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Lecture# Canonical Distribution: Gibbs Entropy and Ensembles

Description

This lecture covers the derivation of the canonical distribution based on Gibbs's entropy and a maximum entropy principle. Starting with the microcanonical ensemble, the instructor explains the Lagrange multiplier method to enforce normalized probability. Moving on to the canonical ensemble, the lecture explores the constant-temperature case and the connection between Lagrange multipliers and thermodynamic variables. The discussion extends to systems with particles in external potentials, illustrating how energy depends on position and how this affects the probability distribution. Throughout, the focus is on maximizing entropy while respecting thermodynamic constraints.

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In course

Instructor

MSE-421: Statistical mechanics

This course presents an introduction to statistical mechanics geared towards materials scientists. The concepts of macroscopic thermodynamics will be related to a microscopic picture and a statistical

Related concepts (26)

Canonical ensemble

In statistical mechanics, a canonical ensemble is the statistical ensemble that represents the possible states of a mechanical system in thermal equilibrium with a heat bath at a fixed temperature. The system can exchange energy with the heat bath, so that the states of the system will differ in total energy. The principal thermodynamic variable of the canonical ensemble, determining the probability distribution of states, is the absolute temperature (symbol: T).

Thermodynamics

Thermodynamics is a branch of physics that deals with heat, work, and temperature, and their relation to energy, entropy, and the physical properties of matter and radiation. The behavior of these quantities is governed by the four laws of thermodynamics which convey a quantitative description using measurable macroscopic physical quantities, but may be explained in terms of microscopic constituents by statistical mechanics.

Boltzmann distribution

In statistical mechanics and mathematics, a Boltzmann distribution (also called Gibbs distribution) is a probability distribution or probability measure that gives the probability that a system will be in a certain state as a function of that state's energy and the temperature of the system. The distribution is expressed in the form: where pi is the probability of the system being in state i, exp is the exponential function, εi is the energy of that state, and a constant kT of the distribution is the product of the Boltzmann constant k and thermodynamic temperature T.

Ensemble (mathematical physics)

In physics, specifically statistical mechanics, an ensemble (also statistical ensemble) is an idealization consisting of a large number of virtual copies (sometimes infinitely many) of a system, considered all at once, each of which represents a possible state that the real system might be in. In other words, a statistical ensemble is a set of systems of particles used in statistical mechanics to describe a single system. The concept of an ensemble was introduced by J. Willard Gibbs in 1902.

Thermodynamic operation

A thermodynamic operation is an externally imposed manipulation that affects a thermodynamic system. The change can be either in the connection or wall between a thermodynamic system and its surroundings, or in the value of some variable in the surroundings that is in contact with a wall of the system that allows transfer of the extensive quantity belonging that variable. It is assumed in thermodynamics that the operation is conducted in ignorance of any pertinent microscopic information.