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import OAI.Probability.Ballisticity.Estimates.GridOscillation
namespace OAI
section
section
open MeasureTheory ProbabilityTheory Filter
open scoped ENNReal NNReal BigOperators Topology
namespace DirectionalTransience
lemma floor_scaled_close {s t u : ℝ} (hs : 0 ≤ s) (_ht : 0 ≤ t)
(hu : 4 ≤ u) (hst : |s-t| ≤ u/2) : ⌊s⌋₊ ≤ ⌊t⌋₊+⌊u⌋₊ := by
have h1 := Nat.floor_le hs
have h2 := Nat.lt_floor_add_one t
have h3 := Nat.lt_floor_add_one u
have hb := (abs_le.mp hst).2
have he : (⌊s⌋₊:ℝ) ≤ (⌊t⌋₊:ℝ)+(⌊u⌋₊:ℝ) := by linarith
exact_mod_cast he
lemma scaledPolygon_oscillation_subset {Ω : Type*} (X : ℕ → Ω → ℝ)
{r n T ε δ : ℝ} (hr : 0 < r) (hn : 2 ≤ n) (hT : 0 ≤ T)
(_hδ : 0 < δ) (hδn : 4 ≤ δ*n) :
{ω | scaledPolygon (fun k => X k ω) r n T ∈ ContinuousOscillation (3*ε)
(δ/(2*(T+1)))} ⊆ GridOscillation X ⌊(T+1)*n⌋₊ ⌊δ*n⌋₊ (ε*r) := by
intro ω hω
by_contra hg
rcases hω with ⟨s,t,hst,hbig⟩
have hn0 : 0 ≤ n := by linarith
have hTn : 0 ≤ T*n := mul_nonneg hT hn0
have hs : 0 ≤ T*n*(s:ℝ) := mul_nonneg hTn s.2.1
have ht : 0 ≤ T*n*(t:ℝ) := mul_nonneg hTn t.2.1
have hsle : T*n*(s:ℝ) ≤ T*n := mul_le_of_le_one_right hTn s.2.2
have htle : T*n*(t:ℝ) ≤ T*n := mul_le_of_le_one_right hTn t.2.2
have hsP : ⌊T*n*(s:ℝ)⌋₊ < ⌊T*n⌋₊+1 := Nat.lt_succ_of_le (Nat.floor_mono hsle)
have htP : ⌊T*n*(t:ℝ)⌋₊ < ⌊T*n⌋₊+1 := Nat.lt_succ_of_le (Nat.floor_mono htle)
have hP : ⌊T*n⌋₊+1 ≤ ⌊(T+1)*n⌋₊ := by
apply Nat.le_floor
have hf := Nat.floor_le hTn
push_cast
nlinarith
have hH : 1 ≤ ⌊δ*n⌋₊ := by apply Nat.le_floor; norm_num; linarith
have hst' : |(s:ℝ)-(t:ℝ)| ≤ δ/(2*(T+1)) := hst
have hclose : |T*n*(s:ℝ)-T*n*(t:ℝ)| ≤ (δ*n)/2 := by
rw [← mul_sub,abs_mul,abs_of_nonneg hTn]
have h1 := mul_le_mul_of_nonneg_left hst' hTn
have hden : 0 < 2*(T+1) := by positivity
have he : T*n*(δ/(2*(T+1))) ≤ δ*n/2 := by
rw [← mul_div_assoc]
apply (div_le_iff₀ hden).2
nlinarith [mul_nonneg _hδ.le hn0]
exact h1.trans he
have hb := linearPolygon_oscillation_le X hg hH hP hs ht hsP htP
(floor_scaled_close hs ht hδn hclose)
(floor_scaled_close ht hs hδn (by simpa [abs_sub_comm] using hclose))
simp only [scaledPolygon_apply] at hbig
rw [← sub_div,abs_div,abs_of_pos hr] at hbig
have hlarge := (lt_div_iff₀ hr).mp hbig
rw [abs_sub_comm] at hb
nlinarith
theorem gaussian_continuous_modulus {Ω : Type*} [MeasurableSpace Ω]
(μ : Measure Ω) [IsProbabilityMeasure μ] (X : ℕ → Ω → ℝ)
(hX : ∀ k, Measurable (X k)) (hind : iIndepFun X μ)
(hident : ∀ k, IdentDistrib (X k) (X 0) μ μ)
(hsym : IdentDistrib (X 0) (fun ω => -X 0 ω) μ μ)
(hI : Integrable (X 0) μ) (hne : 0 < μ {ω | X 0 ω ≠ 0})
(r : ℕ → ℝ) (hr : IsGaussianSequence μ (X 0) r)
{T ε β : ℝ} (hT : 0 ≤ T) (hε : 0 < ε) (hβ : 0 < β) :
∃ δ : ℝ, 0 < δ ∧ ∀ᶠ i in atTop,
μ.real {ω | scaledPolygon (fun k => X k ω) (r i)
(fluctuationScale μ (X 0) (r i)) T ∈ ContinuousOscillation ε δ} ≤ β := by
let n := fun i => fluctuationScale μ (X 0) (r i)
have hn : Tendsto n atTop atTop := (fluctuationScale_tendsto μ (X 0) (hX 0) hI hne).comp hr.1
obtain ⟨δ,hδ,hb⟩ := gaussian_grid_modulus μ X hX hind hident hsym hI hne r hr
(T := T+1) (ε := ε/3) (by linarith) (by positivity) hβ
refine ⟨δ/(2*(T+1)),by positivity,?_⟩
have hδn : Tendsto (fun i => δ*n i) atTop atTop := hn.const_mul_atTop hδ
filter_upwards [hb,hr.1.eventually (eventually_gt_atTop (0:ℝ)),
hn.eventually (eventually_ge_atTop (2:ℝ)),hδn.eventually (eventually_ge_atTop (4:ℝ))]
with i hi hri hni hdni
have hs := scaledPolygon_oscillation_subset X hri hni hT hδ hdni (ε := ε/3)
have he : 3*(ε/3)=ε := by ring
rw [he] at hs
exact (measureReal_mono hs (measure_ne_top _ _)).trans hi
lemma linearPolygon_abs_le_max (x : ℕ → ℝ) {N : ℕ} {t : ℝ}
(ht : 0 ≤ t) (hN : ⌊t⌋₊ < N) : |linearPolygon x N t| ≤ partialSumMax x N := by
let j := ⌊t⌋₊
have hj : (j:ℝ) ≤ t := Nat.floor_le ht
have hj1 : t < j+1 := Nat.lt_floor_add_one t
have h1 := (abs_partialSum_le_max x j).trans (partialSumMax_mono x hN.le)
have h2 := (abs_partialSum_le_max x (j+1)).trans (partialSumMax_mono x hN)
rw [linearPolygon_formula x N ht hN]
have he : realPartialSum x j+(t-j)*x j =
(1-(t-j))*realPartialSum x j+(t-j)*realPartialSum x (j+1) := by
rw [realPartialSum_succ]
ring
change |realPartialSum x j+(t-j)*x j| ≤ _
rw [he]
calc
_ ≤ |(1-(t-j))*realPartialSum x j|+|(t-j)*realPartialSum x (j+1)| := abs_add_le _ _
_ = (1-(t-j))*|realPartialSum x j|+(t-j)*|realPartialSum x (j+1)| := by
rw [abs_mul,abs_mul,abs_of_nonneg (show 0 ≤ 1-(t-j) by linarith),
abs_of_nonneg (show 0 ≤ t-j by linarith)]
_ ≤ (1-(t-j))*partialSumMax x N+(t-j)*partialSumMax x N := by gcongr; linarith
_ = _ := by ring
lemma norm_scaledPolygon_le_max (x : ℕ → ℝ) {r n T : ℝ}
(hr : 0 < r) (hn : 0 ≤ n) (hT : 0 ≤ T) :
‖scaledPolygon x r n T‖ ≤ partialSumMax x (⌊T*n⌋₊+1)/r := by
apply (ContinuousMap.norm_le_of_nonempty _).mpr
intro t
rw [Real.norm_eq_abs,scaledPolygon_apply,abs_div,abs_of_pos hr]
apply (div_le_div_iff_of_pos_right hr).2
apply linearPolygon_abs_le_max
· exact mul_nonneg (mul_nonneg hT hn) t.2.1
· exact Nat.lt_succ_of_le (Nat.floor_mono (mul_le_of_le_one_right (mul_nonneg hT hn) t.2.2))
lemma gaussian_max_horizon_eventually {Ω : Type*} [MeasurableSpace Ω]
(μ : Measure Ω) [IsProbabilityMeasure μ] (X : ℕ → Ω → ℝ)
(hX : ∀ k, Measurable (X k)) (hind : iIndepFun X μ)
(hident : ∀ k, IdentDistrib (X k) (X 0) μ μ)
(hsym : IdentDistrib (X 0) (fun ω => -X 0 ω) μ μ)
(hne : 0 < μ {ω | X 0 ω ≠ 0}) (r : ℕ → ℝ)
(hr : IsGaussianSequence μ (X 0) r) {α ε β : ℝ}
(hα : 0 ≤ α) (hε : 0 < ε) (hβ : 0 < β)
(H : ℕ → ℕ) (hH : ∀ᶠ i in atTop, (H i : ℝ) ≤ α*fluctuationScale μ (X 0) (r i)) :
∀ᶠ i in atTop, μ.real {ω | ε*r i < partialSumMax (fun k => X k ω) (H i)} ≤
(32*α+96*α^2)/ε^4+β := by
have he := (hr.2 1 zero_lt_one).const_mul α
have hb := (tendsto_order.mp he).2 β (by simpa using hβ)
filter_upwards [hb,hH,hr.1.eventually (eventually_gt_atTop (0:ℝ))] with i hi hHi hri
have h := measureReal_max_scaled_fourth_le μ X hX hind hident hsym hne hri
(η := 1) zero_le_one le_rfl hε hα (H i) 0 hHi
simp only [Nat.zero_add,one_mul,one_pow,mul_one] at h hi
linarith
lemma gaussian_continuous_norm_bound {Ω : Type*} [MeasurableSpace Ω]
(μ : Measure Ω) [IsProbabilityMeasure μ] (X : ℕ → Ω → ℝ)
(hX : ∀ k, Measurable (X k)) (hind : iIndepFun X μ)
(hident : ∀ k, IdentDistrib (X k) (X 0) μ μ)
(hsym : IdentDistrib (X 0) (fun ω => -X 0 ω) μ μ)
(hI : Integrable (X 0) μ) (hne : 0 < μ {ω | X 0 ω ≠ 0})
(r : ℕ → ℝ) (hr : IsGaussianSequence μ (X 0) r)
{T β : ℝ} (hT : 0 ≤ T) (hβ : 0 < β) :
∃ R : ℝ, 0 < R ∧ ∀ᶠ i in atTop,
μ.real {ω | R < ‖scaledPolygon (fun k => X k ω) (r i)
(fluctuationScale μ (X 0) (r i)) T‖} ≤ β := by
let n := fun i => fluctuationScale μ (X 0) (r i)
let C := 32*(T+1)+96*(T+1)^2
have hC : 0 < C := by dsimp [C]; positivity
let R := max 1 (2*C/β)
have hR1 : 1 ≤ R := le_max_left _ _
have hR : 0 < R := zero_lt_one.trans_le hR1
have hRβ : 2*C ≤ R*β := (div_le_iff₀ hβ).mp (le_max_right _ _)
have hR4 : R ≤ R^4 := by nlinarith [sq_nonneg (R-1),sq_nonneg (R^2-1)]
have hsmall : C/R^4 ≤ β/2 := by
rw [div_le_iff₀ (pow_pos hR 4)]
nlinarith
have hn : Tendsto n atTop atTop := (fluctuationScale_tendsto μ (X 0) (hX 0) hI hne).comp hr.1
have hH : ∀ᶠ i in atTop, (⌊T*n i⌋₊+1 : ℝ) ≤ (T+1)*n i := by
filter_upwards [hn.eventually (eventually_ge_atTop (1:ℝ))] with i hi
have hf := Nat.floor_le (mul_nonneg hT (by linarith : 0 ≤ n i))
nlinarith
have hH' : ∀ᶠ i in atTop, ((⌊T*n i⌋₊+1:ℕ):ℝ) ≤ (T+1)*n i := by simpa using hH
have hb := gaussian_max_horizon_eventually μ X hX hind hident hsym hne r hr
(by linarith : 0 ≤ T+1) hR (by linarith : 0 < β/2) (fun i => ⌊T*n i⌋₊+1) hH'
refine ⟨R,hR,?_⟩
filter_upwards [hb,hn.eventually (eventually_ge_atTop (0:ℝ)),
hr.1.eventually (eventually_gt_atTop (0:ℝ))] with i hi hni hri
have hs : {ω | R < ‖scaledPolygon (fun k => X k ω) (r i) (n i) T‖} ⊆
{ω | R*r i < partialSumMax (fun k => X k ω) (⌊T*n i⌋₊+1)} := by
intro ω hω
exact (lt_div_iff₀ hri).mp (hω.trans_le (norm_scaledPolygon_le_max _ hri hni hT))
exact ((measureReal_mono hs (measure_ne_top _ _)).trans hi).trans (by linarith)
lemma continuousOscillation_mono {ε δ δ' : ℝ} (hδ : δ ≤ δ') :
ContinuousOscillation ε δ ⊆ ContinuousOscillation ε δ' := by
rintro f ⟨s,t,hst,h⟩
exact ⟨s,t,hst.trans hδ,h⟩
lemma continuousOscillation_iInter_empty {ε : ℝ} (hε : 0 < ε) :
(⋂ m : ℕ, ContinuousOscillation ε (1/(m+1))) = ∅ := by
apply Set.eq_empty_iff_forall_notMem.2
intro f hf
obtain ⟨δ,hδ,hfδ⟩ := Metric.uniformContinuous_iff.mp (CompactSpace.uniformContinuous_of_continuous f.continuous) ε hε
have hm := (tendsto_order.mp (tendsto_one_div_add_atTop_nhds_zero_nat (𝕜 := ℝ))).2 δ hδ
obtain ⟨m,hm⟩ := hm.exists
rcases Set.mem_iInter.mp hf m with ⟨s,t,hst,hbig⟩
have hc := hfδ (hst.trans_lt hm)
exact (not_lt_of_ge hbig.le) (by simpa [Real.dist_eq] using hc)
lemma tendsto_measure_continuousOscillation (μ : Measure C(unitInterval,ℝ))
[IsFiniteMeasure μ] {ε : ℝ} (hε : 0 < ε) :
Tendsto (fun m : ℕ => μ (ContinuousOscillation ε (1/(m+1)))) atTop (𝓝 0) := by
have ha : Antitone (fun m : ℕ => ContinuousOscillation ε (1/(m+1))) := by
intro j k hjk
apply continuousOscillation_mono
gcongr
have h := tendsto_measure_iInter_atTop (μ := μ)
(fun m : ℕ => (isOpen_continuousOscillation ε (1/(m+1))).measurableSet.nullMeasurableSet)
ha ⟨0,measure_ne_top _ _⟩
rw [continuousOscillation_iInter_empty hε,measure_empty] at h
exact h
lemma continuous_modulus_uniform_of_eventual
(μ : ℕ → Measure C(unitInterval,ℝ)) [∀ i, IsFiniteMeasure (μ i)]
(h : ∀ ε β : ℝ, 0 < ε → 0 < β → ∃ δ : ℝ, 0 < δ ∧
∀ᶠ i in atTop, μ i (ContinuousOscillation ε δ) ≤ ENNReal.ofReal β) :
∀ ε β : ℝ, 0 < ε → 0 < β → ∃ δ : ℝ, 0 < δ ∧
∀ i, μ i (ContinuousOscillation ε δ) ≤ ENNReal.ofReal β := by
intro ε β hε hβ
obtain ⟨δ,hδ,hb⟩ := h ε β hε hβ
obtain ⟨N,hN⟩ := eventually_atTop.1 hb
have he : ∀ᶠ m : ℕ in atTop, ∀ j : Fin N,
μ j (ContinuousOscillation ε (1/(m+1))) ≤ ENNReal.ofReal β := by
apply eventually_all.2
intro j
exact ((tendsto_order.mp (tendsto_measure_continuousOscillation (μ j) hε)).2
_ (ENNReal.ofReal_pos.mpr hβ)).mono (fun _ hm => hm.le)
obtain ⟨m,hm⟩ := he.exists
refine ⟨min δ (1/(m+1)),lt_min hδ (by positivity),?_⟩
intro i
by_cases hi : N ≤ i
· exact (measure_mono (continuousOscillation_mono (min_le_left _ _))).trans (hN i hi)
· exact (measure_mono (continuousOscillation_mono (min_le_right _ _))).trans
(hm ⟨i,by omega⟩)
lemma continuous_norm_uniform_of_eventual
(μ : ℕ → Measure C(unitInterval,ℝ)) [∀ i, IsFiniteMeasure (μ i)]
(h : ∀ β : ℝ, 0 < β → ∃ R : ℝ, 0 < R ∧
∀ᶠ i in atTop, μ i {f | R < ‖f‖} ≤ ENNReal.ofReal β) :
∀ β : ℝ, 0 < β → ∃ R : ℝ, 0 < R ∧
∀ i, μ i {f | R < ‖f‖} ≤ ENNReal.ofReal β := by
intro β hβ
obtain ⟨R,hR,hb⟩ := h β hβ
obtain ⟨N,hN⟩ := eventually_atTop.1 hb
have he : ∀ᶠ r : ℝ in atTop, ∀ j : Fin N,
μ j {f | r < ‖f‖} ≤ ENNReal.ofReal β := by
apply eventually_all.2
intro j
have ht := tendsto_measure_norm_gt_of_isTightMeasureSet
(isTightMeasureSet_singleton (μ := μ j))
simp only [Set.mem_singleton_iff,iSup_iSup_eq_left] at ht
exact ((tendsto_order.mp ht).2 _ (ENNReal.ofReal_pos.mpr hβ)).mono (fun _ hm => hm.le)
obtain ⟨r,hr⟩ := he.exists
refine ⟨max R r, hR.trans_le (le_max_left _ _),?_⟩
intro i
by_cases hi : N ≤ i
· exact (measure_mono (μ := μ i) (show {f : C(unitInterval,ℝ) | max R r < ‖f‖} ⊆ {f | R < ‖f‖} from fun _ hf => (le_max_left R r).trans_lt hf)).trans (hN i hi)
· exact (measure_mono (μ := μ i) (show {f : C(unitInterval,ℝ) | max R r < ‖f‖} ⊆ {f | r < ‖f‖} from fun _ hf => (le_max_right R r).trans_lt hf)).trans
(hr ⟨i,by omega⟩)
noncomputable def pathCompact (R : ℝ) (δ : ℕ → ℝ) : Set C(unitInterval,ℝ) :=
{f | ‖f‖ ≤ R} ∩ ⋂ m : ℕ, (ContinuousOscillation (1/(m+1)) (δ m))ᶜ
lemma isClosed_pathCompact (R : ℝ) (δ : ℕ → ℝ) : IsClosed (pathCompact R δ) := by
exact (isClosed_le continuous_norm continuous_const).inter
(isClosed_iInter (fun m => (isOpen_continuousOscillation _ _).isClosed_compl))
lemma isCompact_pathCompact (R : ℝ) (δ : ℕ → ℝ) (hδ : ∀ m, 0 < δ m) :
IsCompact (pathCompact R δ) := by
let e := ContinuousMap.isometryEquivBoundedOfCompact unitInterval ℝ
have hc : IsCompact (e.symm ⁻¹' pathCompact R δ) := by
apply BoundedContinuousFunction.arzela_ascoli₂ (Set.Icc (-R) R) isCompact_Icc
(e.symm ⁻¹' pathCompact R δ) ((isClosed_pathCompact R δ).preimage e.symm.continuous)
· intro f t hf
have hnorm : ‖e.symm f‖ ≤ R := hf.1
have hval := ContinuousMap.norm_coe_le_norm (e.symm f) t
have habs : |f t| ≤ R := hval.trans hnorm
exact abs_le.mp habs
· intro t
apply Metric.equicontinuousAt_iff.2
intro ε hε
have hm := (tendsto_order.mp (tendsto_one_div_add_atTop_nhds_zero_nat (𝕜 := ℝ))).2 ε hε
obtain ⟨m,hm⟩ := hm.exists
refine ⟨δ m,hδ m,?_⟩
intro s hst f
have hf := Set.mem_iInter.mp f.2.2 m
have hb : |f.1 t-f.1 s| ≤ 1/(m+1) := by
by_contra! hb
exact hf ⟨t,s,by simpa [dist_comm] using hst.le,hb⟩
simpa [Real.dist_eq] using hb.trans_lt hm
have he : e.symm '' (e.symm ⁻¹' pathCompact R δ) = pathCompact R δ :=
Set.image_preimage_eq _ e.symm.surjective
rw [← he]
exact hc.image e.symm.continuous
lemma isTightMeasureSet_of_continuous_modulus
(μ : ℕ → Measure C(unitInterval,ℝ)) [∀ i, IsFiniteMeasure (μ i)]
(hnorm : ∀ β : ℝ, 0 < β → ∃ R : ℝ, 0 < R ∧
∀ᶠ i in atTop, μ i {f | R < ‖f‖} ≤ ENNReal.ofReal β)
(hmod : ∀ ε β : ℝ, 0 < ε → 0 < β → ∃ δ : ℝ, 0 < δ ∧
∀ᶠ i in atTop, μ i (ContinuousOscillation ε δ) ≤ ENNReal.ofReal β) :
IsTightMeasureSet (Set.range μ) := by
have hn := continuous_norm_uniform_of_eventual μ hnorm
have hm := continuous_modulus_uniform_of_eventual μ hmod
apply isTightMeasureSet_iff_exists_isCompact_measure_compl_le.2
intro ε hε
obtain ⟨b,hb,hbs⟩ := ENNReal.exists_pos_sum_of_countable hε.ne' ℕ
obtain ⟨R,hR,hRb⟩ := hn (b 0) (by exact_mod_cast hb 0)
have hd : ∀ m : ℕ, ∃ δ : ℝ, 0 < δ ∧ ∀ i,
μ i (ContinuousOscillation (1/(m+1)) δ) ≤ (b (m+1) : ℝ≥0∞) := by
intro m
simpa only [ENNReal.ofReal_coe_nnreal] using
hm (1/(m+1)) (b (m+1)) (by positivity) (by exact_mod_cast hb (m+1))
choose δ hδ hd using hd
refine ⟨pathCompact R δ,isCompact_pathCompact R δ hδ,?_⟩
rintro _ ⟨i,rfl⟩
have he : (pathCompact R δ)ᶜ = {f | R < ‖f‖} ∪
⋃ m : ℕ, ContinuousOscillation (1/(m+1)) (δ m) := by
ext f
simp [pathCompact,imp_iff_not_or]
rw [he]
calc
_ ≤ μ i {f | R < ‖f‖}+μ i (⋃ m : ℕ, ContinuousOscillation (1/(m+1)) (δ m)) := measure_union_le _ _
_ ≤ (b 0 : ℝ≥0∞) + ∑' m : ℕ, (b (m+1) : ℝ≥0∞) := by
gcongr
· simpa only [ENNReal.ofReal_coe_nnreal] using hRb i
· exact (measure_iUnion_le _).trans (ENNReal.tsum_le_tsum (fun m => hd m i))
_ = ∑' m : ℕ, (b m : ℝ≥0∞) := (tsum_eq_zero_add' (f := fun m : ℕ => (b m : ℝ≥0∞)) ENNReal.summable).symm
_ ≤ ε := hbs.le
theorem gaussian_iid_path_tight {Ω : Type*} [MeasurableSpace Ω]
(μ : Measure Ω) [IsProbabilityMeasure μ] (X : ℕ → Ω → ℝ)
(hX : ∀ k, Measurable (X k)) (hind : iIndepFun X μ)
(hident : ∀ k, IdentDistrib (X k) (X 0) μ μ)
(hsym : IdentDistrib (X 0) (fun ω => -X 0 ω) μ μ)
(hI : Integrable (X 0) μ) (hne : 0 < μ {ω | X 0 ω ≠ 0})
(r : ℕ → ℝ) (hr : IsGaussianSequence μ (X 0) r)
{T : ℝ} (hT : 0 ≤ T) :
IsTightMeasureSet (Set.range (fun i => μ.map (fun ω =>
scaledPolygon (fun k => X k ω) (r i) (fluctuationScale μ (X 0) (r i)) T))) := by
let P := fun i ω => scaledPolygon (fun k => X k ω) (r i)
(fluctuationScale μ (X 0) (r i)) T
have hP : ∀ i, Measurable (P i) := fun i => measurable_scaledPolygon X hX _ _ _
have : ∀ i, IsProbabilityMeasure (μ.map (P i)) := fun i =>
(Measure.isProbabilityMeasure_map_iff (hP i).aemeasurable).mpr inferInstance
apply isTightMeasureSet_of_continuous_modulus
· intro β hβ
obtain ⟨R,hR,hb⟩ := gaussian_continuous_norm_bound μ X hX hind hident hsym hI hne r hr hT hβ
refine ⟨R,hR,hb.mono (fun i hi => ?_)⟩
rw [Measure.map_apply (hP i) (isOpen_lt continuous_const continuous_norm).measurableSet]
exact (ENNReal.le_ofReal_iff_toReal_le (measure_ne_top _ _) hβ.le).2 hi
· intro ε β hε hβ
obtain ⟨δ,hδ,hb⟩ := gaussian_continuous_modulus μ X hX hind hident hsym hI hne r hr hT hε hβ
refine ⟨δ,hδ,hb.mono (fun i hi => ?_)⟩
rw [Measure.map_apply (hP i) (isOpen_continuousOscillation ε δ).measurableSet]
exact (ENNReal.le_ofReal_iff_toReal_le (measure_ne_top _ _) hβ.le).2 hi
lemma tendstoInMeasure_pi {Ω ι : Type*} [MeasurableSpace Ω] [Fintype ι]
(μ : Measure Ω) [IsFiniteMeasure μ] (F : ℕ → Ω → ι → ℝ)
(h : ∀ j, TendstoInMeasure μ (fun n ω => F n ω j) atTop 0) :
TendstoInMeasure μ F atTop 0 := by
apply tendstoInMeasure_iff_measureReal_norm.2
intro ε hε
have ht : Tendsto (fun n => ∑ j, μ.real {ω | ε ≤ |F n ω j|}) atTop (𝓝 0) := by
convert tendsto_finsetSum Finset.univ (fun j _ =>
(tendstoInMeasure_iff_measureReal_norm.1 (h j)) ε hε) using 1 <;>
simp only [Pi.zero_apply,sub_zero,Real.norm_eq_abs,Finset.sum_const_zero]
apply squeeze_zero (fun _ => measureReal_nonneg) _ ht
intro n
have hs : {ω | ε ≤ ‖F n ω-(0 : Ω → ι → ℝ) ω‖} ⊆ ⋃ j, {ω | ε ≤ |F n ω j|} := by
intro ω hω
by_contra! hc
have hl : ‖F n ω‖ < ε := (pi_norm_lt_iff hε).2 (by simpa [Real.norm_eq_abs] using hc)
exact (not_lt_of_ge (show ε ≤ ‖F n ω‖ by simpa using hω)) hl
exact (measureReal_mono hs (measure_ne_top _ _)).trans (measureReal_iUnion_fintype_le _)
lemma tendstoInMeasure_of_abs_le {Ω : Type*} [MeasurableSpace Ω]
(μ : Measure Ω) [IsFiniteMeasure μ] (F G : ℕ → Ω → ℝ)
(hG : TendstoInMeasure μ G atTop 0)
(hb : ∀ᶠ n in atTop, ∀ ω, |F n ω| ≤ |G n ω|) :
TendstoInMeasure μ F atTop 0 := by
apply tendstoInMeasure_iff_measureReal_norm.2
intro ε hε
have hg := (tendstoInMeasure_iff_measureReal_norm.1 hG) ε hε
simp only [Pi.zero_apply,sub_zero,Real.norm_eq_abs] at hg ⊢
apply squeeze_zero' (Eventually.of_forall fun _ => measureReal_nonneg) _ hg
filter_upwards [hb] with n hn
exact measureReal_mono (fun ω hω => hω.trans (hn ω)) (measure_ne_top _ _)
lemma selected_iid_div_tendstoInMeasure {Ω : Type*} [MeasurableSpace Ω]
(μ : Measure Ω) [IsFiniteMeasure μ] (X : ℕ → Ω → ℝ)
(hX : Measurable (X 0)) (hident : ∀ k, IdentDistrib (X k) (X 0) μ μ)
(r : ℕ → ℝ) (hr : Tendsto r atTop atTop) (k : ℕ → ℕ) :
TendstoInMeasure μ (fun n ω => X (k n) ω/r n) atTop 0 := by
have h0 : TendstoInMeasure μ (fun n ω => X 0 ω/r n) atTop 0 := by
apply tendstoInMeasure_of_tendsto_ae (fun n => (hX.div_const _).aestronglyMeasurable)
filter_upwards [] with ω
exact tendsto_const_nhds.div_atTop hr
apply tendstoInMeasure_iff_measureReal_norm.2
intro ε hε
have he n : μ.real {ω | ε ≤ ‖X (k n) ω/r n-(0 : Ω → ℝ) ω‖} =
μ.real {ω | ε ≤ ‖X 0 ω/r n-(0 : Ω → ℝ) ω‖} := by
simp only [Pi.zero_apply,sub_zero]
unfold Measure.real
apply congrArg ENNReal.toReal
exact ((hident (k n)).comp (show Measurable (fun x : ℝ => x/r n) by fun_prop)).measure_mem_eq
(s := {x : ℝ | ε ≤ ‖x‖}) (isClosed_le continuous_const continuous_norm).measurableSet
simp_rw [he]
exact (tendstoInMeasure_iff_measureReal_norm.1 h0) ε hε
lemma polygon_eval_error_tendstoInMeasure {Ω : Type*} [MeasurableSpace Ω]
(μ : Measure Ω) [IsFiniteMeasure μ] (X : ℕ → Ω → ℝ)
(hX : Measurable (X 0)) (hident : ∀ k, IdentDistrib (X k) (X 0) μ μ)
(r n : ℕ → ℝ) (hr : Tendsto r atTop atTop) (hn : ∀ᶠ i in atTop, 0 ≤ n i)
{T : ℝ} (hT : 0 ≤ T) (s : unitInterval) :
TendstoInMeasure μ (fun i ω => scaledPolygon (fun k => X k ω) (r i) (n i) T s -
realPartialSum (fun k => X k ω) ⌊(T*s)*n i⌋₊/r i) atTop 0 := by
have hsel := selected_iid_div_tendstoInMeasure μ X hX hident r hr (fun i => ⌊(T*s)*n i⌋₊)
apply tendstoInMeasure_of_abs_le μ _ _ hsel
filter_upwards [hn,hr.eventually (eventually_gt_atTop (0:ℝ))] with i hni hri
intro ω
rw [scaledPolygon_apply]
have he : T*n i*s = (T*s)*n i := by ring
rw [he,← sub_div,abs_div,abs_div]
apply div_le_div_of_nonneg_right _ (abs_nonneg _)
apply linearPolygon_near_partialSum
· exact mul_nonneg (mul_nonneg hT s.2.1) hni
· apply Nat.lt_succ_of_le
apply Nat.floor_mono
calc
(T*s)*n i = (T*n i)*s := by ring
_ ≤ T*n i := mul_le_of_le_one_right (mul_nonneg hT hni) s.2.2
· exact le_rfl
end DirectionalTransience
end
end
end OAI
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