In probability theory and statistical mechanics, a Gibbs state is an equilibrium probability distribution which remains invariant under future evolution of the system.
For example, a stationary or steady-state distribution of a Markov chain, such as that achieved by running a Markov chain Monte Carlo iteration for a sufficiently long time, is a Gibbs state.
to be a Gibbs state is In physics there may be several physically distinct Gibbs states in which a system may be trapped, particularly at lower temperatures.
They are named after Josiah Willard Gibbs, for his work in determining equilibrium properties of statistical ensembles.
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