \to \infty with fixed density, thermodynamic properties become extensive (e.g., F \propto N), fluctuations relative to mean values vanish, and corrections from finite-size effects diminish, ensuring ensemble equivalence and macroscopic reproducibility of thermodynamic relations.^[24]

Fluctuations and Correlations

In the canonical ensemble, the energy of the system fluctuates due to thermal exchange with the reservoir, with the variance of these fluctuations given by \langle (\Delta E)^2 \rangle = k T^2 C_V, where C_V = \partial \langle E \rangle / \partial T is the heat capacity at constant volume and k is Boltzmann's constant.^[29] This relation arises from the second derivative of the partition function with respect to the inverse temperature \beta = 1/(kT), specifically \langle (\Delta E)^2 \rangle = -\partial^2 \ln Z / \partial \beta^2, which connects microscopic probability distributions to macroscopic thermodynamic response.^[30] Physically, these fluctuations reflect the stochastic nature of energy transfers, becoming negligible for large systems but essential for understanding finite-size effects in mesoscopic or nanoscale systems. The relative magnitude of energy fluctuations scales as \Delta E / \langle E \rangle \approx 1 / \sqrt{N}, where N is the number of particles, ensuring that \Delta E / \langle E \rangle \to 0 in the thermodynamic limit N \to \infty. This scaling demonstrates the self-averaging property of the ensemble, where statistical uncertainties diminish as system size increases, justifying the use of ensemble averages to represent thermodynamic properties. For practical systems like ideal gases, this implies that energy measurements are highly precise even at moderate scales, with fluctuations on the order of 1% or less for N \gtrsim 10^4. More generally, correlations between observables A and B in the canonical ensemble are captured by the covariance \langle AB \rangle - \langle A \rangle \langle B \rangle = k T \partial \langle A \rangle / \partial \lambda, where \lambda is the parameter conjugate to B in the Hamiltonian (e.g., an external field).^[30] This fluctuation-response relation quantifies how perturbations induce changes in averages through intrinsic correlations, providing a bridge between equilibrium fluctuations and linear response theory. A key application is the static fluctuation-dissipation theorem, which links dissipative susceptibilities to equilibrium variances; for instance, the magnetic susceptibility satisfies \chi = (\langle M^2 \rangle - \langle M \rangle^2) / (k T), where M is the total magnetization.^[31] This theorem underscores the unified treatment of noise and response in thermal systems, with implications for transport coefficients and critical phenomena. In systems composed of independent modes, such as non-interacting particles or harmonic oscillators, the energy contributions from each mode are independent, with variances adding for the total observable. In the classical high-temperature limit, the energy per mode follows an exponential distribution with variance equal to (mean energy)^2, and the central limit theorem yields Gaussian distributions for collective quantities in the large-mode limit, aligning with the overall $1/\sqrt{N} scaling of relative fluctuations.^[10]^[29]

Examples

Non-interacting Systems

In systems consisting of non-interacting particles or independent modes, the canonical ensemble simplifies significantly because the total Hamiltonian is the sum of individual Hamiltonians, allowing the partition function to factorize as a product over the components.^[6] This factorization implies that the probability distribution for the overall system state is the product of individual probabilities, known as the Boltzmann distribution: P(\{ \mathbf{r}_i, \mathbf{p}_i \}) = \prod_{i=1}^N p_i(\mathbf{r}_i, \mathbf{p}_i), where each p_i is proportional to e^{-\beta H_i} with H_i the single-particle Hamiltonian and \beta = 1/(kT). Such systems are exactly solvable, providing foundational examples for understanding thermodynamic properties in the canonical ensemble. A prime example is the classical ideal gas of N indistinguishable particles in volume V. The single-particle partition function is z = V / \lambda^3, where \lambda = h / \sqrt{2\pi m k T} is the thermal de Broglie wavelength, with m the particle mass, k Boltzmann's constant, T temperature, and h Planck's constant. The total partition function is then Z = z^N / N!, accounting for indistinguishability via the factorial correction. From this, the average energy is \langle E \rangle = \frac{3}{2} N k T, reflecting the equipartition of kinetic energy over three degrees of freedom per particle. This result follows from evaluating the phase space integrals in the classical formulation of the canonical ensemble. The momentum integrals in z also yield the Maxwell-Boltzmann speed distribution, f(v) dv = 4\pi v^2 \left( \frac{m}{2\pi k T} \right)^{3/2} e^{-m v^2 / (2 k T)} dv, which describes the probability of particles having speeds between v and v + dv.^[32] For quantum systems of non-interacting harmonic oscillators, such as vibrational modes in solids, the partition function for a single oscillator of frequency \omega is z = \frac{1}{2 \sinh(\beta \hbar \omega / 2)}, derived from summing over energy levels E_n = \hbar \omega (n + 1/2), n = 0, 1, 2, \dots. For f independent modes (all at the same \omega), the total partition function is Z = z^f. This includes the quantum zero-point energy contribution, \frac{1}{2} f \hbar \omega, which persists even at absolute zero and leads to the average energy \langle E \rangle = f \hbar \omega \left( \frac{1}{2} + \frac{1}{e^{\beta \hbar \omega} - 1} \right). Due to the absence of interactions, thermodynamic potentials are additive across subsystems. In particular, the Helmholtz free energy satisfies F = -k T \ln [Z](/page/Z) = \sum_i F_i, where F_i is the free energy of the i-th independent component, facilitating the analysis of composite non-interacting systems.^[6]

Interacting Systems

In interacting systems within the canonical ensemble, the particles or degrees of freedom are coupled through potential energy terms in the Hamiltonian, preventing the partition function from factoring into independent single-particle contributions as in non-interacting cases. For classical systems of N particles, the partition function is given by

Z = \frac{1}{N! h^{3N}} \int d^{3N}p \, d^{3N}q \, e^{-\beta H(\mathbf{p},\mathbf{q})},

where H = \sum_{i=1}^N \frac{p_i^2}{2m_i} + \sum_{i<j} V(r_{ij}) includes the interaction potential V(r_{ij}) between pairs of particles separated by distance r_{ij}, \beta = 1/(k_B T), and h is Planck's constant. This integral generally cannot be evaluated analytically due to the correlations induced by interactions, leading to challenges in computing thermodynamic quantities like the Helmholtz free energy F = -k_B T \ln Z or average energy \langle E \rangle = -\partial \ln Z / \partial \beta. To address this, perturbation methods such as the virial expansion express Z in powers of density, where the second virial coefficient B_2(T) = -\frac{1}{2} \int d^3 r \, (e^{-\beta V(r)} - 1) captures pairwise interactions. A representative approximation for weakly interacting gases is the van der Waals model, which treats repulsive interactions via an excluded volume b per particle and attractive interactions via a mean-field term -a N^2 / V, modifying the partition function to Z \approx Z_\text{ideal} (V - N b)^N e^{\beta a N^2 / V}. This yields the equation of state (P + a/V_m^2)(V_m - b) = k_B T, where V_m = V/N is the molar volume, capturing phenomena like gas-liquid coexistence absent in ideal gases. The approximation assumes uniform density, neglecting higher-order correlations, and is valid at low densities where the second virial coefficient dominates.^[33] For lattice-based interacting systems, such as magnetic spins, the Ising model serves as a paradigmatic example. The Hamiltonian is H = -J \sum_{\langle i,j \rangle} s_i s_j - h \sum_i s_i, where s_i = \pm 1 are spins on a lattice, J > 0 is the ferromagnetic coupling between nearest neighbors \langle i,j \rangle, and h is an external field. The partition function Z = \sum_{\{s\}} e^{-\beta H} encodes cooperative effects, leading to phase transitions in dimensions d \geq 2. In one dimension (without field), an exact solution gives Z = [2 \cosh(\beta J)]^N, resulting in zero spontaneous magnetization at any finite temperature, with energy \langle E \rangle = -N J \tanh(\beta J).^[34] In two dimensions, Onsager's exact solution reveals a critical temperature k_B T_c / J = 2 / \ln(1 + \sqrt{2}) \approx 2.27, below which long-range order emerges, demonstrating how interactions drive collective behavior like ferromagnetism.^[35]

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[PDF] Lecture 8: Free energy
Next, consider how to compute free energy from the partition function in the canonical ensemble. ... energy is the constant pressure version of Helmholtz free ...Missing: seminal | Show results with:seminal
[21]
[PDF] Statistical Ensembles - Physics Courses
Like the Helmholtz free energy, the Gibbs free energy G(T,p,N) is also a double Legendre transform of the energy E(S,V,N), viz. G = E − TS + pV. dG = −S dT ...
[22]
[PDF] Lecture 7: Ensembles
Ensembles are the possible microstates a system could be in, sharing a macroscopic property. Examples include microcanonical, canonical, Gibbs, and grand ...
[23]
[PDF] Chapter 9 Canonical ensemble
A canonical ensemble is an ensemble in contact with a heat reservoir at temperature T, with the Boltzmann factor exp(−βEα) describing the canonical ...
[24]
[PDF] Statistical Mechanics Lecture set 3: Canonical Ensemble
In this set of lectures, we will introduce and discuss the canonical ensemble description of quan- tum and classical statistical mechanics, deriving it by ...Missing: coherence | Show results with:coherence
[25]
The Ergodic Hypothesis - The Information Philosopher
Boltzmann described a system he called "ergode," later called the canonical ensemble by J. Willard Gibbs. Equal a priori probabilities for all the phase space ...
[26]
[PDF] Part II - Statistical Physics (Theorems with proof) - Dexter Chua
Since the temperatures are equal, we know that we also need p1 = p2. Proposition (First law of thermodynamics). dE = T dS − p dV. 1.3 The canonical ensemble.
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[PDF] The Canonical Ensemble 4.1 The Boltzmann distribution 4.2 The ...
One of the tasks in statistical mechanics is to derive this van der Waals equation from, say, canonical ensemble approach. In canonical-ensemble approach ...
[28]
[PDF] Energy Fluctuations in the Canonical Ensemble
The standard deviation of energy fluctuations is related to heat capacity by (ΔE)² = kT²CV, and relative fluctuations scale as √kT² / √CV(E) ∝ √N/N.
[29]
[PDF] Statistical Mechanics - University of Oregon
1.4.4 The Grand Canonical Ensemble . ... The canonical distribution has a finite variance, and hence CLT applies. By §1.2.6, we have: xi = nEi. (i = 1,...,n).
[30]
[PDF] The fluctuation-dissipation theorem - Physics Courses
Oct 30, 2019 · This theorem may be represented by a stochastic equation describing the fluctuation, which is a generalization of the familiar Langevin equation ...
[31]
Part I. On the motions and collisions of perfectly elastic spheres
May 26, 2009 · Illustrations of the dynamical theory of gases.—Part I. On the motions and collisions of perfectly elastic spheres. J. C. Maxwell M.A. ...<|control11|><|separator|>
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[PDF] V.C The Second Virial Coefficient & van der Waals Equation
In a canonical ensemble, the gas density is reduced at the walls. This is because the particles in the middle of the box experience an attractive potential ...
[33]
[PDF] Ensembles - UMD Physics
With fewer quantum states populated with appreciable frequency, the system exhibits a higher degree of order and pos- sesses lower entropy. Therefore, the ...Missing: coherence | Show results with:coherence