Mem W01p of mem W1p of tsupport subset
DeGiorgi.memW01p_of_memW1p_of_tsupport_subset
Plain-language statement
Localization by compact support: a finite-p Sobolev function whose support is compactly contained in an open set belongs to W₀^{1,p}.
Exact Lean statement
theorem memW01p_of_memW1p_of_tsupport_subset
{Ω : Set E} (hΩ : IsOpen Ω)
{p : ℝ} (hp : 1 < p) {u : E → ℝ}
(hu : MemW1p (ENNReal.ofReal p) u Ω)
(hu_compact : HasCompactSupport u)
(hu_sub : tsupport u ⊆ Ω) :
MemW01p (ENNReal.ofReal p) u ΩFormal artifact
Lean source
theorem memW01p_of_memW1p_of_tsupport_subset {Ω : Set E} (hΩ : IsOpen Ω) {p : ℝ} (hp : 1 < p) {u : E → ℝ} (hu : MemW1p (ENNReal.ofReal p) u Ω) (hu_compact : HasCompactSupport u) (hu_sub : tsupport u ⊆ Ω) : MemW01p (ENNReal.ofReal p) u Ω := by have hp_enn : (1 : ℝ≥0∞) ≤ ENNReal.ofReal p := by simpa using (ENNReal.ofReal_le_ofReal (le_of_lt hp) : ENNReal.ofReal (1 : ℝ) ≤ ENNReal.ofReal p) rcases hu with ⟨hu_memLp, hu_grad⟩ choose g hg_memLp hg_weak using hu_grad let G : E → E := fun x => WithLp.toLp 2 fun i => g i x let hw : MemW1pWitness (ENNReal.ofReal p) u Ω := { memLp := hu_memLp weakGrad := G weakGrad_component_memLp := hg_memLp isWeakGrad := hg_weak } obtain ⟨δ, hδ_pos, hδΩ⟩ := hu_compact.isCompact.exists_cthickening_subset_open hΩ hu_sub let K : Set E := Metric.cthickening δ (tsupport u) have hK_compact : IsCompact K := hu_compact.isCompact.cthickening (r := δ) have hKΩ : K ⊆ Ω := hδΩ obtain ⟨η, hη_smooth, hη_compact, hη_range, hη_one, hη_sub⟩ := exists_smooth_cutoff (d := d) hK_compact hΩ hKΩ have hη_bound : ∀ x, |η x| ≤ 1 := by intro x rcases hη_range ⟨x, rfl⟩ with ⟨hx0, hx1⟩ rw [abs_of_nonneg hx0] exact hx1 have hη_fderiv_compact : HasCompactSupport (fderiv ℝ η) := hη_compact.fderiv (𝕜 := ℝ) obtain ⟨Cη, hCη⟩ := hη_fderiv_compact.isCompact.exists_bound_of_continuousOn ((hη_smooth.continuous_fderiv (by simp)).continuousOn) let C₁ : ℝ := max Cη 0 have hC₁_nonneg : 0 ≤ C₁ := le_max_right _ _ have hη_grad_bound : ∀ x, ‖fderiv ℝ η x‖ ≤ C₁ := by intro x by_cases hx : x ∈ tsupport (fderiv ℝ η) · exact (hCη x hx).trans (le_max_left _ _) · have hzero : fderiv ℝ η x = 0 := image_eq_zero_of_notMem_tsupport hx simp [C₁, hzero] let v : E → ℝ := fun x => η x * u x let hwCut := MemW1pWitness.mul_smooth_bounded_p (d := d) (p := ENNReal.ofReal p) hp_enn hΩ hw hη_smooth zero_le_one hC₁_nonneg hη_bound hη_grad_bound have hv_eq_u : v = u := by funext x by_cases hx : x ∈ tsupport u · have hηx : η x = 1 := hη_one x (Metric.self_subset_cthickening (tsupport u) hx) simp [v, hηx] · have hux : u x = 0 := image_eq_zero_of_notMem_tsupport hx simp [v, hux] have hv_sub : tsupport v ⊆ tsupport η := tsupport_smul_subset_left η u have hgrad_sub : ∀ i : Fin d, tsupport (fun x => hwCut.weakGrad x i) ⊆ tsupport η := by intro i exact tsupport_mul_smooth_bounded_p_weakGrad_component_subset (d := d) (p := ENNReal.ofReal p) hp_enn hΩ hw hη_smooth zero_le_one hC₁_nonneg hη_bound hη_grad_bound i rcases exists_smooth_W1p_approx_of_supportedWitness (d := d) (Ω := Ω) (K := tsupport η) hΩ hp hwCut hη_compact.isCompact hη_sub hv_sub hgrad_sub with ⟨φ, hφ_smooth, hφ_compact, hφ_sub, hφ_fun, hφ_grad⟩ simpa [v, hv_eq_u] using memW01p_of_global_approx_supported hwCut φ hφ_smooth hφ_compact hφ_sub hφ_fun hφ_grad- Project
- DeGiorgi
- License
- Apache-2.0
- Commit
- 4c1b3077d378
- Source
- DeGiorgi/SobolevSpace/Approximation.lean:1440-1503
Reuse this declaration
Bring the exact result into your workflow
The import identifies the source module. Your project still needs the pinned package dependency shown on this page.
What this badge means
This completion status comes from the project or community source. It has not yet been represented here as an independent rebuild and axiom audit.
Continue in this project
Related declarations
Ae eq of tendsto e Lp Norm sub
BareFunction.ae_eq_of_tendsto_eLpNorm_sub
Plain-language statement
Lp limit uniqueness: if f_n → g₁ and f_n → g₂ in eLpNorm, then g₁ =ᵐ g₂.
Source project: DeGiorgi
Person-level attribution pending.
E Lp Norm pi le sum component
BareFunction.eLpNorm_pi_le_sum_component
Plain-language statement
Vector eLpNorm ≤ sum of component eLpNorms for Pi-valued functions. Uses eLpNorm_mono_real for the pointwise bound together with eLpNorm_sum_le for ℝ-valued functions, avoiding Pi instance synthesis.
Source project: DeGiorgi
Person-level attribution pending.
Mem Lp of tendsto e Lp Norm
BareFunction.memLp_of_tendsto_eLpNorm
Plain-language statement
If f n → g in eLpNorm and each f n ∈ Lp, then g ∈ Lp, provided g is AEStronglyMeasurable. Avoids the Lp type entirely. The key observation: eLpNorm (f n - g) → 0 means eLpNorm (f N - g) < 1 for some N. Then eLpNorm g ≤ eLpNorm (f N - g) + eLpNorm (f N) < ∞.
Source project: DeGiorgi
Person-level attribution pending.