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ClosedGraphResolvent: mathematical reading route

Read the statements and derivations in source order. Every result has its own optional Lean statement and proof. Source assumptions, library reuse and unproved boundaries are kept explicit.

  1. A unique weak resolvent from a closed Hilbert graph
ASTIS mathematical exposition

A unique weak resolvent from a closed Hilbert graph

AutoSamplingTheory.TechnicalLemmas.FunctionalInequalities.ClosedGraphResolvent.weak_resolvent · theorem · Teaching coverage

Statement

Let H,K be real Hilbert spaces and A a partial real-linear operator with closed graph. For each epsilon>0 and f in H, there is a unique domain element u such that epsilon inner(u,v)+inner(Au,Av)=inner(f,v) for every v in the domain. It satisfies the exact energy identity epsilon norm(u)^2+norm(Au)^2=inner(f,u), the ambient bound norm(u)<=epsilon^-1 norm(f), and the energy bound <=epsilon^-1 norm(f)^2. No density, boundedness, Poincare or prior solvability is assumed.

\[\varepsilon\langle u,v\rangle_H+\langle Au,Av\rangle_K=\langle f,v\rangle_H\quad(v\in\operatorname{Dom}A),\qquad \|u\|_H\le\varepsilon^{-1}\|f\|_H.\]

All objects and hypotheses

  • H and K are complete real inner-product spaces; they may be infinite dimensional.
  • A is a partial real-linear map with a linear-subspace domain, and its graph is closed in H times K. The domain is not assumed dense or all of H, and A is not assumed bounded.
  • Epsilon is strictly positive and f is an arbitrary H element. Domain-element norms in the statement are ambient H norms, not graph norms.
  • This is an abstract Hilbert weak-form prerequisite inspired by the Poisson/Sobolev discussion in Kolesnikov-Milman sections2.4-2.5. It is not that source compact-manifold Poisson existence/regularity theorem, nor PBPS conditional Poincare.

Mathematical proof

1. Place the scaled graph in a Hilbert product

Set s=sqrt(epsilon)>0. On H direct-sum K with its L2 product norm use T(a,b)=(s^-1 a,b). Define G as the inverse image under T of the graph of A. T is continuous linear, so G is a closed subspace and therefore complete. This avoids assuming the unbounded operator is continuous.

\[G=T^{-1}(\operatorname{Graph}A)=\{(s u,Au):u\in\operatorname{Dom}A\},\qquad s=\sqrt\varepsilon.\]
Corresponding Lean step

The local hex proof uses WithLp.fstL/sndL, Submodule.comap, hA.preimage T.continuous and hG.completeSpace_coe.

2. Project and recover a genuine domain element

Project z=(s^-1 f,0) orthogonally onto G. Membership of p in G gives an actual u in the domain with u=s^-1 p_1 and Au=p_2. Since s is nonzero, p_1=s u. No totalized inverse or arbitrary differential representative is used.

\[p=P_G(s^{-1}f,0)=(s u,Au),\qquad u\in\operatorname{Dom}A.\]
Corresponding Lean step

starProjection_apply_mem and LinearPMap.mem_graph_iff provide u; scalar cancellation establishes hu'.

3. Orthogonality is exactly the weak equation

For every domain v, the vector w=(s v,Av) lies in G. Orthogonality of z-p to w gives inner(s^-1 f-s u,s v)-inner(Au,Av)=0. Expanding both inner products and using s^2=epsilon yields the weak equation for every test in the closed domain.

\[0=\langle z-p,(s v,Av)\rangle=\langle f,v\rangle-\varepsilon\langle u,v\rangle-\langle Au,Av\rangle.\]
Corresponding Lean step

Submodule.starProjection_inner_eq_zero, the L2 product inner product and explicit nonzero-s scalar simplification close the local existence proof.

4. Derive the exact energy and explicit bounds

Use v=u in the weak equation. Cauchy-Schwarz bounds its right side by norm(f) norm(u). When norm(u)=0 the norm bound is immediate; otherwise divide its positive value to obtain epsilon norm(u)<=norm(f). Substitute this estimate back into the energy identity. The constants are explicit and deteriorate as epsilon approaches zero.

\[\varepsilon\|u\|_H^2+\|Au\|_K^2=\langle f,u\rangle_H\le\|f\|_H\|u\|_H\le\varepsilon^{-1}\|f\|_H^2.\]
Corresponding Lean step

he is the self-test identity; hn handles the zero/nonzero norm branches, hb divides by positive epsilon, heb combines Cauchy-Schwarz and hb.

5. Prove uniqueness by testing the difference

If w also solves the same equation, subtract the two equations tested at d=w-u. Domain linearity and A(w-u)=Aw-Au give epsilon norm(d)^2+norm(Ad)^2=0. Positivity of epsilon forces the ambient norm of d to vanish, hence the two domain elements are equal.

\[\varepsilon\|w-u\|_H^2+\|A(w-u)\|_K^2=0\quad\Longrightarrow\quad w=u.\]
Corresponding Lean step

The last quantified clause assumes only the weak equation for w, not its norm/energy bounds; Subtype.ext concludes equality from ambient norm zero.

Lean statement · weak_resolvent

Existence, exact energy, ambient H norm bound, energy bound, and uniqueness among all weak solutions on A.domain.

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 weak_resolvent {H K : Type*}
    [NormedAddCommGroup H] [InnerProductSpace ℝ H] [CompleteSpace H]
    [NormedAddCommGroup K] [InnerProductSpace ℝ K] [CompleteSpace K]
    (A : H →ₗ.[ℝ] K) (hA : A.IsClosed) (ε : ℝ) (hε : 0 < ε) (f : H) :
    ∃ u : A.domain,
      (∀ v : A.domain, ε * ⟪(u : H), (v : H)⟫ + ⟪A u, A v⟫ = ⟪f, (v : H)⟫) ∧
      ε * ‖(u : H)‖^2 + ‖A u‖^2 = ⟪f, (u : H)⟫ ∧
      ‖(u : H)‖ ≤ ε⁻¹ * ‖f‖ ∧
      ε * ‖(u : H)‖^2 + ‖A u‖^2 ≤ ε⁻¹ * ‖f‖^2 ∧
      ∀ w : A.domain,
        (∀ v : A.domain, ε * ⟪(w : H), (v : H)⟫ + ⟪A w, A v⟫ = ⟪f, (v : H)⟫) → w = u

Exact module and namespace context

Lean proof · weak_resolvent

The scaled-graph existence proof is local to the single public theorem; the complete folded proof includes it and all bounds and uniqueness.

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 weak_resolvent {H K : Type*}
    [NormedAddCommGroup H] [InnerProductSpace ℝ H] [CompleteSpace H]
    [NormedAddCommGroup K] [InnerProductSpace ℝ K] [CompleteSpace K]
    (A : H →ₗ.[ℝ] K) (hA : A.IsClosed) (ε : ℝ) (hε : 0 < ε) (f : H) :
    ∃ u : A.domain,
      (∀ v : A.domain, ε * ⟪(u : H), (v : H)⟫ + ⟪A u, A v⟫ = ⟪f, (v : H)⟫) ∧
      ε * ‖(u : H)‖^2 + ‖A u‖^2 = ⟪f, (u : H)⟫ ∧
      ‖(u : H)‖ ≤ ε⁻¹ * ‖f‖ ∧
      ε * ‖(u : H)‖^2 + ‖A u‖^2 ≤ ε⁻¹ * ‖f‖^2 ∧
      ∀ w : A.domain,
        (∀ v : A.domain, ε * ⟪(w : H), (v : H)⟫ + ⟪A w, A v⟫ = ⟪f, (v : H)⟫) → w = u := by
  have hex : ∃ u : A.domain, ∀ v : A.domain,
      ε * ⟪(u : H), (v : H)⟫ + ⟪A u, A v⟫ = ⟪f, (v : H)⟫ := by
    let s := Real.sqrt ε
    have hs : 0 < s := Real.sqrt_pos.2 hε
    have hs0 : s ≠ 0 := ne_of_gt hs
    have hss : s * s = ε := Real.mul_self_sqrt hε.le
    let T : WithLp 2 (H × K) →L[ℝ] H × K :=
      (s⁻¹ • (WithLp.fstL 2 ℝ H K)).prod (WithLp.sndL 2 ℝ H K)
    let G : Submodule ℝ (WithLp 2 (H × K)) := A.graph.comap T.toLinearMap
    have hG : IsClosed (G : Set (WithLp 2 (H × K))) := hA.preimage T.continuous
    let : CompleteSpace G := hG.completeSpace_coe
    let z : WithLp 2 (H × K) := WithLp.toLp 2 (s⁻¹ • f, 0)
    let p := G.starProjection z
    have hp : T p ∈ A.graph := G.starProjection_apply_mem z
    obtain ⟨u,hu,hAu⟩ := A.mem_graph_iff.mp hp
    have hu' : s • (u : H) = p.fst := by
      rw [hu]
      change s • (s⁻¹ • p.fst) = p.fst
      simp [smul_smul, hs0]
    refine ⟨u, ?_⟩
    intro v
    let w : WithLp 2 (H × K) := WithLp.toLp 2 (s • (v : H), A v)
    have hw : w ∈ G := by
      change T w ∈ A.graph
      apply A.mem_graph_iff.mpr
      refine ⟨v, ?_, ?_⟩
      · change (v : H) = s⁻¹ • (s • (v : H))
        simp [smul_smul, hs0]
      · rfl
    have ho := G.starProjection_inner_eq_zero z w hw
    change ⟪s⁻¹ • f - p.fst, s • (v : H)⟫ + ⟪(0 : K) - p.snd, A v⟫ = 0 at ho
    have hAu' : A u = p.snd := hAu
    rw [← hu', ← hAu'] at ho
    simp only [inner_sub_left, real_inner_smul_left, real_inner_smul_right, zero_sub,
      inner_neg_left] at ho
    simp only [← mul_assoc, mul_inv_cancel₀ hs0, hss, one_mul] at ho
    linarith
  obtain ⟨u,hu⟩ := hex
  have he : ε * ‖(u : H)‖^2 + ‖A u‖^2 = ⟪f, (u : H)⟫ := by
    simpa only [real_inner_self_eq_norm_sq] using hu u
  have hn : ε * ‖(u : H)‖ ≤ ‖f‖ := by
    have hcs := real_inner_le_norm f (u : H)
    by_cases hz : ‖(u : H)‖ = 0
    · simp [hz]
    · have hp : 0 < ‖(u : H)‖ := lt_of_le_of_ne (norm_nonneg _) (Ne.symm hz)
      nlinarith [sq_nonneg ‖A u‖]
  have hb : ‖(u : H)‖ ≤ ε⁻¹ * ‖f‖ := by
    have hn' : ‖(u : H)‖ ≤ ‖f‖ / ε := (le_div_iff₀ hε).2 (by simpa [mul_comm] using hn)
    simpa [div_eq_mul_inv, mul_comm] using hn'
  have heb : ε * ‖(u : H)‖^2 + ‖A u‖^2 ≤ ε⁻¹ * ‖f‖^2 := by
    rw [he]
    calc
      ⟪f, (u : H)⟫ ≤ ‖f‖ * ‖(u : H)‖ := real_inner_le_norm _ _
      _ ≤ ‖f‖ * (ε⁻¹ * ‖f‖) := mul_le_mul_of_nonneg_left hb (norm_nonneg _)
      _ = _ := by ring
  refine ⟨u,hu,he,hb,heb,?_⟩
  intro w hw
  let d : A.domain := w-u
  have hd : ε * ⟪(d : H), (d : H)⟫ + ⟪A d, A d⟫ = 0 := by
    have heq := sub_eq_zero.mpr ((hw d).trans (hu d).symm)
    have hAd : A d = A w - A u := A.toFun.map_sub w u
    rw [hAd, inner_sub_left]
    change ε * ⟪(w : H) - (u : H), (d : H)⟫ + _ = 0
    rw [inner_sub_left]
    rw [hAd] at heq
    nlinarith
  rw [real_inner_self_eq_norm_sq, real_inner_self_eq_norm_sq] at hd
  have hz : ‖(d : H)‖ = 0 := by
    by_contra hz
    have hp : 0 < ‖(d : H)‖ := lt_of_le_of_ne (norm_nonneg _) (Ne.symm hz)
    have hpos := mul_pos hε (sq_pos_of_pos hp)
    nlinarith [sq_nonneg ‖A d‖]
  apply Subtype.ext
  exact sub_eq_zero.mp (norm_eq_zero.mp hz)

end AutoSamplingTheory.TechnicalLemmas.FunctionalInequalities.ClosedGraphResolvent

Exact module and namespace context

Scope and omitted-condition boundaries

  • Weak equation on the closed gradient domain only. No classical PDE regularity, identified maximal differential domain, D*D operator core, compact-test Bochner extension, epsilon-uniform estimate, Poincare, noncompact score variance, measurable parameter selection, process/error/cost or full-paper conclusion.

Source and reuse

ASTIS parents called

    Mathlib API called (external library)

    • WithLp.fstL
    • WithLp.sndL
    • Submodule.comap
    • IsClosed.completeSpace_coe
    • Submodule.starProjection_apply_mem
    • Submodule.starProjection_inner_eq_zero
    • LinearPMap.mem_graph_iff
    • real_inner_le_norm

    Mathematical sources

    ASTIS prose is not a quotation or a source-equivalence certificate. Definitions and aliases are explained as constructions, not counted as new mathematical proofs.