Download lean/OAI/Analysis/BernoulliCone/CompactGradient.lean from roseking/openAI-math-dataset: direct link, hf CLI and curl.
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1.54 kB
| import OAI.Analysis.BernoulliCone.HalfspaceDifferential | |
| namespace OAI | |
| section | |
| noncomputable section | |
| open MeasureTheory Set Filter Metric | |
| open scoped Topology NNReal ENNReal ContDiff | |
| namespace Bernoulli | |
| open scoped _root_.Bernoulli | |
| variable {d : ℕ} | |
| lemma integral_gradient_compact {q : Space d → ℝ} {K : ℝ≥0} | |
| (hq : LipschitzWith K q) (hc : HasCompactSupport q) (e : Space d) : | |
| (∫ x, inner ℝ (gradient q x) e) = 0 := by | |
| have hh := (LipschitzWith.const (1:ℝ)).integral_lineDeriv_mul_eq | |
| (μ:=volume) hq hc (-e) | |
| have he : (fun x => lineDeriv ℝ q x (-(-e)) * (1:ℝ)) =ᵐ[volume] | |
| (fun x => inner ℝ (gradient q x) e) := by | |
| filter_upwards [hq.ae_differentiableAt] with x hx | |
| simp only [neg_neg,mul_one,hx.lineDeriv_eq_fderiv,inner_gradient_left] | |
| rw [integral_congr_ae he] at hh | |
| have hz (x : Space d) : lineDeriv ℝ (fun _ : Space d => (1:ℝ)) x (-e)=0 := by | |
| rw [(differentiableAt_const (1:ℝ)).lineDeriv_eq_fderiv] | |
| simp | |
| simpa only [hz,zero_mul,integral_zero] using hh.symm | |
| lemma setIntegral_gradient_compact {q : Space d → ℝ} {K : ℝ≥0} | |
| (hq : LipschitzWith K q) (hc : HasCompactSupport q) | |
| {D : Set (Space d)} (hD : tsupport q ⊆ D) (e : Space d) : | |
| (∫ x in D, inner ℝ (gradient q x) e) = 0 := by | |
| rw [setIntegral_eq_integral_of_forall_compl_eq_zero] | |
| · exact integral_gradient_compact hq hc e | |
| · intro x hx | |
| have hn : x∉tsupport q := fun hh => hx (hD hh) | |
| simp [gradient,fderiv_of_notMem_tsupport ℝ hn] | |
| end Bernoulli | |
| end | |
| end | |
| end OAI | |