Propagation of Chaos and Residual Dependence in Gibbs Measures on Finite Sets

<jats:title>Abstract</jats:title> <jats:p>We compare a mean-field Gibbs distribution on a finite state space on <jats:italic>N</jats:italic> spins to that of an explicit simple mixture of product measures. This illustrates the situation beyond the so-called <jats:italic>increasing propagation of chaos</jats:italic> introduced by Ben Arous and Zeitouni [3], where marginal distributions of size <jats:inline-formula> <jats:alternatives> <jats:tex-math>$$k=o(N)$$</jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>k</mml:mi> <mml:mo>=</mml:mo> <mml:mi>o</mml:mi> <mml:mo>(</mml:mo> <mml:mi>N</mml:mi> <mml:mo>)</mml:mo> </mml:mrow> </mml:math> </jats:alternatives> </jats:inline-formula> are compared to product measures.</jats:p>