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IndisputableMonolith.Foundation.DAlembert.AnalyticBridge

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This module defines the log-lift of a cost function to bridge discrete cost structures with continuous d'Alembert equations in log-coordinates. Researchers deriving physics from the Recognition Composition Law would cite it when translating multiplicative costs into hyperbolic metrics. The module consists of definitions for the lift and supporting consistency results that prepare the curvature and entanglement gates.

claimThe log-lift $G(t) := F(e^t)$ of a cost function $F$, with associated $H$ and consistency properties under the curvature condition $ds^2 = G''(t) dt^2$.

background

The module sits in the Foundation.DAlembert namespace and imports Cost for the base cost function together with the three gate modules. CurvatureGate requires that the log-coordinate representation $G(t) = F(e^t)$ yields a 1D metric via $ds^2 = G''(t) dt^2$. EntanglementGate enforces nonzero cross-derivatives in the combiner $P$. NecessityGates shows that symmetry plus normalization alone fail to force the full d'Alembert/RCL structure.

proof idea

This is a definition module, no proofs. It introduces the log-lift via G_of and H_of, then records consistency lemmas such as log_consistency and the boundary and ODE results that follow from the lift.

why it matters in Recognition Science

The module supplies the analytic translation layer that the DAlembert gates rely on to connect cost functions to the Recognition Composition Law. It prepares the geometric setting in which the forcing chain (T5 J-uniqueness through T8 D=3) can be recovered from the curvature and entanglement conditions.

scope and limits

depends on (4)

Lean names referenced from this declaration's body.

declarations in this module (24)