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IndisputableMonolith.Foundation.DAlembert.AnalyticBridge

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This module supplies the log-lift of a cost function as the analytic bridge inside the d'Alembert development. Researchers formalizing RCL necessity cite it to connect cost metrics to the curvature and entanglement gates. The module organizes the argument by importing Cost, NecessityGates, EntanglementGate, and CurvatureGate without internal proofs.

claimThe log-lift $G(t) = F(e^t)$ of a cost function $F$, equipped with the 1D metric $ds^2 = G''(t) dt^2$ and the cross-derivative condition on the combiner $P$.

background

The module resides in Foundation.DAlembert and imports Cost together with three gate modules. CurvatureGate states that the cost metric must have constant nonzero curvature, realized by the log-coordinate representation $G(t) = F(e^t)$ with $ds^2 = G''(t) dt^2$. EntanglementGate requires the combiner $P$ to satisfy $\partial^2 P / \partial u \partial v eq 0$. NecessityGates records that symmetry, normalization, $C^2$ regularity, calibration, and existence of some $P$ do not force the d'Alembert/RCL structure, as shown by the counterexample in Counterexamples.lean. The module doc comment identifies its central object as the log-lift of a cost function.

proof idea

This is a definition module, no proofs.

why it matters in Recognition Science

The module supplies the analytic bridge that feeds the curvature and entanglement characterizations into the necessity argument for the Recognition Composition Law. It directly supports the d'Alembert development whose parent results appear in the NecessityGates and CurvatureGate modules. No used_by edges are recorded, indicating it functions as an internal connector rather than a terminal theorem.

scope and limits

depends on (4)

Lean names referenced from this declaration's body.

declarations in this module (24)