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๐ŸฅตThermodynamics Unit 14 Review

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14.2 Probability and statistical ensembles

๐ŸฅตThermodynamics
Unit 14 Review

14.2 Probability and statistical ensembles

Written by the Fiveable Content Team โ€ข Last updated September 2025
Written by the Fiveable Content Team โ€ข Last updated September 2025
๐ŸฅตThermodynamics
Unit & Topic Study Guides

Statistical ensembles are the backbone of thermodynamics, helping us understand how microscopic behavior leads to macroscopic properties. They're collections of identical systems, each representing a possible microstate, that bridge the gap between the tiny world of particles and the observable world around us.

Probability plays a crucial role in determining which microstates a system occupies. The Boltzmann distribution tells us that lower energy states are more likely, especially at cooler temperatures. Different ensemble types - microcanonical, canonical, and grand canonical - help us model various real-world scenarios.

Probability and Statistical Ensembles

Concept of statistical ensembles

  • Large collection of identical systems, each representing a possible microstate (configuration) of the system characterized by particle positions and momenta
  • Describes macroscopic properties based on collective behavior of microscopic components
  • Ensemble average of a physical quantity corresponds to macroscopic value observed in experiments (temperature, pressure)
  • Bridges gap between microscopic and macroscopic descriptions of a system in statistical mechanics

Probability in microstates

  • Probability of a system being in a particular microstate depends on microstate energy and system temperature
  • Boltzmann distribution describes probability $p_i$ of a system in microstate with energy $E_i$ at temperature $T$: $p_i = \frac{e^{-E_i / k_B T}}{\sum_j e^{-E_j / k_B T}}$
    • $k_B$ = Boltzmann constant
    • Denominator = partition function $Z$, normalizes probabilities
  • Lower energy microstates more probable than higher energy microstates
  • As temperature increases, probability distribution becomes more uniform, system explores wider range of microstates (gas molecules, spin systems)

Types of statistical ensembles

  • Microcanonical ensemble (NVE):
    • Isolated system with fixed number of particles (N), volume (V), and total energy (E)
    • All accessible microstates with same energy have equal probability
  • Canonical ensemble (NVT):
    • System in thermal contact with heat bath at fixed temperature (T)
    • Fixed number of particles (N) and volume (V)
    • System exchanges energy with heat bath, microstate probability given by Boltzmann distribution
  • Grand canonical ensemble (ฮผVT):
    • System exchanges energy and particles with reservoir at fixed temperature (T) and chemical potential (ฮผ)
    • Fixed volume (V)
    • Microstate probability depends on energy and number of particles (ideal gas, adsorption)

Microstate probability distributions

  • Microcanonical ensemble: equal probability for each accessible microstate $p_i = \frac{1}{\Omega(E)}$, $\Omega(E)$ = number of microstates with energy E
  • Canonical ensemble: Boltzmann distribution $p_i = \frac{e^{-E_i / k_B T}}{Z}$, $Z = \sum_j e^{-E_j / k_B T}$ = canonical partition function
  • Grand canonical ensemble: probability of microstate with energy $E_i$ and $N_i$ particles $p_i = \frac{e^{-(E_i - \mu N_i) / k_B T}}{\Xi}$, $\Xi = \sum_{j,N} e^{-(E_j - \mu N_j) / k_B T}$ = grand canonical partition function