Plain-English statement
- Correct each original value/gradient reply using known quadratic data. For every adaptive program and fuel, this preserves the actual regularized execution, including its state, halt/exhaustion outcome and query count.
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Proof architecture
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Lean statement
theorem simulate_regularized
{E S X : Type*} [NormedAddCommGroup E] [InnerProductSpace ℝ E] [CompleteSpace E]
(next : S → Sum X E) (update : S → E → (ℝ × E) → S)
{f : E → ℝ} (hd : Differentiable ℝ f) (hc : ConvexOn ℝ univ f)
{β δ : ℝ≥0} (hL : LipschitzWith β (gradient f)) (u : E) (fuel : ℕ) (s : S) :
let W := fun x => f x + (δ : ℝ)/2*‖x-u‖^2
let corrected := fun s x (a : ℝ × E) =>
update s x (a.1 + (δ : ℝ)/2*‖x-u‖^2, a.2 + (δ : ℝ) • (x-u))
let base := run next corrected (fun x => (f x, gradient f x)) fuel s
let target := run next update (fun x => (W x, gradient W x)) fuel s
base = target ∧ base.2 ≤ fuel := by
dsimp only
have hg := (QuadraticRegularizationFirstOrder.curvature_gradient_and_smoothness
hd hc hL (δ := δ) u).2.2.1
induction fuel generalizing s with
| zero => cases h : next s <;> simp [run, h]
| succ n ih =>
cases h : next s with
| inl x => simp [run, h]
| inr x =>
have step (upd : S → E → (ℝ × E) → S) (O : E → ℝ × E) :
run next upd O (n+1) s =
let tail := run next upd O n (upd s x (O x))
(tail.1, tail.2+1) := by rw [run, h]
simp only [step, hg]
obtain ⟨he, hn⟩ := ih (update s x
(f x + (δ : ℝ)/2*‖x-u‖^2, gradient f x + (δ : ℝ) • (x-u)))
refine ⟨?_, Nat.succ_le_succ hn⟩
simpa only [hg] using congrArg (fun r => (r.1, r.2+1)) he
end AutoSamplingTheory.TechnicalLemmas.Analysis.QuadraticRegularizationOracle
Open AutoSamplingTheory/TechnicalLemmas/Analysis/QuadraticRegularizationOracle.lean:33published source at 0e31a3cda412
Proof architecture
Actual adaptive first-order oracle execution with one original reply per regularized reply.
Lean proof walkthrough
- Read the quantified variables and typeclass brackets as part of the mathematical statement; inferred arguments are not missing assumptions.
- `have` creates a named intermediate mathematical fact.
- `rw` rewrites by an established identity.
- `simp` normalizes through registered definitional and theorem rewrites.
- `refine` instantiates a reusable theorem while leaving explicit subgoals.
- `simpa` closes the goal after a controlled simplification of a typed result.
Why the statement has this shape
The declaration is kept at the reusable level recorded by its Registry tags and direct consumers. Explicit measures, spaces, wrappers, and regularity hypotheses expose interfaces that paper notation often infers. A theorem card explains those interfaces but never widens the compiled statement.
Hidden assumptions and non-claims
- Genuine differentiability is localized to the hypotheses shown in the Lean statement.