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Samplinglib mathematical lesson

Noncompact C2 Gaussian function log-Sobolev inequality

AutoSamplingTheory.TechnicalLemmas.FunctionalInequalities.GaussianLogSobolev.gaussian_logSobolev_of_contDiff · theorem · Teaching coverage

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Mathematical statement

For every finite-dimensional complete real Hilbert/Borel space E, including rank zero, let gamma be literal stdGaussian E. Every signed real globally C2 f with actual f in L2(gamma), true gradient f in L2(gamma), and Phi(f²) integrable satisfies homogeneous Ent_gamma(f²)≤2 integral norm(gradient f)^2. The actual cutoff mass, entropy and gradient-energy limits are proved internally. Phi(t)=t log t is continuous at zero; neither positive mass nor normalization nor compact support is assumed.

\[\operatorname{Ent}_{\gamma}(f^2):=\int\Phi(f^2)\,d\gamma-\Phi\!\left(\int f^2\,d\gamma\right)\le2\int\|\nabla f\|^2\,d\gamma,\quad\gamma=\mathrm{stdGaussian}(E),\quad\Phi(t)=t\log t.\]
Lean statement · gaussian_logSobolev_of_contDiff

For every finite-dimensional complete real Hilbert/Borel space E, including rank zero, let gamma be literal stdGaussian E. Every signed real globally C2 f with actual f in L2(gamma), true gradient f in L2(gamma), and Phi(f²) integrable satisfies homogeneous Ent_gamma(f²)<=2 integral norm(gradient f)^2. The actual cutoff mass, entropy and gradient-energy limits are proved internally. Phi(t)=t log t is continuous at zero; neither positive mass nor normalization nor compact support is assumed.

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 gaussian_logSobolev_of_contDiff
    {E : Type*} [NormedAddCommGroup E] [InnerProductSpace ℝ E]
    [CompleteSpace E] [FiniteDimensional ℝ E]
    [MeasurableSpace E] [BorelSpace E]
    (f : E → ℝ) (hf : ContDiff ℝ 2 f)
    (hf2 : MemLp f 2 (ProbabilityTheory.stdGaussian E))
    (hgrad2 : MemLp (gradient f) 2 (ProbabilityTheory.stdGaussian E))
    (hentropy : Integrable (fun x => (f x)^2 * Real.log ((f x)^2))
      (ProbabilityTheory.stdGaussian E)) :
    let γ : Measure E := ProbabilityTheory.stdGaussian E
    (∫ x, (f x)^2 * Real.log ((f x)^2) ∂γ) -
      (∫ x, (f x)^2 ∂γ) * Real.log (∫ x, (f x)^2 ∂γ) ≤
      2 * ∫ x, ‖gradient f x‖^2 ∂γ

Exact module and namespace context

Proof roadmap

  1. 1Derive genuine square and energy domains

    The two genuine L2 hypotheses imply square and Hilbert-gradient-energy L1. The entropy L1 is the third analytic-domain premise. C2 gives continuity and the true Riesz-gradient measurability needed below; no totalized-integral fallback is used.

  2. 2Construct actual compact approximants

    Use the canonical radial cutoff at R_n=n+1, multiply by f, and derive C2compact regularity. One positive derivative constant C is chosen before all radii. Range[0,1] and the real neighborhood plateau come from the same actual cutoff.

  3. 3Bound the true gradient and identify its limit

    Apply the real product derivative and Riesz inverse, whose isometry identifies derivative norm with gradient norm. With R_n≥1, the square energy is dominated by2G²+2C²f². For each point the cutoff equals1 on a neighborhood for all sufficiently large radii, so its product has exactly the original true gradient there, including rank0.

  4. 4Control entropy even where the density vanishes

    The totalized zero-aware product identity gives Phi(aq)=aPhi(q)+qPhi(a). For0≤a≤1, the lower bound a-1≤Phi(a) and Phi(a)≤0 imply |Phi(a)|≤1. With a=chi_n² and q=f² this gives an integrable dominator without taking log of f or dividing by mass.

  5. 5Prove all three real integral limits

    Apply dominated convergence separately with q, |Phi(q)|+q and2G²+2C²q. Every sequence is strongly measurable through actual continuity, every dominator is L1 from the analytic domains, and the pointwise limits are proved using the actual cutoff and gradient plateau.

  6. 6Pass the compact inequalities without changing the constant

    Apply actual compact41LSI to each f_n. Continuity of Phi at the limiting mass, including mass0, gives the homogeneous entropy limit. Closed-order convergence passes the inequalities with the unchanged coefficient2.

  7. 7Exercise the actual noncompact posterior

    The true standardizedRGO theorem supplies C2, fL2, gradientL2 and qlogqL1 at its actual proximal witness, with f²=q. The Test applies this new result to the raw f=exp(-rho/2)/sqrtZ, without a cutoff certificate or upper step-size restriction. The distinct33KL witness must still be reconciled; GaussianT2/FIRST4.6 remain separate.

Full assumptions and notation

All objects and hypotheses

  • E is a finite-dimensional complete real Hilbert space with compatible Borel measurable structure; rank0 is permitted.
  • f is signed globally C2; actual MemLp f2 and MemLp true gradient f2 hold under literal gamma.
  • Actual Phi(f²) is Integrable gamma. These domain predicates are real32 outputs at the paper consumer, not extra FIRST premises or limit certificates.
  • Real Bochner integrals use true L1 domains; coefficient2 is variance1 Gaussian, with homogeneous entropy allowing mass0.

Mathematical proof

1. Derive genuine square and energy domains

The two genuine L2 hypotheses imply square and Hilbert-gradient-energy L1. The entropy L1 is the third analytic-domain premise. C2 gives continuity and the true Riesz-gradient measurability needed below; no totalized-integral fallback is used.

\[f\in L^2(\gamma),\ \nabla f\in L^2(\gamma),\ \Phi(f^2)\in L^1(\gamma)\ \Longrightarrow\ f^2,\|\nabla f\|^2\in L^1(\gamma).\]
Corresponding Lean step

MemLp.integrable_sq; memLp_two_iff_integrable_sq_norm; continuous_gradient_of_contDiff_one

2. Construct actual compact approximants

Use the canonical radial cutoff at R_n=n+1, multiply by f, and derive C2compact regularity. One positive derivative constant C is chosen before all radii. Range[0,1] and the real neighborhood plateau come from the same actual cutoff.

\[R_n=n+1,\quad\chi_n=\mathrm{radialSmoothCutoff}(R_n),\quad f_n=\chi_nf,\quad0\le\chi_n\le1,\quad\|D\chi_n\|\le C/R_n.\]
Corresponding Lean step

radialSmoothCutoff_contDiff; radialSmoothCutoff_hasCompactSupport; radialSmoothCutoff_mem_Icc; radialSmoothCutoff_fderiv_bound

3. Bound the true gradient and identify its limit

Apply the real product derivative and Riesz inverse, whose isometry identifies derivative norm with gradient norm. With R_n≥1, the square energy is dominated by2G²+2C²f². For each point the cutoff equals1 on a neighborhood for all sufficiently large radii, so its product has exactly the original true gradient there, including rank0.

\[\nabla f_n=\chi_n\nabla f+f\nabla\chi_n,\quad\|\nabla f_n\|^2\le2\|\nabla f\|^2+2C^2f^2,\quad\nabla f_n(x)=\nabla f(x)\ \text{eventually}.\]
Corresponding Lean step

gradient_mul; cutoff_energy_bound; cutoff_gradient_eventually_eq; Filter.EventuallyEq.gradient_eq

4. Control entropy even where the density vanishes

The totalized zero-aware product identity gives Phi(aq)=aPhi(q)+qPhi(a). For0≤a≤1, the lower bound a-1≤Phi(a) and Phi(a)≤0 imply |Phi(a)|≤1. With a=chi_n² and q=f² this gives an integrable dominator without taking log of f or dividing by mass.

\[\Phi(aq)=a\Phi(q)+q\Phi(a),\quad|\Phi(a)|\le1\ (0\le a\le1),\quad|\Phi(f_n^2)|\le|\Phi(f^2)|+f^2.\]
Corresponding Lean step

entropy_dilation_bound; Real.negMulLog_mul; Real.self_sub_one_le_mul_log; Real.mul_log_nonpos

5. Prove all three real integral limits

Apply dominated convergence separately with q, |Phi(q)|+q and2G²+2C²q. Every sequence is strongly measurable through actual continuity, every dominator is L1 from the analytic domains, and the pointwise limits are proved using the actual cutoff and gradient plateau.

\[\int f_n^2\,d\gamma\to\int f^2\,d\gamma,\quad\int\Phi(f_n^2)\,d\gamma\to\int\Phi(f^2)\,d\gamma,\quad\int\|\nabla f_n\|^2\,d\gamma\to\int\|\nabla f\|^2\,d\gamma.\]
Corresponding Lean step

cutoff_integral_limits; tendsto_integral_of_dominated_convergence; radialSmoothCutoff_tendsto_one

6. Pass the compact inequalities without changing the constant

Apply actual compact41LSI to each f_n. Continuity of Phi at the limiting mass, including mass0, gives the homogeneous entropy limit. Closed-order convergence passes the inequalities with the unchanged coefficient2.

\[\operatorname{Ent}_{\gamma}(f_n^2)\le2\int\|\nabla f_n\|^2\,d\gamma\ \Longrightarrow\ \operatorname{Ent}_{\gamma}(f^2)\le2\int\|\nabla f\|^2\,d\gamma.\]
Corresponding Lean step

compact_stdGaussian_logSobolev; Real.continuous_mul_log; le_of_tendsto_of_tendsto

7. Exercise the actual noncompact posterior

The true standardizedRGO theorem supplies C2, fL2, gradientL2 and qlogqL1 at its actual proximal witness, with f²=q. The Test applies this new result to the raw f=exp(-rho/2)/sqrtZ, without a cutoff certificate or upper step-size restriction. The distinct33KL witness must still be reconciled; GaussianT2/FIRST4.6 remain separate.

\[f(u)=e^{-\rho(u)/2}/\sqrt Z,\quad f^2=q,\quad\operatorname{Ent}_{\gamma}(f^2)\le2\int\|\nabla f\|^2\,d\gamma.\]
Corresponding Lean step

actual_posterior_noncompact_lsi; standardized_rgo_sqrt_density_domain

Lean verification

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

Lean proof · gaussian_logSobolev_of_contDiff

Derive genuine square and energy domains; Construct actual compact approximants; Bound the true gradient and identify its limit; Control entropy even where the density vanishes; Prove all three real integral limits; Pass the compact inequalities without changing the constant; Exercise the actual noncompact posterior

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 gaussian_logSobolev_of_contDiff
    {E : Type*} [NormedAddCommGroup E] [InnerProductSpace ℝ E]
    [CompleteSpace E] [FiniteDimensional ℝ E]
    [MeasurableSpace E] [BorelSpace E]
    (f : E → ℝ) (hf : ContDiff ℝ 2 f)
    (hf2 : MemLp f 2 (ProbabilityTheory.stdGaussian E))
    (hgrad2 : MemLp (gradient f) 2 (ProbabilityTheory.stdGaussian E))
    (hentropy : Integrable (fun x => (f x)^2 * Real.log ((f x)^2))
      (ProbabilityTheory.stdGaussian E)) :
    let γ : Measure E := ProbabilityTheory.stdGaussian E
    (∫ x, (f x)^2 * Real.log ((f x)^2) ∂γ) -
      (∫ x, (f x)^2 ∂γ) * Real.log (∫ x, (f x)^2 ∂γ) ≤
      2 * ∫ x, ‖gradient f x‖^2 ∂γ := by
  dsimp only
  let γ := ProbabilityTheory.stdGaussian E
  let fn := fun n : ℕ => fun x : E => radialSmoothCutoff ((n:ℝ)+1) x * f x
  obtain ⟨hm,hp,he⟩ := cutoff_integral_limits γ f hf hf2 hgrad2 hentropy
  have hle (n : ℕ) :
      (∫ x, (fn n x)^2 * Real.log ((fn n x)^2) ∂γ) -
      (∫ x, (fn n x)^2 ∂γ) * Real.log (∫ x, (fn n x)^2 ∂γ) ≤
        2 * ∫ x, ‖gradient (fn n) x‖^2 ∂γ := by
    have hc : ContDiff ℝ 2 (radialSmoothCutoff ((n:ℝ)+1) : E → ℝ) :=
      (radialSmoothCutoff_contDiff (by positivity)).of_le
        (WithTop.coe_le_coe.mpr (le_top : (2 : ℕ∞) ≤ ⊤))
    have hs : HasCompactSupport (fn n) :=
      (radialSmoothCutoff_hasCompactSupport (by positivity)).mul_right
    exact (GaussianCompactHilbertLogSobolev.compact_stdGaussian_logSobolev
      (fn n) (hc.mul hf) hs).2.2.2
  exact le_of_tendsto_of_tendsto
    (hp.sub (Real.continuous_mul_log.continuousAt.tendsto.comp hm))
    (he.const_mul 2) (Eventually.of_forall hle)

end AutoSamplingTheory.TechnicalLemmas.FunctionalInequalities.GaussianLogSobolev

Exact module and namespace context

Scope and omitted-condition boundaries
  • Actual stdGaussian E on finite-dimensional real Hilbert/Borel E, signed globally C2 f with real fL2/gradientL2/Phi(f²)L1 domains. These are produced by actual32 for its true sqrt-density. No cutoff limit/desired inequality/domain-of-repaired-density/law/energy certificate premises. Genuine noncompact function-LSI coefficient2 through internally derived actual cutoff limits; rank0/zero mass retained. Coherent33 KL/Fisher, full weak W12 extension, separate GaussianT2/FIRST4.6/both paper main/error/cost/composition/fullreader remain OPEN. Actual focused3813 passes: true noncompact32 posterior f and its real analytic domains, generic zero and negative constant actualmass4 in every dimension. Independent wholeproof/source/exactcommit/shared admission pending. No coherent33canonicalKL/Fisher or T2/FIRST/main/cost claim.
Sources, dependencies, and reuse

Source and reuse

Samplinglib parents called

Mathlib API called (external library)

  • MemLp.integrable_sq
  • memLp_two_iff_integrable_sq_norm
  • fderiv_fun_mul
  • InnerProductSpace.toDual
  • Real.negMulLog_mul
  • Real.self_sub_one_le_mul_log
  • Real.mul_log_nonpos
  • Filter.EventuallyEq.gradient_eq
  • Real.continuous_mul_log
  • MeasureTheory.tendsto_integral_of_dominated_convergence
  • le_of_tendsto_of_tendsto

Mathematical sources

  • FIRST S4.E6 / S4.SS1.p4.3 omitted GaussianLSI background; actual32 domain consumer — Actual stdGaussian E on finite-dimensional real Hilbert/Borel E, signed globally C2 f with real fL2/gradientL2/Phi(f²)L1 domains. These are produced by actual32 for its true sqrt-density. No cutoff limit/desired inequality/domain-of-repaired-density/law/energy certificate premises. Genuine noncompact function-LSI coefficient2 through internally derived actual cutoff limits; rank0/zero mass retained. Coherent33 KL/Fisher, full weak W12 extension, separate GaussianT2/FIRST4.6/both paper main/error/cost/composition/fullreader remain OPEN. Actual focused3813 passes: true noncompact32 posterior f and its real analytic domains, generic zero and negative constant actualmass4 in every dimension. Independent wholeproof/source/exactcommit/shared admission pending. No coherent33canonicalKL/Fisher or T2/FIRST/main/cost claim.

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