openAI-math-dataset / lean /OAI /Probability /FreeIsing /Martingales /SpatialRandomEvaluation.lean
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import OAI.Probability.FreeIsing.Martingales.RandomEvaluation
import OAI.Probability.FreeIsing.Martingales.SpatialLimit
import OAI.Probability.FreeIsing.Stochastic.IntegralAssociativityLimit
namespace OAI
noncomputable section
open MeasureTheory Filter
open scoped NNReal Topology
namespace Problem367.MartingaleSpatialRandomEvaluation
variable {Ω ι : Type*} [mΩ : MeasurableSpace Ω] {P : Measure Ω} [IsFiniteMeasure P]
{F : Filtration ℝ≥0 mΩ} {I : ι → ℝ≥0 → Ω → ℝ} {Y : ℝ≥0 → Ω → ℝ}
theorem tendsto_finiteSum_random_evaluation
(hI : ∀ a, Martingale (I a) F P) (hY : Martingale Y F P)
(hI2 : ∀ a t, MemLp (I a t) 2 P) (hY2 : ∀ t, MemLp (Y t) 2 P)
(hcI : ∀ a, ∀ᵐ ω ∂P, Continuous (fun t => I a t ω))
(hcY : ∀ᵐ ω ∂P, Continuous (fun t => Y t ω))
(T : ℝ≥0)
(hsum : HasSum (fun a => (hI2 a T).toLp (I a T)) ((hY2 T).toLp (Y T)))
(r : Finset ι → Ω → ℝ≥0) (hr : ∀ q, Measurable (r q))
(hb : ∀ q ω, r q ω ≤ T) :
Tendsto (fun q : Finset ι => ∫ ω,
((∑ a ∈ q, I a (r q ω) ω) - Y (r q ω) ω) ^ 2 ∂P) atTop (𝓝 0) := by
classical
have ht := PredictableL2.tendsto_integral_sq_error_of_hasSum
(fun a => I a T) (fun a => hI2 a T) (hY2 T) hsum
apply squeeze_zero (fun q => integral_nonneg (fun ω => sq_nonneg _))
(fun q => ?_) (by simpa only [mul_zero] using ht.const_mul 4)
have hc : ∀ᵐ ω ∂P, Continuous
(fun t => (MartingaleSpatialLimit.finiteSum I q - Y) t ω) := by
filter_upwards [MartingaleSpatialLimit.finiteSum_ae_continuous hcI q, hcY]
with ω hq hy
exact hq.sub hy
simpa only [MartingaleSpatialLimit.finiteSum, Pi.sub_apply] using
MartingaleRandomEvaluation.integral_sq_random_evaluation_le
((MartingaleSpatialLimit.finiteSum_martingale hI q).sub hY)
(fun t => (MartingaleSpatialLimit.finiteSum_memLp hI2 q t).sub (hY2 t))
hc (hr q) (hb q)
theorem exists_hasSum_random_evaluation
(hI : ∀ a, Martingale (I a) F P) (hY : Martingale Y F P)
(hI2 : ∀ a t, MemLp (I a t) 2 P) (hY2 : ∀ t, MemLp (Y t) 2 P)
(hcI : ∀ a, ∀ᵐ ω ∂P, Continuous (fun t => I a t ω))
(hcY : ∀ᵐ ω ∂P, Continuous (fun t => Y t ω))
(T : ℝ≥0)
(hsum : HasSum (fun a => (hI2 a T).toLp (I a T)) ((hY2 T).toLp (Y T)))
(r : Ω → ℝ≥0) (hr : Measurable r) (hb : ∀ ω, r ω ≤ T) :
∃ (hIr : ∀ a, MemLp (fun ω => I a (r ω) ω) 2 P)
(hYr : MemLp (fun ω => Y (r ω) ω) 2 P),
HasSum (fun a => (hIr a).toLp (fun ω => I a (r ω) ω))
(hYr.toLp (fun ω => Y (r ω) ω)) := by
classical
have hIr (a : ι) : MemLp (fun ω => I a (r ω) ω) 2 P :=
MartingaleRandomEvaluation.memLp_random_evaluation (hI a) (hI2 a) (hcI a) hr hb
have hYr : MemLp (fun ω => Y (r ω) ω) 2 P :=
MartingaleRandomEvaluation.memLp_random_evaluation hY hY2 hcY hr hb
refine ⟨hIr, hYr, ?_⟩
have hl := (SimpleIntegral.tendsto_toLp_iff_meanSquare
(fun q : Finset ι => memLp_finsetSum q (fun a _ => hIr a)) hYr).mpr
(tendsto_finiteSum_random_evaluation hI hY hI2 hY2 hcI hcY T hsum
(fun _ => r) (fun _ => hr) (fun _ => hb))
change Tendsto (fun q : Finset ι => ∑ a ∈ q, (hIr a).toLp (fun ω => I a (r ω) ω))
atTop (𝓝 (hYr.toLp (fun ω => Y (r ω) ω)))
exact hl.congr (fun q => PredictableL2.toLp_finsetSum
(fun a ω => I a (r ω) ω) hIr q)
theorem exists_hasSum_stoppedProcess
(hI : ∀ a, Martingale (I a) F P) (hY : Martingale Y F P)
(hI2 : ∀ a t, MemLp (I a t) 2 P) (hY2 : ∀ t, MemLp (Y t) 2 P)
(hcI : ∀ a, ∀ᵐ ω ∂P, Continuous (fun t => I a t ω))
(hcY : ∀ᵐ ω ∂P, Continuous (fun t => Y t ω))
(T : ℝ≥0)
(hsum : HasSum (fun a => (hI2 a T).toLp (I a T)) ((hY2 T).toLp (Y T)))
{τ : Ω → WithTop ℝ≥0} (hτ : IsStoppingTime F τ)
{t : ℝ≥0} (ht : t ≤ T) :
∃ (hIs : ∀ a, MemLp (stoppedProcess (I a) τ t) 2 P)
(hYs : MemLp (stoppedProcess Y τ t) 2 P),
HasSum (fun a => (hIs a).toLp (stoppedProcess (I a) τ t))
(hYs.toLp (stoppedProcess Y τ t)) := by
exact exists_hasSum_random_evaluation hI hY hI2 hY2 hcI hcY T hsum
(fun ω => (min (t : WithTop ℝ≥0) (τ ω)).untopA)
(WithTop.measurable_untopA.comp
(measurable_const.min (hτ.measurable.mono hτ.measurableSpace_le le_rfl)))
(fun ω => (WithTop.untopA_le (min_le_left _ _)).trans ht)
end Problem367.MartingaleSpatialRandomEvaluation
end
end OAI