roseking's picture
Add lean source and binary files (part 121)
f61e547 verified
Raw History Blame Contribute Delete
6.3 kB
import OAI.Probability.FreeIsing.Conditioning.CopyVariance
import OAI.Probability.FreeIsing.Conditioning.KernelConditionalExpectation
namespace OAI
noncomputable section
open MeasureTheory ProbabilityTheory
namespace Problem367
variable {W Ω : Type*} [MeasurableSpace W] [MeasurableSpace Ω]
(ν : Measure W) [SFinite ν] (κ : Kernel W Ω) [IsMarkovKernel κ]
theorem measurePreserving_conditionalCopy_fst :
MeasurePreserving (Prod.map id Prod.fst : W × (Ω × Ω) → W × Ω)
(ν ⊗ₘ (κ ×ₖ κ)) (ν ⊗ₘ κ) := by
refine ⟨by fun_prop, ?_⟩
rw [← Measure.compProd_map measurable_fst, ← Kernel.fst_eq, Kernel.fst_prod]
theorem measurePreserving_conditionalCopy_snd :
MeasurePreserving (Prod.map id Prod.snd : W × (Ω × Ω) → W × Ω)
(ν ⊗ₘ (κ ×ₖ κ)) (ν ⊗ₘ κ) := by
refine ⟨by fun_prop, ?_⟩
rw [← Measure.compProd_map measurable_snd, ← Kernel.snd_eq, Kernel.snd_prod]
variable {ν κ}
theorem memLp_conditionalCopy_fst {X : Ω → ℝ}
(hX : MemLp (fun z : W × Ω => X z.2) 2 (ν ⊗ₘ κ)) :
MemLp (fun z : W × (Ω × Ω) => X z.2.1) 2 (ν ⊗ₘ (κ ×ₖ κ)) := by
convert hX.comp_measurePreserving (measurePreserving_conditionalCopy_fst ν κ) using 1
rfl
theorem memLp_conditionalCopy_snd {X : Ω → ℝ}
(hX : MemLp (fun z : W × Ω => X z.2) 2 (ν ⊗ₘ κ)) :
MemLp (fun z : W × (Ω × Ω) => X z.2.2) 2 (ν ⊗ₘ (κ ×ₖ κ)) := by
convert hX.comp_measurePreserving (measurePreserving_conditionalCopy_snd ν κ) using 1
rfl
theorem ae_memLp_conditionalCopies_fiber {X : Ω → ℝ}
(hX : MemLp (fun z : W × Ω => X z.2) 2 (ν ⊗ₘ κ)) :
∀ᵐ z : W × (Ω × Ω) ∂ν ⊗ₘ (κ ×ₖ κ), MemLp X 2 (κ z.1) := by
refine ae_of_ae_map (μ := ν ⊗ₘ (κ ×ₖ κ)) (f := Prod.fst)
(p := fun w => MemLp X 2 (κ w)) measurable_fst.aemeasurable ?_
change ∀ᵐ w ∂(ν ⊗ₘ (κ ×ₖ κ)).fst, MemLp X 2 (κ w)
rw [Measure.fst_compProd]
exact ae_memLp_two_of_compProd hX
theorem integral_sq_sub_conditionalCopies {X : Ω → ℝ}
(hX : MemLp (fun z : W × Ω => X z.2) 2 (ν ⊗ₘ κ)) :
(∫ z : W × (Ω × Ω), (X z.2.1 - X z.2.2) ^ 2 ∂ν ⊗ₘ (κ ×ₖ κ)) =
2 * ∫ w, variance X (κ w) ∂ν := by
have h₁ := memLp_conditionalCopy_fst hX
have h₂ := memLp_conditionalCopy_snd hX
have hi : Integrable (fun z : W × (Ω × Ω) => (X z.2.1 - X z.2.2) ^ 2)
(ν ⊗ₘ (κ ×ₖ κ)) := (h₁.sub h₂).integrable_sq
rw [Measure.integral_compProd hi]
calc
(∫ w, ∫ p : Ω × Ω, (X p.1 - X p.2) ^ 2 ∂(κ ×ₖ κ) w ∂ν) =
∫ w, 2 * variance X (κ w) ∂ν := by
apply integral_congr_ae
filter_upwards [ae_memLp_two_of_compProd hX] with w hw
simpa only [Kernel.prod_apply] using integral_sq_sub_copies_eq_two_variance hw
_ = 2 * ∫ w, variance X (κ w) ∂ν := integral_const_mul _ _
theorem integrable_variance_kernel {X : Ω → ℝ}
(hX : MemLp (fun z : W × Ω => X z.2) 2 (ν ⊗ₘ κ)) :
Integrable (fun w => variance X (κ w)) ν := by
have hi : Integrable (fun z : W × (Ω × Ω) => (X z.2.1 - X z.2.2) ^ 2)
(ν ⊗ₘ (κ ×ₖ κ)) :=
((memLp_conditionalCopy_fst hX).sub (memLp_conditionalCopy_snd hX)).integrable_sq
have hn := ((Measure.integrable_compProd_iff hi.aestronglyMeasurable).1 hi).2
have hm : Integrable (fun w => ∫ p : Ω × Ω,
(X p.1 - X p.2) ^ 2 ∂(κ ×ₖ κ) w) ν := by
simpa only [Real.norm_eq_abs, abs_sq] using hn
have hv : Integrable (fun w => 2 * variance X (κ w)) ν := hm.congr (by
filter_upwards [ae_memLp_two_of_compProd hX] with w hw
simpa only [Kernel.prod_apply] using integral_sq_sub_copies_eq_two_variance hw)
convert hv.const_mul (1 / 2 : ℝ) using 1
funext w
ring
theorem conditionalCopies_ae_eq_of_integral_variance_eq_zero {X : Ω → ℝ}
(hX : MemLp (fun z : W × Ω => X z.2) 2 (ν ⊗ₘ κ))
(hv : (∫ w, variance X (κ w) ∂ν) = 0) :
∀ᵐ z : W × (Ω × Ω) ∂ν ⊗ₘ (κ ×ₖ κ), X z.2.1 = X z.2.2 := by
have hi : Integrable (fun z : W × (Ω × Ω) => (X z.2.1 - X z.2.2) ^ 2)
(ν ⊗ₘ (κ ×ₖ κ)) :=
((memLp_conditionalCopy_fst hX).sub (memLp_conditionalCopy_snd hX)).integrable_sq
have hz : (∫ z : W × (Ω × Ω), (X z.2.1 - X z.2.2) ^ 2
∂ν ⊗ₘ (κ ×ₖ κ)) = 0 := by
rw [integral_sq_sub_conditionalCopies hX, hv, mul_zero]
have heq := (integral_eq_zero_iff_of_nonneg (fun _ => sq_nonneg _) hi).1 hz
filter_upwards [heq] with z hz
simpa only [Pi.zero_apply, sq_eq_zero_iff, sub_eq_zero] using hz
section ConditionalExpectation
variable [StandardBorelSpace Ω] [Nonempty Ω] [IsFiniteMeasure ν]
theorem condExp_sq_sub_conditionalCopies {X : Ω → ℝ}
(hX : MemLp (fun z : W × Ω => X z.2) 2 (ν ⊗ₘ κ)) :
(ν ⊗ₘ (κ ×ₖ κ))[(fun z : W × (Ω × Ω) => (X z.2.1 - X z.2.2) ^ 2) |
(inferInstance : MeasurableSpace W).comap Prod.fst] =ᵐ[ν ⊗ₘ (κ ×ₖ κ)]
fun z => 2 * variance X (κ z.1) := by
have hi : Integrable (fun z : W × (Ω × Ω) => (X z.2.1 - X z.2.2) ^ 2)
(ν ⊗ₘ (κ ×ₖ κ)) :=
((memLp_conditionalCopy_fst hX).sub (memLp_conditionalCopy_snd hX)).integrable_sq
have hlift := ae_memLp_conditionalCopies_fiber hX
filter_upwards [condExp_compProd_fst hi, hlift] with z hcz hz
rw [hcz, Kernel.prod_apply]
exact integral_sq_sub_copies_eq_two_variance hz
theorem condExp_sub_conditionalCopies {X : Ω → ℝ}
(hX : MemLp (fun z : W × Ω => X z.2) 2 (ν ⊗ₘ κ)) :
(ν ⊗ₘ (κ ×ₖ κ))[(fun z : W × (Ω × Ω) => X z.2.1 - X z.2.2) |
(inferInstance : MeasurableSpace W).comap Prod.fst] =ᵐ[ν ⊗ₘ (κ ×ₖ κ)] 0 := by
have hi : Integrable (fun z : W × (Ω × Ω) => X z.2.1 - X z.2.2)
(ν ⊗ₘ (κ ×ₖ κ)) :=
((memLp_conditionalCopy_fst hX).sub (memLp_conditionalCopy_snd hX)).integrable (by simp)
filter_upwards [condExp_compProd_fst hi, ae_memLp_conditionalCopies_fiber hX]
with z hcz hz
rw [hcz, Kernel.prod_apply,
integral_sub ((hz.comp_fst (κ z.1)).integrable (by simp))
((hz.comp_snd (κ z.1)).integrable (by simp))]
simp [integral_fun_fst, integral_fun_snd]
end ConditionalExpectation
end Problem367
end
end OAI