Thermodynamics and Statistical Mechanics
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Recall prompts
Section titled “Recall prompts”Attempt these from memory before reading.
- State the zeroth law and say what it is actually for.
- Write the four laws of thermodynamics in your own words.
- Define enthalpy, Helmholtz free energy and Gibbs free energy. Which one is the natural potential at constant temperature and pressure, and why?
- State one Maxwell relation. What thermodynamic identity does it express?
- What is the Boltzmann distribution, and what assumption does it make about the system?
- Why does entropy increase in an isolated system? In terms of what?
Check your answers against the text. The last prompt is the one the whole subject rests on, and the naive answer — “because disorder increases” — is the one worth catching before you read, because the correct answer is sharper.
Motivation: why a second law is needed at all
Section titled “Motivation: why a second law is needed at all”The first law is bookkeeping: energy is conserved. Conservation laws of that kind are common, and on their own they are satisfied by a universe in which a cup of tea cools by spontaneously absorbing heat from the air, or a gas that mixes and then unmixes. Nothing in the first law forbids either.
So thermodynamics needs a direction. The second law supplies one, and it is the only place in classical physics where an arrow of time enters from observation rather than from the equations. Every other law in mechanics is reversible in time; Newton’s laws do not distinguish running forwards from running backwards. The second law is the exception, and it is an empirical statement about what actually happens.
The cost of that direction is a quantity that increases monotonically in an isolated system. That quantity is entropy, and the second law is the statement that it exists.
1. The Laws of Thermodynamics
Section titled “1. The Laws of Thermodynamics”1.1 Zeroth Law
Section titled “1.1 Zeroth Law”Zeroth Law: If system is in thermal equilibrium with system And is in thermal Equilibrium with system Then is in thermal equilibrium with .
This law establishes the existence of temperature as an equivalence relation. Two systems are in Thermal equilibrium if and only if they are at the same temperature.
1.2 First Law
Section titled “1.2 First Law”First Law (Conservation of Energy): The change in internal energy of a system equals the heat Added to the system minus the work done by the system:
Where and are inexact differentials (path-dependent), while is an Exact differential (state function).
For a quasi-static process with pressure-volume work:
So the first law becomes:
Definition (Heat capacity). The heat capacity at constant volume and constant pressure are:
Where is the enthalpy.
1.3 Second Law
Section titled “1.3 Second Law”Second Law (Clausius Statement): Heat cannot spontaneously flow from a colder body to a hotter Body without external work.
Second Law (Kelvin-Planck Statement): No cyclic process can convert heat entirely into work.
Theorem 1.1 (Carnot’s Theorem). No engine operating between two heat reservoirs is more Efficient than a Carnot engine. All reversible engines operating between the same two reservoirs have the same efficiency.
Proof. Suppose engine (claimed more efficient than Carnot) operates between reservoirs at and . Let extract heat from the hot reservoir, do work And reject heat to the cold reservoir. Run a Carnot engine in reverse as a refrigerator using Work from : it extracts from the cold reservoir and delivers to the Hot reservoir. If Then So the combined system transfers net Heat from cold to hot with no external work, violating the Clausius statement.
1.4 Entropy and the Clausius Inequality
Section titled “1.4 Entropy and the Clausius Inequality”Definition (Entropy). For a reversible process, the entropy change is:
dS = \frac{\delta Q_{\mathrm{rev}}{T}}Clausius Inequality: For any cyclic process:
With equality if and only if the process is reversible.
Proof of entropy increase for irreversible processes. Consider a system undergoing an Irreversible process from state to state Then returning via a reversible process. By the Clausius inequality:
\int_1^2 \frac{\delta Q_{\mathrm{irrev}}{T} + \int_2^1 \frac{\delta Q_{\mathrm{rev}}{T} \leq 0}} \int_1^2 \frac{\delta Q_{\mathrm{irrev}}{T} - \int_1^2 \frac{\delta Q_{\mathrm{rev}}{T} \leq 0}}Since :
With equality for reversible processes.
1.5 Third Law
Section titled “1.5 Third Law”Third Law (Nernst Heat Theorem): As The entropy of a perfect crystal approaches zero:
This sets an absolute reference for entropy and implies that it is impossible to reach absolute zero in a finite number of steps.
1.6 Thermodynamic Response Functions
Section titled “1.6 Thermodynamic Response Functions”Several material-dependent quantities characterise how a system responds to changes in its state Variables.
Definition (Isothermal compressibility).
Definition (Adiabatic compressibility).
Definition (Coefficient of thermal expansion).
Theorem 1.2 (Relation between heat capacities).
Proof. From the identity And writing in terms of and along a constant- path:
Multiply by and use , And the Maxwell relation :
Now use the cyclic relation To obtain:
Since for stable systems and We always have .
Theorem 1.3 (Adiabatic index). The ratio satisfies:
Proof. Along an adiabat, . Using the chain rule:
Similarly, along an isotherm:
Using the identity and simplifying gives .
1.7 Second Law from Statistical Mechanics
Section titled “1.7 Second Law from Statistical Mechanics”Theorem 1.4 (Statistical basis of the second law). For an isolated system, the entropy can only increase or remain constant.
Proof. Consider an isolated system with fixed energy Volume And particle number . The system evolves through accessible microstates. If the system starts in a non-equilibrium Macrostate with microstates and evolves to macrostate with microstates, The evolution is driven by the ergodic exploration of phase space.
Since the system explores all accessible microstates with equal probability over time, it will Overwhelmingly be found in the macrostate with the largest number of microstates. If , then .
More rigorously: suppose the system starts in a subset of microstates out of a total . The probability that the system remains in this subset after randomising over all Microstates is . The system therefore evolves toward the macrostate that Maximises And hence maximises .
This shows that the second law is not absolute but statistical: fluctuations can temporarily Decrease entropy, but the probability of a macroscopic fluctuation is exponentially small in .
Solution: Worked Example, Response Functions for an Ideal Gas
For an ideal gas :
This confirms for an ideal gas, a result that also follows directly from Equipartition.
2. Thermodynamic Potentials
Section titled “2. Thermodynamic Potentials”2.1 The Four Potentials
Section titled “2.1 The Four Potentials”The internal energy is the fundamental thermodynamic potential. By performing Legendre Transformations on We obtain the other potentials:
| Potential | Symbol | Natural Variables | Differential |
|---|---|---|---|
| Internal energy | |||
| Enthalpy | |||
| Helmholtz free energy | |||
| Gibbs free energy |
The Legendre transforms are:
2.2 Derivation of the Differential Relations
Section titled “2.2 Derivation of the Differential Relations”Starting from the first law for a reversible process:
This tells us , And .
For enthalpy, So:
For Helmholtz free energy, So:
For Gibbs free energy, So:
2.3 Physical Meaning of the Potentials
Section titled “2.3 Physical Meaning of the Potentials”- : Total energy at constant entropy and volume.
- : Total energy plus the work needed to make room for the system (). Useful for constant-pressure processes (e.g., chemical reactions at atmospheric pressure).
- : The maximum work extractable from a system at constant temperature. Minimised at equilibrium for systems in contact with a heat bath at fixed .
- : The maximum non-expansion work extractable. Minimised at equilibrium for systems at fixed .
2.4 Maxwell Relations from Thermodynamic Potentials
Section titled “2.4 Maxwell Relations from Thermodynamic Potentials”Since each thermodynamic potential is a state function, its differential is exact. By Euler’s Reciprocity, mixed second partial derivatives are equal. This yields the four Maxwell relations Directly:
| From potential | Exact differential | Maxwell relation |
|---|---|---|
These relations allow us to express unmeasurable quantities (entropy changes) in terms of Measurable ones (equations of state).
Solution: Worked Example, Free Energy Minimisation
A gas cylinder at K is divided by a frictionless piston. Side has volume L with mol of ideal gas. Side has volume L with mol of ideal Gas. The piston is released and the system equilibrates at constant . Find the equilibrium Volumes.
The total Helmholtz free energy is:
Where is the thermal de Broglie wavelength. At constant is constant, so minimising with respect to (with ):
So . With L: L, L.
This is just mechanical equilibrium: I.e., .
2.5 Equilibrium Conditions
Section titled “2.5 Equilibrium Conditions”Theorem 2.1. At equilibrium:
- For an isolated system: is maximised (at fixed ).
- For a system in contact with a heat bath at temperature and pressure : is minimised.
- For a system at constant : is minimised.
Proof (for ). Consider a system in contact with a reservoir at . The total entropy Of system plus reservoir is . At equilibrium, is Maximised, so for any variation. Since and by energy conservation :
Where . Hence So is Minimised.
3. Maxwell Relations
Section titled “3. Maxwell Relations”3.1 Derivation from Exact Differentials
Section titled “3.1 Derivation from Exact Differentials”Since are state functions, their differentials are exact. By the symmetry of second Derivatives (Euler’s reciprocity), if Then:
Applying this to each thermodynamic potential:
From :
From :
From :
From :
3.2 Applications
Section titled “3.2 Applications”Derivation of the heat capacity relation. From :
Using the chain rule and Maxwell relations:
Proof. Expand as :
Multiply by :
Using the Maxwell relation :
3.3 Applications of Maxwell Relations
Section titled “3.3 Applications of Maxwell Relations”Application: entropy change of an ideal gas. Using And the ideal gas law :
Integrating: for an isothermal expansion.
Similarly, using :
So Consistent.
Application: internal energy of an ideal gas. Using (a Maxwell relation consequence from ):
This confirms that the internal energy of an ideal gas depends only on (Joule’s law).
Solution: Worked Example, Maxwell Relation for a Van der Waals Gas
For a van der Waals gas where :
Using :
From the EOS: So .
Therefore:
Integrating at constant :
For a free expansion (, Hence for ideal gas), the van der Waals Gas heats up because the internal energy depends on volume through the term representing Intermolecular attraction. The temperature change is:
Which is negative for : the gas cools during free expansion.
4. Heat Engines and Refrigerators
Section titled “4. Heat Engines and Refrigerators”4.1 The Carnot Cycle
Section titled “4.1 The Carnot Cycle”The Carnot cycle consists of four reversible stages operating between temperatures (hot) and (cold):
- Isothermal expansion at : absorb heat from hot reservoir.
- Adiabatic expansion: temperature drops from to .
- Isothermal compression at : reject heat to cold reservoir.
- Adiabatic compression: temperature rises from to .
The efficiency is:
Derivation. For the isothermal steps, and . Since entropy is a state function and the cycle returns to the initial state, So .
4.2 Heat Pumps and Refrigerators
Section titled “4.2 Heat Pumps and Refrigerators”A refrigerator is a Carnot engine run in reverse. The coefficient of performance (COP):
\mathrm{COP_}{\mathrm{ref} = \frac{Q_c}{W} = \frac{T_c}{T_h - T_c}}A heat pump heats the hot reservoir:
\mathrm{COP_}{\mathrm{hp} = \frac{Q_h}{W} = \frac{T_h}{T_h - T_c}}4.3 The Otto and Diesel Cycles
Section titled “4.3 The Otto and Diesel Cycles”Otto cycle (idealised petrol engine): two isochoric and two adiabatic processes.
Where is the compression ratio and .
Diesel cycle: one isobaric, two adiabatic, and one isochoric process:
Where is the cutoff ratio.
4.4 Worked Example: Carnot Cycle Calculation
Section titled “4.4 Worked Example: Carnot Cycle Calculation”Solution: Carnot Cycle with a Monatomic Ideal Gas
A Carnot engine uses mol of monatomic ideal gas (, ). The reservoirs are at K and K. At state (start of Isothermal expansion): atm, L.
Step 1: Isothermal expansion at K from to . Let L.
(isothermal, so )
atm.
Step 2: Adiabatic expansion from to . K. From :
, .
Step 3: Isothermal compression at K from to . From On the adiabat : L.
J (heat rejected; for compression).
Step 4: Adiabatic compression from to . , J.
Summary:
| Quantity | Value |
|---|---|
| (absorbed) | 6915 J |
| (rejected) | 3458 J |
| 3457 J | |
| 0.500 | |
| 0.500 |
The efficiency matches the Carnot prediction exactly, as expected for a reversible cycle.
5. Entropy and Free Energy
Section titled “5. Entropy and Free Energy”5.1 Statistical Definition of Entropy
Section titled “5.1 Statistical Definition of Entropy”Definition (Boltzmann Entropy). For a macrostate with accessible microstates:
Where J/K is Boltzmann’s constant.
Justification. Consider two independent systems and . The total number of microstates is . We require (additivity). The logarithm is the unique function satisfying .
5.2 Gibbs Entropy Formula
Section titled “5.2 Gibbs Entropy Formula”For a system with probability of being in microstate :
This reduces to the Boltzmann formula when all accessible microstates are equally probable: .
Theorem 5.1 (Concavity of entropy). The Gibbs entropy is maximised when all accessible Microstates are equally probable.
Proof. Maximise subject to using a Lagrange Multiplier :
This gives for all . The constraint Then gives .
Derivation from Boltzmann. For identical systems distributed among equally probable Microstates, the most probable macrostate has systems in each microstate. The Number of ways to arrange this is:
Using Stirling’s approximation :
Where . Multiplying by gives the Gibbs entropy.
5.3 Helmholtz Free Energy and the Partition Function
Section titled “5.3 Helmholtz Free Energy and the Partition Function”The Helmholtz free energy connects thermodynamics to statistical mechanics:
Where is the canonical partition function and .
Derivation. From the Gibbs entropy with the Boltzmann distribution :
Since and :
6. Phase Transitions
Section titled “6. Phase Transitions”6.1 Classification of Phase Transitions
Section titled “6.1 Classification of Phase Transitions”First-order transition: Discontinuity in first derivatives of (e.g., , ). There is a Latent heat .
Second-order (continuous) transition: First derivatives are continuous, but second derivatives (e.g., , , ) diverge or are discontinuous.
Ehrenfest classification: An -th order transition has discontinuities in the -th Derivatives of With all lower derivatives continuous.
6.2 The Clausius-Clapeyron Equation
Section titled “6.2 The Clausius-Clapeyron Equation”For a first-order phase transition between phases and in equilibrium ():
Where is the latent heat and .
Derivation. Along the coexistence curve, . Since :
Application: liquid-gas coexistence. Assuming the vapour is an ideal gas and :
Integrating (assuming is constant) gives the Clausius equation:
6.4 Worked Example: Clausius-Clapeyron Applications
Section titled “6.4 Worked Example: Clausius-Clapeyron Applications”Solution: Boiling Point at Different Pressures
The latent heat of vaporisation of water at 1 atm ( K) is J/mol. Find the Boiling point at atm.
Integrating the Clausius-Clapeyron equation:
This explains why water boils at a lower temperature at high altitude.
Solution: Solid-Liquid Coexistence, Pressure Melting of Ice
For the ice-water transition: J/mol, K, m/mol.
The negative slope means increasing pressure lowers the melting point:
At atm: K, so ice melts at approximately K. This is the Principle behind ice skating: the pressure under the blade slightly lowers the melting point, Creating a thin lubricating layer of water.
6.5 Worked Example: Phase Diagram Construction
Section titled “6.5 Worked Example: Phase Diagram Construction”Solution: Estimating the Triple Point
Given for a substance: normal boiling point K at atm, normal melting point K at atm, J/mol, J/mol, and m/mol.
At the triple point, the solid-gas, solid-liquid, and liquid-gas coexistence curves meet. To Estimate, we find where the sublimation curve meets the vaporisation curve.
For the sublimation curve: J/mol.
\ln\frac{P_{\mathrm{sub}}{P_0} = -\frac{L_s}{R}\left(\frac{1}{T} - \frac{1}{T_0}\right)}At K on the sublimation curve (assuming solid-gas equilibrium at the melting point at low ):
For the vaporisation curve at K:
The triple point is where the sublimation and vaporisation curves intersect. In this simplified Model (neglecting the curvature of the solid-liquid line), the triple point is near atm, K. More accurate treatment requires integrating both curves and finding Their intersection numerically.
7. The Boltzmann Distribution
Section titled “7. The Boltzmann Distribution”7.1 Derivation from the Microcanonical Ensemble
Section titled “7.1 Derivation from the Microcanonical Ensemble”Consider a system in thermal contact with a large heat reservoir at temperature . The Total energy is conserved.
The probability that is in state with energy is proportional to the number of Microstates of the reservoir:
Since the reservoir is large, expand to first order:
Where we used (the thermodynamic definition of Temperature). Therefore:
Normalising:
This is the Boltzmann distribution (canonical ensemble).
7.2 Connection to Thermodynamics
Section titled “7.2 Connection to Thermodynamics”From the partition function, all thermodynamic quantities follow:
- Internal energy:
- Entropy:
- Helmholtz free energy:
- Pressure:
- Heat capacity:
7.3 Worked Example: Two-Level System
Section titled “7.3 Worked Example: Two-Level System”A system has two energy levels: and .
At high (): and (equipartition). At low (): and (Schottky anomaly).
8. Partition Functions
Section titled “8. Partition Functions”8.1 Molecular Partition Function
Section titled “8.1 Molecular Partition Function”For a single molecule, the total partition function factors into contributions from different Degrees of freedom:
8.2 Translational Partition Function
Section titled “8.2 Translational Partition Function”For a particle of mass in a box of volume :
In the continuum limit (replace sum with integral):
Where is the quantum concentration.
Derivation. Using :
8.3 Rotational Partition Function
Section titled “8.3 Rotational Partition Function”For a rigid rotor (diatomic molecule) with moment of inertia :
At high temperature (), the sum can be approximated by an integral:
For a heteronuclear diatomic, we multiply by the symmetry number . For a homonuclear Diatomic, (exchange of identical nuclei gives indistinguishable configurations).
8.4 Vibrational Partition Function
Section titled “8.4 Vibrational Partition Function”For a harmonic oscillator with frequency :
The mean vibrational energy is:
The first term is the zero-point energy.
9. The Ideal Gas
Section titled “9. The Ideal Gas”9.1 Classical Ideal Gas
Section titled “9.1 Classical Ideal Gas”For distinguishable particles, . For indistinguishable particles:
The factor corrects for overcounting (Gibbs paradox).
Proof (Gibbs paradox). Without the factor, the entropy is not Extensive: mixing two identical gases gives . With Using Stirling’s approximation:
Which is now extensive.
9.2 Equation of State
Section titled “9.2 Equation of State”From the translational partition function:
This recovers the ideal gas law .
9.3 Maxwell-Boltzmann Speed Distribution
Section titled “9.3 Maxwell-Boltzmann Speed Distribution”The probability distribution for the speed of a molecule in an ideal gas at temperature :
Characteristic speeds:
- Most probable speed:
- Mean speed:
- Root-mean-square speed:
9.4 Equipartition Theorem
Section titled “9.4 Equipartition Theorem”Theorem 9.1 (Equipartition). Each quadratic degree of freedom in the Hamiltonian contributes to the average energy.
Proof. If contains a term or with Then:
So . Similarly for momentum terms.
This gives and where is the number of quadratic Degrees of freedom.
9.5 Kinetic Theory of Gases
Section titled “9.5 Kinetic Theory of Gases”Mean Free Path
Section titled “Mean Free Path”The mean free path is the average distance a molecule travels between Collisions.
Theorem 9.2 (Mean free path). For a gas of hard-sphere molecules of diameter in volume :
Where is the number density.
Proof. A molecule of diameter sweeps out a cylinder of cross-section (per collision cross-section for identical particles, the effective cross-section is But the relative velocity correction introduces the factor ). In time The molecule travels and sweeps volume . The Number of collisions is So the mean free path is:
For the correct treatment, one must use the mean relative velocity. Since both colliding molecules are moving, the relative speed is times the mean speed:
Numerical example. For air at STP ( m, m):
The collision frequency is s.
Transport Properties
Section titled “Transport Properties”Viscosity. The shear viscosity of a dilute gas:
Substituting :
A key prediction: viscosity is independent of density for a dilute gas (Maxwell’s result, Verified experimentally). This is because but the momentum Transfer per collision is proportional to the number of molecules per unit volume, giving .
Thermal conductivity. For a monatomic gas:
Where for a monatomic gas. The ratio is predicted to be a Universal constant (Eucken’s formula).
Diffusion (self-diffusion). The self-diffusion coefficient:
Theorem 9.3 (Einstein relation). The diffusion coefficient is related to mobility by:
This is a consequence of the fluctuation-dissipation theorem.
Solution: Worked Example, Viscosity of Nitrogen
For N at K: kg, m.
The experimental value is PaS. The discrepancy is due to the hard-sphere model being an approximation; real molecules have softer repulsive potentials.
Derivation of the Maxwell-Boltzmann Speed Distribution
Section titled “Derivation of the Maxwell-Boltzmann Speed Distribution”Theorem 9.4. The speed distribution for molecules in an ideal gas at temperature is:
Proof. In the canonical ensemble, the probability of a molecule having momentum is Proportional to . The velocity distribution is:
To find the speed distribution, transform to spherical coordinates in velocity space and integrate over angles:
Characteristic speeds from . The most probable speed maximises :
The mean speed:
The RMS speed:
10. Quantum Statistical Mechanics
Section titled “10. Quantum Statistical Mechanics”10.1 Identical Particles and Indistinguishability
Section titled “10.1 Identical Particles and Indistinguishability”Classical particles are distinguishable. Quantum particles are not. There are two types:
- Fermions (half-integer spin): obey the Pauli exclusion principle; the total wavefunction is antisymmetric under particle exchange.
- Bosons (integer spin): the total wavefunction is symmetric under particle exchange.
10.2 Fermi-Dirac Statistics
Section titled “10.2 Fermi-Dirac Statistics”For fermions, each state can be occupied by at most one particle. The occupation number is or .
The average occupation number:
Derivation from the grand canonical ensemble. The grand partition function for a single state at Energy :
The Fermi energy is the chemical potential at : .
The Fermi temperature: .
Density of states for a 3D free electron gas:
The total number of electrons:
10.3 Bose-Einstein Statistics
Section titled “10.3 Bose-Einstein Statistics”For bosons, any number of particles can occupy a single state:
The chemical potential for bosons must satisfy (lowest single-particle Energy) to ensure .
Derivation. For a single bosonic state:
10.4 Bose-Einstein Condensation
Section titled “10.4 Bose-Einstein Condensation”For an ideal Bose gas in 3D, the critical temperature is:
Where is the particle density and .
Below The chemical potential is essentially zero (), and a macroscopic Fraction of particles condense into the ground state:
Derivation. The number of particles in excited states is:
This has a maximum value at . When The excess Particles must go to the ground state. Setting at Gives the critical temperature above.
10.5 Comparison of the Three Statistics
Section titled “10.5 Comparison of the Three Statistics”In the classical (dilute) limit All three reduce to the Maxwell-Boltzmann distribution. This occurs when (dilute gas) or for Fermions.
10.6 Worked Example: Electron Gas in Metals
Section titled “10.6 Worked Example: Electron Gas in Metals”For copper: one conduction electron per atom, m.
At room temperature ( K), So the gas is deeply degenerate. The heat Capacity is:
This is much smaller than the classical prediction Explaining why electrons Contribute negligibly to the heat capacity of metals at room temperature.
11. Grand Canonical Ensemble
Section titled “11. Grand Canonical Ensemble”11.1 Definition
Section titled “11.1 Definition”The grand canonical ensemble describes a system that can exchange both energy and particles with A reservoir at temperature and chemical potential .
The grand partition function:
The probability of finding the system in state with particles:
11.2 Connection to Thermodynamics
Section titled “11.2 Connection to Thermodynamics”This follows from the Euler relation for the grand potential .
Key relations:
- Average particle number:
- Pressure:
- Entropy:
11.3 Fluctuations
Section titled “11.3 Fluctuations”The number fluctuations in the grand canonical ensemble:
Where is the isothermal compressibility. For an Ideal gas, this gives Consistent With Poisson …/4-statistics-and-probability/2_statistics.
12. Fluctuation-Dissipation Theorem
Section titled “12. Fluctuation-Dissipation Theorem”12.1 Energy Fluctuations
Section titled “12.1 Energy Fluctuations”In the canonical ensemble:
Proof. .
This is a manifestation of the fluctuation-dissipation theorem: the response of the system () is related to the equilibrium fluctuations.
12.2 General Fluctuation-Dissipation Relation
Section titled “12.2 General Fluctuation-Dissipation Relation”For a general observable coupled to its conjugate field via :
Where is the susceptibility. This connects the Linear response of a system to its spontaneous fluctuations.
13. Blackbody Radiation
Section titled “13. Blackbody Radiation”13.1 Planck Distribution
Section titled “13.1 Planck Distribution”Treating electromagnetic radiation in a cavity as a gas of non-interacting photons (bosons with ):
The spectral energy density (energy per unit volume per unit frequency):
Derivation. The density of photon states in a cavity of volume is . Each photon has energy And the mean occupation Number is the Bose-Einstein distribution with :
13.2 Stefan-Boltzmann Law
Section titled “13.2 Stefan-Boltzmann Law”The total energy density:
Substituting :
The Stefan-Boltzmann law for radiated power per unit area:
13.3 Wien’s Displacement Law
Section titled “13.3 Wien’s Displacement Law”The peak of occurs at:
This follows from maximising with respect to .
13.4 Detailed Derivation of Planck’s Law
Section titled “13.4 Detailed Derivation of Planck’s Law”Theorem 13.1 (Planck’s law). The spectral radiance of a blackbody is:
Proof. Consider electromagnetic modes in a cavity of volume with periodic boundary Conditions. The allowed wavevectors are with . The number of modes with wavevector magnitude between and (counting two Polarisations) is:
Converting to frequency using and :
Each mode is a quantum harmonic oscillator with energy . Since photons are Bosons with (photon number is not conserved), the mean occupation number is:
The energy in modes between and is:
The spectral energy density is :
Historical note. Planck originally derived this result in 1900 by interpolating between the Rayleigh-Jeans law (valid at low frequencies, ) and Wien’s law (valid At high frequencies, ). The Rayleigh-Jeans law Leads to the “ultraviolet catastrophe”, infinite total energy, which Planck resolved by Postulating that energy is quantised in units of .
13.5 Derivation of the Stefan-Boltzmann Law
Section titled “13.5 Derivation of the Stefan-Boltzmann Law”Theorem 13.2 (Stefan-Boltzmann). The total radiated power per unit area from a blackbody is:
Proof. Integrate the spectral energy density:
Substituting :
The integral .
The radiated power per unit area (intensity) relates to the energy density by (the Factor of accounts for the projection effect and the average of over the Hemisphere):
13.6 Wien’s Displacement Law
Section titled “13.6 Wien’s Displacement Law”Theorem 13.3 (Wien’s displacement law). The peak of occurs at:
Proof. Express the spectral energy density in terms of wavelength :
Setting and substituting :
This transcendental equation has the solution Giving .
Solution: Worked Example, Temperature of the Sun's Surface
The Sun’s emission peaks at nm (green). Using Wien’s law:
The total radiated power per unit area:
With solar radius m, the total luminosity is:
This matches the measured solar luminosity to within a few percent, validating blackbody theory.
14. The Ising Model
Section titled “14. The Ising Model”14.1 Definition
Section titled “14.1 Definition”The Ising model is a lattice of spin-1/2 variables with Hamiltonian:
Where is the coupling constant, denotes nearest neighbours, and is an External magnetic field.
- : ferromagnetic (spins tend to align).
- : antiferromagnetic (spins tend to anti-align).
14.2 Exact Solution in 1D
Section titled “14.2 Exact Solution in 1D”Theorem 14.1 (Ising, 1925). The 1D Ising model has no phase transition at .
Proof sketch. Using the transfer matrix method, the partition function for spins with Periodic boundary conditions is:
Where .
In the thermodynamic limit (), (the larger eigenvalue dominates).
The magnetisation per spin is:
For : And for all . There is no spontaneous magnetisation, hence no phase transition.
14.3 Mean-Field Approximation
Section titled “14.3 Mean-Field Approximation”Replace the interaction of spin with its neighbours by the mean field :
Where is the coordination number. The self-consistency equation:
For A non-zero solution exists when .
The critical exponents in mean-field theory: , , .
14.4 Landau Theory of Phase Transitions
Section titled “14.4 Landau Theory of Phase Transitions”The Landau theory provides a phenomenological description of second-order phase transitions using a Free energy expanded in the order parameter :
Where and .
- For : the minimum is at (disordered phase).
- For : the minimum is at (ordered phase).
Specific heat jump. The entropy has a discontinuity at :
Limitations. Landau theory neglects fluctuations and gives incorrect critical exponents in low Dimensions. It is exact in mean-field (infinite-range) models and above the upper critical dimension .
14.5 Scaling and Critical Exponents
Section titled “14.5 Scaling and Critical Exponents”Near a critical point, thermodynamic quantities follow power laws:
| Quantity | Power law | Exponent |
|---|---|---|
| Order parameter () | ||
| Susceptibility | ||
| Specific heat | ||
| Correlation length |
The scaling relations (from the homogeneity hypothesis):
These are verified experimentally and by renormalisation group calculations.
15. The Microcanonical Ensemble
Section titled “15. The Microcanonical Ensemble”15.1 Definition and Fundamental Postulate
Section titled “15.1 Definition and Fundamental Postulate”The microcanonical ensemble describes an isolated system with fixed energy Volume And Particle number . The fundamental postulate of statistical mechanics states:
All accessible microstates of an isolated system are equally probable.
For a classical system, the number of microstates with energy between and is:
The factor makes dimensionless (and is justified by quantum mechanics), and accounts for indistinguishability.
15.2 Connection to Thermodynamics
Section titled “15.2 Connection to Thermodynamics”Definition (Microcanonical temperature). The temperature is defined by:
Definition (Microcanonical pressure).
Definition (Microcanonical chemical potential).
15.3 The Ideal Gas in the Microcanonical Ensemble
Section titled “15.3 The Ideal Gas in the Microcanonical Ensemble”Theorem 15.1 (Sackur-Tetrode equation). The entropy of a monatomic ideal gas is:
Proof. For non-interacting particles, . The number of Microstates with total energy between and is the volume of a spherical shell in -dimensional momentum space:
The factor is the shell thickness in radius. Taking the logarithm:
Using Stirling’s approximation and :
The terms (from the shell thickness) are negligible compared to the Terms in the thermodynamic limit.
This is the Sackur-Tetrode equation, which gives the absolute entropy of a monatomic ideal gas. It satisfies the third law in the sense that as Indicating the Breakdown of the classical description at low temperatures.
15.4 Derivation of the Canonical Ensemble from the Microcanonical Ensemble
Section titled “15.4 Derivation of the Canonical Ensemble from the Microcanonical Ensemble”Theorem 15.2. A small subsystem of a large microcanonical ensemble obeys the Boltzmann Distribution.
Proof. Consider a total system with energy composed of subsystem (with Energy ) and reservoir (with energy ). The probability that is in a specific microstate with energy is:
P(E_S) = \frac{\Omega_R(E_{\mathrm{tot} - E_S)}{\Omega_{\mathrm{tot}(E_{\mathrm{tot})}}}}Since the reservoir is large, expand to first order:
Using :
Normalising gives the Boltzmann distribution .
Solution: Worked Example, Entropy of Mixing Revisited
Two ideal gases, each with particles at the same and Are separated by a partition. The partition is removed. Find .
Before mixing: each gas occupies volume . The total entropy is .
After mixing: each gas occupies volume . The total entropy is:
From the Sackur-Tetrode equation, the change for each gas is:
If the gases are different: .
If the gases are identical: removing the partition does nothing observable. The total entropy is (using correction), and . The factor in The partition function automatically resolves this paradox.
16. The Canonical Ensemble, Detailed Treatment
Section titled “16. The Canonical Ensemble, Detailed Treatment”16.1 Derivation of Thermodynamic Quantities
Section titled “16.1 Derivation of Thermodynamic Quantities”The canonical partition function is for a discrete spectrum, or
For a classical system.
Theorem 16.1. All thermodynamic quantities follow from :
| Quantity | Formula |
|---|---|
| Internal energy | |
| Helmholtz free energy | |
| Entropy | |
| Pressure | |
| Chemical potential | |
| Heat capacity |
Proof (energy and heat capacity).
16.2 The Classical Partition Function for an Ideal Gas
Section titled “16.2 The Classical Partition Function for an Ideal Gas”Theorem 16.2. The classical partition function for indistinguishable ideal gas particles is:
Where is the thermal de Broglie wavelength.
Proof. For non-interacting particles, :
Using the Gaussian integral :
From this, all ideal gas thermodynamics follows: , , .
17. Problem Set
Section titled “17. Problem Set”Problem 1: Entropy change in free expansion
Problem. One mole of ideal gas doubles its volume in a free expansion (no heat exchange, no Work done). Calculate . Does this violate the second law?
Solution. For a free expansion, and So and (ideal gas). The entropy change is:
This does not violate the second law. The second law states . For the system, . For the surroundings, (no heat exchanged). So Consistent with an Irreversible process.
If you get this wrong, revise: Section 1.4 (Clausius inequality) and Section 9.2 (ideal gas Entropy).
Problem 2: Carnot efficiency with given temperatures
Problem. A Carnot engine operates between K and K, absorbing 1000 J per Cycle from the hot reservoir. Find , And .
Solution.
If you get this wrong, revise: Section 4.1 (Carnot cycle) and Theorem 1.1 (Carnot’s theorem).
Problem 3: Maxwell relation for a general equation of state
Problem. A gas obeys (van der Waals). Use a Maxwell relation to Find .
Solution. Using :
Integrating at constant :
If you get this wrong, revise: Section 3.1 (Maxwell relation derivation) and Section 3.3 (applications).
Problem 4: Heat capacity relation for a solid
Problem. A solid has K, PaMolar volume m/mol, and J/(molK). Find and .
Solution.
For a solid at room temperature, is small (a few percent of ).
If you get this wrong, revise: Section 1.6 (thermodynamic response functions) and Theorem 1.2.
Problem 5: Helmholtz free energy of a paramagnet
Problem. A paramagnetic system of non-interacting spin-1/2 particles in a magnetic field Has energy levels per particle ( is the Bohr magneton). Find , And .
Solution. Single-particle partition function: .
At high : (Curie’s law). At : (saturation).
If you get this wrong, revise: Section 7.1 (Boltzmann distribution) and Section 7.3 (two-level System).
Problem 6: Partition function of a quantum harmonic oscillator
Problem. A 1D quantum harmonic oscillator has . Calculate , And . Find the high- and low-temperature limits.
Solution.
High (): , (equipartition). Low (): (zero-point energy), exponentially.
If you get this wrong, revise: Section 8.4 (vibrational partition function) and Section 9.4 (equipartition).
Problem 7: Fermi energy of a 3D electron gas
Problem. Sodium has one conduction electron per atom, atomic mass g/mol, density Kg/m. Calculate the Fermi energy and Fermi temperature .
Solution. Number density: m.
If you get this wrong, revise: Section 10.2 (Fermi-Dirac …/4-statistics-and-probability/2_statistics) and Section 10.6 (electron Gas in metals).
Problem 8: Bose-Einstein condensation temperature
Problem. rubidium-87 atoms are trapped in a harmonic potential. Estimate the BEC Transition temperature. ( kg.)
Solution. For a harmonic trap, the density of states is where . The BEC condition Is :
Assuming Hz:
This is consistent with experimental BEC observations in laser-cooled atom traps.
If you get this wrong, revise: Section 10.3 (Bose-Einstein …/4-statistics-and-probability/2_statistics) and Section 10.4 (BEC).
Problem 9: Chemical potential of a classical ideal gas
Problem. Show that the chemical potential of a classical ideal gas is Where and is the thermal de Broglie wavelength. Discuss the sign of .
Solution. From :
When (classical regime, dilute gas or high ): . When (approaching quantum degeneracy): . For fermions, in the degenerate Regime ().
If you get this wrong, revise: Section 9.2 (equation of state) and Section 10.5 (comparison of Statistics).
Problem 10: Entropy of a spin system
Problem. A system of non-interacting spin-1/2 particles in zero magnetic field. What Is the total entropy? If a field is applied and all spins align, what is ?
Solution. In zero field, all microstates are equally probable:
When all spins are aligned (one microstate):
This is the maximum entropy change achievable by applying a magnetic field to a spin system, and Forms the basis of magnetic cooling (adiabatic demagnetisation refrigeration).
If you get this wrong, revise: Section 5.1 (Boltzmann entropy) and Section 5.2 (Gibbs entropy).
Problem 11: Blackbody radiation in a cavity
Problem. A cavity of volume cm is maintained at K. Find the total Radiant energy inside and the radiation pressure on the walls.
Solution. Total energy density:
Total energy: J.
Radiation pressure: Pa.
If you get this wrong, revise: Section 13.2 (Stefan-Boltzmann law) and Section 13.1 (Planck Distribution).
Problem 12: Clausius-Clapeyron application
Problem. The vapour pressure of benzene is 75 mmHg at C and 300 mmHg at C. Estimate the enthalpy of vaporisation and the normal boiling point.
Solution. From the integrated Clausius-Clapeyron equation:
Normal boiling point ( mmHg):
(Experimental value: C, showing good agreement.)
If you get this wrong, revise: Section 6.2 (Clausius-Clapeyron equation) and Section 6.4 (worked examples).
Problem 13: Grand canonical partition function of a single orbital
Problem. A single quantum orbital at energy is in contact with a reservoir at Chemical potential and temperature . Calculate and for (a) fermions and (b) bosons.
Solution.
(a) Fermions: .
(since for )
(b) Bosons: .
Note: boson fluctuations are larger than fermion fluctuations at the same .
If you get this wrong, revise: Section 10.2 (Fermi-Dirac), Section 10.3 (Bose-Einstein), and Section 11 (grand canonical ensemble).
Problem 14: Ising model mean-field critical temperature
Problem. For a 2D square lattice Ising model with coupling and Use mean-field Theory to find . The exact result (Onsager, 1944) is . Compare.
Solution. The coordination number is . Mean-field theory gives:
Exact result:
The ratio: . Mean-field theory Overestimates by 76% in 2D, because fluctuations (neglected in mean-field) are large in two Dimensions.
If you get this wrong, revise: Section 14.3 (mean-field approximation) and the Common Pitfall Box in Section 14.
Problem 15: Deriving the Sackur-Tetrode equation
Problem. Starting from the microcanonical ensemble, derive the Sackur-Tetrode equation for the Entropy of a monatomic ideal gas. State all assumptions.
Solution. See Theorem 15.1 for the full derivation. Key assumptions:
- Particles are non-interacting (ideal gas).
- Particles are indistinguishable (Gibbs factor ).
- Classical phase space is quantised in units of .
- Thermodynamic limit (, , ).
If you get this wrong, revise: Section 15.3 (ideal gas in the microcanonical ensemble).
Problem 16: Transport coefficients from kinetic theory
Problem. Estimate the thermal conductivity of argon at STP. ( kg, m, per atom.)
Solution. Mean free path: .
With m:
Mean speed: m/s.
The experimental value is approximately 0.018 W/(mK), reasonable agreement for the hard-sphere Model.
If you get this wrong, revise: Section 9.5 (kinetic theory, transport properties).
Problem 17: Landau theory specific heat jump
Problem. A system undergoes a second-order phase transition at K described by Landau theory with J/(molK) and J/mol. Calculate the order parameter at K and the specific heat jump at .
Solution. Order parameter below :
Specific heat jump:
If you get this wrong, revise: Section 14.4 (Landau theory) and Section 6.1 (classification of Phase transitions).
Problem 18: Grand canonical fluctuations
Problem. For an ideal gas in the grand canonical ensemble, show that the relative number Fluctuation is .
Solution. The grand partition function for an ideal gas factorises into single-particle Contributions. Each single-particle state contributes independently, so the particle number is a sum of independent Bernoulli-like random variables. By the central limit theorem:
(Poisson …/4-statistics-and-probability/2_statistics for an ideal gas.)
For : relative fluctuations are Completely negligible
- the grand canonical and canonical ensembles are equivalent for macroscopic systems.
If you get this wrong, revise: Section 11.3 (grand canonical fluctuations) and Section 12 (fluctuation-dissipation theorem).
Problem 19: Wien's law and stellar classification
Problem. A star has peak emission at nm. (a) What is its surface Temperature? (b) What spectral class does it belong to? (c) What is the total power radiated per Square metre?
Solution.
(a) K K.
(b) A surface temperature of K corresponds to spectral class A (white stars, like Sirius).
(c) W/m.
If you get this wrong, revise: Section 13.3 (Wien’s displacement law) and Section 13.2 (Stefan-Boltzmann law).
Problem 20: Free energy and phase equilibrium
Problem. The Gibbs free energy of a substance near its melting point is given by: J/mol and J/mol (valid for near the melting point). Find and .
Solution. At the melting point, :
Latent heat:
We can verify with the Clausius-Clapeyron equation if is known.
If you get this wrong, revise: Section 2.3 (physical meaning of potentials), Section 2.5 (equilibrium conditions), and Section 6.2 (Clausius-Clapeyron).
18. Nonequilibrium Thermodynamics
Section titled “18. Nonequilibrium Thermodynamics”13.1 Entropy Production and the Second Law
Section titled “13.1 Entropy Production and the Second Law”For a system not in equilibrium, the second law takes the form:
Where is the entropy exchange with the environment (can be positive or negative) and is the entropy production rate (always non-negative).
For coupled transport processes (heat flow and particle flow driven by and ):
13.2 Onsager Reciprocal Relations
Section titled “13.2 Onsager Reciprocal Relations”In the linear regime (small gradients), the fluxes are linear functions of the forces:
Onsager’s theorem: The Onsager coefficients satisfy (when the forces and fluxes are chosen as conjugate pairs). This is a consequence of microscopic reversibility and has important implications:
- Thermoelectric effects: The Seebeck coefficient and Peltier coefficient are related: (Kelvin relation).
- Cross-diffusion: The diffusivity of species A in a gradient of species B equals the diffusivity of B in a gradient of A.
13.3 Boltzmann Transport Equation
Section titled “13.3 Boltzmann Transport Equation”The Boltzmann equation describes the evolution of the distribution function :
The collision integral is often approximated by the relaxation time approximation:
Where is the equilibrium (Maxwell—Boltzmann) distribution and is the relaxation time.
The -theorem: Define . The Boltzmann equation implies With equality only at equilibrium. This is the microscopic basis of the second law.
13.4 Fick’s Law and Diffusion
Section titled “13.4 Fick’s Law and Diffusion”Fick’s first law: where is the diffusion coefficient.
Fick’s second law (diffusion equation): .
Einstein relation: where is the mobility.
Green’s function solution (point source at origin, ):
The mean squared displacement: .
Worked Example 13.1: Thermal Diffusion (Soret Effect)
In a mixture of two gases with a temperature gradient, particles tend to migrate toward the cold end. The mass flux includes a thermal diffusion term:
Where is the thermal diffusion coefficient. The Soret coefficient characterises the strength of the effect.
For a — mixture of He— He below 2 K, is large and positive: He migrates toward the warm end. This is exploited in He— He dilution refrigerators, the workhorses of millikelvin physics.
The steady-state concentration gradient is:
For K and K across a 10 cm column:
19. Kinetic Theory in Detail
Section titled “19. Kinetic Theory in Detail”14.1 Maxwell—Boltzmann Distribution
Section titled “14.1 Maxwell—Boltzmann Distribution”The velocity distribution of an ideal gas at temperature :
Speed distribution (integrating over angles):
Characteristic speeds:
- Most probable:
- Mean:
- RMS:
14.2 Mean Free Path and Collisions
Section titled “14.2 Mean Free Path and Collisions”The mean free path for hard-sphere molecules of diameter :
The factor accounts for the relative motion of the scattering partners.
The collision frequency: .
For air at STP ( m, m):
14.3 Transport Coefficients
Section titled “14.3 Transport Coefficients”Viscosity (gas): .
Thermal conductivity: where is the specific heat per unit mass.
Self-diffusion: .
Chapman—Enskog theory gives more accurate expressions with numerical corrections:
Worked Example 14.1: Effusion Through a Small Hole
A container of nitrogen ( amu, K) has a small hole of area . The effusion rate (molecules per second escaping):
At Pa, K: m.
For : molecules/s.
Knudsen effusion: The ratio of effusion rates for two gases with masses and :
This is the basis for isotope separation by gaseous diffusion.
20. Information Theory and Statistical Mechanics
Section titled “20. Information Theory and Statistical Mechanics”15.1 Shannon Entropy
Section titled “15.1 Shannon Entropy”The Shannon entropy of a probability distribution :
This is mathematically identical to the Boltzmann entropy (up to the constant ), providing a deep connection between information theory and thermodynamics.
Maximum entropy principle: The least biased probability distribution, given constraints (e.g., fixed mean energy), is the one that maximises the Shannon entropy. This reproduces the canonical ensemble: maximising subject to gives the Boltzmann distribution.
15.2 Landauer’s Principle
Section titled “15.2 Landauer’s Principle”Erasing one bit of information in a memory element necessarily dissipates at least:
Of energy as heat. This establishes a fundamental lower bound on the energy cost of computation.
Reversible computation: If no information is erased (e.g., in logically reversible operations like NOT), no energy dissipation is required in principle. This motivates research into reversible computing architectures.
15.3 Maxwell’s Demon
Section titled “15.3 Maxwell’s Demon”Maxwell’s demon appears to violate the second law by sorting fast and slow molecules, creating a temperature difference from an initially uniform gas without doing work.
Resolution (Bennett, 1982): The demon must acquire information about molecular speeds (measurement) and then erase this information to reset its memory. By Landauer’s principle, erasing the information costs at least per bit, exactly compensating the entropy decrease of the gas. The second law is upheld: .
Worked Example 15.1: Maximum Entropy Distribution
Find the probability distribution on that maximises subject to the constraint (fixed mean).
Using Lagrange multipliers:
Normalising : (geometric distribution).
The constraint So .
For : , .
This shows that the exponential (geometric) distribution arises from maximum entropy with a constraint on the mean value --- a deep connection between information theory and statistical physics.
Common Pitfalls (Additional)
Section titled “Common Pitfalls (Additional)”Onsager relations require careful force-flux pairing: The reciprocal relations hold only when the forces and fluxes are properly chosen as conjugate pairs (both contributing positively to ). An incorrect pairing can lead to wrong cross-coefficients.
The relaxation time approximation is not exact: Setting assumes a single relaxation time for all processes. In reality, depends on velocity (energy), and different scattering processes have different time scales. The approximation works well for order-of-magnitude estimates but fails for quantitatively accurate transport predictions.
Effusion vs. Hydrodynamic flow: Effusion (molecular flow through a small hole) occurs when the hole diameter is much smaller than the mean free path ( Knudsen number ). For larger holes (), hydrodynamic flow (described by the Navier—Stokes equations) dominates. The transition between regimes is important in vacuum systems.
Landauer’s bound is per bit, not per operation: Only logically irreversible operations (those that erase information) incur the cost. Logically reversible operations (e.g., swapping two bits) have no minimum energy cost in principle, though real physical implementations always have some dissipation.
Maximum entropy is not the same as most probable: The maximum entropy distribution is the least biased distribution consistent with the constraints. It may not be the distribution you would observe in a specific realisation. The ergodic hypothesis connects time averages to ensemble averages, but the convergence can be very slow for systems with long-range interactions or glassy dynamics.
Problems (Additional)
Section titled “Problems (Additional)”Problem 21: Thermal Conductivity of a Gas
Calculate the thermal conductivity of argon at STP using kinetic theory.
Data: amu, m, (monatomic), m.
Compare with the experimental value of W/(mK) and comment on the discrepancy.
Solution:
Mean speed: m/s.
Mean free path: nm.
The kinetic theory prediction (0.039) overestimates the experimental value (0.0177) by about a factor of 2.2. This discrepancy is systematic and is resolved by the Chapman—Enskog theory, which gives:
Still an overestimate; the remaining discrepancy is due to the hard-sphere model not accurately representing the real intermolecular potential of argon (which has an attractive well that reduces the effective collision cross-section at lower temperatures).
Problem 22: Boltzmann $H$-Theorem
(a) Show that for a spatially uniform gas, the Boltzmann equation with the BGK collision operator leads to where .
(b) Identify the equilibrium state where .
Solution:
(a) For a spatially uniform gas with no external forces: .
Since (number conservation):
Using the Gibbs inequality (since with equality at ):
Since for (with equality at ), the integrand So .
Therefore .
(b) requires everywhere, i.e., the distribution is Maxwell—Boltzmann. This is the equilibrium state, as expected.
21. Statistical Mechanics of Interacting Systems
Section titled “21. Statistical Mechanics of Interacting Systems”16.1 The Ising Model Revisited
Section titled “16.1 The Ising Model Revisited”The 1D Ising model was solved exactly by Ising (1925) using the transfer matrix method. The 2D Ising model was solved by Onsager (1944), providing one of the most important exact results in statistical mechanics.
Correlation functions: The spin-spin correlation function:
For the 1D chain with . The correlation length:
As : (critical point).
Scaling near : The correlation function takes the scaling form:
Where is a critical exponent ( for the 2D Ising model).
16.2 Renormalisation Group (Conceptual)
Section titled “16.2 Renormalisation Group (Conceptual)”The renormalisation group (RG) provides a framework for understanding critical phenomena. The key idea: progressively integrate out short-wavelength fluctuations, rescaling, and look for fixed points.
RG flow diagram:
- Start with a Hamiltonian with coupling constants .
- Integrate out short-wavelength modes (thin out the lattice).
- Rescale lengths: ().
- Rescale spins: .
- Repeat.
Fixed points: Values of the coupling constants that are invariant under RG transformation. Fixed points correspond to scale-invariant theories (critical points).
- Gaussian fixed point: The mean-field critical exponents (, ).
- Wilson—Fisher fixed point: The nontrivial fixed point of the theory in dimensions, giving non-mean-field exponents.
- IR-stable fixed point: Controls the low-energy (long-wavelength) physics.
epsilon expansion: Expand in . At one loop:
Setting : .
The critical exponents to order :
For (): (compare with the numerical value ).
16.3 Mean-Field Theory of Phase Transitions
Section titled “16.3 Mean-Field Theory of Phase Transitions”The Landau free energy for a scalar order parameter near :
Mean-field exponents: (jump in ), , , , .
These are exact above the upper critical dimension . Below Fluctuations modify the exponents (as computed by the epsilon expansion).
Ginzburg criterion: Mean-field theory is valid when the fluctuation contribution to the free energy is small compared to the mean-field part:
This gives a Ginzburg temperature below which fluctuations become important. For conventional superconductors ( nm, K): (mean-field is excellent). For high- superconductors ( nm, K): (fluctuations are important, explaining the broad fluctuation regime above ).
Worked Example 16.1: RG Flow for the Gaussian Model
Consider the Gaussian (free field) model: .
After thinning out modes in the shell and rescaling:
- Integrate out short-wavelength modes: the correlation function transforms as .
- The rescaled coupling: (since has dimensions of mass and we rescale ).
The RG flow for : (relevant operator).
This means grows under RG, flowing away from the Gaussian fixed point (). The fixed point is unstable, indicating that the disordered phase (, is stable) is separated from the ordered phase by the critical point.
The correlation length exponent: Giving (the mean-field value).
Worked Examples
Section titled “Worked Examples”Example 1: Carnot efficiency
Section titled “Example 1: Carnot efficiency”Problem. A Carnot engine operates between and . Find the maximum efficiency.
Solution. .
Example 2: Entropy change
Section titled “Example 2: Entropy change”Problem. Find the entropy change when of ice at melts ().
Solution. .
Intuition
Section titled “Intuition”Thermodynamics is the universe’s accounting system. The first law is a balance sheet: energy can change form but the total never changes. Temperature measures the average kinetic energy of particles, like a crowd’s average excitement level. Entropy tracks how many microscopic arrangements correspond to the same macroscopic state, so it measures information disorder. The second law says the universe’s entropy always increases because there are overwhelmingly more disordered states than ordered ones. Carnot efficiency is the theoretical maximum because it assumes no wasted motion, like a frictionless machine. Statistical mechanics bridges the microscopic and macroscopic by counting microstates.
Common Pitfalls
Section titled “Common Pitfalls”- Confusing heat, temperature, and internal energy. Temperature is a state variable; heat is energy transfer due to temperature difference; internal energy is the total kinetic energy of particles. Fix: (first law); is a state function, and are path-dependent.
- Wrong entropy interpretation. Entropy is a state function; . Fix: The second law states for all processes; entropy of an isolated system never decreases.
- Confusing microstates and macrostates. Macrostate: specified by macroscopic variables. Microstate: specific arrangement of particles. Fix: where is the number of microstates.
flowchart TD A[Thermodynamics] --> B[Macroscopic: Laws of Thermodynamics] A --> C[Microscopic: Statistical Mechanics] B --> D[Zeroth: Thermal Equilibrium] B --> E[First: Energy Conservation] B --> F[Second: Entropy Increases] B --> G[Third: T=0 Unattainability] C --> H[Microstates and Multiplicity] C --> I[Boltzmann Distribution] C --> J[Ensembles] J --> K[Microcanonical: Fixed E,N,V] J --> L[Canonical: Fixed T,N,V] J --> M[Grand Canonical: Fixed T,V,mu] I --> N[Partition Function Z] N --> O[Free Energy: F = -kT ln Z] O --> P[All Thermodynamic Quantities]Summary
Section titled “Summary”- First law: ; conservation of energy.
- Second law: ; entropy of an isolated system never decreases.
- Carnot efficiency: (maximum possible for given temperatures).
- Statistical mechanics: ; Boltzmann distribution: .
import { Citation } from “@components/Citations.astro”
<Citations sources={[ {title=“Thermodynamics and an Introduction to Thermostatistics”, author=“Callen”, year=“1985”, type=“book”}, {title=“Statistical Mechanics”, author=“Pathria”, year=“2017”, type=“book”}, {title=“An Introduction to Thermal Physics”, author=“Schroeder”, year=“2021”, type=“book”}, ]} />
Counterexamples worth knowing by name
Section titled “Counterexamples worth knowing by name”| Claim | True? | Counterexample |
|---|---|---|
| Energy conservation implies heat flows from hot to cold | no | all four laws together forbid it; a cup of tea cooling does not violate the first law, it violates the second |
| Entropy always increases | no | it is non-decreasing; it is constant in an idealised reversible process, and it decreases in an open system |
| A reversible process is one that happens slowly | no | slowness is neither necessary nor sufficient; a frictionless piston moving slowly is near-reversible, a violently stirred bath is not |
| The second law holds in every corner of the universe | no | fluctuations can decrease entropy locally over short times, at a cost elsewhere; this is Gibbs fluctuation theorem territory |
| Two systems in thermal contact are at the same temperature | not always | only if thermal equilibrium is actually reached; the zeroth law is what makes that statement well posed |
| Every isolated system reaches equilibrium | no in practice | some systems are metastable or kinetically trapped; glasses are the standard example |
| for any process | no | only for reversible paths; the entropy change of a state function is path independent, the heat is not |
| Phase transitions are first order | no | the critical point is second order, and third-order and higher transitions exist |
| The canonical and microcanonical ensembles give the same answer | no | they agree only in the thermodynamic limit; finite systems differ, and the difference is measurable |
The first row is the one worth internalising: every one of the four laws is consistent with the others in isolation, and the second law cannot be derived from the first three. That is why it has to be stated rather than proved.
The last row is the one that most often surprises people at research level. For a system of particles the ensembles agree to leading order in but differ at order , and that difference is the entire basis of fluctuation theorems and of numerical work on finite systems.
Where the research frontier is
Section titled “Where the research frontier is”- Fluctuation theorems. The second law holds on average, not instance by instance. Jarzynski’s equality and the Crooks relation turn that asymmetry into an exact, measurable statement about the distribution of work done on a system driven out of equilibrium.
- Nonequilibrium steady states. Linear response gives the fluctuation- dissipation theorem; away from equilibrium there is a fluctuating hydrodynamic theory, and its consistency conditions are still being worked out.
- Thermodynamic geometry. Taking Fisher information as a Riemannian metric on parameter space gives a natural curvature tensor. It is not the Levi- Civita curvature — the relation between them is subtle and still studied — so treating thermodynamic and geometric curvature as the same object is a common and instructive mistake.
- Phase transitions and criticality. Renormalisation group methods and the study of non-universal behaviour at critical points remain active, with much of the current work on quantum criticality and on systems far from equilibrium.
- Information thermodynamics. Landauerer’s principle gives the work cost of erasing a bit, but the tension between information as physical and information as abstract is unresolved in its general form.
Interleaving problems
Section titled “Interleaving problems”Mix these with material from Lagrangian Mechanics, Microcanonical Ensemble, Stochastic Calculus and Spectral Theory.
- (Microcanonical.) Show that the equipartition theorem gives for degrees of freedom, and explain why each quadratic degree of freedom contributes exactly regardless of its coefficient.
- (Lagrangian.) Derive Hamilton’s equations from the canonical partition function , and identify which step requires the result to be an extensive logarithm.
- (Stochastic analysis.) The Langevin equation is a deterministic force law plus Brownian noise. Write it in the Itô and Stratonovich conventions, explain why the two differ, and say which one the overdamped limit of physical Brownian motion actually satisfies.
- (Spectral theory.) The Boltzmann operator on has a continuous spectrum whose spectral measures are the occupation numbers. Show the connection to the spectral theorem for self-adjoint operators, and say what the gap in the spectrum means for the equilibrium state.
- (Linear algebra.) Compute the partition function of a two-level system directly and via the trace of an explicit matrix, and check the two agree. This is the same identity the spectral-theoretic route uses.
- (Research.) The second law constrains typical behaviour; fluctuation theorems constrain the tails. Formulate a version of the second law that survives at , and say what it costs in strength.