openAI-math-dataset / lean /OAI /Probability /FreeIsing /Gaussian /BinaryFusionPosterior.lean
roseking's picture
Add lean source and binary files (part 121)
f61e547 verified
Raw History Blame Contribute Delete
4.8 kB
import OAI.Probability.FreeIsing.Conditioning.FiniteBayesCondExp
import OAI.Probability.FreeIsing.Gaussian.BinaryFusion
import OAI.Probability.FreeIsing.Spins.Kernel
namespace OAI
noncomputable section
open MeasureTheory ProbabilityTheory Filter
open scoped ENNReal ProbabilityTheory
namespace Problem367
local instance : MeasurableSingletonClass IsingSpin where
measurableSet_singleton _ := trivial
local instance : Nonempty IsingSpin := ⟨.neg⟩
theorem binaryFusion_likelihood_nonneg {u v : ℝ}
(hu : |u| ≤ 1) (hv : |v| ≤ 1) (a : IsingSpin) :
0 ≤ (1 + spinSign a * u) * (1 + spinSign a * v) := by
rcases abs_le.mp hu with ⟨hu₁, hu₂⟩
rcases abs_le.mp hv with ⟨hv₁, hv₂⟩
cases a <;> simp only [spinSign_neg, spinSign_pos, neg_one_mul, one_mul] <;>
apply mul_nonneg <;> linarith
theorem binaryFusion_likelihood_sum {u v : ℝ}
(hu : |u| ≤ 1) (hv : |v| ≤ 1) :
(∑ a : IsingSpin, ENNReal.ofReal (1 / 2 : ℝ) *
ENNReal.ofReal ((1 + spinSign a * u) * (1 + spinSign a * v))) =
ENNReal.ofReal (1 + u * v) := by
simp_rw [← ENNReal.ofReal_mul (by norm_num : (0 : ℝ) ≤ 1 / 2)]
rw [sum_isingSpin, ← ENNReal.ofReal_add
(mul_nonneg (by norm_num) (binaryFusion_likelihood_nonneg hu hv .neg))
(mul_nonneg (by norm_num) (binaryFusion_likelihood_nonneg hu hv .pos))]
congr 1
simp only [spinSign_neg, spinSign_pos]
ring
theorem posterior_spinMean_eq_binaryFusion
{X : Type*} [MeasurableSpace X]
(π : Measure IsingSpin) [IsProbabilityMeasure π]
(hπ : ∀ a, π {a} = ENNReal.ofReal (1 / 2 : ℝ))
(ν : Measure X) [SigmaFinite ν]
(κ : Kernel IsingSpin X) [IsFiniteKernel κ]
(u v : X → ℝ) (hu : Measurable u) (hv : Measurable v)
(hu₁ : ∀ᵐ x ∂ν, |u x| < 1) (hv₁ : ∀ᵐ x ∂ν, |v x| < 1)
(hκ : ∀ a, κ a = ν.withDensity
(fun x => ENNReal.ofReal ((1 + spinSign a * u x) * (1 + spinSign a * v x)))) :
∀ᵐ x ∂κ ∘ₘ π,
(∫ a, spinSign a ∂(posterior κ π) x) = binaryFusion (u x) (v x) := by
let L : IsingSpin → X → ℝ≥0∞ := fun a x =>
ENNReal.ofReal ((1 + spinSign a * u x) * (1 + spinSign a * v x))
have hL (a : IsingSpin) : Measurable (L a) :=
((measurable_const.add (measurable_const.mul hu)).mul
(measurable_const.add (measurable_const.mul hv))).ennreal_ofReal
have hpos : ∀ᵐ x ∂ν, (∑ a, π {a} * L a x) ≠ 0 := by
filter_upwards [hu₁, hv₁] with x hux hvx
simp only [L, hπ]
rw [binaryFusion_likelihood_sum hux.le hvx.le]
exact ne_of_gt (ENNReal.ofReal_pos.mpr (binaryFusion_denominator_pos hux hvx))
have hfinite : ∀ᵐ x ∂ν, (∑ a, π {a} * L a x) ≠ ∞ := by
apply ae_of_all
intro x
exact ENNReal.sum_ne_top.mpr (fun a _ =>
ENNReal.mul_ne_top (measure_ne_top π _) ENNReal.ofReal_ne_top)
have hpost := finite_posterior_singletons π ν κ L hL hκ hpos hfinite
have hac : κ ∘ₘ π ≪ ν := by
rw [finite_observation_law_density π ν κ L hL hκ]
exact withDensity_absolutelyContinuous _ _
filter_upwards [hpost, hac.ae_le hu₁, hac.ae_le hv₁] with x hx hux hvx
rw [integral_fintype Integrable.of_finite]
simp only [measureReal_def, hx, hπ, L,
binaryFusion_likelihood_sum hux.le hvx.le, smul_eq_mul,
ENNReal.toReal_div, ENNReal.toReal_mul,
ENNReal.toReal_ofReal (by norm_num : (0 : ℝ) ≤ 1 / 2),
ENNReal.toReal_ofReal (binaryFusion_denominator_pos hux hvx).le]
simp_rw [ENNReal.toReal_ofReal (binaryFusion_likelihood_nonneg hux.le hvx.le _)]
rw [sum_isingSpin]
simp only [spinSign_neg, spinSign_pos]
unfold binaryFusion
ring
theorem condExp_spin_eq_binaryFusion_of_likelihood
{Ω X : Type*} [MeasurableSpace Ω] [MeasurableSpace X]
(μ : Measure Ω) [IsFiniteMeasure μ]
(π : Measure IsingSpin) [IsProbabilityMeasure π]
(hπ : ∀ a, π {a} = ENNReal.ofReal (1 / 2 : ℝ))
(ν : Measure X) [SigmaFinite ν]
(κ : Kernel IsingSpin X) [IsFiniteKernel κ]
(S : Ω → IsingSpin) (Y : Ω → X) (hS : Measurable S) (hY : Measurable Y)
(hlaw : μ.map (fun ω => (S ω, Y ω)) = π ⊗ₘ κ)
(u v : X → ℝ) (hu : Measurable u) (hv : Measurable v)
(hu₁ : ∀ᵐ x ∂ν, |u x| < 1) (hv₁ : ∀ᵐ x ∂ν, |v x| < 1)
(hκ : ∀ a, κ a = ν.withDensity
(fun x => ENNReal.ofReal ((1 + spinSign a * u x) * (1 + spinSign a * v x)))) :
μ[fun ω => spinSign (S ω) | (inferInstance : MeasurableSpace X).comap Y]
=ᵐ[μ] fun ω => binaryFusion (u (Y ω)) (v (Y ω)) := by
exact FiniteBayes.condExp_state_eq_of_posterior_integral μ π κ S Y hS hY hlaw
spinSign (fun x => binaryFusion (u x) (v x))
(posterior_spinMean_eq_binaryFusion π hπ ν κ u v hu hv hu₁ hv₁ hκ)
end Problem367
end
end OAI