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HilbertCorrectorPerturbation: 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. Hilbert corrector perturbation identity
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Hilbert corrector perturbation identity

AutoSamplingTheory.TechnicalLemmas.Analysis.HilbertCorrectorPerturbation.quadratic_corrector_perturbation · theorem · Teaching coverage

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Mathematical statement

Let H be a complete real Hilbert space, allowing the zero space. Let A,G,Inv:H→H be bounded real-linear endomorphisms. Assume A,G,Inv are selfadjoint, A commutes with Inv, Inv G=G Inv=I, and A²+G²=I. Every one of these structural conditions is an explicit hypothesis of this auxiliary algebra theorem. For arbitrary u,v,r∈H define C(a,b)=(||a||²−||b||²)/2−⟨A(Inv a),b⟩. Then C(u+Gr,v−Ar)−C(u,v)=⟨u,Inv r⟩+||r||²/2. The half, plus sign, operator order and same three operators are exact. This is an ASTIS Hilbert-space auxiliary generalization of the algebra in Chen–Chewi–Lu–Zhang's PBPS B20 and Lemma B4 expansion Ex28–Ex34, rather than a claim that the paper states a theorem for arbitrary Hilbert operators. No positivity, finite dimension, spectral gap, surjectivity or probability hypothesis is needed by this algebra identity. The actual PBPS consumer constructs all seven operator facts internally on its same centered space. Arbitrary r is not yet the paper's r_rho; the actual H/K/B27 adapter and B4/B28 decay proof remain open.

\[C(u,v)=\frac{\|u\|^2-\|v\|^2}{2}-\langle A\operatorname{Inv}u,v\rangle,\quad C(u+Gr,v-Ar)-C(u,v)=\langle u,\operatorname{Inv}r\rangle+\frac{\|r\|^2}{2}.\]
Lean statement · quadratic_corrector_perturbation

Let H be a complete real Hilbert space, allowing the zero space. Let A,G,Inv:H→H be bounded real-linear endomorphisms. Assume A,G,Inv are selfadjoint, A commutes with Inv, Inv G=G Inv=I, and A²+G²=I. Every one of these structural conditions is an explicit hypothesis of this auxiliary algebra theorem. For arbitrary u,v,r∈H define C(a,b)=(||a||²−||b||²)/2−⟨A(Inv a),b⟩. Then C(u+Gr,v−Ar)−C(u,v)=⟨u,Inv r⟩+||r||²/2. The half, plus sign, operator order and same three operators are exact. This is an ASTIS Hilbert-space auxiliary generalization of the algebra in Chen–Chewi–Lu–Zhang's PBPS B20 and Lemma B4 expansion Ex28–Ex34, rather than a claim that the paper states a theorem for arbitrary Hilbert operators. No positivity, finite dimension, spectral gap, surjectivity or probability hypothesis is needed by this algebra identity. The actual PBPS consumer constructs all seven operator facts internally on its same centered space. Arbitrary r is not yet the paper's r_rho; the actual H/K/B27 adapter and B4/B28 decay proof remain open.

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 quadratic_corrector_perturbation
    {H : Type*} [NormedAddCommGroup H] [InnerProductSpace ℝ H]
    [CompleteSpace H]
    (A G Inv : H →L[ℝ] H)
    (hA : IsSelfAdjoint A) (hG : IsSelfAdjoint G)
    (hInv : IsSelfAdjoint Inv) (hAInv : Commute A Inv)
    (hInvG : Inv * G = 1) (hGInv : G * Inv = 1)
    (hSquares : A * A + G * G = 1)
    (u v r : H) :
    let C : H → H → ℝ := fun u v =>
      (‖u‖^2 - ‖v‖^2)/2 - inner ℝ (A (Inv u)) v
    C (u + G r) (v - A r) - C u v =
      inner ℝ u (Inv r) + ‖r‖^2/2

Exact module and namespace context

Proof roadmap

  1. 1Expose the exact functional and typed selfadjoint identities

    Unfold only C. State each selfadjointness consequence as an equality of real inner products on the same H, avoiding coercion-sensitive rewrites. No mathematical assumption is added.

  2. 2Evaluate the inverse and square-sum operator equalities

    Apply Inv G=I and A²+G²=I to an arbitrary vector x. These give vector equalities without dividing by a scalar or assuming a nonzero space.

  3. 3Obtain the energy identity

    Take the inner product of the square-sum equality with x and move A and G across the inner product by selfadjointness. The two summands become squared norms.

  4. 4Recover the remaining linear operator

    Use Inv(G(Gx))=Gx and linearity to write Inv(A(Ax))+Gx=Inv(A(Ax)+G(Gx))=Inv x. This avoids any additional A–G commutation hypothesis.

  5. 5Identify the mixed linear contribution

    Move A and Inv through the inner products and apply the preceding vector identity with x=r. Thus the sum of the two surviving u-linear terms is exactly the claimed right-hand linear term.

  6. 6Expand and cancel the perturbation terms

    Expand the two squared norms and C cross term. Since Inv Gr=r, the increment is ⟨u,Gr⟩+⟨v,Ar⟩+(||Gr||²−||Ar||²)/2+⟨A Inv u,Ar⟩−⟨Ar,v⟩+||Ar||². Real symmetry cancels the v terms, the energy identity reduces the quadratic terms to ||r||²/2, and the mixed identity gives ⟨u,Inv r⟩. The result retains the exact positive half.

Full assumptions and notation

All objects and hypotheses

  • H is a complete real Hilbert space, including the zero space; A,G,Inv are bounded real-linear endomorphisms.
  • A,G,Inv are selfadjoint; A commutes with Inv; Inv G=G Inv=I; A²+G²=I. All seven structural facts are explicit premises of this auxiliary algebra theorem.
  • u,v,r are arbitrary in H; C is the exact displayed local definition. No finite dimension, positivity, spectral gap, nontriviality or probability premise.

Mathematical proof

1. Expose the exact functional and typed selfadjoint identities

Unfold only C. State each selfadjointness consequence as an equality of real inner products on the same H, avoiding coercion-sensitive rewrites. No mathematical assumption is added.

\[\langle Ax,y\rangle=\langle x,Ay\rangle,\quad\langle Gx,y\rangle=\langle x,Gy\rangle,\quad\langle\operatorname{Inv}x,y\rangle=\langle x,\operatorname{Inv}y\rangle.\]
Corresponding Lean step
  dsimp only
  have ha (x y : H) : inner ℝ (A x) y=inner ℝ x (A y) := hA.isSymmetric x y
  have hg (x y : H) : inner ℝ (G x) y=inner ℝ x (G y) := hG.isSymmetric x y
  have hi (x y : H) : inner ℝ (Inv x) y=inner ℝ x (Inv y) := hInv.isSymmetric x y

Exact compiled contiguous BODY span; preceding local definitions and inherited Hilbert structures remain in scope.

2. Evaluate the inverse and square-sum operator equalities

Apply Inv G=I and A²+G²=I to an arbitrary vector x. These give vector equalities without dividing by a scalar or assuming a nonzero space.

\[\operatorname{Inv}(Gx)=x,\qquad A(Ax)+G(Gx)=x.\]
Corresponding Lean step
  have hIG (x : H) : Inv (G x)=x := by
    have h := congrArg (fun L : H →L[ℝ] H => L x) hInvG
    simpa only [ContinuousLinearMap.mul_apply,ContinuousLinearMap.one_apply] using h
  have hSq (x : H) : A (A x)+G (G x)=x := by
    have h := congrArg (fun L : H →L[ℝ] H => L x) hSquares
    simpa only [ContinuousLinearMap.add_apply,ContinuousLinearMap.mul_apply,
      ContinuousLinearMap.one_apply] using h

Exact compiled contiguous BODY span; preceding local definitions and inherited Hilbert structures remain in scope.

3. Obtain the energy identity

Take the inner product of the square-sum equality with x and move A and G across the inner product by selfadjointness. The two summands become squared norms.

\[\|Ax\|^2+\|Gx\|^2=\|x\|^2.\]
Corresponding Lean step
  have hEnergy (x : H) : ‖A x‖^2+‖G x‖^2=‖x‖^2 := by
    have h := congrArg (fun z : H => inner ℝ z x) (hSq x)
    rw [inner_add_left,ha (A x) x,hg (G x) x] at h
    simpa only [real_inner_self_eq_norm_sq] using h

Exact compiled contiguous BODY span; preceding local definitions and inherited Hilbert structures remain in scope.

4. Recover the remaining linear operator

Use Inv(G(Gx))=Gx and linearity to write Inv(A(Ax))+Gx=Inv(A(Ax)+G(Gx))=Inv x. This avoids any additional A–G commutation hypothesis.

\[\operatorname{Inv}(A(Ax))+Gx=\operatorname{Inv}x.\]
Corresponding Lean step
  have hLinear (x : H) : Inv (A (A x))+G x=Inv x := by
    calc
      Inv (A (A x))+G x=Inv (A (A x))+Inv (G (G x)) := by rw [hIG]
      _ = Inv (A (A x)+G (G x)) := by rw [map_add]
      _ = Inv x := congrArg Inv (hSq x)

Exact compiled contiguous BODY span; preceding local definitions and inherited Hilbert structures remain in scope.

5. Identify the mixed linear contribution

Move A and Inv through the inner products and apply the preceding vector identity with x=r. Thus the sum of the two surviving u-linear terms is exactly the claimed right-hand linear term.

\[\langle A\operatorname{Inv}u,Ar\rangle+\langle u,Gr\rangle=\langle u,\operatorname{Inv}r\rangle.\]
Corresponding Lean step
  have hMixed : inner ℝ (A (Inv u)) (A r)+inner ℝ u (G r)=inner ℝ u (Inv r) := by
    rw [ha (Inv u) (A r),hi u (A (A r)),
      ← inner_add_right,hLinear r]

Exact compiled contiguous BODY span; preceding local definitions and inherited Hilbert structures remain in scope.

6. Expand and cancel the perturbation terms

Expand the two squared norms and C cross term. Since Inv Gr=r, the increment is ⟨u,Gr⟩+⟨v,Ar⟩+(||Gr||²−||Ar||²)/2+⟨A Inv u,Ar⟩−⟨Ar,v⟩+||Ar||². Real symmetry cancels the v terms, the energy identity reduces the quadratic terms to ||r||²/2, and the mixed identity gives ⟨u,Inv r⟩. The result retains the exact positive half.

\[C(u,v)=\frac{\|u\|^2-\|v\|^2}{2}-\langle A\operatorname{Inv}u,v\rangle,\quad C(u+Gr,v-Ar)-C(u,v)=\langle u,\operatorname{Inv}r\rangle+\frac{\|r\|^2}{2}.\]
Corresponding Lean step
  rw [norm_add_sq_real,norm_sub_sq_real]
  simp only [map_add,hIG,inner_add_left,inner_sub_right,real_inner_self_eq_norm_sq]
  rw [real_inner_comm v (A r)]
  nlinarith only [hEnergy r,hMixed]

Exact compiled contiguous BODY span; preceding local definitions and inherited Hilbert structures remain in scope.

Lean verification

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

Lean proof · quadratic_corrector_perturbation

Expose the exact functional and typed selfadjoint identities; Evaluate the inverse and square-sum operator equalities; Obtain the energy identity; Recover the remaining linear operator; Identify the mixed linear contribution; Expand and cancel the perturbation terms

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 quadratic_corrector_perturbation
    {H : Type*} [NormedAddCommGroup H] [InnerProductSpace ℝ H]
    [CompleteSpace H]
    (A G Inv : H →L[ℝ] H)
    (hA : IsSelfAdjoint A) (hG : IsSelfAdjoint G)
    (hInv : IsSelfAdjoint Inv) (hAInv : Commute A Inv)
    (hInvG : Inv * G = 1) (hGInv : G * Inv = 1)
    (hSquares : A * A + G * G = 1)
    (u v r : H) :
    let C : H → H → ℝ := fun u v =>
      (‖u‖^2 - ‖v‖^2)/2 - inner ℝ (A (Inv u)) v
    C (u + G r) (v - A r) - C u v =
      inner ℝ u (Inv r) + ‖r‖^2/2
 := by
  dsimp only
  have ha (x y : H) : inner ℝ (A x) y=inner ℝ x (A y) := hA.isSymmetric x y
  have hg (x y : H) : inner ℝ (G x) y=inner ℝ x (G y) := hG.isSymmetric x y
  have hi (x y : H) : inner ℝ (Inv x) y=inner ℝ x (Inv y) := hInv.isSymmetric x y
  have hIG (x : H) : Inv (G x)=x := by
    have h := congrArg (fun L : H →L[ℝ] H => L x) hInvG
    simpa only [ContinuousLinearMap.mul_apply,ContinuousLinearMap.one_apply] using h
  have hSq (x : H) : A (A x)+G (G x)=x := by
    have h := congrArg (fun L : H →L[ℝ] H => L x) hSquares
    simpa only [ContinuousLinearMap.add_apply,ContinuousLinearMap.mul_apply,
      ContinuousLinearMap.one_apply] using h
  have hEnergy (x : H) : ‖A x‖^2+‖G x‖^2=‖x‖^2 := by
    have h := congrArg (fun z : H => inner ℝ z x) (hSq x)
    rw [inner_add_left,ha (A x) x,hg (G x) x] at h
    simpa only [real_inner_self_eq_norm_sq] using h
  have hLinear (x : H) : Inv (A (A x))+G x=Inv x := by
    calc
      Inv (A (A x))+G x=Inv (A (A x))+Inv (G (G x)) := by rw [hIG]
      _ = Inv (A (A x)+G (G x)) := by rw [map_add]
      _ = Inv x := congrArg Inv (hSq x)
  have hMixed : inner ℝ (A (Inv u)) (A r)+inner ℝ u (G r)=inner ℝ u (Inv r) := by
    rw [ha (Inv u) (A r),hi u (A (A r)),
      ← inner_add_right,hLinear r]
  rw [norm_add_sq_real,norm_sub_sq_real]
  simp only [map_add,hIG,inner_add_left,inner_sub_right,real_inner_self_eq_norm_sq]
  rw [real_inner_comm v (A r)]
  nlinarith only [hEnergy r,hMixed]

end
end AutoSamplingTheory.TechnicalLemmas.Analysis.HilbertCorrectorPerturbation

#print axioms AutoSamplingTheory.TechnicalLemmas.Analysis.HilbertCorrectorPerturbation.quadratic_corrector_perturbation

Exact module and namespace context

Scope and omitted-condition boundaries
  • The bounded corrector perturbation identity is focused-compiled. Arbitrary r is not the actual source residual r_rho. Actual conditional half-turn H, K/B7, r/r_rho/B27, B4/B28 dynamics, H1/B2, invariance/nonexplosion, full PBPS/SPHMC results, implementation errors/caps, expected-query costs and actual-input composition remain open. The perturbation identity alone establishes no Exposition Seal, PURIFIED, main/live, whole-paper or Goal completion; independent review and serialized integration are separate admissions.
Sources, dependencies, and reuse

Source and reuse

Samplinglib parents called

    Mathlib API called (external library)

    • IsSelfAdjoint.isSymmetric
    • ContinuousLinearMap.mul_apply
    • ContinuousLinearMap.one_apply
    • real_inner_self_eq_norm_sq
    • norm_add_sq_real
    • norm_sub_sq_real
    • real_inner_comm
    • congrArg

    Mathematical sources

    • PBPS B20 and Appendix B4 Ex28--Ex34 perturbation algebra; future actual B27/B28 adapter — The bounded corrector perturbation identity is focused-compiled. Arbitrary r is not the actual source residual r_rho. Actual conditional half-turn H, K/B7, r/r_rho/B27, B4/B28 dynamics, H1/B2, invariance/nonexplosion, full PBPS/SPHMC results, implementation errors/caps, expected-query costs and actual-input composition remain open. The perturbation identity alone establishes no Exposition Seal, PURIFIED, main/live, whole-paper or Goal completion; independent review and serialized integration are separate admissions.

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