import Mathlib import OAI.LinearAlgebra.MatrixFields.Entropy.ZeroLeafRates namespace OAI namespace MatrixAllFields open scoped BigOperators Topology Polynomial section noncomputable section namespace MatrixMultiplication.Foundation.StageHierarchyResources open Filter HierarchySeparationRates LabelHierarchyCounts open scoped BigOperators Topology universe u v local instance (priority := low) {B : Type*} : DecidableEq B := Classical.decEq B variable {A : Type u} [Fintype A] {Label : ℕ → Type v} [∀ n, Fintype (Label n)] def stageRefinementCount (counts : A → ℕ) (labels : ∀ n, A → Label n) (n t : ℕ) : ℕ := refinementCount (sourcePrefixCounts (fun a => t * counts a) labels) n def stageNodeCounts (counts : A → ℕ) (labels : ∀ n, A → Label n) (n : ℕ) (r : LabelRecord Label n) (s : Label n) : ℕ := sourcePrefixCounts counts labels (n + 1) (r, s) theorem stageRefinementCount_eq_nodeProduct (counts : A → ℕ) (labels : ∀ n, A → Label n) (n t : ℕ) : stageRefinementCount counts labels n t = pairingProduct (stageNodeCounts counts labels n) t := by unfold stageRefinementCount refinementCount pairingProduct apply Finset.prod_congr rfl intro r hr change Nat.multinomial Finset.univ (fun s : Label n => sourcePrefixCounts (fun a => t * counts a) labels (n + 1) (r, s)) = Nat.multinomial Finset.univ (fun s : Label n => t * sourcePrefixCounts counts labels (n + 1) (r, s)) apply Nat.multinomial_congr intro s hs exact sourcePrefixCounts_mul counts labels t (n + 1) (r, s) theorem stageRefinementCount_eq_sourcePoolProduct (counts : A → ℕ) (labels : ∀ n, A → Label n) (depth : ℕ) (n : Fin depth) (t : ℕ) : stageRefinementCount counts labels n.val t = ∏ r : LabelRecord Label n.val, poolTypeCount (sourcePoolCounts counts labels depth) ⟨n, r⟩ t := stageRefinementCount_eq_nodeProduct counts labels n.val t theorem stageRefinementCount_pos (counts : A → ℕ) (labels : ∀ n, A → Label n) (n t : ℕ) : 0 < stageRefinementCount counts labels n t := by unfold stageRefinementCount refinementCount exact Finset.prod_pos (fun r _ => Nat.multinomial_pos _ _) theorem stageConditionalWords_card {Position : Type*} [Fintype Position] (counts : A → ℕ) (labels : ∀ n, A → Label n) (n t : ℕ) (w : Position → LabelRecord Label n) (hword : ∀ r, wordPopulation w r = sourcePrefixCounts (fun a => t * counts a) labels n r) : Fintype.card (ConditionalWords w (fun r s => sourcePrefixCounts (fun a => t * counts a) labels (n + 1) (r, s))) = stageRefinementCount counts labels n t := by exact conditionalWords_card w (fun r s => sourcePrefixCounts (fun a => t * counts a) labels (n + 1) (r, s)) (fun r => (hword r).trans (sourcePrefixCounts_compatible (fun a => t * counts a) labels n r)) theorem stageConditionalPool_card {Position : Type*} [Fintype Position] (counts : A → ℕ) (labels : ∀ n, A → Label n) (n t : ℕ) (w : Position → LabelRecord Label n) (hword : ∀ r, wordPopulation w r = sourcePrefixCounts (fun a => t * counts a) labels n r) : (Finset.univ.filter (fun fine : Position → Label n => ∀ r s, Fintype.card {i // w i = r ∧ fine i = s} = sourcePrefixCounts (fun a => t * counts a) labels (n + 1) (r, s))).card = stageRefinementCount counts labels n t := by simpa only [ConditionalWords, Fintype.card_subtype] using stageConditionalWords_card counts labels n t w hword theorem stageConditionalWords_nonempty {Position : Type*} [Fintype Position] (counts : A → ℕ) (labels : ∀ n, A → Label n) (n t : ℕ) (w : Position → LabelRecord Label n) (hword : ∀ r, wordPopulation w r = sourcePrefixCounts (fun a => t * counts a) labels n r) : Nonempty (ConditionalWords w (fun r s => sourcePrefixCounts (fun a => t * counts a) labels (n + 1) (r, s))) := by apply Fintype.card_pos_iff.mp rw [stageConditionalWords_card counts labels n t w hword] exact stageRefinementCount_pos counts labels n t def stageEntropyRate (counts : A → ℕ) (labels : ∀ n, A → Label n) (n : ℕ) : ℝ := poolEntropyTotal (stageNodeCounts counts labels n) theorem stageEntropyRate_nonneg (counts : A → ℕ) (labels : ∀ n, A → Label n) (n : ℕ) : 0 ≤ stageEntropyRate counts labels n := by exact Finset.sum_nonneg (fun r _ => populationEntropyRate_nonneg (stageNodeCounts counts labels n r)) theorem tendsto_log_stageRefinementCount_div (counts : A → ℕ) (labels : ∀ n, A → Label n) (n : ℕ) : Tendsto (fun t : ℕ => Real.log (stageRefinementCount counts labels n t : ℝ) / (t : ℝ)) atTop (𝓝 (stageEntropyRate counts labels n)) := by simpa only [stageRefinementCount_eq_nodeProduct, stageEntropyRate] using tendsto_log_pairingProduct_div (stageNodeCounts counts labels n) def stageCost (counts : A → ℕ) (labels : ∀ n, A → Label n) (n t : ℕ) : ℕ := LabelHierarchySeparation.poolAuxiliaryCost (stageRefinementCount counts labels n t) theorem tendsto_log_stageCost_div (counts : A → ℕ) (labels : ∀ n, A → Label n) (n : ℕ) : Tendsto (fun t : ℕ => Real.log (stageCost counts labels n t : ℝ) / (t : ℝ)) atTop (𝓝 (stageEntropyRate counts labels n)) := LabelHierarchySeparation.tendsto_log_poolAuxiliaryCost_div_nat (stageRefinementCount_pos counts labels n) (stageEntropyRate_nonneg counts labels n) (tendsto_log_stageRefinementCount_div counts labels n) def stagePairingProduct (counts : A → ℕ) (labels : ∀ n, A → Label n) (depth t : ℕ) : ℕ := ∏ n : Fin depth, stageRefinementCount counts labels n.val t def stageAuxiliaryBudget (counts : A → ℕ) (labels : ∀ n, A → Label n) (depth t : ℕ) : ℕ := ∏ n : Fin depth, stageCost counts labels n.val t theorem stagePairingProduct_succ (counts : A → ℕ) (labels : ∀ n, A → Label n) (n t : ℕ) : stagePairingProduct counts labels (n + 1) t = stagePairingProduct counts labels n t * stageRefinementCount counts labels n t := by exact Fin.prod_univ_castSucc (fun i : Fin (n + 1) => stageRefinementCount counts labels i.val t) theorem stageAuxiliaryBudget_succ (counts : A → ℕ) (labels : ∀ n, A → Label n) (n t : ℕ) : stageAuxiliaryBudget counts labels (n + 1) t = stageAuxiliaryBudget counts labels n t * stageCost counts labels n t := by exact Fin.prod_univ_castSucc (fun i : Fin (n + 1) => stageCost counts labels i.val t) theorem stagePairingProduct_eq_exactWords_card (counts : A → ℕ) (labels : ∀ n, A → Label n) (depth : ℕ) (hinjective : Function.Injective (labelRecordOf labels depth)) (t : ℕ) : stagePairingProduct counts labels depth t = Fintype.card (ExactWords (fun a => t * counts a)) := by unfold stagePairingProduct stageRefinementCount rw [Fin.prod_univ_eq_prod_range] exact source_refinementCount_product_eq_exactWords_card (fun a => t * counts a) labels depth hinjective theorem stagePairingProduct_le_budget (counts : A → ℕ) (labels : ∀ n, A → Label n) (depth t : ℕ) : stagePairingProduct counts labels depth t ≤ stageAuxiliaryBudget counts labels depth t := by exact Finset.prod_le_prod (fun n _ => LabelHierarchySeparation.population_le_poolAuxiliaryCost (stageRefinementCount counts labels n.val t)) theorem stageAuxiliaryBudget_pos (counts : A → ℕ) (labels : ∀ n, A → Label n) (depth t : ℕ) : 0 < stageAuxiliaryBudget counts labels depth t := by exact Finset.prod_pos (fun n _ => LabelHierarchySeparation.poolAuxiliaryCost_pos (stageRefinementCount counts labels n.val t)) abbrev StageAuxiliaryCoordinates (counts : A → ℕ) (labels : ∀ n, A → Label n) (depth t : ℕ) := ∀ n : Fin depth, LabelHierarchySeparation.PoolAuxiliaryGroup (stageRefinementCount counts labels n.val t) local instance stageHierarchyAuxiliaryModulusNeZero (population : ℕ) : NeZero (4 * Separation.gridWidth population) := ⟨Nat.ne_of_gt (Nat.mul_pos (by decide) (lt_of_lt_of_le (by decide : 0 < 2) (Separation.gridWidth_ge_two population)))⟩ def stageAuxiliaryTensor (counts : A → ℕ) (labels : ∀ n, A → Label n) (depth t : ℕ) : Tensor ℂ (StageAuxiliaryCoordinates counts labels depth t) (StageAuxiliaryCoordinates counts labels depth t) (StageAuxiliaryCoordinates counts labels depth t) := LabelHierarchySeparation.bankTensor (fun n : Fin depth => LabelHierarchySeparation.poolAuxiliaryTensor (stageRefinementCount counts labels n.val t)) theorem stageAuxiliaryTensor_rankAtMost (counts : A → ℕ) (labels : ∀ n, A → Label n) (depth t : ℕ) : Tensor.RankAtMost (stageAuxiliaryTensor counts labels depth t) (stageAuxiliaryBudget counts labels depth t) := by exact LabelHierarchySeparation.bankTensor_rankAtMost (fun n : Fin depth => LabelHierarchySeparation.poolAuxiliaryTensor (stageRefinementCount counts labels n.val t)) (fun n => stageCost counts labels n.val t) (fun n => LabelHierarchySeparation.poolAuxiliaryTensor_rankAtMost (stageRefinementCount counts labels n.val t)) theorem stageAuxiliaryTensor_borderRankAtMost (counts : A → ℕ) (labels : ∀ n, A → Label n) (depth t : ℕ) : Tensor.BorderRankAtMost (stageAuxiliaryTensor counts labels depth t) (stageAuxiliaryBudget counts labels depth t) := (stageAuxiliaryTensor_rankAtMost counts labels depth t).borderRankAtMost abbrev StagePairingCoordinates (counts : A → ℕ) (labels : ∀ n, A → Label n) (depth t : ℕ) := ∀ n : Fin depth, Fin (stageRefinementCount counts labels n.val t) theorem card_stagePairingCoordinates (counts : A → ℕ) (labels : ∀ n, A → Label n) (depth t : ℕ) : Fintype.card (StagePairingCoordinates counts labels depth t) = stagePairingProduct counts labels depth t := by simp only [StagePairingCoordinates, Fintype.card_pi, Fintype.card_fin, stagePairingProduct] theorem sum_stageEntropyRate_eq_nodeEntropyTotal (counts : A → ℕ) (labels : ∀ n, A → Label n) (depth : ℕ) : (∑ n : Fin depth, stageEntropyRate counts labels n.val) = poolEntropyTotal (sourcePoolCounts counts labels depth) := by simp only [stageEntropyRate, poolEntropyTotal, Fintype.sum_sigma] apply Finset.sum_congr rfl intro n hn apply Finset.sum_congr rfl intro r hr rfl theorem sum_stageEntropyRate_eq_source (counts : A → ℕ) (labels : ∀ n, A → Label n) (depth : ℕ) (hinjective : Function.Injective (labelRecordOf labels depth)) : (∑ n : Fin depth, stageEntropyRate counts labels n.val) = populationEntropyRate counts := by rw [sum_stageEntropyRate_eq_nodeEntropyTotal] exact source_poolEntropyTotal_eq counts labels depth hinjective theorem tendsto_log_stageAuxiliaryBudget_div (counts : A → ℕ) (labels : ∀ n, A → Label n) (depth : ℕ) (hinjective : Function.Injective (labelRecordOf labels depth)) : Tendsto (fun t : ℕ => Real.log (stageAuxiliaryBudget counts labels depth t : ℝ) / (t : ℝ)) atTop (𝓝 (populationEntropyRate counts)) := by have h := Separation.tendsto_log_nat_prod_div_nat (I := Fin depth) Finset.univ (fun n _ t => LabelHierarchySeparation.poolAuxiliaryCost_pos (stageRefinementCount counts labels n.val t)) (fun n _ => tendsto_log_stageCost_div counts labels n.val) simpa only [stageAuxiliaryBudget, stageCost, sum_stageEntropyRate_eq_source counts labels depth hinjective] using h theorem tendsto_log_stagePairingProduct (counts : A → ℕ) (hD : 0 < ∑ a, counts a) (labels : ∀ n, A → Label n) (depth : ℕ) (hinjective : Function.Injective (labelRecordOf labels depth)) : Tendsto (fun t : ℕ => Real.log (stagePairingProduct counts labels depth t : ℝ) / ((t : ℝ) * (∑ a, counts a : ℕ))) atTop (𝓝 (finiteEntropy (fun a => (counts a : ℝ) / (∑ a, counts a : ℕ)))) := by simpa only [stagePairingProduct_eq_exactWords_card counts labels depth hinjective] using tendsto_log_exactWords_card_mul counts hD theorem tendsto_log_stageAuxiliaryBudget (counts : A → ℕ) (hD : 0 < ∑ a, counts a) (labels : ∀ n, A → Label n) (depth : ℕ) (hinjective : Function.Injective (labelRecordOf labels depth)) : Tendsto (fun t : ℕ => Real.log (stageAuxiliaryBudget counts labels depth t : ℝ) / ((t : ℝ) * (∑ a, counts a : ℕ))) atTop (𝓝 (finiteEntropy (fun a => (counts a : ℝ) / (∑ a, counts a : ℕ)))) := by have hD' : ((∑ a, counts a : ℕ) : ℝ) ≠ 0 := Nat.cast_ne_zero.mpr (Nat.ne_of_gt hD) have hmain : populationEntropyRate counts / (∑ a, counts a : ℕ) = finiteEntropy (fun a => (counts a : ℝ) / (∑ a, counts a : ℕ)) := by unfold populationEntropyRate exact mul_div_cancel_left₀ _ hD' simpa only [div_div, hmain] using (tendsto_log_stageAuxiliaryBudget_div counts labels depth hinjective).div_const ((∑ a, counts a : ℕ) : ℝ) theorem source_stage_resource_rates (counts : A → ℕ) (hD : 0 < ∑ a, counts a) (labels : ∀ n, A → Label n) (depth : ℕ) (hinjective : Function.Injective (labelRecordOf labels depth)) : (∀ t, Tensor.RankAtMost (stageAuxiliaryTensor counts labels depth t) (stageAuxiliaryBudget counts labels depth t)) ∧ (∀ t, stagePairingProduct counts labels depth t = Fintype.card (ExactWords (fun a => t * counts a))) ∧ (∀ t, stagePairingProduct counts labels depth t ≤ stageAuxiliaryBudget counts labels depth t) ∧ Tendsto (fun t : ℕ => Real.log (stagePairingProduct counts labels depth t : ℝ) / ((t : ℝ) * (∑ a, counts a : ℕ))) atTop (𝓝 (finiteEntropy (fun a => (counts a : ℝ) / (∑ a, counts a : ℕ)))) ∧ Tendsto (fun t : ℕ => Real.log (stageAuxiliaryBudget counts labels depth t : ℝ) / ((t : ℝ) * (∑ a, counts a : ℕ))) atTop (𝓝 (finiteEntropy (fun a => (counts a : ℝ) / (∑ a, counts a : ℕ)))) := ⟨stageAuxiliaryTensor_rankAtMost counts labels depth, stagePairingProduct_eq_exactWords_card counts labels depth hinjective, stagePairingProduct_le_budget counts labels depth, tendsto_log_stagePairingProduct counts hD labels depth hinjective, tendsto_log_stageAuxiliaryBudget counts hD labels depth hinjective⟩ end MatrixMultiplication.Foundation.StageHierarchyResources end end end MatrixAllFields namespace MatrixAllFields open scoped BigOperators Topology Polynomial section noncomputable section namespace MatrixMultiplication open MatrixMultiplication.Foundation Filter open scoped Topology BigOperators Classical inductive ReaderPair where | xy | xz | yz deriving DecidableEq instance : Fintype ReaderPair where elems := {.xy, .xz, .yz} complete pair := by cases pair <;> simp namespace ConditionalLabels universe u v section PairAccounting variable {I : Type u} [Fintype I] def pairingSize (population : I → ℕ) (reader : I → ReaderPair) (pair : ReaderPair) : ℕ := ∏ i, if reader i = pair then population i else 1 def pairingRate (rate : I → ℝ) (reader : I → ReaderPair) (pair : ReaderPair) : ℝ := ∑ i, if reader i = pair then rate i else 0 theorem pairingSize_pos (population : I → ℕ) (reader : I → ReaderPair) (pair : ReaderPair) (positive : ∀ i, 0 < population i) : 0 < pairingSize population reader pair := by apply Finset.prod_pos intro i _ split_ifs · exact positive i · exact Nat.zero_lt_one theorem pairingRate_nonneg (rate : I → ℝ) (reader : I → ReaderPair) (pair : ReaderPair) (nonneg : ∀ i, 0 ≤ rate i) : 0 ≤ pairingRate rate reader pair := by apply Finset.sum_nonneg intro i _ split_ifs · exact nonneg i · exact le_rfl theorem pairingSize_product (population : I → ℕ) (reader : I → ReaderPair) : pairingSize population reader .xy * pairingSize population reader .xz * pairingSize population reader .yz = ∏ i, population i := by simp only [pairingSize, ← Finset.prod_mul_distrib] apply Finset.prod_congr rfl intro i _ cases reader i <;> simp theorem pairingRate_sum (rate : I → ℝ) (reader : I → ReaderPair) : pairingRate rate reader .xy + pairingRate rate reader .xz + pairingRate rate reader .yz = ∑ i, rate i := by simp only [pairingRate, ← Finset.sum_add_distrib] apply Finset.sum_congr rfl intro i _ cases reader i <;> simp theorem tendsto_log_pairingSize (population : I → ℕ → ℕ) (rate : I → ℝ) (reader : I → ReaderPair) (pair : ReaderPair) (positive : ∀ i n, 0 < population i n) (growth : ∀ i, Tendsto (fun n => Real.log (population i n : ℝ) / (n : ℝ)) atTop (𝓝 (rate i))) : Tendsto (fun n => Real.log (pairingSize (fun i => population i n) reader pair : ℝ) / (n : ℝ)) atTop (𝓝 (pairingRate rate reader pair)) := by apply Separation.tendsto_log_nat_prod_div_nat Finset.univ · intro i _ n split_ifs · exact positive i n · exact Nat.zero_lt_one · intro i _ by_cases h : reader i = pair · simpa only [h, ite_true] using growth i · simpa only [h, ite_false, Nat.cast_one, Real.log_one, zero_div] using (tendsto_const_nhds : Tendsto (fun _ : ℕ => (0 : ℝ)) atTop (𝓝 0)) end PairAccounting section SourceHierarchy variable {A : Type u} [Fintype A] {Label : ℕ → Type v} [∀ n, Fintype (Label n)] open StageHierarchyResources HierarchySeparationRates def stagePairingSize (counts : A → ℕ) (labels : ∀ n, A → Label n) (depth : ℕ) (reader : Fin depth → ReaderPair) (pair : ReaderPair) (t : ℕ) : ℕ := pairingSize (fun n : Fin depth => stageRefinementCount counts labels n.val t) reader pair def stagePairingRate (counts : A → ℕ) (labels : ∀ n, A → Label n) (depth : ℕ) (reader : Fin depth → ReaderPair) (pair : ReaderPair) : ℝ := pairingRate (fun n : Fin depth => stageEntropyRate counts labels n.val) reader pair theorem stagePairingSize_product (counts : A → ℕ) (labels : ∀ n, A → Label n) (depth : ℕ) (reader : Fin depth → ReaderPair) (complete : Function.Injective (labelRecordOf labels depth)) (t : ℕ) : stagePairingSize counts labels depth reader .xy t * stagePairingSize counts labels depth reader .xz t * stagePairingSize counts labels depth reader .yz t = Fintype.card (ExactWords (fun a => t * counts a)) := by rw [stagePairingSize, stagePairingSize, stagePairingSize, pairingSize_product] exact stagePairingProduct_eq_exactWords_card counts labels depth complete t theorem stagePairingRate_sum (counts : A → ℕ) (labels : ∀ n, A → Label n) (depth : ℕ) (reader : Fin depth → ReaderPair) (complete : Function.Injective (labelRecordOf labels depth)) : stagePairingRate counts labels depth reader .xy + stagePairingRate counts labels depth reader .xz + stagePairingRate counts labels depth reader .yz = populationEntropyRate counts := by rw [stagePairingRate, stagePairingRate, stagePairingRate, pairingRate_sum] exact sum_stageEntropyRate_eq_source counts labels depth complete theorem tendsto_log_stagePairingSize (counts : A → ℕ) (labels : ∀ n, A → Label n) (depth : ℕ) (reader : Fin depth → ReaderPair) (pair : ReaderPair) : Tendsto (fun t => Real.log (stagePairingSize counts labels depth reader pair t : ℝ) / (t : ℝ)) atTop (𝓝 (stagePairingRate counts labels depth reader pair)) := by exact tendsto_log_pairingSize _ _ reader pair (fun n => stageRefinementCount_pos counts labels n.val) (fun n => tendsto_log_stageRefinementCount_div counts labels n.val) theorem tendsto_log_stagePairingSize_normalized (counts : A → ℕ) (labels : ∀ n, A → Label n) (depth : ℕ) (reader : Fin depth → ReaderPair) (pair : ReaderPair) : Tendsto (fun t => Real.log (stagePairingSize counts labels depth reader pair t : ℝ) / ((t : ℝ) * (∑ a, counts a : ℕ))) atTop (𝓝 (stagePairingRate counts labels depth reader pair / (∑ a, counts a : ℕ))) := by simpa only [div_div] using (tendsto_log_stagePairingSize counts labels depth reader pair).div_const ((∑ a, counts a : ℕ) : ℝ) theorem auxiliary_overhead_tendsto_zero (counts : A → ℕ) (hD : 0 < ∑ a, counts a) (labels : ∀ n, A → Label n) (depth : ℕ) (complete : Function.Injective (labelRecordOf labels depth)) : Tendsto (fun t => (Real.log (stageAuxiliaryBudget counts labels depth t : ℝ) - Real.log (Fintype.card (ExactWords (fun a => t * counts a)) : ℝ)) / ((t : ℝ) * (∑ a, counts a : ℕ))) atTop (𝓝 0) := by have h := (tendsto_log_stageAuxiliaryBudget counts hD labels depth complete).sub (tendsto_log_exactWords_card_mul counts hD) simpa only [sub_self, sub_div] using h theorem auxiliary_overhead_nonneg (counts : A → ℕ) (labels : ∀ n, A → Label n) (depth : ℕ) (complete : Function.Injective (labelRecordOf labels depth)) (t : ℕ) : 0 ≤ Real.log (stageAuxiliaryBudget counts labels depth t : ℝ) - Real.log (Fintype.card (ExactWords (fun a => t * counts a)) : ℝ) := by apply sub_nonneg.mpr rw [← stagePairingProduct_eq_exactWords_card counts labels depth complete t] apply Real.log_le_log · apply Nat.cast_pos.mpr exact Finset.prod_pos (fun n _ => stageRefinementCount_pos counts labels n.val t) · exact_mod_cast stagePairingProduct_le_budget counts labels depth t theorem charged_cost_tendsto (counts : A → ℕ) (hD : 0 < ∑ a, counts a) (labels : ∀ n, A → Label n) (depth : ℕ) (complete : Function.Injective (labelRecordOf labels depth)) (C : ℝ) : Tendsto (fun t => C + (Real.log (stageAuxiliaryBudget counts labels depth t : ℝ) - Real.log (Fintype.card (ExactWords (fun a => t * counts a)) : ℝ)) / ((t : ℝ) * (∑ a, counts a : ℕ))) atTop (𝓝 C) := by simpa only [add_zero] using (auxiliary_overhead_tendsto_zero counts hD labels depth complete).const_add C theorem limit_le_source_cost (counts : A → ℕ) (hD : 0 < ∑ a, counts a) (labels : ∀ n, A → Label n) (depth : ℕ) (complete : Function.Injective (labelRecordOf labels depth)) {value : ℕ → ℝ} {rate C : ℝ} (limit : Tendsto value atTop (𝓝 rate)) (finite_bound : ∀ᶠ t in atTop, value t ≤ C + (Real.log (stageAuxiliaryBudget counts labels depth t : ℝ) - Real.log (Fintype.card (ExactWords (fun a => t * counts a)) : ℝ)) / ((t : ℝ) * (∑ a, counts a : ℕ))) : rate ≤ C := le_of_tendsto_of_tendsto limit (charged_cost_tendsto counts hD labels depth complete C) finite_bound def lawPairingRate (p : FiniteLaw A) (labels : ∀ n, A → Label n) (depth : ℕ) (reader : Fin depth → ReaderPair) (pair : ReaderPair) : ℝ := pairingRate (fun n : Fin depth => (FiniteLabelHierarchy.ofLawLabels p labels depth).refinementEntropy n.val) reader pair theorem lawPairingRate_sum (p : FiniteLaw A) (labels : ∀ n, A → Label n) (depth : ℕ) (reader : Fin depth → ReaderPair) (complete : Function.Injective (labelRecordOf labels depth)) : lawPairingRate p labels depth reader .xy + lawPairingRate p labels depth reader .xz + lawPairingRate p labels depth reader .yz = finiteEntropy p.mass := by rw [lawPairingRate, lawPairingRate, lawPairingRate, pairingRate_sum, Fin.sum_univ_eq_sum_range] exact FiniteLabelHierarchy.ofLawLabels_refinementEntropy_sum p labels depth complete theorem incident_rate_eq_prefix_entropy (p : FiniteLaw A) (labels : ∀ n, A → Label n) (depth cut : ℕ) (hcut : cut ≤ depth) (reader : Fin depth → ReaderPair) (incident_prefix : ∀ n : Fin depth, (reader n = .xy ∨ reader n = .xz) ↔ n.val < cut) : lawPairingRate p labels depth reader .xy + lawPairingRate p labels depth reader .xz = finiteEntropy (p.map (labelRecordOf labels cut)).mass := by let hierarchy := FiniteLabelHierarchy.ofLawLabels p labels depth have hterms : ∀ n : Fin depth, (if reader n = .xy then hierarchy.refinementEntropy n.val else 0) + (if reader n = .xz then hierarchy.refinementEntropy n.val else 0) = if n.val < cut then hierarchy.refinementEntropy n.val else 0 := by intro n cases hr : reader n with | xy => have hn := (incident_prefix n).mp (Or.inl hr) simp [hn] | xz => have hn := (incident_prefix n).mp (Or.inr hr) simp [hn] | yz => have hn : ¬n.val < cut := by intro h rcases (incident_prefix n).mpr h with h | h <;> simp [hr] at h simp [hn] have hfilter : (Finset.range depth).filter (fun n => n < cut) = Finset.range cut := by ext n simp only [Finset.mem_filter, Finset.mem_range] omega calc lawPairingRate p labels depth reader .xy + lawPairingRate p labels depth reader .xz = ∑ n : Fin depth, if n.val < cut then hierarchy.refinementEntropy n.val else 0 := by simp only [lawPairingRate, pairingRate, ← Finset.sum_add_distrib] exact Finset.sum_congr rfl (fun n _ => hterms n) _ = ∑ n ∈ Finset.range cut, hierarchy.refinementEntropy n := by rw [show (∑ n : Fin depth, if n.val < cut then hierarchy.refinementEntropy n.val else 0) = ∑ n ∈ Finset.range depth, if n < cut then hierarchy.refinementEntropy n else 0 from Fin.sum_univ_eq_sum_range (fun n => if n < cut then hierarchy.refinementEntropy n else 0) depth] rw [← Finset.sum_filter, hfilter] _ = finiteEntropy (hierarchy.prefixLaw cut hcut).mass := (hierarchy.prefixLaw_entropy cut hcut).symm _ = finiteEntropy (p.map (labelRecordOf labels cut)).mass := by rw [FiniteLabelHierarchy.ofLawLabels_prefixLaw_mass] theorem remaining_rate_eq_entropy_sub_prefix (p : FiniteLaw A) (labels : ∀ n, A → Label n) (depth cut : ℕ) (hcut : cut ≤ depth) (reader : Fin depth → ReaderPair) (incident_prefix : ∀ n : Fin depth, (reader n = .xy ∨ reader n = .xz) ↔ n.val < cut) (complete : Function.Injective (labelRecordOf labels depth)) : lawPairingRate p labels depth reader .yz = finiteEntropy p.mass - finiteEntropy (p.map (labelRecordOf labels cut)).mass := by have hsum := lawPairingRate_sum p labels depth reader complete have hprefix := incident_rate_eq_prefix_entropy p labels depth cut hcut reader incident_prefix linarith end SourceHierarchy end ConditionalLabels end MatrixMultiplication end end end MatrixAllFields end OAI