Plain-English statement
- The step `2/(α+β)` gives the sharp uniform curvature-envelope contraction. Its factor minimizes the endpoint max-envelope over every real step. The `α=0` boundary is nonexpansive, and `α=β` is retained.
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Proof architecture
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Lean statement
theorem optimal_gradient_step {f : E → ℝ} {α β : ℝ}
(hf : ContDiff ℝ 2 f) (hsc : StrongConvexOn univ α f)
(hα : 0 ≤ α) (hβ : 0 < β) (hαβ : α ≤ β)
(hu : ∀ x y, f y ≤ f x + inner ℝ (gradient f x) (y - x) + β / 2 * ‖y - x‖ ^ 2)
(x y : E) :
‖(y - (2 / (α + β)) • gradient f y) - (x - (2 / (α + β)) • gradient f x)‖ ≤
((β - α) / (α + β)) * ‖y - x‖ ∧
∀ h : ℝ, (β - α) / (α + β) ≤ max |1 - h * α| |1 - h * β| := by
have hD : 0 < α + β := add_pos_of_nonneg_of_pos hα hβ
have hq : 0 ≤ (β - α) / (α + β) := div_nonneg (sub_nonneg.mpr hαβ) hD.le
have ha : 1 - 2 / (α + β) * α = (β - α) / (α + β) := by field_simp; ring
have hb : 1 - 2 / (α + β) * β = -((β - α) / (α + β)) := by field_simp; ring
constructor
· have hc := gradient_step_endpoint_bound hf hsc (show 0 ≤ 2 / (α + β) by positivity) hu x y
simpa only [ha, hb, abs_neg, abs_of_nonneg hq, max_self] using hc
· intro h
let M := max |1 - h * α| |1 - h * β|
have ha' : 1 - h * α ≤ M := (le_abs_self _).trans (le_max_left _ _)
have hb' : -(1 - h * β) ≤ M := (neg_le_abs _).trans (le_max_right _ _)
apply (div_le_iff₀ hD).mpr
have h1 := mul_le_mul_of_nonneg_left ha' hβ.le
have h2 := mul_le_mul_of_nonneg_left hb' hα
nlinarith
end AutoSamplingTheory.TechnicalLemmas.Analysis.GradientDescentOptimalStep
Open AutoSamplingTheory/TechnicalLemmas/Analysis/GradientDescentOptimalStep.lean:102published source at 0e31a3cda412
Proof architecture
Balanced step 2/(alpha+beta) gives factor (beta-alpha)/(alpha+beta), minimizing the endpoint envelope over all real steps.
Lean proof walkthrough
- Read the quantified variables and typeclass brackets as part of the mathematical statement; inferred arguments are not missing assumptions.
- `intro` introduces quantified hypotheses into the local proof context.
- `have` creates a named intermediate mathematical fact.
- `apply` reduces the goal to the hypotheses of a reusable theorem.
- `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
- No additional hidden-contract keyword was inferred; the exact Lean hypotheses remain controlling.