openAI-math-dataset / lean /OAI /Probability /FreeIsing /Brownian /FiltrationUniformIntegral.lean
roseking's picture
Add lean source and binary files (part 121)
f61e547 verified
Raw History Blame Contribute Delete
17.3 kB
import OAI.Probability.FreeIsing.Brownian.FiltrationIntegral
import OAI.Probability.FreeIsing.Brownian.UniformIsometry
namespace OAI
noncomputable section
open MeasureTheory ProbabilityTheory Filter
open scoped NNReal Topology
namespace Problem367.BrownianFiltrationGrid
open BrownianGrid
theorem preBrownian_difference_isometry
{Ω : Type*} [mΩ : MeasurableSpace Ω] {P : Measure Ω}
{B : ℝ≥0 → Ω → ℝ} (hB : IsPreBrownianReal B P)
{F : Filtration ℝ≥0 mΩ} (hAd : StronglyAdapted F B)
(hind : ∀ s t, s ≤ t → Indep
(MeasurableSpace.comap (fun ω => B t ω - B s ω) inferInstance) (F s) P)
(t : ℕ → ℝ≥0) (ht : Monotone t) (H K : ℕ → Ω → ℝ)
{k : ℕ} (hk : 0 < k)
(hH : ∀ j, StronglyMeasurable[F (t (j * k))] (H j))
(hK : ∀ i, StronglyMeasurable[F (t i)] (K i))
(hH2 : ∀ j, MemLp (H j) 2 P) (hK2 : ∀ i, MemLp (K i) 2 P) (n : ℕ) :
(∫ ω, (integralSum B (fun j => t (j * k)) H n ω -
integralSum B t K (n * k) ω) ^ 2 ∂P) =
∑ i ∈ Finset.range (n * k), ((t (i + 1) : ℝ) - (t i : ℝ)) *
∫ ω, (H (i / k) ω - K i ω) ^ 2 ∂P := by
rw [integralSum_refinement B t H n hk]
simpa only [integralSum, sub_mul, Finset.sum_sub_distrib] using
BrownianFiltration.predictable_sum_isometry hB hAd hind t ht
(fun i ω => H (i / k) ω - K i ω)
(fun i => ((hH (i / k)).mono (F.mono (ht (Nat.div_mul_le_self i k)))).sub (hK i))
(fun i => (hH2 (i / k)).sub (hK2 i)) (Finset.range (n * k))
theorem preBrownian_uniform_difference_isometry
{Ω : Type*} [mΩ : MeasurableSpace Ω] {P : Measure Ω}
{B : ℝ≥0 → Ω → ℝ} (hB : IsPreBrownianReal B P)
{F : Filtration ℝ≥0 mΩ} (hAd : StronglyAdapted F B)
(hind : ∀ s t, s ≤ t → Indep
(MeasurableSpace.comap (fun ω => B t ω - B s ω) inferInstance) (F s) P) (H : ℝ≥0 → Ω → ℝ)
(hH : StronglyAdapted (F) H)
(hH2 : ∀ t, MemLp (H t) 2 P)
(T : ℝ≥0) {n k : ℕ} (hn : 0 < n) (hk : 0 < k) :
(∫ ω, (uniformSum B H T n ω - uniformSum B H T (n * k) ω) ^ 2 ∂P) =
∑ i ∈ Finset.range (n * k),
((uniformGrid T (n * k) (i + 1) : ℝ) - (uniformGrid T (n * k) i : ℝ)) *
∫ ω, (H (uniformGrid T n (i / k)) ω - H (uniformGrid T (n * k) i) ω) ^ 2 ∂P := by
have hgrid : (fun j => uniformGrid T (n * k) (j * k)) = uniformGrid T n := by
funext j
exact uniformGrid_refine T hn hk j
have hcoeff : ∀ j, StronglyMeasurable[
F (uniformGrid T (n * k) (j * k))]
(H (uniformGrid T n j)) := by
intro j
rw [uniformGrid_refine T hn hk]
exact hH _
simpa only [hgrid, uniformSum] using preBrownian_difference_isometry hB hAd hind
(uniformGrid T (n * k)) (uniformGrid_mono T (n * k))
(fun j => H (uniformGrid T n j)) (fun i => H (uniformGrid T (n * k) i)) hk
hcoeff (fun i => hH _) (fun j => hH2 _) (fun i => hH2 _) n
theorem preBrownian_uniform_difference_bound
{Ω : Type*} [mΩ : MeasurableSpace Ω] {P : Measure Ω}
{B : ℝ≥0 → Ω → ℝ} (hB : IsPreBrownianReal B P)
{F : Filtration ℝ≥0 mΩ} (hAd : StronglyAdapted F B)
(hind : ∀ s t, s ≤ t → Indep
(MeasurableSpace.comap (fun ω => B t ω - B s ω) inferInstance) (F s) P) (H : ℝ≥0 → Ω → ℝ)
(hH : StronglyAdapted (F) H)
(hH2 : ∀ t, MemLp (H t) 2 P)
(T : ℝ≥0) {n k : ℕ} (hn : 0 < n) (hk : 0 < k) {ε : ℝ}
(happrox : ∀ i < n * k,
(∫ ω, (H (uniformGrid T n (i / k)) ω -
H (uniformGrid T (n * k) i) ω) ^ 2 ∂P) ≤ ε) :
(∫ ω, (uniformSum B H T n ω - uniformSum B H T (n * k) ω) ^ 2 ∂P) ≤
(T : ℝ) * ε := by
rw [preBrownian_uniform_difference_isometry hB hAd hind H hH hH2 T hn hk]
calc
_ ≤ ∑ i ∈ Finset.range (n * k),
((uniformGrid T (n * k) (i + 1) : ℝ) - (uniformGrid T (n * k) i : ℝ)) * ε := by
apply Finset.sum_le_sum
intro i hi
apply mul_le_mul_of_nonneg_left (happrox i (Finset.mem_range.mp hi))
exact sub_nonneg.mpr (NNReal.coe_le_coe.mpr (uniformGrid_mono T (n * k) (Nat.le_succ i)))
_ = (T : ℝ) * ε := by
rw [← Finset.sum_mul, Finset.sum_range_sub (fun i => (uniformGrid T (n * k) i : ℝ))]
simp [uniformGrid_end T (Nat.mul_pos hn hk)]
theorem integralSum_memLp
{Ω : Type*} [mΩ : MeasurableSpace Ω] {P : Measure Ω}
{B : ℝ≥0 → Ω → ℝ} (hB : IsPreBrownianReal B P)
{F : Filtration ℝ≥0 mΩ} (_hAd : StronglyAdapted F B)
(hind : ∀ s t, s ≤ t → Indep
(MeasurableSpace.comap (fun ω => B t ω - B s ω) inferInstance) (F s) P)
(t : ℕ → ℝ≥0) (ht : Monotone t) (H : ℕ → Ω → ℝ)
(hH : ∀ i, StronglyMeasurable[F (t i)] (H i))
(hH2 : ∀ i, MemLp (H i) 2 P) (n : ℕ) :
MemLp (integralSum B t H n) 2 P := by
apply memLp_finsetSum
intro i hi
exact BrownianFiltration.predictable_mul_memLp_two hB (hind _ _ (ht (Nat.le_succ i))) (hH i) (hH2 i)
theorem uniformSum_memLp
{Ω : Type*} [mΩ : MeasurableSpace Ω] {P : Measure Ω}
{B : ℝ≥0 → Ω → ℝ} (hB : IsPreBrownianReal B P)
{F : Filtration ℝ≥0 mΩ} (hAd : StronglyAdapted F B)
(hind : ∀ s t, s ≤ t → Indep
(MeasurableSpace.comap (fun ω => B t ω - B s ω) inferInstance) (F s) P) (H : ℝ≥0 → Ω → ℝ)
(hH : StronglyAdapted (F) H)
(hH2 : ∀ t, MemLp (H t) 2 P) (T : ℝ≥0) (n : ℕ) :
MemLp (uniformSum B H T n) 2 P :=
integralSum_memLp hB hAd hind (uniformGrid T n) (uniformGrid_mono T n)
(fun i => H (uniformGrid T n i)) (fun _ => hH _) (fun _ => hH2 _) n
theorem preBrownian_uniform_difference_bound_of_modulus
{Ω : Type*} [mΩ : MeasurableSpace Ω] {P : Measure Ω}
{B : ℝ≥0 → Ω → ℝ} (hB : IsPreBrownianReal B P)
{F : Filtration ℝ≥0 mΩ} (hAd : StronglyAdapted F B)
(hind : ∀ s t, s ≤ t → Indep
(MeasurableSpace.comap (fun ω => B t ω - B s ω) inferInstance) (F s) P) (H : ℝ≥0 → Ω → ℝ)
(hH : StronglyAdapted (F) H)
(hH2 : ∀ t, MemLp (H t) 2 P)
(T : ℝ≥0) {n k : ℕ} (hn : 0 < n) (hk : 0 < k) {ε δ : ℝ}
(hmesh : (T : ℝ) / (n : ℝ) ≤ δ)
(hmod : ∀ s t : ℝ≥0, s ≤ t → t ≤ T → (t : ℝ) - (s : ℝ) ≤ δ →
(∫ ω, (H s ω - H t ω) ^ 2 ∂P) ≤ ε) :
(∫ ω, (uniformSum B H T n ω - uniformSum B H T (n * k) ω) ^ 2 ∂P) ≤
(T : ℝ) * ε := by
apply preBrownian_uniform_difference_bound hB hAd hind H hH hH2 T hn hk
intro i hi
apply hmod
· exact uniformGrid_floor_le T hn hk i
· exact uniformGrid_le_horizon T (Nat.mul_pos hn hk) hi.le
· exact (uniformGrid_floor_sub_le T hn hk i).trans hmesh
theorem preBrownian_uniform_pair_bound
{Ω : Type*} [mΩ : MeasurableSpace Ω] {P : Measure Ω}
{B : ℝ≥0 → Ω → ℝ} (hB : IsPreBrownianReal B P)
{F : Filtration ℝ≥0 mΩ} (hAd : StronglyAdapted F B)
(hind : ∀ s t, s ≤ t → Indep
(MeasurableSpace.comap (fun ω => B t ω - B s ω) inferInstance) (F s) P) (H : ℝ≥0 → Ω → ℝ)
(hH : StronglyAdapted (F) H)
(hH2 : ∀ t, MemLp (H t) 2 P)
(T : ℝ≥0) {n m : ℕ} (hn : 0 < n) (hmn : 0 < m) {ε δ : ℝ}
(hmeshN : (T : ℝ) / (n : ℝ) ≤ δ) (hmeshM : (T : ℝ) / (m : ℝ) ≤ δ)
(hmod : ∀ s t : ℝ≥0, s ≤ t → t ≤ T → (t : ℝ) - (s : ℝ) ≤ δ →
(∫ ω, (H s ω - H t ω) ^ 2 ∂P) ≤ ε) :
(∫ ω, (uniformSum B H T n ω - uniformSum B H T m ω) ^ 2 ∂P) ≤
4 * (T : ℝ) * ε := by
have hN := preBrownian_uniform_difference_bound_of_modulus hB hAd hind H hH hH2 T hn hmn hmeshN hmod
have hM := preBrownian_uniform_difference_bound_of_modulus hB hAd hind H hH hH2 T hmn hn hmeshM hmod
rw [Nat.mul_comm m n] at hM
have htriangle := integral_sq_sub_le_two (uniformSum_memLp hB hAd hind H hH hH2 T n)
(uniformSum_memLp hB hAd hind H hH hH2 T m) (uniformSum_memLp hB hAd hind H hH hH2 T (n * m))
linarith
def uniformSumLp
{Ω : Type*} [mΩ : MeasurableSpace Ω] {P : Measure Ω}
{B : ℝ≥0 → Ω → ℝ} (hB : IsPreBrownianReal B P)
{F : Filtration ℝ≥0 mΩ} (hAd : StronglyAdapted F B)
(hind : ∀ s t, s ≤ t → Indep
(MeasurableSpace.comap (fun ω => B t ω - B s ω) inferInstance) (F s) P) (H : ℝ≥0 → Ω → ℝ)
(hH : StronglyAdapted (F) H)
(hH2 : ∀ t, MemLp (H t) 2 P) (T : ℝ≥0) (n : ℕ) : Lp ℝ 2 P :=
(uniformSum_memLp hB hAd hind H hH hH2 T n).toLp (uniformSum B H T n)
lemma coe_uniformSumLp
{Ω : Type*} [mΩ : MeasurableSpace Ω] {P : Measure Ω}
{B : ℝ≥0 → Ω → ℝ} (hB : IsPreBrownianReal B P)
{F : Filtration ℝ≥0 mΩ} (hAd : StronglyAdapted F B)
(hind : ∀ s t, s ≤ t → Indep
(MeasurableSpace.comap (fun ω => B t ω - B s ω) inferInstance) (F s) P) (H : ℝ≥0 → Ω → ℝ)
(hH : StronglyAdapted (F) H)
(hH2 : ∀ t, MemLp (H t) 2 P) (T : ℝ≥0) (n : ℕ) :
(uniformSumLp hB hAd hind H hH hH2 T n : Ω → ℝ) =ᵐ[P] uniformSum B H T n :=
(uniformSum_memLp hB hAd hind H hH hH2 T n).coeFn_toLp
theorem cauchySeq_uniformSumLp
{Ω : Type*} [mΩ : MeasurableSpace Ω] {P : Measure Ω}
{B : ℝ≥0 → Ω → ℝ} (hB : IsPreBrownianReal B P)
{F : Filtration ℝ≥0 mΩ} (hAd : StronglyAdapted F B)
(hind : ∀ s t, s ≤ t → Indep
(MeasurableSpace.comap (fun ω => B t ω - B s ω) inferInstance) (F s) P) (H : ℝ≥0 → Ω → ℝ)
(hH : StronglyAdapted (F) H)
(hH2 : ∀ t, MemLp (H t) 2 P) (T : ℝ≥0)
(hcont : ∀ ε > (0 : ℝ), ∃ δ > (0 : ℝ),
∀ s t : ℝ≥0, s ≤ t → t ≤ T → (t : ℝ) - (s : ℝ) ≤ δ →
(∫ ω, (H s ω - H t ω) ^ 2 ∂P) ≤ ε) :
CauchySeq (uniformSumLp hB hAd hind H hH hH2 T) := by
apply Metric.cauchySeq_iff.mpr
intro ε hε
let η := ε ^ 2 / (4 * (T : ℝ) + 1)
have hden : 0 < 4 * (T : ℝ) + 1 := by positivity
have hη : 0 < η := div_pos (sq_pos_of_pos hε) hden
obtain ⟨δ, hδ, hmod⟩ := hcont η hη
obtain ⟨N, hN⟩ := exists_nat_gt ((T : ℝ) / δ)
have hmesh (n : ℕ) (hn : N + 1 ≤ n) : (T : ℝ) / (n : ℝ) ≤ δ := by
have hn0 : 0 < n := by omega
have hnR : (0 : ℝ) < n := by exact_mod_cast hn0
apply (div_le_iff₀ hnR).2
have hN' : (T : ℝ) < (N : ℝ) * δ := (div_lt_iff₀ hδ).mp hN
have hNn : (N : ℝ) ≤ (n : ℝ) := by exact_mod_cast (show N ≤ n by omega)
nlinarith
refine ⟨N + 1, ?_⟩
intro n hn m hmn
have hn0 : 0 < n := by omega
have hm0 : 0 < m := by omega
have hb := preBrownian_uniform_pair_bound hB hAd hind H hH hH2 T hn0 hm0
(hmesh n hn) (hmesh m hmn) hmod
have hnorm : ‖uniformSumLp hB hAd hind H hH hH2 T n - uniformSumLp hB hAd hind H hH hH2 T m‖ ^ 2 ≤
4 * (T : ℝ) * η := by
rw [uniformSumLp, uniformSumLp, norm_sq_toLp_sub]
exact hb
have hsmall : 4 * (T : ℝ) * η < ε ^ 2 := by
dsimp [η]
rw [← mul_div_assoc]
apply (div_lt_iff₀ hden).2
nlinarith [sq_pos_of_pos hε]
rw [dist_eq_norm]
nlinarith [norm_nonneg
(uniformSumLp hB hAd hind H hH hH2 T n - uniformSumLp hB hAd hind H hH hH2 T m)]
theorem exists_uniformSumLp_limit
{Ω : Type*} [mΩ : MeasurableSpace Ω] {P : Measure Ω}
{B : ℝ≥0 → Ω → ℝ} (hB : IsPreBrownianReal B P)
{F : Filtration ℝ≥0 mΩ} (hAd : StronglyAdapted F B)
(hind : ∀ s t, s ≤ t → Indep
(MeasurableSpace.comap (fun ω => B t ω - B s ω) inferInstance) (F s) P) (H : ℝ≥0 → Ω → ℝ)
(hH : StronglyAdapted (F) H)
(hH2 : ∀ t, MemLp (H t) 2 P) (T : ℝ≥0)
(hcont : ∀ ε > (0 : ℝ), ∃ δ > (0 : ℝ),
∀ s t : ℝ≥0, s ≤ t → t ≤ T → (t : ℝ) - (s : ℝ) ≤ δ →
(∫ ω, (H s ω - H t ω) ^ 2 ∂P) ≤ ε) :
∃ I : Lp ℝ 2 P, Tendsto (uniformSumLp hB hAd hind H hH hH2 T) atTop (𝓝 I) :=
cauchySeq_tendsto_of_complete (cauchySeq_uniformSumLp hB hAd hind H hH hH2 T hcont)
theorem exists_uniform_integral
{Ω : Type*} [mΩ : MeasurableSpace Ω] {P : Measure Ω}
{B : ℝ≥0 → Ω → ℝ} (hB : IsPreBrownianReal B P)
{F : Filtration ℝ≥0 mΩ} (hAd : StronglyAdapted F B)
(hind : ∀ s t, s ≤ t → Indep
(MeasurableSpace.comap (fun ω => B t ω - B s ω) inferInstance) (F s) P) (H : ℝ≥0 → Ω → ℝ)
(hH : StronglyAdapted (F) H)
(hH2 : ∀ t, MemLp (H t) 2 P) (T : ℝ≥0)
(hcont : ∀ ε > (0 : ℝ), ∃ δ > (0 : ℝ),
∀ s t : ℝ≥0, s ≤ t → t ≤ T → (t : ℝ) - (s : ℝ) ≤ δ →
(∫ ω, (H s ω - H t ω) ^ 2 ∂P) ≤ ε) :
∃ I : Ω → ℝ, StronglyMeasurable I ∧ MemLp I 2 P ∧
Tendsto (fun n => ∫ ω, (uniformSum B H T n ω - I ω) ^ 2 ∂P) atTop (𝓝 0) := by
obtain ⟨I, hI⟩ := exists_uniformSumLp_limit hB hAd hind H hH hH2 T hcont
refine ⟨I, Lp.stronglyMeasurable I, Lp.memLp I, ?_⟩
have hnorm := (hI.sub (tendsto_const_nhds (x := I))).norm.pow 2
simp only [sub_self, norm_zero, zero_pow (by norm_num : (2 : ℕ) ≠ 0)] at hnorm
apply hnorm.congr'
apply Filter.Eventually.of_forall
intro n
dsimp only
rw [norm_sq_L2_eq_integral]
apply integral_congr_ae
filter_upwards [Lp.coeFn_sub (uniformSumLp hB hAd hind H hH hH2 T n) I,
coe_uniformSumLp hB hAd hind H hH hH2 T n] with ω hsub hsum
simp only [Pi.sub_apply] at hsub
rw [hsub, hsum]
theorem exists_uniform_integral_of_bounded_continuous
{Ω : Type*} [mΩ : MeasurableSpace Ω] {P : Measure Ω}
{B : ℝ≥0 → Ω → ℝ} (hB : IsPreBrownianReal B P)
{F : Filtration ℝ≥0 mΩ} (hAd : StronglyAdapted F B)
(hind : ∀ s t, s ≤ t → Indep
(MeasurableSpace.comap (fun ω => B t ω - B s ω) inferInstance) (F s) P) (H : ℝ≥0 → Ω → ℝ)
(hH : StronglyAdapted (F) H)
(hc : ∀ᵐ ω ∂P, Continuous (fun t => H t ω))
{C : ℝ} (hC : 0 ≤ C) (hb : ∀ᵐ ω ∂P, ∀ t, |H t ω| ≤ C)
(T : ℝ≥0) :
∃ I : Ω → ℝ, StronglyMeasurable I ∧ MemLp I 2 P ∧
Tendsto (fun n => ∫ ω, (uniformSum B H T n ω - I ω) ^ 2 ∂P) atTop (𝓝 0) := by
let : IsProbabilityMeasure P := hB.isGaussianProcess.isProbabilityMeasure
have hHm : ∀ t, AEStronglyMeasurable (H t) P := fun t =>
((hH t).mono (F.le t)).aestronglyMeasurable
have hH2 : ∀ t, MemLp (H t) 2 P := by
intro t
apply MemLp.of_bound (hHm t) C
filter_upwards [hb] with ω hω
simpa only [Real.norm_eq_abs] using hω t
apply exists_uniform_integral hB hAd hind H hH hH2 T
intro ε hε
exact MeanSquareContinuity.uniform_integral_sq_sub_le hHm hc hC hb T hε
theorem uniformSumLp_norm_sq
{Ω : Type*} [mΩ : MeasurableSpace Ω] {P : Measure Ω}
{B : ℝ≥0 → Ω → ℝ} (hB : IsPreBrownianReal B P)
{F : Filtration ℝ≥0 mΩ} (hAd : StronglyAdapted F B)
(hind : ∀ s t, s ≤ t → Indep
(MeasurableSpace.comap (fun ω => B t ω - B s ω) inferInstance) (F s) P) (H : ℝ≥0 → Ω → ℝ)
(hH : StronglyAdapted (F) H)
(hH2 : ∀ t, MemLp (H t) 2 P) (T : ℝ≥0) (n : ℕ) :
‖uniformSumLp hB hAd hind H hH hH2 T n‖ ^ 2 =
((T : ℝ) / n) * ∑ i ∈ Finset.range n, ∫ ω, (H (uniformGrid T n i) ω) ^ 2 ∂P := by
calc
_ = ∫ ω, (uniformSum B H T n ω) ^ 2 ∂P := by
rw [norm_sq_L2_eq_integral]
apply integral_congr_ae
filter_upwards [coe_uniformSumLp hB hAd hind H hH hH2 T n] with ω hω
rw [hω]
_ = ∑ i ∈ Finset.range n,
((uniformGrid T n (i + 1) : ℝ) - (uniformGrid T n i : ℝ)) *
∫ ω, (H (uniformGrid T n i) ω) ^ 2 ∂P :=
BrownianFiltration.predictable_sum_isometry hB hAd hind (uniformGrid T n) (uniformGrid_mono T n)
(fun i => H (uniformGrid T n i)) (fun i => hH _) (fun i => hH2 _) (Finset.range n)
_ = _ := by simp_rw [uniformGrid_step]; rw [← Finset.mul_sum]
theorem uniformSumLp_limit_isometry
{Ω : Type*} [mΩ : MeasurableSpace Ω] {P : Measure Ω}
{B : ℝ≥0 → Ω → ℝ} (hB : IsPreBrownianReal B P)
{F : Filtration ℝ≥0 mΩ} (hAd : StronglyAdapted F B)
(hind : ∀ s t, s ≤ t → Indep
(MeasurableSpace.comap (fun ω => B t ω - B s ω) inferInstance) (F s) P) (H : ℝ≥0 → Ω → ℝ)
(hH : StronglyAdapted (F) H)
(hH2 : ∀ t, MemLp (H t) 2 P)
(hc : ∀ᵐ ω ∂P, Continuous (fun t => H t ω))
{C : ℝ} (hC : 0 ≤ C) (hb : ∀ᵐ ω ∂P, ∀ t, |H t ω| ≤ C)
(T : ℝ≥0) {I : Lp ℝ 2 P}
(hI : Tendsto (uniformSumLp hB hAd hind H hH hH2 T) atTop (𝓝 I)) :
(∫ ω, (I ω) ^ 2 ∂P) =
∫ t in (0 : ℝ)..(T : ℝ), ∫ ω, (H t.toNNReal ω) ^ 2 ∂P := by
let : IsProbabilityMeasure P := hB.isGaussianProcess.isProbabilityMeasure
have henergy := EnergyRiemann.tendsto_energy_sum
(fun t => (hH2 t).aestronglyMeasurable) hc hC hb T
have hnorm := hI.norm.pow 2
have henergy' : Tendsto
(fun n => ((T : ℝ) / n) * ∑ i ∈ Finset.range n,
∫ ω, (H (uniformGrid T n i) ω) ^ 2 ∂P) atTop (𝓝 (‖I‖ ^ 2)) := by
apply hnorm.congr'
exact Filter.Eventually.of_forall (uniformSumLp_norm_sq hB hAd hind H hH hH2 T)
rw [← norm_sq_L2_eq_integral]
exact tendsto_nhds_unique henergy' henergy
end Problem367.BrownianFiltrationGrid
end
end OAI