openAI-math-dataset / lean /OAI /Analysis /CircleDomains /Uniformization /FirstExitFragmentLimits.lean
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Add lean source and binary files (part 14)
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import OAI.Analysis.CircleDomains.Modulus.FirstExitFragmentBudget
namespace OAI
/-! Joint compact hit-position limits and their genuine limiting cost
budget for the actual first-exit fragment array. -/
open Set Function Filter MeasureTheory
open scoped ENNReal Topology
noncomputable section
namespace CircleDomainRigidity
variable {X Y : Type*} [MetricSpace X] [CompactSpace X] [MetricSpace Y]
[MeasurableSpace X] [BorelSpace X] [MeasurableSpace Y] [BorelSpace Y]
[MeasurableSpace C(PathTime, X)]
theorem exists_firstExit_fragment_limits
(d : PathCodeData X Y) (hU : IsOpen d.quotientDomain)
(Γ : ℕ → TaggedPhysicalPath d) (V : ℕ → Set X)
(hcut : ∀n j, j ≤ n → firstExitTime (Γ n).1.val (V (j+1)) <
firstExitTime (Γ n).1.val (V j))
(hV : ∀j, IsOpen (V j)) (hanti : Antitone V)
(hstart : ∀n, (Γ n).1.val ⊥ ∈ V (n+1)) (hend : ∀n, (Γ n).1.val ⊤ ∉ V 0)
(g : Y → ℝ≥0∞) (hg : Measurable g) (m : X → ℝ≥0∞)
(hm : ∀n j, j ≤ n+1 → m ((Γ n).1.val (firstExitTime (Γ n).1.val (V j))) = 0)
(A : ℝ≥0∞) (hA : Tendsto (fun n => physicalTollCost d g m (Γ n).1) atTop (𝓝 A)) :
∃ (s : ℕ → ℕ) (x : ℕ → X) (c : ℕ → ℝ≥0∞), StrictMono s ∧
(∀j, x j ∈ frontier (V j)) ∧
(∀j, Tendsto (fun n => (firstExitFragmentArray d hU Γ V hcut (s n) j).1.val ⊥)
atTop (𝓝 (x (j+1)))) ∧
(∀j, Tendsto (fun n => (firstExitFragmentArray d hU Γ V hcut (s n) j).1.val ⊤)
atTop (𝓝 (x j))) ∧
(∀j, Tendsto (fun n => physicalTollCost d g m
(firstExitFragmentArray d hU Γ V hcut (s n) j).1) atTop (𝓝 (c j))) ∧
(∑'j, c j) ≤ A := by
let hit : ℕ → ℕ → X := fun n j => (Γ n).1.val (firstExitTime (Γ n).1.val (V j))
let cost : ℕ → ℕ → ℝ≥0∞ := fun n j =>
physicalTollCost d g m (firstExitFragmentArray d hU Γ V hcut n j).1
obtain ⟨s, _, x, c, hs, _, hx, hc⟩ := exists_joint_fragment_limits hit hit cost
have hindex (j : ℕ) : ∀ᶠn in atTop, j ≤ s n :=
hs.tendsto_atTop.eventually_ge_atTop j
have hxfront (j : ℕ) : x j ∈ frontier (V j) := by
apply isClosed_frontier.mem_of_tendsto (hx j)
filter_upwards [hindex j] with n hn
exact firstExit_frontier (Γ (s n)).1.val (hV j)
(hanti (hn.trans (Nat.le_succ _)) (hstart (s n)))
(fun h => hend (s n) (hanti (Nat.zero_le j) h))
have hstartlim (j : ℕ) : Tendsto
(fun n => (firstExitFragmentArray d hU Γ V hcut (s n) j).1.val ⊥)
atTop (𝓝 (x (j+1))) := by
apply (hx (j+1)).congr'
filter_upwards [hindex j] with n hn
exact (firstExitFragmentArray_endpoints d hU Γ V hcut hn).1.symm
have hstoplim (j : ℕ) : Tendsto
(fun n => (firstExitFragmentArray d hU Γ V hcut (s n) j).1.val ⊤)
atTop (𝓝 (x j)) := by
apply (hx j).congr'
filter_upwards [hindex j] with n hn
exact (firstExitFragmentArray_endpoints d hU Γ V hcut hn).2.symm
refine ⟨s, x, c, hs, hxfront, hstartlim, hstoplim, hc, ?_⟩
apply fragment_limit_budget_of_eventually (fun n j => cost (s n) j) c
(fun n => physicalTollCost d g m (Γ (s n)).1) A hc (hA.comp hs.tendsto_atTop)
intro F
filter_upwards [hindex (F.sup id)] with n hn
apply firstExitFragmentArray_finite_budget d hU Γ V hcut hV hanti hend g hg m hm F
intro j hj
exact (Finset.le_sup (f := id) hj).trans hn
end CircleDomainRigidity
end
end OAI