import Mathlib import OAI.Combinatorics.KServer.AllocationBudget namespace OAI /- Persistent heavy-slot size tracking filters tangents before adaptive refresh. -/ noncomputable section open scoped BigOperators open Set Finset namespace KServer.KeySizeTracking def tangent (u s : ℝ) : ℝ := u - (1 + Real.log u) * s def entropy (u s : ℝ) : ℝ := s * Real.log (s / u) - s + u lemma tangent_credit {u s : ℝ} (hu : 0 < u) (hs : 0 < s) : tangent u s - tangent s s = entropy u s := by rw [entropy, Real.log_div hs.ne' hu.ne'] unfold tangent ring lemma lower_ratio {x : ℝ} (hx : 0 < x) (hx1 : x ≤ 1) : (x - 1)^2 / 2 ≤ x * Real.log x - x + 1 := by let f : ℝ → ℝ := fun y => (y-1)^2/2 - (y*Real.log y-y+1) have hd (y : ℝ) (hy : 0 < y) : HasDerivAt f (y-1-Real.log y) y := by have h := (((hasDerivAt_id y).sub_const 1).pow 2).div_const 2 have h' := (((hasDerivAt_id y).mul (Real.hasDerivAt_log hy.ne')).sub (hasDerivAt_id y)).add_const 1 convert h.sub h' using 1 <;> first | rfl | (norm_num [id_eq]; field_simp [hy.ne']; ring) have hm : MonotoneOn f (Icc x 1) := by apply monotoneOn_of_hasDerivWithinAt_nonneg (convex_Icc x 1) · intro y hy exact (hd y (hx.trans_le hy.1)).continuousAt.continuousWithinAt · intro y hy exact (hd y (hx.trans_le (interior_subset hy).1)).hasDerivWithinAt · intro y hy have h := Real.log_le_sub_one_of_pos (hx.trans_le (interior_subset hy).1) linarith have h := hm ⟨le_rfl,hx1⟩ ⟨hx1,le_rfl⟩ hx1 dsimp [f] at h norm_num at h linarith lemma upper_ratio {x : ℝ} (hx : 1 ≤ x) : (x - 1)^2 / (2*x) ≤ x * Real.log x - x + 1 := by let f : ℝ → ℝ := fun y => y*Real.log y-y+1 - (y-1)^2/(2*y) have hd (y : ℝ) (hy : 0 < y) : HasDerivAt f (Real.log y - (1-y⁻¹^2)/2) y := by have h := (((hasDerivAt_id y).mul (Real.hasDerivAt_log hy.ne')).sub (hasDerivAt_id y)).add_const 1 have h' := (((hasDerivAt_id y).sub_const 1).pow 2).div ((hasDerivAt_id y).const_mul 2) (by positivity : 2*y ≠ 0) convert h.sub h' using 1 <;> first | rfl | (norm_num [id_eq]; field_simp [hy.ne']; ring) have hm : MonotoneOn f (Icc 1 x) := by apply monotoneOn_of_hasDerivWithinAt_nonneg (convex_Icc 1 x) · intro y hy exact (hd y (by linarith [hy.1])).continuousAt.continuousWithinAt · intro y hy exact (hd y (by linarith [(interior_subset hy).1])).hasDerivWithinAt · intro y hy have hp : 0 < y := by linarith [(interior_subset hy).1] have h := Real.one_sub_inv_le_log_of_pos hp nlinarith [sq_nonneg (1-y⁻¹)] have h := hm ⟨le_rfl,hx⟩ ⟨hx,le_rfl⟩ hx dsimp [f] at h norm_num at h linarith lemma entropy_quadratic {u s : ℝ} (hu : 0 < u) (hs : 0 < s) : (s-u)^2 / (2*max s u) ≤ entropy u s := by have hx : 0 < s/u := div_pos hs hu have he : entropy u s = u*((s/u)*Real.log (s/u)-s/u+1) := by unfold entropy field_simp rw [he] rcases le_total s u with hsu | hus · rw [max_eq_right hsu] have h := mul_le_mul_of_nonneg_left (lower_ratio hx ((div_le_one hu).mpr hsu)) hu.le convert h using 1; first | rfl | field_simp · rw [max_eq_left hus] have h := mul_le_mul_of_nonneg_left (upper_ratio ((one_le_div hu).mpr hus)) hu.le convert h using 1; first | rfl | field_simp lemma relative_credit {u s : ℝ} (hu : 0 < u) (hs : 0 < s) (hfail : s < (5/6:ℝ)*u ∨ (6/5:ℝ)*u < s) : (s+u)/144 ≤ tangent u s-tangent s s := by rw [tangent_credit hu hs] have hq := entropy_quadratic hu hs have hm : 0 < max s u := lt_of_lt_of_le hs (le_max_left _ _) have hgap : (max s u / 6)^2 ≤ (s-u)^2 := by rcases hfail with h | h · have hsu : s ≤ u := by linarith rw [max_eq_right hsu] nlinarith · have hus : u ≤ s := by linarith rw [max_eq_left hus] nlinarith have hsum : s+u ≤ 2*max s u := by linarith [le_max_left s u,le_max_right s u] have hh : (s+u)/144 ≤ (s-u)^2/(2*max s u) := by apply (le_div_iff₀ (by positivity)).mpr nlinarith [mul_le_mul_of_nonneg_right hsum hm.le] exact hh.trans hq variable {Ω : Type} [Fintype Ω] def avg (w : Ω → ℝ) (f : Ω → ℝ) : ℝ := ∑ ω, w ω*f ω lemma avg_add (w f g : Ω → ℝ) : avg w (fun ω => f ω+g ω)=avg w f+avg w g := by simp [avg,mul_add,sum_add_distrib] lemma avg_sub (w f g : Ω → ℝ) : avg w (fun ω => f ω-g ω)=avg w f-avg w g := by simp [avg,mul_sub,sum_sub_distrib] lemma avg_mul (w f : Ω → ℝ) (c : ℝ) : avg w (fun ω => c*f ω)=c*avg w f := by simp only [avg,mul_sum,mul_left_comm (w _) c] lemma avg_sum (w : Ω → ℝ) {ι : Type} [Fintype ι] (f : ι → Ω → ℝ) : avg w (fun ω => ∑ i, f i ω)=∑ i, avg w (f i) := by simp only [avg,mul_sum]; rw [sum_comm] lemma avg_mono {w f g : Ω → ℝ} (hw : ∀ ω, 0 ≤ w ω) (h : ∀ ω, f ω ≤ g ω) : avg w f ≤ avg w g := sum_le_sum fun ω _ => mul_le_mul_of_nonneg_left (h ω) (hw ω) lemma avg_const (w : Ω → ℝ) (hw : ∑ ω, w ω=1) (c : ℝ) : avg w (fun _ => c)=c := by simp [avg,←sum_mul,hw] def Adapted (H : Ω → ℕ) (f : Ω → ℝ) : Prop := ∀ ω ω', H ω=H ω' → f ω=f ω' lemma fiber_weighted_zero (H : Ω → ℕ) (f g : Ω → ℝ) (hf : Adapted H f) (hg : ∀ h, ∑ ω ∈ Finset.univ.filter (fun ω => H ω=h), g ω=0) : ∑ ω, f ω*g ω=0 := by classical let c : ℕ → ℝ := fun h => if hh : ∃ ω, H ω=h then f hh.choose else 0 have hc : ∀ ω, f ω=c (H ω) := by intro ω dsimp [c] rw [dite_eq_left ⟨ω,rfl⟩] exact hf ω _ (Exists.choose_spec (show ∃ ω', H ω'=H ω from ⟨ω,rfl⟩)).symm have hs : (∑ ω, f ω*g ω) = ∑ h ∈ Finset.univ.image H, ∑ ω ∈ Finset.univ.filter (fun ω => H ω=h), f ω*g ω := by symm exact Finset.sum_fiberwise_of_maps_to (by intro ω _; exact Finset.mem_image.mpr ⟨ω,Finset.mem_univ _,rfl⟩) _ rw [hs] apply sum_eq_zero intro h _ calc _ = c h*(∑ ω ∈ Finset.univ.filter (fun ω => H ω=h), g ω) := by rw [mul_sum] apply sum_congr rfl intro ω hω rw [hc ω,(Finset.mem_filter.mp hω).2] _ = 0 := by rw [hg,mul_zero] /-- Old and new membership counts shifted by one, with literal finite-fiber conditioning. There is no policy-existence or budget assumption in this data. -/ structure FilteredSizes (w : Ω → ℝ) (K : ℝ) where history : ℕ → Ω → ℕ refines : ∀ t ω ω', history (t+1) ω=history (t+1) ω' → history t ω=history t ω' s : ℕ → Ω → ℝ before : ℕ → Ω → ℝ range : ∀ t ω, s t ω ∈ Set.Icc 1 K before_range : ∀ t ω, before t ω ∈ Set.Icc 1 K adapted : ∀ t, Adapted (history t) (s t) filtering : ∀ t h, ∑ ω ∈ Finset.univ.filter (fun ω => history t ω=h), w ω*(before (t+1) ω-s t ω)=0 def refresh (s u : ℝ) : Prop := s < (5/6:ℝ)*u ∨ (6/5:ℝ)*u < s instance : DecidableRel refresh := Classical.decRel _ def held (s : ℕ → Ω → ℝ) : ℕ → Ω → ℝ | 0, ω => s 0 ω | t+1, ω => if refresh (s (t+1) ω) (held s t ω) then s (t+1) ω else held s t ω omit [Fintype Ω] in lemma held_range {s : ℕ → Ω → ℝ} {K : ℝ} (hs : ∀ t ω, s t ω ∈ Icc 1 K) : ∀ t ω, held s t ω ∈ Icc 1 K := by intro t induction t with | zero => exact hs 0 | succ t ih => intro ω; dsimp [held]; split_ifs <;> [exact hs _ _; exact ih ω] lemma held_adapted {w : Ω → ℝ} {K : ℝ} (R : FilteredSizes w K) : ∀ t, Adapted (R.history t) (held R.s t) := by intro t induction t with | zero => exact R.adapted 0 | succ t ih => intro ω ω' hh have hprev := ih ω ω' (R.refines t ω ω' hh) have hnow := R.adapted (t+1) ω ω' hh simp only [held,hnow,hprev] omit [Fintype Ω] in lemma held_accurate {s : ℕ → Ω → ℝ} (hs : ∀ t ω, 0 ≤ s t ω) (t : ℕ) (ω : Ω) : (5/6:ℝ)*held s t ω ≤ s t ω ∧ s t ω ≤ (6/5:ℝ)*held s t ω := by cases t with | zero => dsimp [held]; constructor <;> nlinarith [hs 0 ω] | succ t => dsimp [held] split_ifs with h · constructor <;> nlinarith [hs (t+1) ω] · simp only [refresh,not_or,not_lt] at h exact h lemma slope_bound {K u : ℝ} (hu : u ∈ Icc 1 K) : |-(1+Real.log u)| ≤ 1+Real.log K := by have hp : 0 < u := by linarith [hu.1] have hl := Real.log_nonneg hu.1 rw [abs_neg,abs_of_nonneg (by linarith : 0 ≤ 1+Real.log u)] linarith [Real.log_le_log hp hu.2] lemma tangent_bound {K u s : ℝ} (hu : u ∈ Icc 1 K) (hs : s ∈ Icc 1 K) : |tangent u s| ≤ K*(1+(1+Real.log K)) := by have hK : 1 ≤ K := hu.1.trans hu.2 have hu0 : 0 ≤ u := by linarith [hu.1] have hs0 : 0 ≤ s := by linarith [hs.1] have hL : 0 ≤ 1+Real.log K := by linarith [Real.log_nonneg hK] have h := slope_bound hu rw [abs_neg] at h calc |tangent u s| ≤ |u|+|(1+Real.log u)*s| := by simpa [tangent] using abs_sub_le u 0 ((1+Real.log u)*s) _ = u+|1+Real.log u| * s := by rw [abs_of_nonneg hu0,abs_mul,abs_of_nonneg hs0] _ ≤ K+(1+Real.log K)*K := add_le_add hu.2 (mul_le_mul h hs.2 hs0 hL) _ = _ := by ring def refreshCost (s : ℕ → Ω → ℝ) (t : ℕ) (ω : Ω) : ℝ := if refresh (s (t+1) ω) (held s t ω) then held s t ω+held s (t+1) ω else 0 omit [Fintype Ω] in lemma refresh_cost_step {s : ℕ → Ω → ℝ} {K : ℝ} (hs : ∀ t ω, s t ω ∈ Icc 1 K) (t : ℕ) (ω : Ω) : refreshCost s t ω /144 ≤ tangent (held s t ω) (s t ω)-tangent (held s (t+1) ω) (s (t+1) ω) + (-(1+Real.log (held s t ω)))*(s (t+1) ω-s t ω) := by have hp : 0 < held s t ω := by linarith [(held_range hs t ω).1] have hp' : 0 < s (t+1) ω := by linarith [(hs (t+1) ω).1] have he : tangent (held s t ω) (s t ω)-tangent (held s (t+1) ω) (s (t+1) ω) + (-(1+Real.log (held s t ω)))*(s (t+1) ω-s t ω) = tangent (held s t ω) (s (t+1) ω)-tangent (held s (t+1) ω) (s (t+1) ω) := by unfold tangent; ring rw [he] dsimp [refreshCost,held] split_ifs with h · simpa only [add_comm] using relative_credit hp hp' h · simp lemma filtering_zero {w : Ω → ℝ} {K : ℝ} (R : FilteredSizes w K) (t : ℕ) : avg w (fun ω => (-(1+Real.log (held R.s t ω)))*(R.before (t+1) ω-R.s t ω))=0 := by unfold avg simp_rw [mul_left_comm (w _) (-(1+Real.log (held R.s t _)))] apply fiber_weighted_zero (R.history t) _ _ _ (R.filtering t) intro ω ω' hh dsimp only rw [held_adapted R t ω ω' hh] lemma expected_refresh_step {w : Ω → ℝ} {K : ℝ} (hw : ∀ ω, 0 ≤ w ω) (R : FilteredSizes w K) (t : ℕ) : avg w (refreshCost R.s t)/144 ≤ avg w (fun ω => tangent (held R.s t ω) (R.s t ω))- avg w (fun ω => tangent (held R.s (t+1) ω) (R.s (t+1) ω))+ (1+Real.log K)*avg w (fun ω => |R.s (t+1) ω-R.before (t+1) ω|) := by have hs := avg_mono hw (refresh_cost_step R.range t) have he : avg w (fun ω => refreshCost R.s t ω/144)=avg w (refreshCost R.s t)/144 := by simp only [avg,←mul_div_assoc,Finset.sum_div] rw [he] at hs have hsplit : ∀ ω, (-(1+Real.log (held R.s t ω)))*(R.s (t+1) ω-R.s t ω) = (-(1+Real.log (held R.s t ω)))*(R.before (t+1) ω-R.s t ω)+ (-(1+Real.log (held R.s t ω)))*(R.s (t+1) ω-R.before (t+1) ω) := by intro ω; ring simp_rw [hsplit] at hs rw [avg_add,avg_sub,avg_add,filtering_zero,zero_add] at hs apply hs.trans apply add_le_add le_rfl rw [←avg_mul] apply avg_mono hw intro ω calc _ ≤ |(-(1+Real.log (held R.s t ω)))*(R.s (t+1) ω-R.before (t+1) ω)| := le_abs_self _ _ ≤ _ := by rw [abs_mul] exact mul_le_mul_of_nonneg_right (slope_bound (held_range R.range t ω)) (abs_nonneg _) /-- Size-refresh budget, before substituting the mapped-member transport bound. Crucially the constant is independent of the horizon. -/ theorem size_refresh_budget {w : Ω → ℝ} {K : ℝ} (hw : ∀ ω, 0 ≤ w ω) (hw1 : ∑ ω, w ω=1) (R : FilteredSizes w K) (N : ℕ) : ∑ t ∈ range N, avg w (refreshCost R.s t) ≤ 144*(1+Real.log K)*(∑ t ∈ range N, avg w (fun ω => |R.s (t+1) ω-R.before (t+1) ω|))+ 288*K*(1+(1+Real.log K)) := by let V : ℕ → ℝ := fun t => avg w (fun ω => tangent (held R.s t ω) (R.s t ω)) let B : ℝ := K*(1+(1+Real.log K)) have hV t : -B ≤ V t ∧ V t ≤ B := by have hb ω := abs_le.mp (tangent_bound (held_range R.range t ω) (R.range t ω)) constructor · have h := avg_mono hw (fun ω => (hb ω).1) simpa only [avg_const w hw1 (-(K*(1+(1+Real.log K))))] using h · have h := avg_mono hw (fun ω => (hb ω).2) simpa only [avg_const w hw1 (K*(1+(1+Real.log K)))] using h have hsum := sum_le_sum (s := range N) (fun t _ => expected_refresh_step hw R t) change (∑ t ∈ range N, avg w (refreshCost R.s t)/144) ≤ ∑ t ∈ range N, (V t-V (t+1)+(1+Real.log K)*avg w (fun ω => |R.s (t+1) ω-R.before (t+1) ω|)) at hsum rw [←sum_div,sum_add_distrib,Finset.sum_range_sub',←mul_sum] at hsum dsimp [B] at hV nlinarith [(hV 0).2,(hV N).1] end KServer.KeySizeTracking end /-! Persistent heavy-slot size tracking on the actual finite observation experiment. Raw counts can change with both the hidden trajectory and the adapted partition. No martingale identity is postulated. -/ noncomputable section open scoped BigOperators open Finset namespace KServer.PosteriorSizes open RankTracking PosteriorRanks attribute [local instance] Classical.propDecidable Classical.decEq variable {Ω:Type} [Fintype Ω] {w:Ω→ℝ} lemma bounded (hw:∀ ω,0≤w ω) (hwpos:∀ ω,0(hf ρ).1) ω,?_⟩ have h:=posterior_mono_fiber hw (H:=H) (g:=fun _=>K) ω (fun ρ _=>(hf ρ).2) rw [posterior_fiber_const ω (fun _ _=>rfl) (HierarchyCounts.positive_mass hw H ω (hwpos ω)).ne'] at h exact h def process (hw:∀ ω,0≤w ω) (hwpos:∀ ω,0 linarith [h.1,h.2] before_range:=by intro t ω; have h:=bounded hw hwpos (H t) (hN (t-1)) ω; constructor <;> linarith [h.1,h.2] adapted:=by intro t ω ρ he exact congrArg (1+·) (posterior_adapted w (H t) (N t) ω ρ he) filtering:=by intro t h simp only [Nat.add_sub_cancel,add_sub_add_left_eq_sub] exact filtered_fiber hw (H t) (H (t+1)) (hr t) (N t) h lemma process_drift (hw:∀ ω,0≤w ω) (hwpos:∀ ω,0|(process hw hwpos H hr N hN).s (t+1) ω- (process hw hwpos H hr N hN).before (t+1) ω|)≤ avg w (fun ω=>|N (t+1) ω-N t ω|):=by simp only [process,Nat.add_sub_cancel,add_sub_add_left_eq_sub] exact posterior_drift hw (H (t+1)) (N (t+1)) (N t) lemma refresh_budget (hw:∀ ω,0≤w ω) (hwpos:∀ ω,0|N (t+1) ω-N t ω|))+ 288*(K+1)*(1+(1+Real.log (K+1))):=by have h:=KeySizeTracking.size_refresh_budget hw hw1 (process hw hwpos H hr N hN) T have hm:=sum_le_sum (s:=range T) (fun t _=>process_drift hw hwpos H hr N hN t) have hp:0≤144*(1+Real.log (K+1)):=by have :=Real.log_nonneg (by linarith : 1≤K+1); positivity exact h.trans (add_le_add (mul_le_mul_of_nonneg_left hm hp) (le_refl _)) end KServer.PosteriorSizes end /-! Literal children and geometric edge weights of the retained complete prefix tree. These identify the numbered rounding tree without deleting empty words or changing its allocated coordinates. -/ noncomputable section open scoped BigOperators open Finset namespace KServer.PrefixTree attribute [local instance] Classical.propDecidable Classical.decEq variable (A:Type) [Fintype A] (L:ℕ) abbrev Child (v:Vertex A L):= {u:Vertex A L // u≠root A L ∧ parent A L u=v} omit [Fintype A] in lemma depth_zero_iff (v:Vertex A L):v.1.val=0 ↔ v=root A L:=by constructor · rintro h rcases v with ⟨j,f⟩ have hj:j=0:=Fin.ext h subst j congr exact funext (fun i=>Fin.elim0 i) · rintro rfl; rfl omit [Fintype A] in lemma parent_succ {d:ℕ} (hd:d+1x.1.val) u.property.2 simp only [parent,dite_eq_right (by omega : u.val.1.val≠0)] at he omega omit [Fintype A] in lemma child_last_lt {v:Vertex A L} (u:Child A L v):u.val.1.val-1(⟨⟨d+1,he⟩,f⟩:Vertex A L)) hg omit [Fintype A] in lemma no_child (v:Vertex A L) (h:v.1.val=L):IsEmpty (Child A L v):=by refine ⟨fun u=>?_⟩ have hd:=child_depth A L u have hu:=u.val.1.isLt omega def numberedChildEquiv (v:Fin (Fintype.card (Vertex A L))): (tree A L).Child v ≃ Child A L (numbering A L v) where toFun u:=⟨numbering A L u.val,by constructor · intro he apply u.property.1 apply (numbering A L).injective rw [he,numbering_zero] · have he:=congrArg (numbering A L) u.property.2 simpa only [tree,OrderIso.apply_symm_apply] using he⟩ invFun u:=⟨(numbering A L).symm u.val,by constructor · intro he apply u.property.1 have hh:=congrArg (numbering A L) he simpa only [OrderIso.apply_symm_apply,numbering_zero] using hh · change (numbering A L).symm (parent A L (numbering A L ((numbering A L).symm u.val)))=v rw [OrderIso.apply_symm_apply,u.property.2,OrderIso.symm_apply_apply]⟩ left_inv u:=by apply Subtype.ext; exact OrderIso.symm_apply_apply _ _ right_inv u:=by apply Subtype.ext; exact OrderIso.apply_symm_apply _ _ lemma children_sum (v:Fin (Fintype.card (Vertex A L))) (f:Vertex A L→ℝ) (h:(numbering A L v).1.valby change f (extend A L (numbering A L v) h a) = f (numbering A L ((numbering A L).symm (extend A L (numbering A L v) h a))) rw [OrderIso.apply_symm_apply]) lemma children_sum_leaf (v:Fin (Fintype.card (Vertex A L))) (f:Vertex A L→ℝ) (h:(numbering A L v).1.val=L): (∑ u:(tree A L).Child v,f (numbering A L u.val))=0:=by let: IsEmpty (Child A L (numbering A L v)):=no_child A L _ h let:IsEmpty ((tree A L).Child v):=Function.isEmpty (numberedChildEquiv A L v) exact sum_of_isEmpty _ def weight (R τ:ℝ) (v:Fin (Fintype.card (Vertex A L))):ℝ:= R/τ^(numbering A L v).1.val lemma weight_nonneg {R τ:ℝ} (hR:0≤R) (hτ:0≤τ) (v:Fin (Fintype.card (Vertex A L))): 0≤weight A L R τ v:=div_nonneg hR (pow_nonneg hτ _) lemma parent_weight {R τ:ℝ} (hτ:τ≠0) (v:Fin (Fintype.card (Vertex A L))) (hv:v≠0): weight A L R τ ((tree A L).parent v)=τ*weight A L R τ v:=by let hu:Child A L (numbering A L ((tree A L).parent v)):= numberedChildEquiv A L _ ⟨v,hv,rfl⟩ have he: (numbering A L v).1.val=(numbering A L ((tree A L).parent v)).1.val+1:= by simpa only [hu,numberedChildEquiv,Equiv.coe_fn_mk] using child_depth A L hu unfold weight rw [he,pow_succ] field_simp end KServer.PrefixTree end /-! Quotas and parks on the actual numbered complete-prefix tree, with their posterior support witnesses. Rounding.Tree and TreeRounding.Tree have the same parent data; the conversion below changes no vertex or quantity. -/ noncomputable section open scoped BigOperators open Finset namespace KServer.PrefixTree attribute [local instance] Classical.propDecidable Classical.decEq variable (A:Type) [Fintype A] (L:ℕ) def travelTree:Rounding.Tree (Fintype.card (Vertex A L)) where parent:=(tree A L).parent root:=(tree A L).root lower:=(tree A L).lower variable {Ω Y:Type} [Fintype Ω] [Fintype Y] {k:ℕ} {w:Ω→ℝ} variable (hw:∀ ω,0≤w ω) (H:ℕ→Ω→ℕ) variable (hr:∀ t ω ρ,H (t+1) ω=H (t+1) ρ→H t ω=H t ρ) variable (maps:ℕ→Ω→ℕ→Y→A) (q:ℕ→Ω→Fin k→Y) (hk:1≤(k:ℝ)) def Q (t:ℕ) (ω:Ω) (v:Fin (Fintype.card (Vertex A L))):ℝ:= HierarchicalQuota.quota hw H hr maps q hk (numbering A L v).1 (numbering A L v).2 t ω def region (t:ℕ) (ω:Ω) (v:Fin (Fintype.card (Vertex A L))):Finset Y:= univ.filter (HierarchyCounts.hit (maps t ω) (numbering A L v).2) omit [Fintype Y] in lemma Q_root (t:ℕ) (ω:Ω):Q A L hw H hr maps q hk t ω 0=k:=by exact congrArg (fun u:Vertex A L=>HierarchicalQuota.quota hw H hr maps q hk u.1.val u.2 t ω) (numbering_zero A L) omit [Fintype Y] in lemma Q_nonneg (hwpos:∀ ω,0HierarchicalQuota.quota hw H hr maps q hk u.1.val u.2 t ω) hv] exact HierarchicalQuota.children_budget hw H hr maps q hk hwpos (numbering A L v).2 t ω · have he:(numbering A L v).1.val=L:=by have :=(numbering A L v).1.isLt; omega unfold Q rw [children_sum_leaf A L v (fun u:Vertex A L=>HierarchicalQuota.quota hw H hr maps q hk u.1.val u.2 t ω) he] exact Q_nonneg A L hw H hr maps q hk hwpos t ω v omit [Fintype Y] in lemma Q_adapted (t:ℕ) (v:Fin (Fintype.card (Vertex A L))): RankTracking.Adapted (H t) (fun ω=>Q A L hw H hr maps q hk t ω v):=by intro ω ρ he exact HierarchicalQuota.quota_adapted hw H hr maps q hk _ _ t ω ρ he lemma Q_mass (hwpos:∀ ω,0Q_nonneg A L hw H hr maps q hk hwpos t ω u.val end KServer.PrefixTree namespace KServer.Rounding variable {n:ℕ} [NeZero n] lemma Tree.under_root (T:Tree n) (v:Fin n):T.under 0 v=true:=by by_cases hv:v=0 · subst v; exact T.under_self 0 · rw [Tree.under,ite_eq_right hv,dite_eq_right hv] exact T.under_root (T.parent v) termination_by v.val decreasing_by exact T.lower v hv lemma Tree.park_total (T:Tree n) (q:Fin n→ℝ):(∑ v,T.park q v)=q 0:=by have h:=T.park_subtree_total q 0 simpa only [Tree.indicator,T.under_root,↓reduceIte,one_mul] using h end KServer.Rounding end /-! Actual truncation ancestors of complete-prefix words, with the retained numbering used by the finite rounding tree. -/ noncomputable section open scoped BigOperators open Finset namespace KServer.PrefixTree attribute [local instance] Classical.propDecidable Classical.decEq variable (A:Type) [Fintype A] (L:ℕ) def take (v:Vertex A L) (d:ℕ) (hd:d≤v.1.val):Vertex A L:= ⟨⟨d,lt_of_le_of_lt hd v.1.isLt⟩,fun i=>v.2 ⟨i.val,lt_of_lt_of_le i.isLt hd⟩⟩ omit [Fintype A] in lemma take_self (v:Vertex A L):take A L v v.1.val le_rfl=v:=by rcases v with ⟨j,f⟩ rfl omit [Fintype A] in lemma parent_depth (v:Vertex A L) (hv:0exact False.elim (Nat.not_lt_zero _ hd) | succ e=>rfl omit [Fintype A] in lemma hit_take {Y:Type} (maps:ℕ→Y→A) (v:Vertex A L) (d:ℕ) (hd:d≤v.1.val) (y:Y) (hy:HierarchyCounts.hit maps v.2 y): HierarchyCounts.hit maps (take A L v d hd).2 y:=by intro i exact hy ⟨i.val,lt_of_lt_of_le i.isLt hd⟩ lemma numbering_parent (v:Fin (Fintype.card (Vertex A L))): numbering A L ((travelTree A L).parent v)=parent A L (numbering A L v):=by exact (numbering A L).apply_symm_apply _ lemma numbering_eq_root (v:Fin (Fintype.card (Vertex A L))): numbering A L v=root A L ↔ v=0:=by rw [←numbering_zero A L] exact (numbering A L).injective.eq_iff lemma take_under (v:Fin (Fintype.card (Vertex A L))) (d:ℕ) (hd:d≤(numbering A L v).1.val): (travelTree A L).under ((numbering A L).symm (take A L (numbering A L v) d hd)) v=true:=by by_cases he:d=(numbering A L v).1.val · subst d rw [take_self,OrderIso.symm_apply_apply] exact (travelTree A L).under_self v · have hlt:d<(numbering A L v).1.val:=by omega have hv:v≠0:=by intro he subst v rw [numbering_zero] at hlt exact Nat.not_lt_zero _ hlt have hne:v≠(numbering A L).symm (take A L (numbering A L v) d hd):=by intro hh have hhh:=congrArg (fun u=>(numbering A L u).1.val) hh rw [OrderIso.apply_symm_apply] at hhh exact he hhh.symm rw [Rounding.Tree.under,ite_eq_right hne,dite_eq_right hv] have hp:d≤(numbering A L ((travelTree A L).parent v)).1.val:=by rw [numbering_parent,parent_depth A L _ (by omega)] omega have ht:take A L (numbering A L ((travelTree A L).parent v)) d hp= take A L (numbering A L v) d hd:=by simpa only [numbering_parent] using take_parent A L (numbering A L v) hlt rw [←ht] exact take_under ((travelTree A L).parent v) d hp termination_by v.val decreasing_by exact (travelTree A L).lower v hv end KServer.PrefixTree end /-! Cumulative parked mass in the actual prefix cut is bounded by posterior mass of the 67-radius ball. Selection can depend on the completed state. -/ noncomputable section open scoped BigOperators open Finset namespace KServer.PrefixTree attribute [local instance] Classical.propDecidable Classical.decEq variable (A:Type) [Fintype A] (L:ℕ) omit [Fintype A] in lemma eq_of_common_hit {Y:Type} (maps:ℕ→Y→A) (u v:Vertex A L) (hd:u.1.val=v.1.val) (y:Y) (hu:HierarchyCounts.hit maps u.2 y) (hv:HierarchyCounts.hit maps v.2 y):u=v:=by rcases u with ⟨j,f⟩ rcases v with ⟨j',g⟩ have hj:j=j':=Fin.ext hd subst j' congr funext i exact (hu i).symm.trans (hv i) variable {Ω Y:Type} [Fintype Ω] [Fintype Y] [MetricSpace Y] {k:ℕ} {w:Ω→ℝ} variable (hw:∀ ω,0≤w ω) (H:ℕ→Ω→ℕ) variable (hr:∀ t ω ρ,H (t+1) ω=H (t+1) ρ→H t ω=H t ρ) variable (maps:ℕ→Ω→ℕ→Y→A) (q:ℕ→Ω→Fin k→Y) (hk:1≤(k:ℝ)) theorem park_ball_capacity (hwpos:∀ ω,0dist y z≤67*r)):=by let anc:S→Fin (Fintype.card (Vertex A L)):=fun u=> (numbering A L).symm (take A L (numbering A L u.val) d (hd u.val u.property)) let F:Finset (Fin (Fintype.card (Vertex A L))):=univ.image anc have hdepth:∀ v∈F,(numbering A L v).1.val=d:=by intro v hv obtain ⟨u,_,rfl⟩:=mem_image.mp hv simp only [anc,OrderIso.apply_symm_apply,take] have hcover:∀ u∈S,∃ v∈F,(travelTree A L).under v u=true:=by intro u hu refine ⟨anc ⟨u,hu⟩,mem_image.mpr ⟨⟨u,hu⟩,mem_univ _,rfl⟩,?_⟩ exact take_under A L u d (hd u hu) have hdisj:Set.PairwiseDisjoint (↑F) (region A L maps t ω):=by intro u hu v hv hne apply Finset.disjoint_left.mpr intro z hz hz' apply hne apply (numbering A L).injective exact eq_of_common_hit A L (maps t ω) _ _ ((hdepth u hu).trans (hdepth v hv).symm) z (mem_filter.mp hz).2 (mem_filter.mp hz').2 have hwitness:∀ v∈F,∃ z∈region A L maps t ω v,dist y z≤27*r:=by intro v hv obtain ⟨u,_,rfl⟩:=mem_image.mp hv obtain ⟨z,hz,hclose⟩:=hwit u.val u.property refine ⟨z,?_,hclose⟩ apply mem_filter.mpr refine ⟨mem_univ _,?_⟩ rw [show numbering A L (anc u)=take A L (numbering A L u.val) d (hd u.val u.property) from OrderIso.apply_symm_apply _ _] exact hit_take A L (maps t ω) _ d _ z (mem_filter.mp hz).2 exact (travelTree A L).geometric_park_capacity _ (park_nonneg A L hw H hr maps q hk hwpos t ω) S F hcover (region A L maps t ω) _ (PosteriorCounting.measure_nonneg hw (H t) (q t) ω) (by norm_num) y (fun v _=>Q_mass A L hw H hr maps q hk hwpos t ω hm v) hdisj hwitness (fun v hv=>hdiam v (hdepth v hv)) end KServer.PrefixTree end /-! Literal variation of all parks, including the root park, with the exact parent-edge factor. No metric or rounding movement estimate is assumed. -/ noncomputable section open scoped BigOperators open Finset namespace KServer.Rounding attribute [local instance] Classical.propDecidable Classical.decEq variable {n:ℕ} [NeZero n] lemma Tree.park_difference (T:Tree n) (q q':Fin n→ℝ) (v:Fin n): |T.park q' v-T.park q v|≤|q' v-q v|+∑ u:T.Child v,|q' u.val-q u.val|:=by have hh: T.park q' v-T.park q v=(q' v-q v)-∑ u:T.Child v,(q' u.val-q u.val):=by rw [sum_sub_distrib] unfold Tree.park ring rw [hh] exact (abs_sub _ _).trans (add_le_add (le_refl _) (abs_sum_le_sum_abs _ _)) lemma Tree.weighted_park_variation (T:Tree n) (q q' R:Fin n→ℝ) (hR:∀ v,0≤R v) (hroot:q' 0=q 0) {τ:ℝ} (hτ:0<τ) (hgeom:∀ v,v≠0→R (T.parent v)=τ*R v): (∑ v,R v*|T.park q' v-T.park q v|)≤ (1+1/τ)*(∑ v,R (T.parent v)*|q' v-q v|):=by let f:=fun v=>|q' v-q v| have hf:f 0=0:=by simp [f,hroot] have he:(∑ v,R v*f v)=(1/τ)*(∑ v,R (T.parent v)*f v):=by rw [mul_sum] apply sum_congr rfl intro v _ by_cases hv:v=0 · simp [hv,hf] · rw [hgeom v hv] field_simp have hb:=sum_le_sum (s:=univ) (fun v (_:v∈univ)=> mul_le_mul_of_nonneg_left (T.park_difference q q' v) (hR v)) simp only [mul_add,sum_add_distrib] at hb change _≤(∑ v,R v*f v)+(∑ v,R v*∑ u:T.Child v,f u.val) at hb rw [T.weighted_children R f hf,he] at hb convert hb using 1 ring end KServer.Rounding namespace KServer.PrefixTree attribute [local instance] Classical.propDecidable Classical.decEq variable (A:Type) [Fintype A] (L:ℕ) lemma sum_vertices (f:(d:ℕ)→(Fin d→A)→ℝ): (∑ v:Fin (Fintype.card (Vertex A L)),f (numbering A L v).1.val (numbering A L v).2)= ∑ d∈range (L+1),∑ word:Fin d→A,f d word:=by calc _ = ∑ u:Vertex A L,f u.1.val u.2:= Fintype.sum_equiv (numbering A L).toEquiv _ _ (fun _=>rfl) _ = (∑ d:Fin (L+1),∑ word:Fin d.val→A,f d.val word):=by rw [Fintype.sum_sigma] _ = _:=Fin.sum_univ_eq_sum_range (fun d=>∑ word:Fin d→A,f d word) (L+1) end KServer.PrefixTree end /-! Fixed last-key bands in the complete prefix tree. -/ noncomputable section open scoped BigOperators open Finset namespace KServer.PrefixTree attribute [local instance] Classical.propDecidable Classical.decEq variable (A:Type) [Fintype A] (L:ℕ) abbrev Node:=Fin (Fintype.card (Vertex A L)) def depth (v:Node A L):ℕ:=(numbering A L v).1.val def lastKey (v:Node A L):Option A:= if h:0depth A L v=d+1 ∧ lastKey A L v=some a) def bandMass (p:Node A L→ℝ) (d:ℕ) (a:A):ℝ:=∑ v∈band A L d a,p v lemma band_nonneg {p:Node A L→ℝ} (hp:∀ v,0≤p v) (d:ℕ) (a:A): 0≤bandMass A L p d a:=sum_nonneg (fun v _=>hp v) lemma band_key {Y:Type} (maps:ℕ→Y→A) (d:ℕ) (a:A) {v:Node A L} (hv:v∈band A L d a) (y:Y) (hy:HierarchyCounts.hit maps (numbering A L v).2 y): maps d y=a:=by obtain ⟨hd,ha⟩:=(mem_filter.mp hv).2 have hp:0univ.filter (HierarchyCounts.hit maps (numbering A L v).2)):=by intro u hu v hv hne apply Finset.disjoint_left.mpr intro z hz hz' apply hne apply (numbering A L).injective exact eq_of_common_hit A L maps _ _ ((band_depth A L d a hu).trans (band_depth A L d a hv).symm) z (mem_filter.mp hz).2 (mem_filter.mp hz').2 variable {Ω Y:Type} [Fintype Ω] [Fintype Y] [MetricSpace Y] {k:ℕ} {w:Ω→ℝ} variable (hw:∀ ω,0≤w ω) (H:ℕ→Ω→ℕ) variable (hr:∀ t ω ρ,H (t+1) ω=H (t+1) ρ→H t ω=H t ρ) variable (maps:ℕ→Ω→ℕ→Y→A) (q:ℕ→Ω→Fin k→Y) (hk:1≤(k:ℝ)) omit [MetricSpace Y] in lemma band_capacity (hwpos:∀ ω,0maps t ω d y=a)):=by have h:=sum_le_sum (s:=band A L d a) (fun v (_:v∈band A L d a)=> (park_le_Q A L hw H hr maps q hk hwpos t ω v).trans (Q_mass A L hw H hr maps q hk hwpos t ω hm v)) change bandMass A L _ d a≤∑ v∈band A L d a,72*Rounding.countingMass (PosteriorCounting.measure (w:=w) (H t) (q t) ω) (region A L maps t ω v) at h rw [←mul_sum] at h apply h.trans apply mul_le_mul_of_nonneg_left _ (by norm_num) apply Rounding.disjoint_counting_mass (PosteriorCounting.measure_nonneg hw (H t) (q t) ω) (band_disjoint A L (maps t ω) d a) intro v hv y hy exact mem_filter.mpr ⟨mem_univ _,band_key A L (maps t ω) d a hv y (mem_filter.mp hy).2⟩ end KServer.PrefixTree end /-! Literal all-key persistent size references on the adapted complete map. -/ noncomputable section open scoped BigOperators open Finset namespace KServer.KeyReferences open RankTracking PosteriorRanks attribute [local instance] Classical.propDecidable Classical.decEq variable {Ω A Y:Type} [Fintype Ω] [Fintype A] [Fintype Y] {k:ℕ} {w:Ω→ℝ} variable (H:ℕ→Ω→ℕ) (maps:ℕ→Ω→ℕ→Y→A) (q:ℕ→Ω→Fin k→Y) def count (d:ℕ) (a:A) (t:ℕ) (ω:Ω):ℝ:=∑ i:Fin k,if maps t ω d (q t ω i)=a then 1 else 0 omit [Fintype Ω] [Fintype A] [Fintype Y] in lemma count_range (d:ℕ) (a:A) (t:ℕ) (ω:Ω):count maps q d a t ω∈Set.Icc 0 (k:ℝ):=by constructor · exact sum_nonneg fun i _=>by split_ifs <;> norm_num · have hh:=sum_le_sum (s:=(univ:Finset (Fin k))) (f:=fun i=>if maps t ω d (q t ω i)=a then (1:ℝ) else 0) (g:=fun _=>(1:ℝ)) (fun i _=>by split_ifs <;> norm_num) simpa [count] using hh def size (d:ℕ) (a:A) (t:ℕ) (ω:Ω):ℝ:=1+posterior w (H t) (count maps q d a t) ω def reference (d:ℕ) (a:A):ℕ→Ω→ℝ:=KeySizeTracking.held (size (w:=w) H maps q d a) omit [Fintype A] in lemma mass_eq (d:ℕ) (a:A) (t:ℕ) (ω:Ω) (hm:∀ ρ,H t ρ=H t ω→maps t ρ=maps t ω): (∑ y∈univ.filter (fun y=>maps t ω d y=a),PosteriorCounting.measure (w:=w) (H t) (q t) ω y)= posterior w (H t) (count maps q d a t) ω:=by have he:=PosteriorCounting.conditional_integral (w:=w) (H t) (q t) ω (fun ρ y=>if maps t ρ d y=a then (1:ℝ) else 0) (fun ρ h=>by funext y; rw [hm ρ h]) unfold KeyReferences.count simpa only [sum_filter,mul_ite,mul_one,mul_zero] using he variable (hw:∀ ω,0≤w ω) (hwpos:∀ ω,0(by linarith [(size_range H maps q hw hwpos hr d a t ω).1])) t ω omit [Fintype A] [Fintype Y] in lemma reference_adapted (d:ℕ) (a:A) (t:ℕ):Adapted (H t) (reference (w:=w) H maps q d a t):= KeySizeTracking.held_adapted (process H maps q hw hwpos hr d a) t omit [Fintype A] [Fintype Y] in lemma refresh_budget (hw1:∑ ω,w ω=1) (d:ℕ) (a:A) (T:ℕ): (∑ t∈range T,avg w (KeySizeTracking.refreshCost (size (w:=w) H maps q d a) t))≤ 144*(1+Real.log ((k:ℝ)+1))*(∑ t∈range T,avg w (fun ω=>|count maps q d a (t+1) ω-count maps q d a t ω|))+ 288*((k:ℝ)+1)*(1+(1+Real.log ((k:ℝ)+1))):= PosteriorSizes.refresh_budget hw hwpos hw1 (Nat.cast_nonneg k) H hr (count maps q d a) (count_range maps q d a) T end KServer.KeyReferences end /- Height-independent scale-capacity estimates use summation by parts rather than dyadic grouping. -/ noncomputable section open scoped BigOperators open Finset namespace KServer.ParkedCoefficients def tail (b : ℕ → ℝ) (n i : ℕ) : ℝ := ∑ j ∈ Ico i n, b j lemma tail_zero (b : ℕ → ℝ) (n : ℕ) : tail b n n=0 := by simp [tail] lemma tail_step (b : ℕ → ℝ) {n i : ℕ} (hi : i < n) : tail b n i=b i+tail b n (i+1) := by unfold tail exact Finset.sum_eq_sum_Ico_succ_bot hi b lemma logarithmic_increment {a b : ℝ} (ha : 0 < a) (hab : a ≤ b) : (b-a)/b ≤ Real.log b-Real.log a := by have hb := ha.trans_le hab have h := Real.one_sub_inv_le_log_of_pos (div_pos hb ha) rw [Real.log_div hb.ne' ha.ne'] at h convert h using 1 field_simp lemma summation_by_parts (b A : ℕ → ℝ) (n : ℕ) : (∑ i ∈ range n, b i/A i) = tail b n 0/A 0 + ∑ i ∈ range n, tail b n (i+1)*(1/A (i+1)-1/A i) := by have hstep : ∀ i ∈ range n, b i/A i = tail b n i/A i-tail b n (i+1)/A (i+1)+ tail b n (i+1)*(1/A (i+1)-1/A i) := by intro i hi rw [tail_step b (mem_range.mp hi)] ring simp_rw [Finset.sum_congr rfl hstep, sum_add_distrib, Finset.sum_range_sub',tail_zero,zero_div,sub_zero] /-- Positive tail capacities control reciprocal-weighted mass logarithmically. The extra endpoint A n may be chosen as A (n-1), or any smaller positive value. -/ theorem capacity_log_sum {b A : ℕ → ℝ} {n : ℕ} {C K : ℝ} (hC : 0 ≤ C) (hA : ∀ i ≤ n, A i ∈ Set.Icc 1 K) (hdec : ∀ i < n, A (i+1) ≤ A i) (hcap : ∀ i ≤ n, tail b n i ≤ C*A i) : ∑ i ∈ range n, b i/A i ≤ C*(1+Real.log K) := by have hp i (hi : i ≤ n) : 0 < A i := by linarith [(hA i hi).1] have ht : ∀ i ∈ range n, tail b n (i+1)*(1/A (i+1)-1/A i) ≤ C*(Real.log (A i)-Real.log (A (i+1))) := by intro i hi have hin := mem_range.mp hi have h1 : 0 ≤ 1/A (i+1)-1/A i := sub_nonneg.mpr (one_div_le_one_div_of_le (hp (i+1) (by omega)) (hdec i hin)) calc _ ≤ C*A (i+1)*(1/A (i+1)-1/A i) := mul_le_mul_of_nonneg_right (hcap (i+1) (by omega)) h1 _ = C*((A i-A (i+1))/A i) := by field_simp [(hp i (by omega)).ne',(hp (i+1) (by omega)).ne'] _ ≤ _ := mul_le_mul_of_nonneg_left (logarithmic_increment (hp (i+1) (by omega)) (hdec i hin)) hC have h0 : tail b n 0/A 0 ≤ C := (div_le_iff₀ (hp 0 (by omega))).mpr (hcap 0 (by omega)) rw [summation_by_parts] have hs := sum_le_sum ht rw [←mul_sum,Finset.sum_range_sub'] at hs have hlog0 := Real.log_le_log (hp 0 (by omega)) (hA 0 (by omega)).2 have hlogn := Real.log_nonneg (hA n le_rfl).1 have hh := mul_le_mul_of_nonneg_left (show Real.log (A 0)-Real.log (A n) ≤ Real.log K by linarith) hC linarith lemma tail_mono {b c : ℕ → ℝ} {n i : ℕ} (h : ∀ j < n, b j ≤ c j) : tail b n i ≤ tail c n i := by apply sum_le_sum intro j hj exact h j (mem_Ico.mp hj).2 /-- Exact abstract form of §08's geometric estimate. b is selected parked mass, d its held key size, B=1+mass(B(y,r)), A=1+mass(B(y,67r)). The assumptions here are pointwise capacity data, not stochastic or policy-existence interfaces. -/ theorem park_coefficients {b d A B : ℕ → ℝ} {n : ℕ} {C K ρ R L : ℝ} (hC : 0 ≤ C) (hρ : 0 < ρ) (hR : 0 ≤ R) (hb : ∀ i < n, 0 ≤ b i) (hd : ∀ i < n, 0 < d i) (hA : ∀ i ≤ n, A i ∈ Set.Icc 1 K) (hB : ∀ i < n, B i ∈ Set.Icc 1 (A i)) (hdec : ∀ i < n, A (i+1) ≤ A i) (hcap : ∀ i ≤ n, tail b n i ≤ C*A i) (hnorm : ∀ i < n, B i ≤ ρ*d i) (hbound : ∀ i < n, b i/d i ≤ R) (hlog : ∑ i ∈ range n, Real.log (A i/B i) ≤ L) : ∑ i ∈ range n, b i/d i ≤ R*L/Real.log 2+2*ρ*C*(1+Real.log K) := by let good : ℕ → ℝ := fun i => if A i ≤ 2*B i then b i else 0 have hpA i (hi : i ≤ n) : 0 < A i := by linarith [(hA i hi).1] have hpB i (hi : i < n) : 0 < B i := by linarith [(hB i hi).1] have h2 : 0 < Real.log 2 := Real.log_pos (by norm_num) have hg : ∀ i < n, good i ≤ b i := by intro i hi; dsimp [good]; split_ifs <;> [rfl; exact hb i hi] have hgc := capacity_log_sum hC hA hdec (fun i hi => (tail_mono hg).trans (hcap i hi)) have hstep : ∀ i ∈ range n, b i/d i ≤ R/Real.log 2*Real.log (A i/B i)+2*ρ*(good i/A i) := by intro i hi have hin := mem_range.mp hi have hln : 0 ≤ Real.log (A i/B i) := Real.log_nonneg ((one_le_div (hpB i hin)).mpr (hB i hin).2) by_cases hh : A i ≤ 2*B i · have hrad : A i ≤ 2*ρ*d i := hh.trans (by nlinarith [hnorm i hin]) have hw : b i/d i ≤ 2*ρ*(b i/A i) := by apply (div_le_iff₀ (hd i hin)).mpr have hm := mul_le_mul_of_nonneg_left hrad (hb i hin) have he : 2*ρ*(b i/A i)*d i = (b i*(2*ρ*d i))/A i := by ring rw [he] apply (le_div_iff₀ (hpA i (by omega))).mpr simpa [mul_assoc] using hm dsimp only [good] rw [ite_eq_left hh] exact hw.trans (le_add_of_nonneg_left (mul_nonneg (div_nonneg hR h2.le) hln)) · have hratio : 2 ≤ A i/B i := (le_div_iff₀ (hpB i hin)).mpr (le_of_not_ge hh) have hln2 := Real.log_le_log (by norm_num : (0:ℝ) < 2) hratio have ht : R ≤ R/Real.log 2*Real.log (A i/B i) := by have h := mul_le_mul_of_nonneg_left hln2 (div_nonneg hR h2.le) simpa [div_mul_cancel₀ R h2.ne'] using h dsimp only [good] rw [ite_eq_right hh,zero_div,mul_zero,add_zero] exact (hbound i hin).trans ht have hs := sum_le_sum hstep rw [sum_add_distrib,←mul_sum,←mul_sum] at hs have hlu := mul_le_mul_of_nonneg_left hlog (div_nonneg hR h2.le) have hgu := mul_le_mul_of_nonneg_left hgc (by positivity : 0 ≤ 2*ρ) calc _ ≤ R/Real.log 2*L+2*ρ*(C*(1+Real.log K)) := hs.trans (add_le_add hlu hgu) _ = _ := by ring /-- The exact fixed-offset telescope; scales shorter than the offset are included. -/ lemma scale_log_telescope {A B : ℕ → ℝ} {n p : ℕ} {K : ℝ} (hK : 1 ≤ K) (hA : ∀ i < n, A i ∈ Set.Icc 1 K) (hB : ∀ i < n, B i ∈ Set.Icc 1 K) (hshift : ∀ i < n, p ≤ i → A i ≤ B (i-p)) : ∑ i ∈ range n, Real.log (A i/B i) ≤ (p:ℝ)*Real.log K := by have hlogK := Real.log_nonneg hK have hlogB : ∀ i < n, 0 ≤ Real.log (B i) := fun i hi => Real.log_nonneg (hB i hi).1 have hrewrite : (∑ i ∈ range n, Real.log (A i/B i)) = (∑ i ∈ range n, Real.log (A i))-(∑ i ∈ range n, Real.log (B i)) := by rw [←sum_sub_distrib] apply sum_congr rfl intro i hi have ha : 0 < A i := by linarith [(hA i (mem_range.mp hi)).1] have hb : 0 < B i := by linarith [(hB i (mem_range.mp hi)).1] exact Real.log_div ha.ne' hb.ne' rw [hrewrite] by_cases hpn : p ≤ n · have hfirst : ∑ i ∈ range p, Real.log (A i) ≤ (p:ℝ)*Real.log K := by calc _ ≤ ∑ _i ∈ range p, Real.log K := by apply sum_le_sum intro i hi have hin : i < n := (mem_range.mp hi).trans_le hpn exact Real.log_le_log (by linarith [(hA i hin).1]) (hA i hin).2 _ = _ := by simp have hlast : ∑ i ∈ range (n-p), Real.log (A (p+i)) ≤ ∑ i ∈ range (n-p), Real.log (B i) := by apply sum_le_sum intro i hi have hin : p+i < n := by have := mem_range.mp hi; omega have hh := hshift (p+i) hin (by omega) simp only [Nat.add_sub_cancel_left] at hh exact Real.log_le_log (by linarith [(hA (p+i) hin).1]) hh have htail : ∑ i ∈ range (n-p), Real.log (B i) ≤ ∑ i ∈ range n, Real.log (B i) := by apply sum_le_sum_of_subset_of_nonneg (range_mono (by omega)) intro i hi _ exact hlogB i (mem_range.mp hi) have he := Finset.sum_range_add (fun i => Real.log (A i)) p (n-p) rw [Nat.add_sub_of_le hpn] at he linarith · have hupper : ∑ i ∈ range n, Real.log (A i) ≤ (n:ℝ)*Real.log K := by calc _ ≤ ∑ _i ∈ range n, Real.log K := by apply sum_le_sum intro i hi exact Real.log_le_log (by linarith [(hA i (mem_range.mp hi)).1]) (hA i (mem_range.mp hi)).2 _ = _ := by simp have hnon := sum_nonneg (fun i hi => hlogB i (mem_range.mp hi)) have hnp : (n:ℝ) ≤ p := by exact_mod_cast (le_of_not_ge hpn) nlinarith /-- Source offset p=7 gives an absolute height-independent bound. The capacity estimate is slightly relaxed from C*(A-1) to C*A, but the conclusion is the exact O(1+log K) needed and the stronger source capacity implies this premise. -/ theorem seven_scale_park_coefficients {b d A B : ℕ → ℝ} {n : ℕ} {C K ρ R : ℝ} (hC : 0 ≤ C) (hρ : 0 < ρ) (hR : 0 ≤ R) (hK : 1 ≤ K) (hb : ∀ i < n, 0 ≤ b i) (hd : ∀ i < n, 0 < d i) (hA : ∀ i ≤ n, A i ∈ Set.Icc 1 K) (hB : ∀ i < n, B i ∈ Set.Icc 1 (A i)) (hdec : ∀ i < n, A (i+1) ≤ A i) (hcap : ∀ i ≤ n, tail b n i ≤ C*(A i-1)) (hnorm : ∀ i < n, B i ≤ ρ*d i) (hbound : ∀ i < n, b i/d i ≤ R) (hshift : ∀ i < n, 7 ≤ i → A i ≤ B (i-7)) : ∑ i ∈ range n, b i/d i ≤ (7*R/Real.log 2+2*ρ*C)*(1+Real.log K) := by have hlog := scale_log_telescope hK (fun i hi => hA i hi.le) (fun i hi => ⟨(hB i hi).1,(hB i hi).2.trans (hA i hi.le).2⟩) hshift have h := park_coefficients hC hρ hR hb hd hA hB hdec (fun i hi => (hcap i hi).trans (by nlinarith)) hnorm hbound hlog have h2 : 0 < Real.log 2 := Real.log_pos (by norm_num) have hr := div_nonneg hR h2.le have hdiff : R*((7:ℕ):ℝ)*Real.log K/Real.log 2 + 2*ρ*C*(1+Real.log K) ≤ (7*R/Real.log 2+2*ρ*C)*(1+Real.log K) := by calc _ = (7*R/Real.log 2+2*ρ*C)*(1+Real.log K)-7*(R/Real.log 2) := by norm_num; ring _ ≤ _ := sub_le_self _ (by positivity) calc _ ≤ R*((7:ℕ)*Real.log K)/Real.log 2+2*ρ*C*(1+Real.log K) := h _ = R*((7:ℕ):ℝ)*Real.log K/Real.log 2+2*ρ*C*(1+Real.log K) := by ring _ ≤ _ := hdiff end KServer.ParkedCoefficients namespace KServer.ParkedCoefficients section MetricScales variable {Y : Type*} [MetricSpace Y] [Fintype Y] /-- The manuscript's posterior measure of a closed metric ball, as a finite counting sum. We do not restrict to distinct hidden locations. -/ def ballMass (μ : Y → ℝ) (y : Y) (r : ℝ) : ℝ := ∑ z, if dist y z ≤ r then μ z else 0 lemma ballMass_nonneg {μ : Y → ℝ} (hμ : ∀ z, 0 ≤ μ z) (y : Y) (r : ℝ) : 0 ≤ ballMass μ y r := by apply sum_nonneg intro z _ split_ifs <;> [exact hμ z; rfl] lemma ballMass_total {μ : Y → ℝ} (hμ : ∀ z, 0 ≤ μ z) (y : Y) (r : ℝ) : ballMass μ y r ≤ ∑ z, μ z := by apply sum_le_sum intro z _ split_ifs <;> [rfl; exact hμ z] lemma ballMass_mono {μ : Y → ℝ} (hμ : ∀ z, 0 ≤ μ z) (y : Y) {r s : ℝ} (hrs : r ≤ s) : ballMass μ y r ≤ ballMass μ y s := by apply sum_le_sum intro z _ split_ifs with h h' h' <;> first | rfl | exact hμ z | (exfalso; exact h' (h.trans hrs)) def radius (r₀ τ : ℝ) (i : ℕ) := r₀/τ^i lemma radius_pos {r₀ τ : ℝ} (hr : 0 < r₀) (hτ : 0 < τ) (i : ℕ) : 0 < radius r₀ τ i := div_pos hr (pow_pos hτ i) lemma radius_antitone {r₀ τ : ℝ} (hr : 0 ≤ r₀) (hτ : 1 ≤ τ) : Antitone (radius r₀ τ) := by intro i j hij have hp : 0 < τ := by linarith exact div_le_div_of_nonneg_left hr (pow_pos hp i) (pow_le_pow_right₀ hτ hij) lemma radius_seven {r₀ τ : ℝ} (hr : 0 ≤ r₀) (hτ : 2 ≤ τ) {i : ℕ} (hi : 7 ≤ i) : 67*radius r₀ τ i ≤ radius r₀ τ (i-7) := by have hp : 0 < τ := by linarith have hpow : (67:ℝ) ≤ τ^7 := by have hh := pow_le_pow_left₀ (by norm_num : (0:ℝ) ≤ 2) hτ 7 norm_num at hh linarith unfold radius rw [←mul_div_assoc] apply (div_le_div_iff₀ (pow_pos hp i) (pow_pos hp (i-7))).mpr have he : τ^i=τ^(i-7)*τ^7 := by rw [←pow_add,Nat.sub_add_cancel hi] rw [he] have hm := mul_le_mul_of_nonneg_left hpow (mul_nonneg hr (pow_nonneg hp.le (i-7))) nlinarith /-- The pointwise coefficient bound now for the actual metric ball masses and geometric scales of §07-08, not an assumed logarithmic telescope. b is zero on unselected levels. Cumulative subcapacity is supplied by Tree.geometric_park_capacity; held normalization and individual domination are the exact local invariants. -/ theorem metric_park_coefficients {μ : Y → ℝ} (hμ : ∀ z, 0 ≤ μ z) (y : Y) {k C ρ R r₀ τ : ℝ} {n : ℕ} {b d : ℕ → ℝ} (hmass : ∑ z, μ z=k) (hC : 0 ≤ C) (hρ : 0 < ρ) (hR : 0 ≤ R) (hr : 0 ≤ r₀) (hτ : 2 ≤ τ) (hb : ∀ i < n, 0 ≤ b i) (hd : ∀ i < n, 0 < d i) (hcap : ∀ i ≤ n, tail b n i ≤ C*ballMass μ y (67*radius r₀ τ i)) (hnorm : ∀ i < n, 1+ballMass μ y (radius r₀ τ i) ≤ ρ*d i) (hbound : ∀ i < n, b i/d i ≤ R) : ∑ i ∈ range n, b i/d i ≤ (7*R/Real.log 2+2*ρ*C)*(1+Real.log (k+1)) := by let A := fun i => 1+ballMass μ y (67*radius r₀ τ i) let B := fun i => 1+ballMass μ y (radius r₀ τ i) have hk : 0 ≤ k := by rw [←hmass]; exact sum_nonneg (fun z _ => hμ z) have hrad : ∀ i, 0 ≤ radius r₀ τ i := fun i => div_nonneg hr (pow_nonneg (by linarith) i) have hAB : ∀ i, B i ≤ A i := by intro i dsimp [A,B] have h := ballMass_mono hμ y (show radius r₀ τ i ≤ 67*radius r₀ τ i by nlinarith [hrad i]) linarith have hA : ∀ i ≤ n, A i ∈ Set.Icc 1 (k+1) := by intro i _ have hn := ballMass_nonneg hμ y (67*radius r₀ τ i) have ht := ballMass_total hμ y (67*radius r₀ τ i) rw [hmass] at ht dsimp [A] constructor <;> linarith have hB : ∀ i < n, B i ∈ Set.Icc 1 (A i) := by intro i _ exact ⟨by dsimp [B]; linarith [ballMass_nonneg hμ y (radius r₀ τ i)],hAB i⟩ have hdec : ∀ i < n, A (i+1) ≤ A i := by intro i _ have hh := radius_antitone hr (show 1 ≤ τ by linarith) (show i ≤ i+1 by omega) have hm := ballMass_mono hμ y (show 67*radius r₀ τ (i+1) ≤ 67*radius r₀ τ i by linarith) dsimp [A]; linarith have hshift : ∀ i < n, 7 ≤ i → A i ≤ B (i-7) := by intro i _ hi have hm := ballMass_mono hμ y (radius_seven hr hτ hi) dsimp [A,B]; linarith apply seven_scale_park_coefficients hC hρ hR (by linarith) hb hd hA hB hdec _ hnorm hbound hshift intro i hi simpa [A] using hcap i hi end MetricScales end KServer.ParkedCoefficients end /-! All finer selected last-key bands form a literal prefix cut. -/ noncomputable section open scoped BigOperators open Finset namespace KServer.PrefixTree attribute [local instance] Classical.propDecidable Classical.decEq variable (A:Type) [Fintype A] (L:ℕ) def selectedBand (sel:ℕ→Option A) (d:ℕ):Finset (Node A L):= match sel d with | none =>∅ | some a =>band A L d a def selectedMass (p:Node A L→ℝ) (sel:ℕ→Option A) (d:ℕ):ℝ:= ∑ v∈selectedBand A L sel d,p v lemma selected_depth (sel:ℕ→Option A) {d:ℕ} {v:Node A L} (hv:v∈selectedBand A L sel d):depth A L v=d+1:=by unfold selectedBand at hv cases he:sel d with | none=>rw [he] at hv; exact (notMem_empty _ hv).elim | some a=>rw [he] at hv; exact band_depth A L d a hv lemma selected_disjoint (sel:ℕ→Option A) (F:Finset ℕ): Set.PairwiseDisjoint (↑F) (selectedBand A L sel):=by intro i _ j _ hij apply Finset.disjoint_left.mpr intro v hi hj have hd:=selected_depth A L sel hi have hd':=selected_depth A L sel hj omega lemma selected_tail (p:Node A L→ℝ) (sel:ℕ→Option A) (j:ℕ): ParkedCoefficients.tail (selectedMass A L p sel) L j= ∑ v∈(Ico j L).biUnion (selectedBand A L sel),p v:=by rw [sum_biUnion (selected_disjoint A L sel (Ico j L))] rfl variable {Ω Y:Type} [Fintype Ω] [Fintype Y] [MetricSpace Y] {k:ℕ} {w:Ω→ℝ} variable (hw:∀ ω,0≤w ω) (H:ℕ→Ω→ℕ) variable (hr:∀ t ω ρ,H (t+1) ω=H (t+1) ρ→H t ω=H t ρ) variable (maps:ℕ→Ω→ℕ→Y→A) (q:ℕ→Ω→Fin k→Y) (hk:1≤(k:ℝ)) theorem selected_capacity (hwpos:∀ ω,00

rw [hs] at hvi; exact (notMem_empty _ hvi).elim | some a=> rw [hs] at hvi exact (hclose i a hs z (band_key A L (maps t ω) i a hvi z (mem_filter.mp hz).2)).trans (mul_le_mul_of_nonneg_left (ParkedCoefficients.radius_antitone hR (by linarith) (mem_Ico.mp hi).1) (by norm_num)) have hdia:∀ v:Node A L,(numbering A L v).1.val=j+1→ ∀ a∈region A L maps t ω v,∀ b∈region A L maps t ω v, dist a b≤40*ParkedCoefficients.radius R τ j:=by intro v hv a ha b hb have hj:j<(numbering A L v).1.val:=by omega apply hcells exact ((mem_filter.mp ha).2 ⟨j,hj⟩).trans ((mem_filter.mp hb).2 ⟨j,hj⟩).symm have hh:=park_ball_capacity A L hw H hr maps q hk hwpos t ω hm S (j+1) y (ParkedCoefficients.radius R τ j) hd hwi hdia simpa only [Rounding.countingMass,ParkedCoefficients.ballMass,sum_filter] using hh end KServer.PrefixTree end /-! The actual prefix parks satisfy the logarithmic coefficient estimate. The denominator is the held persistent slot size; empty selected levels vanish. -/ noncomputable section open scoped BigOperators open Finset namespace KServer.PrefixTree attribute [local instance] Classical.propDecidable Classical.decEq variable (A:Type) [Fintype A] (L:ℕ) variable {Ω Y:Type} [Fintype Ω] [Fintype Y] [MetricSpace Y] {k:ℕ} {w:Ω→ℝ} variable (hw:∀ ω,0≤w ω) (H:ℕ→Ω→ℕ) variable (hr:∀ t ω ρ,H (t+1) ω=H (t+1) ρ→H t ω=H t ρ) variable (maps:ℕ→Ω→ℕ→Y→A) (q:ℕ→Ω→Fin k→Y) (hk:1≤(k:ℝ)) lemma selected_mass_nonneg {p:Node A L→ℝ} (hp:∀ v,0≤p v) (sel:ℕ→Option A) (j:ℕ): 0 ≤ selectedMass A L p sel j:=sum_nonneg (fun v _=>hp v) lemma ballMass_eq (μ:Y→ℝ) (y:Y) (r:ℝ): ParkedCoefficients.ballMass μ y r=Rounding.countingMass μ (univ.filter (fun z=>dist y z≤r)):=by simp only [ParkedCoefficients.ballMass,Rounding.countingMass,sum_filter] def selectedDenominator (μ:Y→ℝ) (y:Y) (r:ℕ→ℝ) (sel:ℕ→Option A) (u:ℕ→A→ℝ) (i:ℕ):ℝ:= match sel i with | none =>1+ParkedCoefficients.ballMass μ y (r i) | some a =>u i a theorem selected_coefficients (hwpos:∀ ω,0maps t ω i z=a))≤(6/5:ℝ)*u i a) (hclose:∀ i a,sel i=some a→∀ z,maps t ω i z=a→ dist y z≤27*ParkedCoefficients.radius R τ i) (hcontains:∀ i a,sel i=some a→∀ z,dist y z≤ParkedCoefficients.radius R τ i→maps t ω i z=a) (hcells:∀ i a b,maps t ω i a=maps t ω i b→ dist a b≤40*ParkedCoefficients.radius R τ i): let p:Node A L→ℝ:=(travelTree A L).park (Q A L hw H hr maps q hk t ω) let μ:=PosteriorCounting.measure (w:=w) (H t) (q t) ω ∑ i∈range L,selectedMass A L p sel i/ selectedDenominator A μ y (ParkedCoefficients.radius R τ) sel u i≤ (7*((6/5:ℝ)*72)/Real.log 2+2*(6/5:ℝ)*72)*(1+Real.log ((k:ℝ)+1)):=by dsimp only let μ:=PosteriorCounting.measure (w:=w) (H t) (q t) ω let p:Node A L→ℝ:=(travelTree A L).park (Q A L hw H hr maps q hk t ω) have hμ:∀ z,0≤μ z:=PosteriorCounting.measure_nonneg hw (H t) (q t) ω let den:=selectedDenominator A μ y (ParkedCoefficients.radius R τ) sel u have hd:∀ i,0simp only; linarith [ParkedCoefficients.ballMass_nonneg hμ y (ParkedCoefficients.radius R τ i)] | some a=>exact hu i a have hn:∀ i,1+ParkedCoefficients.ballMass μ y (ParkedCoefficients.radius R τ i)≤(6/5:ℝ)*den i:=by intro i dsimp [den,selectedDenominator] cases hs:sel i with | none=>simp only; nlinarith [ParkedCoefficients.ballMass_nonneg hμ y (ParkedCoefficients.radius R τ i)] | some a=> have hb:ParkedCoefficients.ballMass μ y (ParkedCoefficients.radius R τ i)≤ Rounding.countingMass μ (univ.filter (fun z=>maps t ω i z=a)):=by rw [ballMass_eq] apply sum_le_sum_of_subset_of_nonneg · intro z hz exact mem_filter.mpr ⟨mem_univ _,hcontains i a hs z (mem_filter.mp hz).2⟩ · intro z _ _; exact hμ z exact (add_le_add_right hb 1).trans (hnorm i a) have hb:∀ i,selectedMass A L p sel i/den i≤(6/5:ℝ)*72:=by intro i dsimp [selectedMass,selectedBand,den,selectedDenominator] cases hs:sel i with | none=>simp only [sum_empty,zero_div]; norm_num | some a=> change bandMass A L p i a/u i a≤(6/5:ℝ)*72 apply (div_le_iff₀ (hu i a)).mpr have hh:=band_capacity A L hw H hr maps q hk hwpos t ω hm i a have hn:=hnorm i a dsimp only [p] at * nlinarith exact ParkedCoefficients.metric_park_coefficients hμ y (PosteriorCounting.measure_total hw (H t) (q t) ω (hwpos ω)) (by norm_num : (0:ℝ)≤72) (by norm_num : (0:ℝ)<6/5) (by norm_num : (0:ℝ)≤(6/5:ℝ)*72) hR hτ (fun i _=>selected_mass_nonneg A L (park_nonneg A L hw H hr maps q hk hwpos t ω) sel i) (fun i _=>hd i) (fun i _=>selected_capacity A L hw H hr maps q hk hwpos t ω hm sel y hR hτ hclose hcells i) (fun i _=>hn i) (fun i _=>hb i) end KServer.PrefixTree end /-! Literal allocation and persistent bands on the single positive experiment. -/ noncomputable section open scoped BigOperators open Finset namespace KServer.JointAllocation open JointExperiment RankTracking PosteriorRanks attribute [local instance] Classical.propDecidable Classical.decEq variable {Y:Type} [MetricSpace Y] [Fintype Y] {k H L:ℕ} [NeZero k] variable (s:Configuration k Y) (law:FiniteDistribution (Fin H→Y)) variable {r:Fin L→ℝ} (hr:∀ d,0maps_adapted law hr s t ρ ω h have hh:=PrefixTree.band_capacity _ L (weight_nonneg law hr) (history law hr) (history_refines law hr) (maps law hr s) (hidden law hr s) hk (weight_pos law hr) t ω hm d a unfold Rounding.countingMass at hh rw [KeyReferences.mass_eq] at hh · simpa only [band,park,quota,size,KeyReferences.size,add_sub_cancel_left] using hh · exact hm lemma size_range (d:ℕ) (a:A (Y:=Y) (k:=k)) (t:ℕ) (ω:Ω (k:=k) law hr): size s law hr d a t ω∈Set.Icc 1 ((k:ℝ)+1):= KeyReferences.size_range (history law hr) (maps law hr s) (hidden law hr s) (weight_nonneg law hr) (weight_pos law hr) (history_refines law hr) d a t ω lemma reference_range (d:ℕ) (a:A (Y:=Y) (k:=k)) (t:ℕ) (ω:Ω (k:=k) law hr): reference s law hr d a t ω∈Set.Icc 1 ((k:ℝ)+1):= KeySizeTracking.held_range (size_range s law hr d a) t ω lemma reference_pos (d:ℕ) (a:A (Y:=Y) (k:=k)) (t:ℕ) (ω:Ω (k:=k) law hr): 0maps law hr s t ω d y=a), PosteriorCounting.measure (w:=weight law hr) (history law hr t) (hidden law hr s t) ω y:=by change 1+_=1+_ exact congrArg (fun z:ℝ=>1+z) (KeyReferences.mass_eq (w:=weight law hr) (history law hr) (maps law hr s) (hidden law hr s) d a t ω (fun ρ h=>maps_adapted law hr s t ρ ω h)).symm lemma size_mass (d:Fin L) (a:A (Y:=Y) (k:=k)) (t:ℕ) (ω:Ω (k:=k) law hr): size s law hr d.val a t ω=1+∑ y∈univ.filter (fun y=>LevelKeys.map s law (hr d).le ω.val.1 (ω.val.2 d) t y=a),FiniteExperiment.mu s law t ω.val.1 y:=by rw [size_mass_joint] have hm:maps law hr s t ω d.val=LevelKeys.map s law (hr d).le ω.val.1 (ω.val.2 d) t:=by funext y simp only [JointExperiment.maps,dite_eq_left d.isLt] rw [hm] apply congrArg (fun z:ℝ=>1+z) apply sum_congr rfl intro y _ exact JointExperiment.measure_eq law hr s t ω y end KServer.JointAllocation end /-! From the exact conditional allocation construction to levelwise hidden-key changes. This counts both true hidden movement and changing online maps. -/ noncomputable section open scoped BigOperators open Finset namespace KServer.HierarchicalQuota attribute [local instance] Classical.propDecidable Classical.decEq open ActualCharges variable {Ω A Y:Type} [Fintype Ω] [Fintype A] {k:ℕ} {w:Ω→ℝ} variable (hw:∀ ω,0 ≤ w ω) (H:ℕ→Ω→ℕ) variable (hr:∀ t ω ρ,H (t+1) ω=H (t+1) ρ→H t ω=H t ρ) variable (maps:ℕ→Ω→ℕ→Y→A) (q:ℕ→Ω→Fin k→Y) def keyCross (d t:ℕ) (ω:Ω):ℝ:=∑ l:Fin k, if maps (t+1) ω d (q (t+1) ω l)=maps t ω d (q t ω l) then 0 else 1 def keyTransport (r:ℕ→ℝ) (L N:ℕ):ℝ:= ∑ d∈range L,r d*total w N (keyCross maps q d) def prefixTransport (r:ℕ→ℝ) (L N:ℕ):ℝ:= ∑ d∈range L,r d*total w N (prefixCross maps q (d+1)) omit [Fintype Ω] [Fintype A] in lemma prefixCross_zero (t:ℕ) (ω:Ω):prefixCross maps q 0 t ω=0:=by have he:∀ l:Fin k,address maps q 0 (t+1) ω l=address maps q 0 t ω l:=by intro l funext i exact i.elim0 simp [prefixCross,he] omit [Fintype Ω] [Fintype A] in lemma prefixCross_step (d t:ℕ) (ω:Ω):prefixCross maps q (d+1) t ω ≤ prefixCross maps q d t ω+keyCross maps q d t ω:=by unfold prefixCross keyCross rw [←sum_add_distrib] apply sum_le_sum intro l _ by_cases ha:address maps q d (t+1) ω l=address maps q d t ω l · by_cases hb:maps (t+1) ω d (q (t+1) ω l)=maps t ω d (q t ω l) · have he:address maps q (d+1) (t+1) ω l=address maps q (d+1) t ω l:=by funext i exact Fin.lastCases (motive:=fun i:Fin (d+1)=> address maps q (d+1) (t+1) ω l i=address maps q (d+1) t ω l i) hb (fun j=>congrFun ha j) i simp [he,ha,hb] · simp only [ite_eq_left ha,ite_eq_right hb,zero_add] split_ifs <;> norm_num · simp only [ite_eq_right ha] split_ifs <;> norm_num omit [Fintype A] in include hw in lemma prefix_transport_bound (r:ℕ→ℝ) (hrad:∀ d,0 ≤ r d) (hhalf:∀ d,r (d+1) ≤ r d/2) (L N:ℕ): prefixTransport (w:=w) maps q r L N ≤ 2*keyTransport (w:=w) maps q r L N:=by have hs:=sum_le_sum (s:=range L) (fun d _=>mul_le_mul_of_nonneg_left (total_mono hw (N:=N) (fun t ω=>prefixCross_step maps q d t ω)) (hrad d)) simp only [total_add,mul_add,sum_add_distrib] at hs have hp:=weighted_shift r (fun d=>total w N (prefixCross maps q d)) hrad (fun d=>total_nonneg hw (fun t ω=>prefixCross_nonneg maps q d t ω)) (by simp [total,prefixCross_zero,RankTracking.avg]) hhalf L change _ ≤ (1/2:ℝ)*prefixTransport maps q r L N at hp change prefixTransport maps q r L N ≤ _+keyTransport maps q r L N at hs linarith include hw in lemma tree_drift_bound (r:ℕ→ℝ) (hrad:∀ d,0 ≤ r d) (hhalf:∀ d,r (d+1) ≤ r d/2) (L N:ℕ): treeDrift hw H hr maps q r L N ≤ 6*keyTransport (w:=w) maps q r L N:=by have hc d:= (level_drift_count hw H hr maps q d N).trans (level_count_cross hw maps q d N) have hs:=sum_le_sum (s:=range L) (fun d _=>mul_le_mul_of_nonneg_left (hc (d+1)) (hrad d)) have hp:=weighted_shift r (fun d=>levelDrift hw H hr maps q d N) hrad (fun d=>levelDrift_nonneg hw H hr maps q d N) (levelDrift_zero hw H hr maps q N) hhalf L have hx:=prefix_transport_bound hw maps q r hrad hhalf L N have hs':(∑ d∈range L,r d*levelDrift hw H hr maps q (d+1) N) ≤ 2*prefixTransport (w:=w) maps q r L N:=by simpa only [prefixTransport,mul_sum,mul_assoc,mul_comm,mul_left_comm] using hs unfold treeDrift simp only [mul_add,sum_add_distrib] -- The precise coefficient is six with these per-level estimates. linarith end KServer.HierarchicalQuota end noncomputable section open scoped BigOperators open Finset namespace KServer.ActualCharges open RankTracking variable {Ω I:Type} [Fintype Ω] [Fintype I] {w:Ω→ℝ} lemma total_sum (N:ℕ) (f:I→ℕ→Ω→ℝ): total w N (fun t ω=>∑ i,f i t ω)=∑ i,total w N (f i):=by simp only [total,avg_sum] exact sum_comm lemma avg_const_one (hw:∑ ω,w ω=1) (c:ℝ):avg w (fun _=>c)=c:=by unfold avg rw [←sum_mul,hw,one_mul] end KServer.ActualCharges end end OAI