  The Constraint Satisfaction Problem (CSP) and its counting counterpart
appears under different guises in many areas of mathematics, computer science,
and elsewhere. Its structural and algorithmic properties have demonstrated to
play a crucial role in many of those applications. For instance, in the
decision CSPs, structural properties of the relational structures
involved---like, for example, dismantlability---and their logical
characterizations have been instrumental for determining the complexity and
other properties of the problem. Topological properties of the solution set
such as connectedness are related to the hardness of CSPs over random
structures. Additionally, in approximate counting and statistical physics,
where CSPs emerge in the form of spin systems, mixing properties and the
uniqueness of Gibbs measures have been heavily exploited for approximating
partition functions and free energy.
  In spite of the great diversity of those features, there are some eerie
similarities between them. These were observed and made more precise in the
case of graph homomorphisms by Brightwell and Winkler, who showed that
dismantlability of the target graph, connectedness of the set of homomorphisms,
and good mixing properties of the corresponding spin system are all equivalent.
In this paper we go a step further and demonstrate similar connections for
arbitrary CSPs. This requires much deeper understanding of dismantling and the
structure of the solution space in the case of relational structures, and new
refined concepts of mixing introduced by Brice\~no. In addition, we develop
properties related to the study of valid extensions of a given partially
defined homomorphism, an approach that turns out to be novel even in the graph
case. We also add to the mix the combinatorial property of finite duality and
its logic counterpart, FO-definability, studied by Larose, Loten, and Tardif.
