AutoSamplingTheory.TechnicalLemmas.Measure.DisplacementRealQuadraticCost
3 named declarations scanned from AutoSamplingTheory/TechnicalLemmas/Measure/DisplacementRealQuadraticCost.lean.
Declarations
theorem AutoSamplingTheory.TechnicalLemmas.Measure.DisplacementRealQuadraticCost.ofReal_integral_norm_sq_eq_lintegral_quadraticCost Partial Not mapped
- The real Bochner integral of squared displacement and the ENNReal quadratic-cost lintegral are the same finite quantity, viewed in ENNReal.
theorem ofReal_integral_norm_sq_eq_lintegral_quadraticCost
(γ : Measure (E × E))
(hcost : Integrable (fun z : E × E => ‖z.1 - z.2‖ ^ 2) γ) :
ENNReal.ofReal (∫ z, ‖z.1 - z.2‖ ^ 2 ∂γ) =
∫⁻ z, WassersteinSpace.quadraticCost (E := E) z ∂γ := by
simpa [WassersteinSpace.quadraticCost] using
(ofReal_integral_eq_lintegral_ofReal hcost
(Filter.Eventually.of_forall fun z : E × E => sq_nonneg ‖z.1 - z.2‖))
/-- For a quadratic-cost optimal coupling, the real squared-displacement
integral is exactly the squared Wasserstein distance after embedding into
ENNReal. -/
AutoSamplingTheory/TechnicalLemmas/Measure/DisplacementRealQuadraticCost.lean:38published source at 0e31a3cda412
theorem AutoSamplingTheory.TechnicalLemmas.Measure.DisplacementRealQuadraticCost.ofReal_integral_norm_sq_eq_wassersteinDistance_sq_of_optimal Partial Not mapped
- For a quadratic-cost optimal coupling, the real squared-displacement integral is exactly the squared Wasserstein distance after embedding into ENNReal.
theorem ofReal_integral_norm_sq_eq_wassersteinDistance_sq_of_optimal
{γ : Measure (E × E)} {μ₀ μ₁ : Measure E}
(hγ : DisplacementInterpolation.IsQuadraticOptimalCoupling γ μ₀ μ₁)
(hcost : Integrable (fun z : E × E => ‖z.1 - z.2‖ ^ 2) γ) :
ENNReal.ofReal (∫ z, ‖z.1 - z.2‖ ^ 2 ∂γ) =
WassersteinSpace.wassersteinDistance μ₀ μ₁ ^ 2 := by
calc
ENNReal.ofReal (∫ z, ‖z.1 - z.2‖ ^ 2 ∂γ) =
∫⁻ z, WassersteinSpace.quadraticCost (E := E) z ∂γ :=
ofReal_integral_norm_sq_eq_lintegral_quadraticCost γ hcost
_ = Transport.transportCost
(WassersteinSpace.quadraticCost (E := E)) μ₀ μ₁ := hγ.2
_ = WassersteinSpace.wassersteinDistance μ₀ μ₁ ^ 2 :=
(WassersteinSpace.wassersteinDistance_sq μ₀ μ₁).symm
/-- Real-valued form convenient for the potential-energy inequality: the
quadratic coupling integral is the `toReal` value of `W₂^2`. Integrability of
the real cost supplies finiteness automatically through the preceding ENNReal
identity. -/
AutoSamplingTheory/TechnicalLemmas/Measure/DisplacementRealQuadraticCost.lean:50published source at 0e31a3cda412
theorem AutoSamplingTheory.TechnicalLemmas.Measure.DisplacementRealQuadraticCost.integral_norm_sq_eq_wassersteinDistance_sq_toReal_of_optimal Partial Not mapped
- Real-valued form convenient for the potential-energy inequality: the quadratic coupling integral is the `toReal` value of `W₂^2`. Integrability of the real cost supplies finiteness automatically through the preceding ENNReal identity.
theorem integral_norm_sq_eq_wassersteinDistance_sq_toReal_of_optimal
{γ : Measure (E × E)} {μ₀ μ₁ : Measure E}
(hγ : DisplacementInterpolation.IsQuadraticOptimalCoupling γ μ₀ μ₁)
(hcost : Integrable (fun z : E × E => ‖z.1 - z.2‖ ^ 2) γ) :
(∫ z, ‖z.1 - z.2‖ ^ 2 ∂γ) =
(WassersteinSpace.wassersteinDistance μ₀ μ₁ ^ 2).toReal := by
have hnonneg : 0 ≤ ∫ z, ‖z.1 - z.2‖ ^ 2 ∂γ :=
integral_nonneg fun z => sq_nonneg ‖z.1 - z.2‖
have h := congrArg ENNReal.toReal
(ofReal_integral_norm_sq_eq_wassersteinDistance_sq_of_optimal hγ hcost)
simpa [ENNReal.toReal_ofReal hnonneg] using h
end
end DisplacementRealQuadraticCost
end Measure
end TechnicalLemmas
end AutoSamplingTheory
AutoSamplingTheory/TechnicalLemmas/Measure/DisplacementRealQuadraticCost.lean:69published source at 0e31a3cda412