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LeanPool.ParameterFreeGradient.V7.Proofs.Stage5AboveTwoLower.LocalityBridge

Neighborhood equality of smooth objective values determines the complete exact oracle pair.

theorem V7.Stage5AboveTwoLower.observe_eq_of_eventually_value_eq {d : ℕ} (oracle₁ oracle₂ : PairOracle d) (x : Point d) (hgrad₁ : O3.IsCoordinateGradient oracle₁.value oracle₁.gradient) (hgrad₂ : O3.IsCoordinateGradient oracle₂.value oracle₂.gradient) (hlocal : oracle₁.value =ᶠ[nhds x] oracle₂.value) :

Once two differentiable smoothing values agree on a neighbourhood, their exact value-gradient observations agree at the centre. Thus the analytic content of exact-pair locality is precisely neighbourhood stability of the infimal convolution, not a separate gradient oracle assumption.

The minimal analytic bridge still needed from the concrete infimal convolution: equality of the original objectives on the closed smoothing ball must make the two smoothed value functions equal on a neighbourhood of the centre. The strict boundary inequality of the kernel is what supplies the required interior slack.

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    Smoothing a convex one-Lipschitz objective produces an oracle with the exact coordinate gradient.

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      theorem V7.Stage5AboveTwoLower.exact_pair_locality_of_neighborhood_stability {p : ℝ} {d : ℕ} (kernel : SmoothingKernelData p d) (hgradient : SmoothingCoordinateGradientCore kernel) (hstable : LocalSmoothingNeighborhoodStability kernel) (chi : ℝ) :
      0 < chi → ∀ (ell₁ ell₂ : Point d → ℝ), O3.IsConvexObjective ell₁ → IsOneLipschitz p ell₁ → O3.IsConvexObjective ell₂ → IsOneLipschitz p ell₂ → ∀ (x : O3.Vec d), (∀ (v : Point d), lpNorm p v ≤ chi → ell₁ (x + v) = ell₂ (x + v)) → O3.PairOracle.observe (kernel.smooth chi ell₁) x = O3.PairOracle.observe (kernel.smooth chi ell₂) x

      Neighbourhood stability plus the already required coordinate-gradient interface is sufficient for the frozen exact value-gradient locality clause.