Statistical mechanics

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Statistical mechanics is a branch of physics that applies probability theory, which includes mathematical statistics, to a large assembly of particles, in order to simplify the description of complex systems. Statistical mechanics provides a framework for relating the microscopic properties of individual atoms and molecules to the macroscopic or bulk properties of materials that can be observed in everyday life, therefore explaining thermodynamics as a result of statistics.

Overview[edit]

Statistical mechanics is fundamental to the natural sciences. It is necessary for the fundamental study of any physical system that has many degrees of freedom. The approach is based on statistical methods, probability theory and the microscopic physical laws.

It can be used to explain the thermodynamic behaviour of large systems. This branch of statistical mechanics, which treats and extends classical thermodynamics, is known as statistical thermodynamics or equilibrium statistical mechanics.

History[edit]

The field of statistical mechanics was pioneered in the late 19th century by James Clerk Maxwell, Ludwig Boltzmann, and J. Willard Gibbs. These scientists attempted to explain the behavior of systems of particles in thermal equilibrium in terms of their microscopic properties and behaviors.

Principles[edit]

Statistical mechanics provides a bridge between the macroscopic world of thermodynamics and the microscopic world of atoms and molecules. It uses statistics to explain and predict the behavior of a mechanical system whose state is uncertain. A common use of statistical mechanics is in explaining the thermodynamic behavior of large systems.

Applications[edit]

Statistical mechanics is used in many fields, including condensed matter physics, quantum field theory, quantum mechanics, quantum information theory, complex systems, thermodynamics, and particle physics.

See also[edit]

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  • Gibbs - Elementary principles in statistical mechanics
    Gibbs - Elementary principles in statistical mechanics

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