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abbrev definition def or abbrev high

isMinimizer

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isMinimizer is the predicate asserting that a state achieves the global minimum of the strain cost functional J. RRF modelers cite it when proving equilibrium properties or invariance of argmin under monotone transforms such as exponentiation. The declaration is a one-line abbreviation that forwards directly to the core definition in the StrainFunctional module.

claimA state $x$ is a minimizer of the strain functional if for every state $y$ the cost of $x$ is at most the cost of $y$, i.e., $x$ is weakly preferred to $y$ under the strain ordering.

background

In the RRF glossary the strain functional J measures deviation from balance, with the governing law that J tends to zero. The predicate isMinimizer is introduced as the canonical name for the property that a state realizes the infimum of J. It is defined via the weaklyBetter relation on states, which compares costs directly without reference to specific dynamics or channels.

proof idea

One-line wrapper that applies the definition of isMinimizer from StrainFunctional, which expands to the universal quantification forall y, weaklyBetter x y.

why it matters in Recognition Science

The abbreviation supplies the uniform vocabulary required by downstream results such as equilibria_are_minimizers (which shows balanced states are minimizers under non-negative strain) and the quadratic-model theorems that preserve argmin under exp. It directly supports the J to 0 law stated in the module documentation as the fundamental drive of the Recognition framework.

scope and limits

formal statement (Lean)

  53abbrev isMinimizer {State : Type*} := StrainFunctional.isMinimizer (State := State)

proof body

Definition body.

  54
  55/-! ## Key Properties (as propositions) -/
  56
  57/-- The "J → 0" law: strain minimization is the fundamental drive. -/

used by (8)

From the project-wide theorem graph. These declarations reference this one in their body.

depends on (9)

Lean names referenced from this declaration's body.