roseking's picture
Add lean source and binary files (part 121)
f61e547 verified
Raw History Blame Contribute Delete
8.9 kB
import OAI.Probability.FreeIsing.Critical.Endgame
import OAI.Probability.FreeIsing.Estimates.EndpointTimeScale
namespace OAI
noncomputable section
open Set MeasureTheory
namespace Problem367
theorem eq_zero_of_ae_small_critical_large_osgood
{V : ℝ → ℝ} {T K cutoff C : ℝ}
(hT : 0 ≤ T) (hc : cutoff < 1)
(hV : AbsolutelyContinuousOnInterval V 0 T) (hzero : V 0 = 0)
(hnonneg : ∀ t ∈ Icc 0 T, 0 ≤ V t)
(hupper : ∀ t ∈ Icc 0 T, V t ≤ K) (hK : 0 < K)
(hsmall : ∀ᵐ t ∂volume.restrict (Ioc 0 T), t ≤ cutoff → 0 < V t →
deriv V t ≤ C * V t * (1 + Real.log (K / V t)) *
(1 + t ^ (-(3 : ℝ) / 4) + 1 / (t * (Real.log (1 / t)) ^ 2)))
(hlarge : ∀ᵐ t ∂volume.restrict (Ioc 0 T), cutoff < t → 0 < V t →
deriv V t ≤ C * V t * (1 + Real.log (K / V t))) :
∀ t ∈ Icc 0 T, V t = 0 := by
apply eq_zero_of_ae_criticalTimeCoefficient hT hc hV hzero hnonneg hupper hK
rw [← restrict_Ioc_eq_restrict_Icc]
filter_upwards [hsmall, hlarge] with t hs hl
intro hpos
by_cases ht : t ≤ cutoff
· simpa only [criticalTimeCoefficient, ite_eq_left ht, mul_assoc, mul_left_comm,
mul_comm] using hs ht hpos
· simpa only [criticalTimeCoefficient, ite_eq_right ht, mul_one] using
hl (lt_of_not_ge ht) hpos
theorem endpoint_sums_bounded_scale_reduction
{D Q L Z S V C H I R W Rmax Wmax : ℝ}
(hC : 1 ≤ C) (hH : 1 ≤ H) (hI : 1 ≤ I)
(hS : 0 ≤ S) (hV : 0 ≤ V) (hVH : V ≤ H)
(hSV : S ≤ C * V) (hR : 0 ≤ R) (hW : 0 ≤ W)
(hRmax : R ≤ Rmax) (hWmax : W ≤ Wmax)
(hQ : Q ≤ C * (S * (R + (Real.log I) ^ 2) + V ^ 2))
(hL : L ≤ C * (V * (W + Real.log I) + V ^ 2))
(hZ : Z ≤ C * (Real.sqrt S * (W + (Real.log I) ^ ((3 : ℝ) / 2)) + V))
(hD : D ≤ C * (V + Q + L + Real.sqrt V * Z)) :
D ≤ (C ^ 2 * (9 * C + 3 * H + 3) * (C * Rmax + 1 + Wmax)) * V * I := by
have hC0 : 0 ≤ C := zero_le_one.trans hC
have hRmax0 : 0 ≤ Rmax := hR.trans hRmax
have hWmax0 : 0 ≤ Wmax := hW.trans hWmax
have hVI : V ≤ V * I := by nlinarith
have hnoise : S * R ≤ (C * Rmax) * (V * I) := by
calc
S * R ≤ (C * V) * Rmax := mul_le_mul hSV hRmax hR (by positivity)
_ = (C * Rmax) * V := by ring
_ ≤ (C * Rmax) * (V * I) :=
mul_le_mul_of_nonneg_left hVI (by positivity)
have hlinear : V * (I + W) ≤ (1 + Wmax) * (V * I) := by
calc
V * (I + W) ≤ V * I + Wmax * V := by
nlinarith [mul_le_mul_of_nonneg_left hWmax hV]
_ ≤ V * I + Wmax * (V * I) :=
add_le_add le_rfl (mul_le_mul_of_nonneg_left hVI hWmax0)
_ = (1 + Wmax) * (V * I) := by ring
have hscale := endpoint_sums_critical_reduction hC hH hI hS hV hVH hSV
hR hW hQ hL hZ hD
calc
D ≤ C ^ 2 * (9 * C + 3 * H + 3) * (S * R + V * (I + W)) := hscale
_ ≤ C ^ 2 * (9 * C + 3 * H + 3) *
((C * Rmax) * (V * I) + (1 + Wmax) * (V * I)) :=
mul_le_mul_of_nonneg_left (add_le_add hnoise hlinear) (by positivity)
_ = _ := by ring
structure CriticalSpatialEndpointBounds (D Q L Z S V C K ω : ℝ) : Prop where
noise_nonneg : 0 ≤ S
noise_le : S ≤ C * V
quadratic : Q ≤ C * (S * ((ω⁻¹) ^ 2 + (Real.log (1 + Real.log (K / V))) ^ 2) + V ^ 2)
linear : L ≤ C * (V * (ω⁻¹ + Real.log (1 + Real.log (K / V))) + V ^ 2)
square_root : Z ≤ C * (Real.sqrt S * (ω⁻¹ * Real.sqrt (ω⁻¹) +
(Real.log (1 + Real.log (K / V))) ^ ((3 : ℝ) / 2)) + V)
drift : D ≤ C * (V + Q + L + Real.sqrt V * Z)
theorem inv_le_inv_mul_sqrt {ω : ℝ} (hω : 0 < ω) (hω1 : ω ≤ 1) :
ω⁻¹ ≤ ω⁻¹ * Real.sqrt (ω⁻¹) := by
have hi : 1 ≤ ω⁻¹ := (one_le_inv₀ hω).2 hω1
have hs : 1 ≤ Real.sqrt (ω⁻¹) := by
exact (Real.one_le_sqrt).2 hi
simpa using mul_le_mul_of_nonneg_left hs (inv_nonneg.mpr hω.le)
theorem CriticalSpatialEndpointBounds.small_time
{D Q L Z S V C A B c K t : ℝ}
(h : CriticalSpatialEndpointBounds D Q L Z S V C K (Real.sqrt t))
(hC : 0 ≤ C) (hV : 0 ≤ V) (ht : 0 < t) (ht1 : t ≤ 1)
(hsmall : S ≤ A * t ^ ((1 : ℝ) / 4) * V +
min (A * V) (B * Real.exp (-c * (Real.log (1 / t)) ^ 2))) :
CriticalEndpointBounds D Q L Z S V C A B c K t := by
refine ⟨h.noise_nonneg, h.noise_le, hsmall, ?_, ?_, ?_, h.drift⟩
· simpa only [inv_sqrt_sq_time ht.le] using h.quadratic
· apply h.linear.trans
apply mul_le_mul_of_nonneg_left _ hC
apply add_le_add _ le_rfl
apply mul_le_mul_of_nonneg_left _ hV
exact add_le_add (inv_sqrt_le_time_three_quarters ht ht1) le_rfl
· simpa only [inv_sqrt_mul_sqrt_time ht] using h.square_root
def criticalLateCoefficient (C H ε : ℝ) : ℝ :=
C ^ 2 * (9 * C + 3 * H + 3) *
(C * (ε⁻¹) ^ 2 + 1 + ε⁻¹ * Real.sqrt (ε⁻¹))
theorem CriticalSpatialEndpointBounds.late_time
{D Q L Z S V C H K ω ε : ℝ}
(h : CriticalSpatialEndpointBounds D Q L Z S V C K ω)
(hC : 1 ≤ C) (hH : 1 ≤ H) (hV : 0 < V) (hVK : V ≤ K) (hVH : V ≤ H)
(hε : 0 < ε) (hεω : ε ≤ ω) (hω1 : ω ≤ 1) :
D ≤ criticalLateCoefficient C H ε * V * (1 + Real.log (K / V)) := by
have hω : 0 < ω := hε.trans_le hεω
have hωinv : 0 ≤ ω⁻¹ := inv_nonneg.mpr hω.le
have hεinv : 0 ≤ ε⁻¹ := inv_nonneg.mpr hε.le
have hinv : ω⁻¹ ≤ ε⁻¹ := (inv_le_inv₀ hω hε).2 hεω
have hI : 1 ≤ 1 + Real.log (K / V) := by
have := Real.log_nonneg ((one_le_div hV).2 hVK)
linarith
have hlinear : L ≤ C * (V *
(ω⁻¹ * Real.sqrt (ω⁻¹) + Real.log (1 + Real.log (K / V))) + V ^ 2) := by
apply h.linear.trans
apply mul_le_mul_of_nonneg_left _ (zero_le_one.trans hC)
apply add_le_add _ le_rfl
apply mul_le_mul_of_nonneg_left _ hV.le
exact add_le_add (inv_le_inv_mul_sqrt hω hω1) le_rfl
exact endpoint_sums_bounded_scale_reduction hC hH hI h.noise_nonneg hV.le hVH
h.noise_le (sq_nonneg _) (mul_nonneg hωinv (Real.sqrt_nonneg _))
((sq_le_sq₀ hωinv hεinv).2 hinv)
(mul_le_mul hinv (Real.sqrt_le_sqrt hinv) (Real.sqrt_nonneg _) hεinv)
h.quadratic hlinear h.square_root h.drift
theorem eq_zero_of_ae_critical_spatial_endpoint_bounds
{V Q L Z S : ℝ → ℝ} {T cutoff C H A B c K : ℝ}
(hT : 0 ≤ T) (hcutoff0 : 0 < cutoff) (hcutoff : cutoff < 1)
(hC : 1 ≤ C) (hH : 1 ≤ H) (hA : 0 ≤ A) (hB : 0 ≤ B)
(hc : 0 < c) (hK : 1 ≤ K)
(hV : AbsolutelyContinuousOnInterval V 0 T) (hzero : V 0 = 0)
(hnonneg : ∀ t ∈ Icc 0 T, 0 ≤ V t)
(hupperK : ∀ t ∈ Icc 0 T, V t ≤ K)
(hupperH : ∀ t ∈ Icc 0 T, V t ≤ H)
(hendpoint : ∀ᵐ t ∂volume.restrict (Ioc 0 T), 0 < V t →
CriticalSpatialEndpointBounds (deriv V t) (Q t) (L t) (Z t) (S t) (V t) C K
(min (Real.sqrt t) 1))
(hsmall : ∀ᵐ t ∂volume.restrict (Ioc 0 T), t ≤ cutoff → 0 < V t →
S t ≤ A * t ^ ((1 : ℝ) / 4) * V t +
min (A * V t) (B * Real.exp (-c * (Real.log (1 / t)) ^ 2))) :
∀ t ∈ Icc 0 T, V t = 0 := by
let early := C ^ 2 * (9 * C + 3 * H + 3) * (A + 2 * (A + B) / c + 1)
let late := criticalLateCoefficient C H (Real.sqrt cutoff)
let M := max early late
apply eq_zero_of_ae_small_critical_large_osgood (C := M) hT hcutoff hV hzero
hnonneg hupperK (zero_lt_one.trans_le hK)
· filter_upwards [hendpoint, hsmall, ae_restrict_mem measurableSet_Ioc] with t he hs ht
intro htc hpos
have hmem : t ∈ Icc 0 T := ⟨ht.1.le, ht.2⟩
have ht1 : t < 1 := htc.trans_lt hcutoff
have htpos : 0 < t := ht.1
have hscale : min (Real.sqrt t) 1 = Real.sqrt t :=
min_eq_left (Real.sqrt_le_one.2 ht1.le)
have he' := he hpos
rw [hscale] at he'
have hb := (he'.small_time (zero_le_one.trans hC) hpos.le ht.1 ht1.le
(hs htc hpos)).differential_bound hC hH hA hB hc hK hpos
(hupperK t hmem) (hupperH t hmem) ht.1 ht1
have hlog : 0 ≤ Real.log (K / V t) :=
Real.log_nonneg ((one_le_div hpos).2 (hupperK t hmem))
apply hb.trans
apply mul_le_mul_of_nonneg_right _ (by positivity)
apply mul_le_mul_of_nonneg_right _ (by positivity)
exact mul_le_mul_of_nonneg_right (le_max_left early late) hpos.le
· filter_upwards [hendpoint, ae_restrict_mem measurableSet_Ioc] with t he ht
intro htc hpos
have hmem : t ∈ Icc 0 T := ⟨ht.1.le, ht.2⟩
have hscale : Real.sqrt cutoff ≤ min (Real.sqrt t) 1 :=
le_min (Real.sqrt_le_sqrt htc.le) (Real.sqrt_le_one.2 hcutoff.le)
have hb := (he hpos).late_time hC hH hpos (hupperK t hmem) (hupperH t hmem)
(Real.sqrt_pos.2 hcutoff0) hscale (min_le_right _ _)
have hlog : 0 ≤ Real.log (K / V t) :=
Real.log_nonneg ((one_le_div hpos).2 (hupperK t hmem))
apply hb.trans
apply mul_le_mul_of_nonneg_right _ (by positivity)
exact mul_le_mul_of_nonneg_right (le_max_right early late) hpos.le
end Problem367
end
end OAI