Couple the initial and reference phase laws with identical momentum
AutoSamplingTheory.ExampleCases.SmoothedPicardHMC.InitialPhaseTransport.phaseWassersteinSq_initial_le_position_moment · theorem · Teaching coverage
Mathematical statement
The actual initial phase law at xref and any product reference law with standard-Gaussian momentum admit a coupling that uses the same momentum on both sides. Its M-kappa transportation cost is at most the reference law's position second moment about xref.
Lean statement · phaseWassersteinSq_initial_le_position_moment
The result controls the squared Kantorovich value directly. It is generic in the position law, so the paper's smoothed Gibbs law must still be supplied by a separate specialization.
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 phaseWassersteinSq_initial_le_position_moment
(π : Measure E) [IsProbabilityMeasure π] (xref : E)
{κ : ℝ} (hκ : 1 ≤ κ)
(hpos : Integrable (fun y : E => ‖xref - y‖ ^ 2) π) :
PhaseMetric.phaseWassersteinSq κ
((Measure.dirac xref).prod (stdGaussian E))
(π.prod (stdGaussian E)) ≤
ENNReal.ofReal (∫ y : E, ‖xref - y‖ ^ 2 ∂π)Proof roadmap
- 1Build the actual coupling
Draw Y from pi and P independently from the standard Gaussian; pair the phase states (xref,P) and (Y,P). The first and second marginals are exactly the required phase laws.
- 2Cancel the momentum displacement
For a paired sample the momentum difference is zero. The paper's twisted quadratic form therefore reduces to its position coefficient, which is at most one when kappa is at least one.
- 3Bound the Kantorovich infimum
Any admissible coupling upper-bounds the optimal transport cost. Measurability permits pushforward integration, and the finite position moment converts the nonnegative Lebesgue integral back to the ordinary expectation.
Full assumptions and notation
All objects and hypotheses
- E is a finite-dimensional complete real inner-product Borel space.
- The target position law pi is a probability measure with an integrable squared distance from xref.
- The paper phase parameter kappa is at least one; its M_kappa quadratic form is used without changing normalization.
- Both phase laws use the same standard-Gaussian momentum marginal.
Mathematical proof
1. Build the actual coupling
Draw Y from pi and P independently from the standard Gaussian; pair the phase states (xref,P) and (Y,P). The first and second marginals are exactly the required phase laws.
Corresponding Lean step
identicalMomentumCoupling; Measure.fst_map_prodMk, Measure.snd_map_prodMk and Measure.dirac_prod certify both marginals.
2. Cancel the momentum displacement
For a paired sample the momentum difference is zero. The paper's twisted quadratic form therefore reduces to its position coefficient, which is at most one when kappa is at least one.
Corresponding Lean step
phaseCost_identical_momentum_le unfolds the exact phase cost and proves the coefficient inequality.
3. Bound the Kantorovich infimum
Any admissible coupling upper-bounds the optimal transport cost. Measurability permits pushforward integration, and the finite position moment converts the nonnegative Lebesgue integral back to the ordinary expectation.
Corresponding Lean step
Transport.transportCost_le_lintegral_of_isCoupling, lintegral_map, lintegral_mono and ofReal_integral_eq_lintegral_ofReal.
Lean verification
The exact proof begins folded immediately after the mathematical argument; the statement is folded beside the claim above.
Lean proof · phaseWassersteinSq_initial_le_position_moment
The proof constructs an explicit pushforward coupling; it does not assume existence of an optimal coupling. Product-law measurability and square integrability justify the cost calculation.
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 phaseWassersteinSq_initial_le_position_moment
(π : Measure E) [IsProbabilityMeasure π] (xref : E)
{κ : ℝ} (hκ : 1 ≤ κ)
(hpos : Integrable (fun y : E => ‖xref - y‖ ^ 2) π) :
PhaseMetric.phaseWassersteinSq κ
((Measure.dirac xref).prod (stdGaussian E))
(π.prod (stdGaussian E)) ≤
ENNReal.ofReal (∫ y : E, ‖xref - y‖ ^ 2 ∂π) := by
let γ := identicalMomentumCoupling π xref
have hγ := identicalMomentumCoupling_isCoupling π xref
have hcost := Transport.transportCost_le_lintegral_of_isCoupling
(PhaseMetric.phaseCost (E := E) κ) _ _ γ hγ
change PhaseMetric.phaseWassersteinSq κ _ _ ≤ _
refine hcost.trans ?_
have hmeas : Measurable (PhaseMetric.phaseCost (E := E) κ) := by
unfold PhaseMetric.phaseCost
change Measurable (fun z : (E × E) × (E × E) =>
ENNReal.ofReal ((1 / (2 * κ) + 1 / 2) * ‖(z.1 - z.2).1‖ ^ 2 +
inner ℝ (z.1 - z.2).1 (z.1 - z.2).2 + ‖(z.1 - z.2).2‖ ^ 2))
fun_prop
rw [show γ = (π.prod (stdGaussian E)).map (fun z => ((xref, z.2), z)) by rfl,
lintegral_map hmeas (by fun_prop)]
have hbound : (∫⁻ z : E × E,
PhaseMetric.phaseCost κ ((xref, z.2), z) ∂π.prod (stdGaussian E)) ≤
∫⁻ z : E × E, ENNReal.ofReal (‖xref - z.1‖ ^ 2) ∂π.prod (stdGaussian E) := by
apply lintegral_mono
intro z
exact phaseCost_identical_momentum_le hκ xref z.1 z.2
refine hbound.trans_eq ?_
rw [← ofReal_integral_eq_lintegral_ofReal
(hpos.comp_fst (stdGaussian E))
(Filter.Eventually.of_forall fun z => sq_nonneg _)]
congr 1
rw [integral_prod _ (hpos.comp_fst (stdGaussian E))]
simp
end AutoSamplingTheory.ExampleCases.SmoothedPicardHMC.InitialPhaseTransportSource assumptions versus formal assumptions
| Source | Actual Lean | Difference kind | Why it matters |
|---|---|---|---|
| The paper's Lemma 4.16 uses the smoothed Gibbs target Pi_eta. | The coupling-cost theorem accepts any position probability law with an integrable second moment about xref. | generalization | The identical-momentum coupling uses no Gibbs structure; the specialized numeric estimate is a separate remaining proof edge. |
| Lemma 4.16 concludes a W_q estimate for every q at least two. | The statement bounds the squared M_kappa Kantorovich cost, corresponding only to q=2. | source-implicit | This declaration binds only the explicit same-momentum proof component and does not claim the all-q source obligation. |
Only the generic q=2 coupling cost; no Gibbs numeric bound, all-q concentration, Picard history or query cost.
Encoder–denoiser: source-reviewed · 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
- This is only the q=2 coupling-cost edge in the proof of SPHMC Lemma 4.16. It does not yet insert Gibbs concentration or the small-gradient reference-point bound, establish q>2, or control any Picard trajectory.
Sources, dependencies, and reuse
Source and reuse
Samplinglib parents called
AutoSamplingTheory.ExampleCases.SmoothedPicardHMC.PhaseMetric.phaseWassersteinSqAutoSamplingTheory.ExampleCases.SmoothedPicardHMC.PhaseMetric.phaseCostAutoSamplingTheory.TechnicalLemmas.Measure.Transport.transportCost_le_lintegral_of_isCoupling
Mathlib API called (external library)
- Measure.fst_map_prodMk
- Measure.snd_map_prodMk
- Measure.dirac_prod
- lintegral_map
- ofReal_integral_eq_lintegral_ofReal
Mathematical sources
- Smoothed Picard Hamiltonian Monte Carlo, Lemma 4.16 proof — ASTIS expands the source's identical-momentum coupling and the precise Kantorovich-cost estimate.
Samplinglib prose is not a quotation or a source-equivalence certificate. Definitions and aliases are explained as constructions, not counted as new mathematical proofs.