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Explain the Lean lemma `deriv_pos_self_zero` in module `IndisputableMonolith.Cost.FunctionalEquation`. Write for an educated reader who knows science and programming but may not know Lean. Cover: (1) what the declaration says in plain English, (2) why it matters in Recognition Science, (3) how to read the formal statement, (4) visible dependencies or certificates in the supplied source, and (5) what this declaration does not prove. Cite only declarations present in the supplied Recognition source.

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Explanation of deriv_pos_self_zero in IndisputableMonolith.Cost.FunctionalEquation

(1) What the declaration says in plain English

The lemma deriv_pos_self_zero states: if h is any differentiable function from the reals to the reals, if its derivative equals the function itself at every point, and if h is zero at the origin, then h must be the zero function everywhere. This is the uniqueness statement for the simple linear ODE h' = h with zero initial condition.

(2) Why it matters in Recognition Science

The lemma belongs to the helper infrastructure for the T5 cost-uniqueness argument inside the FunctionalEquation module. It is used to conclude that certain auxiliary deviation functions (arising when comparing candidate solutions to the reciprocal-symmetric cost) must vanish identically, thereby supporting the claim that the J-cost form is the unique solution satisfying the required symmetry and normalization.

(3) How to read the formal statement

lemma deriv_pos_self_zero (h : ℝ → ℝ)
    (h_diff : Differentiable ℝ h)
    (h_deriv : ∀ t, deriv h t = h t)
    (h_h0 : h 0 = 0) :
    ∀ t, h t = 0

In ordinary mathematical language: Let h : ℝ → ℝ be differentiable. Assume deriv(h)(t) = h(t) for every real t and h(0) = 0. Then h(t) = 0 for every real t.

(4) Visible dependencies or certificates in the supplied source

The source shows the proof begins by forming the auxiliary function h(s) · exp(−s), applies the product rule via deriv_mul, substitutes the ODE assumption to obtain a zero derivative, invokes is_const_of_deriv_eq_zero to deduce constancy, and finally uses the initial condition h(0) = 0 together with positivity of the exponential to conclude the constant is zero. The lemma sits inside the ODE-uniqueness section of the same module that also contains the companion lemma deriv_neg_self_zero and the d'Alembert identities used for the broader functional-equation argument.

(5) What this declaration does not prove

It does not establish existence of solutions, does not address higher-order smoothness, and does not by itself prove the full T5 uniqueness theorem for the J-cost. The supplied source truncates the proof body, so the complete internal steps and any downstream usage certificates are only partially visible.

cited recognition theorems

outside recognition

Aspects Recognition does not yet address:

  • Complete proof body of deriv_pos_self_zero (source is truncated after the product-rule step)
  • Explicit invocation sites or certificates showing how the lemma is used inside the main T5 result

recognition modules consulted

The Recognition library is at github.com/jonwashburn/shape-of-logic. The model is restricted to the supplied Lean source and instructed not to invent theorem names. Treat output as a starting point, not a verified proof.