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Samplinglib mathematical lesson

Actual compact weak Poisson: one smooth function/gradient/Laplacian sequence

AutoSamplingTheory.TechnicalLemmas.FunctionalInequalities.CompactPoissonSmoothGraph.compact_weak_poisson_smooth_graph_approximation · theorem · Teaching coverage

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Mathematical statement

From the exact compact-supported volumeL2 and original weak-gradient/PDE inputs, Derive one real Schwartz sequence phi_n with one common outer compact Kprime containing every tsupport(phi_n), chosen before all n and all three limits. Actual volumeL2 classes of phi_n converge to v; actual classical gradient(phi_n) is MemLp2 and its class converges to the original G; actual Laplacian(phi_n) classes converge to F. Every phi_n is C-infinity and compactly supported. The same sequence realizes all limits. Kprime need not equal K. No classical derivatives of rough v, real Hessian family, quantitative source complexity constant or weighted operator core is claimed.

\[\int\psi\langle G,a\rangle=-\int vD_a\psi,\quad\int v\Delta\psi=\int F\psi\ \Longrightarrow\ \exists K\prime,\varphi_n\in C_c^\infty(K\prime):\quad\varphi_n\to v,\ \nabla\varphi_n\to G,\ \Delta\varphi_n\to F\ \text{in }L^2(dx).\]
Lean statement · compact_weak_poisson_smooth_graph_approximation

From the exact compact-supported volumeL2 and original weak-gradient/PDE inputs, Derive one real Schwartz sequence phi_n with one common outer compact Kprime containing every tsupport(phi_n), chosen before all n and all three limits. Actual volumeL2 classes of phi_n converge to v; actual classical gradient(phi_n) is MemLp2 and its class converges to the original G; actual Laplacian(phi_n) classes converge to F. Every phi_n is C-infinity and compactly supported. The same sequence realizes all limits. Kprime need not equal K. No classical derivatives of rough v, real Hessian family, quantitative source complexity constant or weighted operator core is claimed.

Braces mark parameters Lean can infer; square brackets request structures such as a measurable space or probability measure. Named hypotheses are mathematical premises, not facts established by this declaration. Section parameters are described in the mathematical hypotheses above; the module link retains their exact source context.

theorem compact_weak_poisson_smooth_graph_approximation
    (v F : E → ℝ) (G : E → E) (K : Set E) (hK : IsCompact K)
    (hv : tsupport v ⊆ K) (hF : tsupport F ⊆ K) (hG : tsupport G ⊆ K)
    (hv2 : MemLp v 2 volume) (hF2 : MemLp F 2 volume) (hG2 : MemLp G 2 volume)
    (hd : ∀ ψ : E → ℝ, ContDiff ℝ 1 ψ → HasCompactSupport ψ → ∀ a : E,
      Integrable (fun x => ψ x * inner ℝ (G x) a) volume ∧
      Integrable (fun x => v x * fderiv ℝ ψ x a) volume ∧
      (∫ x, ψ x * inner ℝ (G x) a) = -∫ x, v x * fderiv ℝ ψ x a)
    (hweak : ∀ ψ : E → ℝ, ContDiff ℝ 2 ψ → HasCompactSupport ψ →
      Integrable (fun x => v x * (Δ ψ) x) volume ∧
      Integrable (fun x => F x * ψ x) volume ∧
      (∫ x, v x * (Δ ψ) x) = ∫ x, F x * ψ x) :
    ∃ K' : Set E, IsCompact K' ∧ ∃ φ : ℕ → SchwartzMap E ℝ,
      (∀ n, tsupport (φ n) ⊆ K') ∧
      Filter.Tendsto (fun n => (φ n).toLp 2 volume) Filter.atTop (𝓝 (hv2.toLp v)) ∧
      ∃ hφG : ∀ n, MemLp (gradient (φ n : E → ℝ)) 2 volume,
        Filter.Tendsto (fun n => (hφG n).toLp (gradient (φ n : E → ℝ)))
          Filter.atTop (𝓝 (hG2.toLp G)) ∧
        Filter.Tendsto (fun n => (Δ (φ n)).toLp 2 volume)
          Filter.atTop (𝓝 (hF2.toLp F))

Exact module and namespace context

Proof roadmap

  1. 1Derive the actual Bessel-L2 witness from the original compact PDE

    Call the accepted real compact-test producer with actual supports and L2 data. It constructs AE-linked complex classes vc/Fc, the true TD Laplacian and Sobolev2. Choose the genuine order2 L2 witness w and invert Bessel; plain L2 approximation of v would not control derivatives.

  2. 2Construct chosen norm-controlled continuous L2 spectral maps

    For each actual bounded temperate complex symbol g, use its genuine Linfinity class, Holder infinity/2/2 bilinear CLM and forward/inverse L2 Fourier isometries to construct A_g. Prove norm(A_g f)≤C norm(f), true Lp/TD compatibility and equality with Schwartz multipliers by LpTD injectivity. The symbols m0, inner(x,a)*m0 and norm(x)^2*m0 have bounds1,norm(a),1; attach exact2pi i and -(2pi)^2 scalars to derivatives.

  3. 3Use one Schwartz approximation of w for every graph component

    Actual L2 density and sequential closure choose q_n.toLp → w. Define s_n=FM(m0)q_n. Continuity of the chosen fixed maps gives same-sequence function, Laplacian and every direction derivative limits. Identify function with vc through true Bessel inversion, and Laplacian with Fc through the actual TD PDE/injectivity. Preserve exact complex casts/Fourier normalization.

  4. 4Identify the original real gradient, not a newly chosen derivative

    The actual spectral limit satisfies T_ga=D_a T_vc. Test it with ofReal of each genuine real compact smooth test, use actual HolderL1 before integral_re, and compare with the original all-C1 weak gradient. Locally integrable compact-test uniqueness identifies Re ga=inner(G,a) AE. Continuous real projection and finite orthonormal-basis reconstruction give the actual full vector-gradient limit; dimension0 has an empty basis.

  5. 5Construct one fixed outer plateau and all bounded coefficient maps

    Choose an actual unnormalized smooth compact theta equal1 near K. Its genuine Schwartz function, gradient and Laplacian supply actual Linfinity coefficients; Holder gives continuous maps on real/vectorL2. Neighborhood locality makes gradtheta/Deltatheta zero on K, while actual v/G/F vanish outsideK. Derive exact limiting identities and zero cross terms without weighted tails or extra position moments.

  6. 6Apply actual product rules to the same sequence

    Set phi_n=theta*Re s_n, a genuine smooth compact function with common supportKprime. Reuse the existing public gradient product rule and the canonical local-C2 LaplacianProduct.laplacian_mul at each point. The already globally smooth factors discharge its local regularity. Actual quotient/AE products and continuous bounded coefficient maps pass all three identities to the limit; the duplicate private Laplacian calculus is removed.

  7. 7Return actual compact graph convergence and stop before weighted core

    Expose real Schwartz approximants/common compact support, actual gradient MemLp witnesses and true function/gradient/Laplacian quotient convergence from input L2 proofs. Weighted transfer, original localized D-domain membership, adjoint/generator identification, global cutoff removal/Bochner/Poincare/BL and source main guarantees remain distinct producers.

Full assumptions and notation

All objects and hypotheses

  • Finite-dimensional real Hilbert/Borel space E with canonical ordinary full-space volume, including dimension zero. Real pointwise v,F and vector G are genuinely global volumeL2; their topological supports lie in the same compact K.
  • Every real C1 compact test psi and every a satisfies both L1 products and integral psi*inner(G,a)=-integral v*D_a psi. Every real C2 compact psi has both L1 products and integral v*Delta psi=integral F*psi. These actual weak equations, measurability/L2 and supports are inputs; graph density, Sobolev membership, smooth sequence, real mixed Hessian and weighted core are not supplied.
  • The rough v/G/F representatives are differentiated only in the actual weak/distributional sense. Classical gradients and Laplacians in the conclusion belong to actual smooth approximants. SchwartzMap E real is genuinely C-infinity/rapidly decaying; common compact support is additionally derived. No positive dimension, jointly measurable selector, source C-infinity potential or normalized plateau is assumed.

Mathematical proof

1. Derive the actual Bessel-L2 witness from the original compact PDE

Call the accepted real compact-test producer with actual supports and L2 data. It constructs AE-linked complex classes vc/Fc, the true TD Laplacian and Sobolev2. Choose the genuine order2 L2 witness w and invert Bessel; plain L2 approximation of v would not control derivatives.

\[B_2T_v=T_w,\quad B_2=I-(2\pi)^{-2}\Delta,\quad B_{-2}T_w=T_v.\]
Corresponding Lean step

CompactWeakPoissonSobolev.compact_weak_poisson_sobolev; spectral_graph

2. Construct chosen norm-controlled continuous L2 spectral maps

For each actual bounded temperate complex symbol g, use its genuine Linfinity class, Holder infinity/2/2 bilinear CLM and forward/inverse L2 Fourier isometries to construct A_g. Prove norm(A_g f)≤C norm(f), true Lp/TD compatibility and equality with Schwartz multipliers by LpTD injectivity. The symbols m0, inner(x,a)*m0 and norm(x)^2*m0 have bounds1,norm(a),1; attach exact2pi i and -(2pi)^2 scalars to derivatives.

\[A_g=\mathcal F^{-1}(g\,\mathcal F\cdot),\quad\|A_gf\|_2\le C\|f\|_2;\quad m_0=(1+\|\xi\|^2)^{-1}.\]
Corresponding Lean step

actualMul; actual_bounded_multiplier_norm; mzero_bound; mdir_bound; mlap_bound; inverse_dir; inverse_lap

3. Use one Schwartz approximation of w for every graph component

Actual L2 density and sequential closure choose q_n.toLp → w. Define s_n=FM(m0)q_n. Continuity of the chosen fixed maps gives same-sequence function, Laplacian and every direction derivative limits. Identify function with vc through true Bessel inversion, and Laplacian with Fc through the actual TD PDE/injectivity. Preserve exact complex casts/Fourier normalization.

\[s_n=A_{m_0}q_n,\quad s_n\to v_C,\quad\Delta s_n\to F_C,\quad D_as_n\to g_a.\]
Corresponding Lean step

schwartz_approx; spectral_graph; besselPotential_neg_apply_eq_iff; lp_td_injective

4. Identify the original real gradient, not a newly chosen derivative

The actual spectral limit satisfies T_ga=D_a T_vc. Test it with ofReal of each genuine real compact smooth test, use actual HolderL1 before integral_re, and compare with the original all-C1 weak gradient. Locally integrable compact-test uniqueness identifies Re ga=inner(G,a) AE. Continuous real projection and finite orthonormal-basis reconstruction give the actual full vector-gradient limit; dimension0 has an empty basis.

\[\operatorname{Re}g_a=_{dx\text{-ae}}\langle G,a\rangle,\quad\operatorname{Re}s_n\to v,\quad\nabla\operatorname{Re}s_n\to G,\quad\Delta\operatorname{Re}s_n\to F.\]
Corresponding Lean step

identify_real_gradient; real_projection_class; finite_gradient_reconstruction; real_schwartz_graph

5. Construct one fixed outer plateau and all bounded coefficient maps

Choose an actual unnormalized smooth compact theta equal1 near K. Its genuine Schwartz function, gradient and Laplacian supply actual Linfinity coefficients; Holder gives continuous maps on real/vectorL2. Neighborhood locality makes gradtheta/Deltatheta zero on K, while actual v/G/F vanish outsideK. Derive exact limiting identities and zero cross terms without weighted tails or extra position moments.

\[\theta=1\text{ near }K,\quad\nabla\theta=\Delta\theta=0\text{ on }K,\quad K\prime=\operatorname{tsupp}\theta.\]
Corresponding Lean step

outer_plateau; coeff_holder_ae; coeff_holder_class; plateau_point_identities

6. Apply actual product rules to the same sequence

Set phi_n=theta*Re s_n, a genuine smooth compact function with common supportKprime. Reuse the existing public gradient product rule and the canonical local-C2 LaplacianProduct.laplacian_mul at each point. The already globally smooth factors discharge its local regularity. Actual quotient/AE products and continuous bounded coefficient maps pass all three identities to the limit; the duplicate private Laplacian calculus is removed.

\[\nabla(\theta r_n)=\theta\nabla r_n+r_n\nabla\theta;\quad\Delta(\theta r_n)=\theta\Delta r_n+2\langle\nabla\theta,\nabla r_n\rangle+r_n\Delta\theta.\]
Corresponding Lean step

GradientAlgebra.gradient_mul_eq_of_differentiableAt; AutoSamplingTheory.TechnicalLemmas.Analysis.Calculus.LaplacianProduct.laplacian_mul; cutoff_schwartz_graph

7. Return actual compact graph convergence and stop before weighted core

Expose real Schwartz approximants/common compact support, actual gradient MemLp witnesses and true function/gradient/Laplacian quotient convergence from input L2 proofs. Weighted transfer, original localized D-domain membership, adjoint/generator identification, global cutoff removal/Bochner/Poincare/BL and source main guarantees remain distinct producers.

\[\varphi_n\to v,\quad\nabla\varphi_n\to G,\quad\Delta\varphi_n\to F\text{ in }L^2(dx);\quad\text{weighted core remains open}.\]
Corresponding Lean step

compact_weak_poisson_smooth_graph_approximation

Lean verification

The exact proof begins folded immediately after the mathematical argument; the statement is folded beside the claim above.

Lean proof · compact_weak_poisson_smooth_graph_approximation

Derive the actual Bessel-L2 witness from the original compact PDE; Construct chosen norm-controlled continuous L2 spectral maps; Use one Schwartz approximation of w for every graph component; Identify the original real gradient, not a newly chosen derivative; Construct one fixed outer plateau and all bounded coefficient maps; Apply actual product rules to the same sequence; Return actual compact graph convergence and stop before weighted core

Braces mark parameters Lean can infer; square brackets request structures such as a measurable space or probability measure. Named hypotheses are mathematical premises, not facts established by this declaration. Section parameters are described in the mathematical hypotheses above; the module link retains their exact source context.

Download module (.lean)
theorem compact_weak_poisson_smooth_graph_approximation
    (v F : E → ℝ) (G : E → E) (K : Set E) (hK : IsCompact K)
    (hv : tsupport v ⊆ K) (hF : tsupport F ⊆ K) (hG : tsupport G ⊆ K)
    (hv2 : MemLp v 2 volume) (hF2 : MemLp F 2 volume) (hG2 : MemLp G 2 volume)
    (hd : ∀ ψ : E → ℝ, ContDiff ℝ 1 ψ → HasCompactSupport ψ → ∀ a : E,
      Integrable (fun x => ψ x * inner ℝ (G x) a) volume ∧
      Integrable (fun x => v x * fderiv ℝ ψ x a) volume ∧
      (∫ x, ψ x * inner ℝ (G x) a) = -∫ x, v x * fderiv ℝ ψ x a)
    (hweak : ∀ ψ : E → ℝ, ContDiff ℝ 2 ψ → HasCompactSupport ψ →
      Integrable (fun x => v x * (Δ ψ) x) volume ∧
      Integrable (fun x => F x * ψ x) volume ∧
      (∫ x, v x * (Δ ψ) x) = ∫ x, F x * ψ x) :
    ∃ K' : Set E, IsCompact K' ∧ ∃ φ : ℕ → SchwartzMap E ℝ,
      (∀ n, tsupport (φ n) ⊆ K') ∧
      Filter.Tendsto (fun n => (φ n).toLp 2 volume) Filter.atTop (𝓝 (hv2.toLp v)) ∧
      ∃ hφG : ∀ n, MemLp (gradient (φ n : E → ℝ)) 2 volume,
        Filter.Tendsto (fun n => (hφG n).toLp (gradient (φ n : E → ℝ)))
          Filter.atTop (𝓝 (hG2.toLp G)) ∧
        Filter.Tendsto (fun n => (Δ (φ n)).toLp 2 volume)
          Filter.atTop (𝓝 (hF2.toLp F)) := by
  obtain ⟨vc,Fc,hvc,hFc,_,hl,hs⟩ :=
    CompactWeakPoissonSobolev.compact_weak_poisson_sobolev v F K hK hv hF hv2 hF2 hweak
  obtain ⟨r,hrv,hrG,hrF⟩ := real_schwartz_graph v F G hv2 hF2 hG2 vc Fc hvc hFc hs hl hd
  obtain ⟨K',hK',φ,hφs,hφv,hφG,hφF⟩ :=
    cutoff_schwartz_graph v F G K hK hv hF hG hv2 hF2 hG2 r hrv hrG hrF
  have hφgrad (n : ℕ) : MemLp (gradient (φ n : E → ℝ)) 2 volume := by
    have he : (schwartz_gradient (φ n) : E → E) = gradient (φ n : E → ℝ) := by
      funext x; exact schwartz_gradient_apply (φ n) x
    rw [← he]
    exact (schwartz_gradient (φ n)).memLp 2 volume
  have heq (n : ℕ) : (hφgrad n).toLp (gradient (φ n : E → ℝ)) =
      (schwartz_gradient (φ n)).toLp 2 volume := by
    apply Lp.ext
    filter_upwards [(hφgrad n).coeFn_toLp,(schwartz_gradient (φ n)).coeFn_toLp 2 volume]
      with x hx hy
    rw [hx,hy,schwartz_gradient_apply]
  exact ⟨K',hK',φ,hφs,hφv,hφgrad,by simpa only [heq] using hφG,hφF⟩

end AutoSamplingTheory.TechnicalLemmas.FunctionalInequalities.CompactPoissonSmoothGraph

Exact module and namespace context

Scope and omitted-condition boundaries
  • Derive one real smooth sequence with common outer compact support and simultaneous actual ordinary-volume L2 function/gradient/Laplacian limits for v=chi*u, g=chi*G+u*gradientchi, F=chi*r+2inner(gradientchi,G)+u*laplacianchi. Same original D before epsilon/f, same u before ALL cutoffs. No supplied graph-density/approximation/mixedHessian/core certificate, no classical rough derivatives, no weighted-domain/operator-core/globalcutoff/Bochner/BL/Poincare/jointmeasurablechoice/main/composition claim. Reflected/RGO quarter Hessian and fourfold energy kept distinct; TV never transfers unbounded cost.
Sources, dependencies, and reuse

Source and reuse

Samplinglib parents called

Mathlib API called (external library)

  • SchwartzMap.denseRange_toLpCLM
  • Lp.fourierTransformₗᵢ
  • Lp.toTemperedDistribution_smul_eq
  • Lp.ker_toTemperedDistributionCLM_eq_bot
  • ContinuousLinearMap.holderL
  • SchwartzMap.fourierMultiplierCLM
  • besselPotential_neg_apply_eq_iff
  • ae_eq_of_integral_contDiff_smul_eq
  • ContinuousLinearMap.compLpL
  • ContDiffBump.eventuallyEq_one_of_mem_ball

Mathematical sources

  • PBPS AppendixC.1 authored analytic prerequisite — Derive one real smooth sequence with common outer compact support and simultaneous actual ordinary-volume L2 function/gradient/Laplacian limits for v=chi*u, g=chi*G+u*gradientchi, F=chi*r+2inner(gradientchi,G)+u*laplacianchi. Same original D before epsilon/f, same u before ALL cutoffs. No supplied graph-density/approximation/mixedHessian/core certificate, no classical rough derivatives, no weighted-domain/operator-core/globalcutoff/Bochner/BL/Poincare/jointmeasurablechoice/main/composition claim. Reflected/RGO quarter Hessian and fourfold energy kept distinct; TV never transfers unbounded cost.

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