production module
AutoSamplingTheory.TechnicalLemmas.Analysis.GradientFlowPL
Read the mathematical statements and proofs in order
1 named declarations scanned from AutoSamplingTheory/TechnicalLemmas/Analysis/GradientFlowPL.lean.
Declarations
theorem AutoSamplingTheory.TechnicalLemmas.Analysis.GradientFlowPL.dissipation_and_decay Partial Not mapped
Read the complete mathematical statement and proof, with Lean below each
- Actual gradient dynamics imply energy dissipation and the PL objective rate, including the initial and final endpoints of a finite nonnegative time interval.
theorem dissipation_and_decay {f : E → ℝ} {X : ℝ → E} {z : E} {α T : ℝ}
(_hα : 0 < α) (_hT : 0 ≤ T) (hf : Differentiable ℝ f)
(hX : ContinuousOn X (Icc 0 T))
(hflow : ∀ t ∈ Ico 0 T,
HasDerivWithinAt X (-gradient f (X t)) (Ici t) t)
(hz : IsMinOn f univ z)
(hpl : ∀ x, 2 * α * (f x - f z) ≤ ‖gradient f x‖ ^ 2) :
(∀ t ∈ Ico 0 T, HasDerivWithinAt (f ∘ X)
(-‖gradient f (X t)‖ ^ 2) (Ici t) t) ∧
∀ t ∈ Icc 0 T, 0 ≤ f (X t) - f z ∧
f (X t) - f z ≤ (f (X 0) - f z) * Real.exp (-2 * α * t) := by
have hd : ∀ t ∈ Ico 0 T, HasDerivWithinAt (f ∘ X)
(-‖gradient f (X t)‖ ^ 2) (Ici t) t := by
intro t ht
have hgrad : HasFDerivAt f (InnerProductSpace.toDual ℝ E (gradient f (X t))) (X t) :=
(hf (X t)).hasGradientAt
have h := hgrad.comp_hasDerivWithinAt t (hflow t ht)
simpa only [InnerProductSpace.toDual_apply_apply, inner_neg_right,
real_inner_self_eq_norm_sq] using h
refine ⟨hd, ?_⟩
intro t ht
refine ⟨sub_nonneg.mpr (hz (mem_univ (X t))), ?_⟩
have hc : ContinuousOn (fun u => f (X u) - f z) (Icc 0 T) :=
(hf.continuous.comp_continuousOn hX).sub continuousOn_const
have hg := le_gronwallBound_of_liminf_deriv_right_le
(f := fun u => f (X u) - f z) (f' := fun u => -‖gradient f (X u)‖ ^ 2)
(δ := f (X 0) - f z) (K := -(2 * α)) (ε := 0) hc
(fun u hu r hr => by
simpa [Function.comp_def, slope] using
((hd u hu).sub_const (f z)).liminf_right_slope_le hr)
le_rfl
(fun u _ => by nlinarith [hpl (X u)]) t ht
simpa [gronwallBound_ε0, sub_zero, neg_mul] using hg
end AutoSamplingTheory.TechnicalLemmas.Analysis.GradientFlowPL
AutoSamplingTheory/TechnicalLemmas/Analysis/GradientFlowPL.lean:22published source at 0e31a3cda412Open detailed card