Pith. sign in
module module high

IndisputableMonolith.Action.EulerLagrange

show as:
view Lean formalization →

The module derives the Euler-Lagrange equation for the cost-rate action S[γ] = ∫ J(γ(t)) dt, reducing it to J'(q) = 0 because the Lagrangian L(q, q̇) = J(q) carries no velocity dependence. Researchers deriving equations of motion from the Recognition Science variational principle cite these results when moving from the action functional to dynamics. The argument applies the standard EL formula directly to the velocity-independent case after convexity of the action is secured upstream.

claimFor the action functional \(S[\gamma] = \int_a^b J(\gamma(t))\,dt\) with Lagrangian \(L(q,\dot q)=J(q)\), the Euler-Lagrange equation reduces to \(J'(q)=0\).

background

The module sits inside the variational setup of PathSpace, which defines admissible paths as continuous strictly positive functions on closed intervals together with the J-action integral and fixed-endpoint relations. Upstream, Cost.Convexity proves J(x) = ½(x + x⁻¹) - 1 is strictly convex on ℝ₊, while FunctionalConvexity establishes convexity of the full integral functional S[γ] and removes the conditional h_min witness. The local theoretical setting is the principle of least action applied to the d'Alembert cost functional J.

proof idea

The module assembles a chain of lemmas (costRateELHolds, costRateEL_const_one, costRateEL_implies_const_one, costRateEL_iff_const_one) that verify the EL equation for the cost-rate action. Each step applies the standard partial derivative ∂L/∂q = J'(q) and sets the result to zero, using the velocity independence already noted in the module doc-comment. The structure is a sequence of direct algebraic reductions and equivalences rather than deep tactic sequences.

why it matters in Recognition Science

This module supplies the equations of motion obtained from the J-action and is imported by the Hamiltonian module to construct the Legendre transform and Hamilton's equations. It fills the variational step that connects the action functional to dynamics in the Recognition Science framework, resting on the convexity results that support T5 J-uniqueness. The downstream Hamiltonian doc-comment explicitly references the small-strain limit of the same J-action.

scope and limits

used by (1)

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

depends on (4)

Lean names referenced from this declaration's body.

declarations in this module (12)