States and pullback of observables [fdip-002B]

How can a model describe many possible fields and average what we observe? A law on a finite set of configurations assigns probability weights to those fields and averages their observables. The 16 binary fields on the four-cycle give a concrete example: summing weights over configurations with the same retained values produces the retained law. These probability weights are chosen independently of the edge energies. Real probability weights on binary fields are distinct from real-valued field coordinates. Observable algebras and normalized functionals express this operation without assuming a finite configuration set.

A supplied algebra map pulls a functional back by precomposition. Over the reals or complexes, positivity and the involution determine which functionals are states; the real dual-number example explains why the hypotheses matter. Coordinate restriction then pulls polynomial observables back. For real fields with infinitely many configurations, reference measure and Gaussian integrability give the corresponding expectations.