Complexity as information in spin-glass Gibbs states and metastates: upper bounds at nonzero temperature and long-range models

In classical finite-range spin systems, especially those with disorder such as spin glasses, a low-temperature Gibbs state may be a mixture of a number of pure or ordered states; the complexity of the Gibbs state has been defined in the past roughly as the logarithm of this number, assuming the question is meaningful in a finite system. As non-trivial mixtures of pure states do not occur in finite size, in a recent paper [Phys. Rev. E 101, 042114 (2020)] H\"oller and the author introduced a definition of the complexity of an infinite-size Gibbs state as the mutual information between the pure state and the spin configuration in a finite region, and applied this also within a metastate construction. (A metastate is a probability distribution on Gibbs states.) They found an upper bound on the complexity for models of Ising spins in which each spin interacts with only a finite number of others, in terms of the surface area of the region, for all $T\geq 0$. In the present paper, the complexity of a metastate is defined likewise in terms of the mutual information between the Gibbs state and the spin configuration. Upper bounds are found for each of these complexities for general finite-range (i.e. short- or long-range, in a sense we define) mixed $p$-spin interactions of discrete or continuous spins (such as $m$-vector models), but only for $T>0$. For short-range models, the bound reduces to the surface area. For long-range interactions, the definition of a Gibbs state has to be modified, and for these models we also prove that the states obtained within the metastate constructions are Gibbs states under the modified definition. All results are valid for a large class of disorder distributions.
Comment: Just over 30 pages. v2: minor changes. v3: filled gap in proof of Prop. 2; published version plus minor corrections