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Add lean source and binary files (part 118)
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import Mathlib
import OAI.Probability.Ballisticity.Geometry.WindowWeak
import OAI.Probability.Ballisticity.Estimates.BadOccupationLimit
import OAI.Probability.Ballisticity.Stationary.BadArraySampling
namespace OAI
section
open MeasureTheory ProbabilityTheory InformationTheory Filter
open scoped ENNReal NNReal Classical Topology
namespace DirectionalTransience
namespace OperationalConstants
variable {d : ℕ} {ν : Measure (Row d)}
{e f : Direction d} {D : ℝ}
lemma paddedTimes_stopping [IsProbabilityMeasure ν]
(C : OperationalConstants ν e f D) (hef : e.1≠f.1)
(N : ℕ) (i : ℤ) (n : ℕ) :
MeasurableSet[rowSigma (BelowHeight (realPosition (step e)) n)]
{ω | C.paddedTimes hef N ω i=n} :=
episodeBoundary_height_event (k:=C.k) e f hef (episodeScaleRadius ν e f)
C.fexp C.g C.χ C.b C.sfloor C.radius_nonneg N i.toNat n
lemma paddedTimes_mono [IsProbabilityMeasure ν]
(C : OperationalConstants ν e f D) (hef : e.1≠f.1)
(N : ℕ) (ω : Environment d) : Monotone (fun i : ℕ => C.paddedTimes hef N ω i) := by
simpa only [paddedTimes,EpisodeChainLedger.arrayTime_nat] using
episodeBoundary_mono (k:=C.k) e f hef (episodeScaleRadius ν e f)
C.fexp C.g C.χ C.b C.sfloor C.radius_nonneg N ω
lemma paddedTimes_active [IsProbabilityMeasure ν]
(C : OperationalConstants ν e f D) (hef : e.1≠f.1)
(N i : ℕ) (ω : Environment d) :
C.paddedTimes hef N ω i<N ↔ i<C.activeCount hef N ω := by
simpa only [paddedTimes,EpisodeChainLedger.arrayTime_nat,activeCount] using
EpisodeChainLedger.active_iff_lt_number (k:=C.k) e f hef (episodeScaleRadius ν e f)
C.fexp C.g C.χ C.b C.sfloor C.radius_nonneg N ω i
noncomputable def windowEntropyConstant (C : OperationalConstants ν e f D) : ℝ :=
(8/3:ℝ)*D*C.injectionCost
lemma windowEntropyConstant_nonneg [IsProbabilityMeasure ν]
(C : OperationalConstants ν e f D) (hD : 0≤D) :
0≤C.windowEntropyConstant := mul_nonneg (mul_nonneg (by norm_num) hD) C.cost_nonneg
variable [IsProbabilityMeasure ν]
lemma bad_window_kl_le (C : OperationalConstants ν e f D) (hef : e.1≠f.1) (hD : 0≤D)
(N m : ℕ) (hN : C.sfloor ≤ (N:ℝ))
(hlarge : 32*C.b ≤ (1/2:ℝ)*Real.log (N:ℝ))
(hmass : (N:ℝ)^(-D) ≤ (environmentLaw ν).real (badCrossingEvent e N (1/2))) :
let W := actualCurrentLaw e m
(C.occupation hef N ((environmentLaw ν)[|badCrossingEvent e N (1/2)]))
klDiv (W : Measure (CurrentWindow e)) (currentReferenceLaw e ν W : Measure (CurrentWindow e)) ≤
ENNReal.ofReal ((m:ℝ)*C.windowEntropyConstant) := by
let Q := (environmentLaw ν)[|badCrossingEvent e N (1/2)]
have hN0 : 0<N := by exact_mod_cast lt_of_lt_of_le zero_lt_one (C.hs.trans hN)
have : IsProbabilityMeasure Q :=
cond_isProbabilityMeasure (badCrossingEvent_pos e N (1/2) D (environmentLaw ν) hN0 hmass)
have hkl := badCrossing_cond_entropy e N (1/2) D (environmentLaw ν) hN0 hmass
have hfin : klDiv Q (environmentLaw ν)≠∞ := ne_top_of_le_ne_top ENNReal.ofReal_ne_top hkl
have hpos := C.bad_raw_mass_pos hef N hN hmass
have hb := actualOccupation_window_kl_le e ν Q hfin
(C.paddedTimes hef N) (C.paddedStages hef N)
(C.paddedTimes_measurable hef N) (C.paddedStages_measurable hef N)
(C.paddedTimes_stopping hef N) (C.paddedTimes_mono hef N) N m (C.activeCount hef N)
(C.paddedTimes_active hef N) hpos
have he := EpisodeChainLedger.operational_raw_mass (k:=C.k) e f hef (episodeScaleRadius ν e f)
C.fexp C.g C.χ C.b C.sfloor C.radius_nonneg N ν Q
change (actualOccupationRaw e ν Q (C.paddedTimes hef N) (C.paddedStages hef N)
(C.paddedTimes_measurable hef N) N (C.activeCount hef N)).real Set.univ = _ at he
rw [he] at hb hpos
apply hb.trans
apply ENNReal.ofReal_le_ofReal
have hlog : 0≤Real.log (N:ℝ) := Real.log_nonneg (by exact_mod_cast Nat.one_le_iff_ne_zero.mpr hN0.ne')
have hkreal : (klDiv Q (environmentLaw ν)).toReal ≤ D*Real.log (N:ℝ) := by
have hh := ENNReal.toReal_mono ENNReal.ofReal_ne_top hkl
rwa [ENNReal.toReal_ofReal (mul_nonneg hD hlog)] at hh
obtain ⟨L,hL,hcharge⟩ := C.finite_charge
have hl := (C.conditional_episode_drops hef hD N hN hlarge hmass L hL hcharge).1
have hd := mul_le_mul_of_nonneg_left hl hD
have hbudget : (klDiv Q (environmentLaw ν)).toReal ≤
C.windowEntropyConstant*(∫ ω, (C.activeCount hef N ω:ℝ) ∂Q) := by
unfold windowEntropyConstant
dsimp only [Q]
nlinarith only [hkreal,hd]
apply (div_le_iff₀ hpos).mpr
have hh := mul_le_mul_of_nonneg_left hbudget (Nat.cast_nonneg m)
simpa only [activeCount,mul_assoc] using hh
lemma bad_occupation_currentOffsets (C : OperationalConstants ν e f D) (hef : e.1≠f.1)
(N : ℕ) (hN : C.sfloor≤(N:ℝ))
(hmass : (N:ℝ)^(-D) ≤ (environmentLaw ν).real (badCrossingEvent e N (1/2))) :
∀ᵐ Y ∂(C.occupation hef N ((environmentLaw ν)[|badCrossingEvent e N (1/2)]) : Measure (ActualEpisodeArray e)),
∀ j, ReferenceClasses.Consistent (currentOffsets e j Y) :=
actualOccupation_currentOffsets e ν _ (C.paddedTimes hef N) (C.paddedStages hef N)
(C.paddedTimes_measurable hef N) (C.paddedStages_measurable hef N) N (C.activeCount hef N)
(C.bad_raw_mass_pos hef N hN hmass)
theorem bad_limit_window_entropy (C : OperationalConstants ν e f D) (hef : e.1≠f.1) (hD : 0≤D)
(Ns : ℕ → ℕ)
(hN : ∀ n, C.sfloor ≤ (Ns n:ℝ))
(hlarge : ∀ n, 32*C.b ≤ (1/2:ℝ)*Real.log (Ns n:ℝ))
(hmass : ∀ n, (Ns n:ℝ)^(-D) ≤ (environmentLaw ν).real (badCrossingEvent e (Ns n) (1/2)))
(ρ : ProbabilityMeasure (ActualEpisodeArray e))
(hlim : Tendsto (fun n => C.occupation hef (Ns n)
((environmentLaw ν)[|badCrossingEvent e (Ns n) (1/2)])) atTop (𝓝 ρ)) (m : ℕ) :
klDiv (actualCurrentLaw e m ρ : Measure (CurrentWindow e))
(currentReferenceLaw e ν (actualCurrentLaw e m ρ) : Measure (CurrentWindow e)) ≤
ENNReal.ofReal ((m:ℝ)*C.windowEntropyConstant) :=
actualCurrentLaw_kl_weak_limit e ν m _ ρ hlim
(fun n => C.bad_occupation_currentOffsets hef (Ns n) (hN n) (hmass n))
((m:ℝ)*C.windowEntropyConstant) (mul_nonneg (Nat.cast_nonneg m) (C.windowEntropyConstant_nonneg hD))
(fun n => C.bad_window_kl_le hef hD (Ns n) m (hN n) (hlarge n) (hmass n))
end OperationalConstants
end DirectionalTransience
end
end OAI