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Add lean source and binary files (part 84)
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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