Samplinglib
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True standardized RGO square-root density domains

Fan Chen, Sinho Chewi, Jianfeng Lu, Matthew S. Zhang; actual S4.Ex8 posterior residual with authored measurable-family extension; no printed inequality completion.

arXiv:2609.06906v1 with pinned Mathlib db584cd6 · S4.Ex8 actual residual/standardized posterior; S4.SS1.p4.2-p4.3 omitted classical domains before FIRST S4.E6 GaussianLSI/T2. · faithful paraphrase

Complete source statement (Samplinglib restatement)

For the true source RGO posterior standardized using the same internally produced measurable stationary proximal point, produce the actual relative Gaussian density, positive partition, C2 square root and all L2/entropy/gradient domains with the exact1/4 energy, for every eta(s)>0.

  • Complete finite-dimensional real Hilbert E with canonical volume and Borel structure, including dimension zero.
  • Unchanged source normalization kappa>=1, global C2 V with Hessian kappa^-1 I..I; measurable eta/y family S and every eta(s)>0 with no cap.
  • S/measurable-family scope is an authored extension. Constant Unit families recover printed fixed parameters. No stationary point, actual probability law, partition, density or domain certificates are public inputs.

True standardized RGO square-root density domains

\[r_s=(x\mapsto\eta_s^{-1/2}(x-p_s))_\#R_s=q_s\gamma,\quad q_s=e^{-\rho_s}/Z_s,\quad\nabla\log q_s=-\nabla\rho_s,\quad\int\|\nabla\sqrt{q_s}\|^2d\gamma=\tfrac14\int\|\nabla\rho_s\|^2dr_s.\]

Read the formalized proofs

Each statement and proof below has its own closed Lean disclosure. Samplinglib parents, Mathlib calls and external mathematical sources are distinguished in each proof.

Samplinglib mathematical lesson

True standardized RGO square-root density domains

AutoSamplingTheory.ExampleCases.SmoothedPicardHMC.StandardizedRGOSqrtDensity.standardized_rgo_sqrt_density_domain · theorem · Teaching coverage

Read this first

Mathematical statement

For the true source RGO posterior standardized using the same internally produced measurable stationary proximal point, produce the actual relative Gaussian density, positive partition, C2 square root and all L2/entropy/gradient domains with the exact1/4 energy, for every eta(s)>0.

\[r_s=(x\mapsto\eta_s^{-1/2}(x-p_s))_\#R_s=q_s\gamma,\quad q_s=e^{-\rho_s}/Z_s,\quad\nabla\log q_s=-\nabla\rho_s,\quad\int\|\nabla\sqrt{q_s}\|^2d\gamma=\tfrac14\int\|\nabla\rho_s\|^2dr_s.\]
Lean statement · standardized_rgo_sqrt_density_domain

For the true source RGO posterior standardized using the same internally produced measurable stationary proximal point, produce the actual relative Gaussian density, positive partition, C2 square root and all L2/entropy/gradient domains with the exact1/4 energy, for every eta(s)>0.

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 standardized_rgo_sqrt_density_domain
    {E S : Type*} [NormedAddCommGroup E] [InnerProductSpace ℝ E]
    [CompleteSpace E] [FiniteDimensional ℝ E] [MeasurableSpace E] [BorelSpace E]
    [MeasurableSpace S] {V : E → ℝ} {κ : ℝ}
    (hκ : 1 ≤ κ) (hV : ContDiff ℝ 2 V)
    (hH : ∀ x v : E, κ⁻¹*‖v‖^2 ≤ fderiv ℝ (fderiv ℝ V) x v v ∧
      fderiv ℝ (fderiv ℝ V) x v v ≤ ‖v‖^2)
    {eta : S → ℝ} {y : S → E} (heta : Measurable eta) (hy : Measurable y)
    (hpos : ∀ s, 0 < eta s) :
    ∃ p : S → E, Measurable p ∧
      (∀ s, p s+eta s • gradient V (p s)=y s) ∧
      let rho := fun s u => V (p s+Real.sqrt (eta s) • u)-V (p s)-
        Real.sqrt (eta s)*inner ℝ (gradient V (p s)) u
      let mu := (volume : Measure E).tilted (fun x => -V x)
      let R := fun s => mu.tilted (fun x => -‖x-y s‖^2/(2*eta s))
      let r := fun s => (R s).map (fun x => (Real.sqrt (eta s))⁻¹ • (x-p s))
      let gamma := stdGaussian E
      let Z := fun s => ∫ u, Real.exp (-rho s u) ∂gamma
      let q := fun s u => Real.exp (-rho s u)/Z s
      let f := fun s u => Real.exp (-rho s u/2)/Real.sqrt (Z s)
      ∀ s, 0 < Z s ∧ Z s ≤ 1 ∧
        r s = gamma.tilted (fun u => -rho s u) ∧
        r s = gamma.withDensity (fun u => ENNReal.ofReal (q s u)) ∧
        IsProbabilityMeasure (r s) ∧
        (∀ u, 0 < q s u ∧ f s u^2 = q s u) ∧
        (∫ u, q s u ∂gamma) = 1 ∧
        ContDiff ℝ 2 (f s) ∧ MemLp (f s) 2 gamma ∧
        MemLp (gradient (f s)) 2 gamma ∧ MemLp (gradient (rho s)) 2 (r s) ∧
        Integrable (fun u => q s u*Real.log (q s u)) gamma ∧
        (∀ u, gradient (f s) u = -(f s u/2) • gradient (rho s) u) ∧
        (∀ u, gradient (fun z => Real.log (q s z)) u = -gradient (rho s) u) ∧
        (∫ u, ‖gradient (f s) u‖^2 ∂gamma) =
          (1/4 : ℝ)*(∫ u, ‖gradient (rho s) u‖^2 ∂r s)

Exact module and namespace context

Proof roadmap

  1. 1Reuse the true posterior and the same stationary point

    The existing allpositive true standardized RGO producer constructs a measurable p with p+eta gradVp=y. Its literal affine pushforward r is the actual volume Gibbs law of norm²/2+rho, and its residual is C2 with gradientrho0=0 and Hessian0..eta. The residual value at0 is computed from its definition.

  2. 2Apply the new density-domain producer to that actual residual

    Instantiate the shared theorem with L=eta(s) and the same actual rho. Its canonical volume-law equality agrees with the true affine posterior law, yielding r=gamma.tilted(-rho), the actual normalized q, all square-root/entropy domains and actual probability. No output density or moment certificate is supplied.

  3. 3Keep the same law in every derivative and energy conclusion

    Transport only measure-valued fields along the proved actual-law equality. f_s and both gradients retain their literal representatives, and the exact1/4 energy uses that same true r_s. The measurable family is an authored extension; fixed parameters follow by Unit specialization. No eta upper cap or GaussianLSI/T2 conclusion is added.

Full assumptions and notation

All objects and hypotheses

  • Complete finite-dimensional real Hilbert E with canonical volume and Borel structure, including dimension zero.
  • Unchanged source normalization kappa≥1, global C2 V with Hessian kappa^-1 I..I; measurable eta/y family S and every eta(s)>0 with no cap.
  • S/measurable-family scope is an authored extension. Constant Unit families recover printed fixed parameters. No stationary point, actual probability law, partition, density or domain certificates are public inputs.

Mathematical proof

1. Reuse the true posterior and the same stationary point

The existing allpositive true standardized RGO producer constructs a measurable p with p+eta gradVp=y. Its literal affine pushforward r is the actual volume Gibbs law of norm²/2+rho, and its residual is C2 with gradientrho0=0 and Hessian0..eta. The residual value at0 is computed from its definition.

\[p_s+\eta_s\nabla V(p_s)=y_s,\quad r_s=(x\mapsto\eta_s^{-1/2}(x-p_s))_\#R_s,\quad\rho_s(u)=V(p_s+\sqrt{\eta_s}u)-V(p_s)-\sqrt{\eta_s}\langle\nabla V(p_s),u\rangle.\]
Corresponding Lean step

StandardizedRGOPositionFisher.standardized_rgo_position_and_fisher

2. Apply the new density-domain producer to that actual residual

Instantiate the shared theorem with L=eta(s) and the same actual rho. Its canonical volume-law equality agrees with the true affine posterior law, yielding r=gamma.tilted(-rho), the actual normalized q, all square-root/entropy domains and actual probability. No output density or moment certificate is supplied.

\[0<Z_s\le1,\quad q_s=e^{-\rho_s}/Z_s,\quad f_s=e^{-\rho_s/2}/\sqrt{Z_s},\quad r_s=q_s\gamma.\]
Corresponding Lean step

GaussianSqrtDensityDomain.gaussian_sqrt_density_domain; actual htrue

3. Keep the same law in every derivative and energy conclusion

Transport only measure-valued fields along the proved actual-law equality. f_s and both gradients retain their literal representatives, and the exact1/4 energy uses that same true r_s. The measurable family is an authored extension; fixed parameters follow by Unit specialization. No eta upper cap or GaussianLSI/T2 conclusion is added.

\[\nabla f_s=-\tfrac12f_s\nabla\rho_s,\quad\nabla\log q_s=-\nabla\rho_s,\quad\int\|\nabla f_s\|^2d\gamma=\frac14\int\|\nabla\rho_s\|^2dr_s\qquad(\eta_s>0).\]
Corresponding Lean step

actual hprob/hρlp/henergy transported along htrue; literal source family definitions

Lean verification

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

Lean proof · standardized_rgo_sqrt_density_domain

Reuse the true posterior and the same stationary point; Apply the new density-domain producer to that actual residual; Keep the same law in every derivative and energy conclusion

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 standardized_rgo_sqrt_density_domain
    {E S : Type*} [NormedAddCommGroup E] [InnerProductSpace ℝ E]
    [CompleteSpace E] [FiniteDimensional ℝ E] [MeasurableSpace E] [BorelSpace E]
    [MeasurableSpace S] {V : E → ℝ} {κ : ℝ}
    (hκ : 1 ≤ κ) (hV : ContDiff ℝ 2 V)
    (hH : ∀ x v : E, κ⁻¹*‖v‖^2 ≤ fderiv ℝ (fderiv ℝ V) x v v ∧
      fderiv ℝ (fderiv ℝ V) x v v ≤ ‖v‖^2)
    {eta : S → ℝ} {y : S → E} (heta : Measurable eta) (hy : Measurable y)
    (hpos : ∀ s, 0 < eta s) :
    ∃ p : S → E, Measurable p ∧
      (∀ s, p s+eta s • gradient V (p s)=y s) ∧
      let rho := fun s u => V (p s+Real.sqrt (eta s) • u)-V (p s)-
        Real.sqrt (eta s)*inner ℝ (gradient V (p s)) u
      let mu := (volume : Measure E).tilted (fun x => -V x)
      let R := fun s => mu.tilted (fun x => -‖x-y s‖^2/(2*eta s))
      let r := fun s => (R s).map (fun x => (Real.sqrt (eta s))⁻¹ • (x-p s))
      let gamma := stdGaussian E
      let Z := fun s => ∫ u, Real.exp (-rho s u) ∂gamma
      let q := fun s u => Real.exp (-rho s u)/Z s
      let f := fun s u => Real.exp (-rho s u/2)/Real.sqrt (Z s)
      ∀ s, 0 < Z s ∧ Z s ≤ 1 ∧
        r s = gamma.tilted (fun u => -rho s u) ∧
        r s = gamma.withDensity (fun u => ENNReal.ofReal (q s u)) ∧
        IsProbabilityMeasure (r s) ∧
        (∀ u, 0 < q s u ∧ f s u^2 = q s u) ∧
        (∫ u, q s u ∂gamma) = 1 ∧
        ContDiff ℝ 2 (f s) ∧ MemLp (f s) 2 gamma ∧
        MemLp (gradient (f s)) 2 gamma ∧ MemLp (gradient (rho s)) 2 (r s) ∧
        Integrable (fun u => q s u*Real.log (q s u)) gamma ∧
        (∀ u, gradient (f s) u = -(f s u/2) • gradient (rho s) u) ∧
        (∀ u, gradient (fun z => Real.log (q s z)) u = -gradient (rho s) u) ∧
        (∫ u, ‖gradient (f s) u‖^2 ∂gamma) =
          (1/4 : ℝ)*(∫ u, ‖gradient (rho s) u‖^2 ∂r s) := by
  obtain ⟨p,hpm,heq,hparent⟩ :=
    StandardizedRGOPositionFisher.standardized_rgo_position_and_fisher hκ hV hH heta hy hpos
  let rho := fun s u => V (p s+Real.sqrt (eta s) • u)-V (p s)-
    Real.sqrt (eta s)*inner ℝ (gradient V (p s)) u
  let mu := (volume : Measure E).tilted (fun x => -V x)
  let R := fun s => mu.tilted (fun x => -‖x-y s‖^2/(2*eta s))
  let r := fun s => (R s).map (fun x => (Real.sqrt (eta s))⁻¹ • (x-p s))
  let gamma := stdGaussian E
  let Z := fun s => ∫ u, Real.exp (-rho s u) ∂gamma
  let q := fun s u => Real.exp (-rho s u)/Z s
  let f := fun s u => Real.exp (-rho s u/2)/Real.sqrt (Z s)
  refine ⟨p,hpm,heq,?_⟩
  change ∀ s, 0 < Z s ∧ Z s ≤ 1 ∧ _
  intro s
  obtain ⟨_hRp,hρ,_hQ,hρgrad,_hQgrad,hρH,_hQH,hlaw,_hrest⟩ := hparent.2 s
  have hρzero : rho s 0 = 0 := by simp [rho]
  let L : ℝ≥0 := ⟨eta s,(hpos s).le⟩
  have hHρ : ∀ u v : E, 0 ≤ fderiv ℝ (fderiv ℝ (rho s)) u v v ∧
      fderiv ℝ (fderiv ℝ (rho s)) u v v ≤ (L : ℝ)*‖v‖^2 := hρH
  have hg := AutoSamplingTheory.TechnicalLemmas.Measure.GaussianSqrtDensityDomain.gaussian_sqrt_density_domain
    hρ hρzero hρgrad hHρ
  obtain ⟨hZ,hZone,hvolume,hdensity,hprob,hfq,hqone,hf,hflp,hfglp,hρlp,he,hdf,hdlog,henergy⟩ := hg
  have htrue : r s=gamma.tilted (fun u => -rho s u) := hlaw.trans hvolume.symm
  have hprob' : IsProbabilityMeasure (r s) := htrue.symm ▸ hprob
  have hρlp' : MemLp (gradient (rho s)) 2 (r s) := htrue.symm ▸ hρlp
  have henergy' : (∫ u, ‖gradient (f s) u‖^2 ∂gamma) =
      (1/4 : ℝ)*(∫ u, ‖gradient (rho s) u‖^2 ∂r s) := htrue.symm ▸ henergy
  exact ⟨hZ,hZone,htrue,htrue.trans hdensity,hprob',hfq,hqone,hf,hflp,hfglp,hρlp',
    he,hdf,hdlog,henergy'⟩

end
end AutoSamplingTheory.ExampleCases.SmoothedPicardHMC.StandardizedRGOSqrtDensity

Exact module and namespace context

Source assumptions versus formal assumptions

SourceActual LeanDifference kindWhy it matters
Standing normalized C2/curvature and eta>0 on finite Euclidean space.Complete finite-dimensional real Hilbert E with canonical volume and Borel structure, including dimension zero. Unchanged source normalization kappa>=1, global C2 V with Hessian kappa^-1 I..I; measurable eta/y family S and every eta(s)>0 with no cap. S/measurable-family scope is an authored extension. Constant Unit families recover printed fixed parameters. No stationary point, actual probability law, partition, density or domain certificates are public inputs.source-implicitConvex normalized rho hypotheses are internally derived from unchanged source V for the actual consumer; no domain certificate enters public source inputs.
S4.Ex8 and implicit density domains before GaussianLSI/T2.For the true source RGO posterior standardized using the same internally produced measurable stationary proximal point, produce the actual relative Gaussian density, positive partition, C2 square root and all L2/entropy/gradient domains with the exact1/4 energy, for every eta(s)>0.source-implicitSupply missing actual explicit-representative regularity and finite integrals as producer conclusions, without asserting GaussianLSI/T2 or changing source laws.
Printed source fixes eta and y.Existential measurable p over arbitrary measurable parameter S, with every positive eta(s).source-implicitAuthored extension explicitly marked; constant Unit specialization recovers source fixed parameters.
FIRST4.6 W2/LSI/T2, weakSobolev/KL identification, bias4.2, algorithms/main/work/composition.Actual positive Gaussian relative-density and classical C2/L2 square-root/entropy/log-gradient/Dirichlet=Fisher/4 domains, genuinely consumed by the source standardized true RGO. No Gaussian LSI/T2/KL weak representative/Sobolev adapter/W2/bias/fullLemma/main/work/composition credit. Focused3748 passed with E0/L0 and actual eta2y3 posterior tests, standard3 axioms only. Independent proof/blind/source/commit review and integration pending; postmerge purification, renderedQA and Copy/Download remain open.unresolvedThis packet only supplies classical actual-density and energy domains; no inequality, algorithm or paper completion.

Actual positive Gaussian relative-density and classical C2/L2 square-root/entropy/log-gradient/Dirichlet=Fisher/4 domains, genuinely consumed by the source standardized true RGO. No Gaussian LSI/T2/KL weak representative/Sobolev adapter/W2/bias/fullLemma/main/work/composition credit. Focused3748 passed with E0/L0 and actual eta2y3 posterior tests, standard3 axioms only. Independent proof/blind/source/commit review and integration pending; postmerge purification, renderedQA and Copy/Download remain open.

Encoder–denoiser: accepted · equivalent-after-elaboration

A generalization is not a source correction. Proposed missing conditions require separate independent repair review. No proposed repair silently changes the original theorem.

Scope and omitted-condition boundaries
  • Actual positive Gaussian relative-density and classical C2/L2 square-root/entropy/log-gradient/Dirichlet=Fisher/4 domains, genuinely consumed by the source standardized true RGO. No Gaussian LSI/T2/KL weak representative/Sobolev adapter/W2/bias/fullLemma/main/work/composition credit. Focused3748 passed with E0/L0 and actual eta2y3 posterior tests, standard3 axioms only. Independent proof/blind/source/commit review and integration pending; postmerge purification, renderedQA and Copy/Download remain open.
Sources, dependencies, and reuse

Source and reuse

Samplinglib parents called

Mathlib API called (external library)

No direct Mathlib call recorded; see the Samplinglib parents.

Mathematical sources

  • Actual source residual and omitted analytic prerequisites — Actual positive Gaussian relative-density and classical C2/L2 square-root/entropy/log-gradient/Dirichlet=Fisher/4 domains, genuinely consumed by the source standardized true RGO. No Gaussian LSI/T2/KL weak representative/Sobolev adapter/W2/bias/fullLemma/main/work/composition credit. Focused3748 passed with E0/L0 and actual eta2y3 posterior tests, standard3 axioms only. Independent proof/blind/source/commit review and integration pending; postmerge purification, renderedQA and Copy/Download remain open.

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

Which proof obligations and prerequisites are covered?

  • Formalized proof edge; source adapter/review separate Actual relative density, square-root/entropy and finite gradient energy domains
  • TODO — not closed by these contributions ActualLSI/T2/KL/weakSobolev/W2/bias/algorithm/work/main/composition remain open