OAI/Probability/DilutedSpin/ScheduledEvaluationContinuity.lean
6 declarations, 0 contain sorry, 0 declared as axioms
- def
OAI.DilutedSpinGlass.ReducedTopology.scheduledPrefixMeanline 14Source documentation
Conditional scheduled-tree mean after a genuine sampled prefix. The terminal reserve n is held fixed and the evaluation depth ranges over the first r transitions. No unobserved ancestral variable is resampled.
noncomputable def scheduledPrefixMean (n : ℕ) : (r d : ℕ) → Fin (r+1) → (S : ReducedTopology) → (S.Vertex → ℕ) → KernelTower Ω (n+r) → (FinitePath Ω (n+r) → ℝ) → FinitePath Ω (n+r) → ℝ | 0,d,_,S,q,T,f,_ => PrescribedTree.treeMean (realize n d S q) T f | r+1,d,e,S,q,T,f,x => Fin.cases (PrescribedTree.treeMean (realize (n+r+1) d S q) T f) (fun e => scheduledPrefixMean n r (d+1) e S q (T.2 x.1) (fun y => f (x.1,y)) x.2) eMentions: OAI.DilutedSpinGlass.ReducedTopology, OAI.DilutedSpinGlass.KernelTower, OAI.DilutedSpinGlass.FinitePath, OAI.DilutedSpinGlass.q, OAI.DilutedSpinGlass.PrescribedTree.treeMean, OAI.DilutedSpinGlass.ReducedTopology.realize
- lemma
OAI.DilutedSpinGlass.ReducedTopology.scheduledPrefixMean_zeroline 22 - lemma
OAI.DilutedSpinGlass.ReducedTopology.scheduledPrefixMean_eq_stemMeanAtline 30Source documentation
Before the first child branching the literal scheduled conditional mean is exactly the martingale used in the energy theorem. All later assigned depths stay fixed in this identity.
lemma scheduledPrefixMean_eq_stemMeanAt (n r d : ℕ) (S : ReducedTopology) (q : S.Vertex → ℕ) (hq : ∀ v, d+r≤q v) (e : Fin (r+1)) (T : KernelTower Ω (n+r)) (f : FinitePath Ω (n+r) → ℝ) (x : FinitePath Ω (n+r)) : scheduledPrefixMean n r d e S q T f x= PrescribedTree.stemMeanAt (realize n (d+r) S q) r e T f x := by …Mentions: OAI.DilutedSpinGlass.ReducedTopology, OAI.DilutedSpinGlass.q, OAI.DilutedSpinGlass.KernelTower, OAI.DilutedSpinGlass.FinitePath, OAI.DilutedSpinGlass.ReducedTopology.scheduledPrefixMean, OAI.DilutedSpinGlass.PrescribedTree.stemMeanAt, OAI.DilutedSpinGlass.ReducedTopology.realize
- def
OAI.DilutedSpinGlass.ReducedTopology.scheduledProductMeanline 46Source documentation
Ranged proper-child conditional product in the actual scheduled shape.
noncomputable def scheduledProductMean {ι : Type*} [Fintype ι] (n r d : ℕ) (C : ι → ReducedTopology) (q : (j : ι) → (C j).Vertex → ℕ) (e : Fin (r+1)) (T : KernelTower Ω (n+r)) (f : FinitePath Ω (n+r) → Fin N → ℝ) (x : FinitePath Ω (n+r)) (i : Fin N) : ℝ := …Mentions: OAI.DilutedSpinGlass.ReducedTopology, OAI.DilutedSpinGlass.q, OAI.DilutedSpinGlass.ReducedTopology.Vertex, OAI.DilutedSpinGlass.KernelTower, OAI.DilutedSpinGlass.FinitePath
- lemma
OAI.DilutedSpinGlass.ReducedTopology.scheduledProductMean_eqline 52 - theorem
OAI.DilutedSpinGlass.ReducedTopology.scheduled_target_evaluation_cost_leline 67Source documentation
The evaluation component of h_N on the exact scheduled proper-child family, with later branching depths fixed and arbitrary allowed evaluation subsets. Targets and anchors may vary with the evaluation coordinate.
theorem scheduled_target_evaluation_cost_le {ι : Type*} [Fintype ι] (n r d L : ℕ) (C : ι → ReducedTopology) (q : (j : ι) → (C j).Vertex → ℕ) (hq : ∀ j v, d+r≤q j v) (U : Finset (Fin r)) (T : KernelTower Ω (n+r)) (f : FinitePath Ω (n+r) → Fin N → ℝ) (hf : ∀ x i, |f x i|≤1) (Target : Fin r → PrescribedTree (n+r)) (a b : (e : Fin r) → (Target e).Leaf) : (∑ e ∈ U, PrescribedTree.targetContractionChangeSq (Target e) T (a e) (b e) (scheduledProductMean n r d C q e.succ T f) (scheduledProductMean n r d C q e.castSucc T f))/(L:ℝ) ≤ 4*(Fintype.card ι:ℝ)^2/(L:ℝ) := by …Mentions: OAI.DilutedSpinGlass.ReducedTopology, OAI.DilutedSpinGlass.q, OAI.DilutedSpinGlass.ReducedTopology.Vertex, OAI.DilutedSpinGlass.KernelTower, OAI.DilutedSpinGlass.FinitePath, OAI.DilutedSpinGlass.PrescribedTree, OAI.DilutedSpinGlass.ReducedTopology.Leaf, OAI.DilutedSpinGlass.PrescribedTree.targetContractionChangeSq, OAI.DilutedSpinGlass.ReducedTopology.scheduledProductMean