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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<w ω) (H:Ω→ℕ)
{f:Ω→ℝ} {K:ℝ} (hf:∀ ω,f ω∈Set.Icc 0 K) (ω:Ω):
posterior w H f ω∈Set.Icc 0 K:=by
refine ⟨posterior_nonneg hw H (fun ρ=>(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<w ω) {K:ℝ}
(H:ℕ→Ω→ℕ) (hr:∀ t ω ρ,H (t+1) ω=H (t+1) ρ→H t ω=H t ρ)
(N:ℕ→Ω→ℝ) (hN:∀ t ω,N t ω∈Set.Icc 0 K):KeySizeTracking.FilteredSizes w (K+1) where
history:=H
refines:=hr
s t ω:=1+posterior w (H t) (N t) ω
before t ω:=1+posterior w (H t) (N (t-1)) ω
range:=by intro t ω; have h:=bounded hw hwpos (H t) (hN t) ω; constructor <;> 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<w ω) {K:ℝ}
(H:ℕ→Ω→ℕ) (hr:∀ t ω ρ,H (t+1) ω=H (t+1) ρ→H t ω=H t ρ)
(N:ℕ→Ω→ℝ) (hN:∀ t ω,N t ω∈Set.Icc 0 K) (t:ℕ):
avg w (fun ω=>|(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<w ω) (hw1:∑ ω,w ω=1)
{K:ℝ} (hK:0≤K) (H:ℕ→Ω→ℕ)
(hr:∀ t ω ρ,H (t+1) ω=H (t+1) ρ→H t ω=H t ρ)
(N:ℕ→Ω→ℝ) (hN:∀ t ω,N t ω∈Set.Icc 0 K) (T:ℕ):
(∑ t∈range T,avg w (KeySizeTracking.refreshCost (process hw hwpos H hr N hN).s t)) ≤
144*(1+Real.log (K+1))*(∑ t∈range T,avg w (fun ω=>|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+1<L+1) (f:Fin (d+1)→A):
parent A L ⟨⟨d+1,hd⟩,f⟩=⟨⟨d,by omega⟩,Fin.init f⟩:=by
simp only [parent,Nat.add_eq_zero_iff,one_ne_zero,and_false,↓reduceDIte]
rfl
omit [Fintype A] in
lemma child_depth {v:Vertex A L} (u:Child A L v):u.val.1.val=v.1.val+1:=by
have hp:0<u.val.1.val:=Nat.pos_of_ne_zero ((depth_zero_iff A L _).not.mpr u.property.1)
have he:=congrArg (fun x:Vertex A L=>x.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<u.val.1.val:=by
have :=child_depth A L u
omega
def extend (v:Vertex A L) (h:v.1.val<L) (a:A):Vertex A L:=
⟨⟨v.1.val+1,by omega⟩,Fin.snoc v.2 a⟩
omit [Fintype A] in
lemma parent_extend (v:Vertex A L) (h:v.1.val<L) (a:A):
parent A L (extend A L v h a)=v:=by
rw [extend,parent_succ]
simp only [Fin.init_snoc]
omit [Fintype A] in
lemma extend_ne_root (v:Vertex A L) (h:v.1.val<L) (a:A):
extend A L v h a≠root A L:=by
intro he
have he':=(depth_zero_iff A L _).mpr he
dsimp [extend] at he'
omega
def childEquiv (v:Vertex A L) (h:v.1.val<L):A≃Child A L v where
toFun a:=⟨extend A L v h a,extend_ne_root A L v h a,parent_extend A L v h a⟩
invFun u:=u.val.2 ⟨u.val.1.val-1,child_last_lt A L u⟩
left_inv a:=by
simp only [extend,Nat.add_sub_cancel]
exact Fin.snoc_last _ _
right_inv u:=by
apply Subtype.ext
rcases v with ⟨⟨d,hd⟩,f⟩
rcases u with ⟨⟨⟨e,he⟩,g⟩,hn,hp⟩
have hdeg:e=d+1:=child_depth A L ⟨_,hn,hp⟩
subst e
rw [parent_succ] at hp
have hf:Fin.init g=f:=by cases hp; rfl
dsimp only [extend,Nat.add_sub_cancel]
change (⟨⟨d+1,he⟩,Fin.snoc f (g (Fin.last d))⟩:Vertex A L) = _
rw [←hf]
have hg:Fin.snoc (Fin.init g) (g (Fin.last d))=g:=Fin.snoc_init_self g
exact congrArg (fun f:Fin (d+1)→A=>(⟨⟨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.val<L):
(∑ u:(tree A L).Child v,f (numbering A L u.val))=
∑ a:A,f (extend A L (numbering A L v) h a):=by
let e: A ≃ (tree A L).Child v :=
(childEquiv A L (numbering A L v) h).trans (numberedChildEquiv A L v).symm
symm
exact Fintype.sum_equiv e _ _ (fun a=>by
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,0<w ω) (t:ℕ) (ω:Ω) (v:Fin (Fintype.card (Vertex A L))):
0≤Q A L hw H hr maps q hk t ω v:=
HierarchicalQuota.quota_nonneg hw H hr maps q hk hwpos _ t ω
omit [Fintype Y] in
lemma Q_children (hwpos:∀ ω,0<w ω) (t:ℕ) (ω:Ω) (v:Fin (Fintype.card (Vertex A L))):
(∑ u:(tree A L).Child v,Q A L hw H hr maps q hk t ω u.val)≤Q A L hw H hr maps q hk t ω v:=by
by_cases hv:(numbering A L v).1.val<L
· unfold Q
rw [children_sum A L v (fun u:Vertex A L=>HierarchicalQuota.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,0<w ω) (t:ℕ) (ω:Ω)
(hm:∀ ρ,H t ρ=H t ω→maps t ρ=maps t ω) (v:Fin (Fintype.card (Vertex A L))):
Q A L hw H hr maps q hk t ω v≤
72*∑ y∈region A L maps t ω v,PosteriorCounting.measure (w:=w) (H t) (q t) ω y:=by
exact (HierarchicalQuota.quota_bounds hw H hr maps q hk hwpos _ _ t ω).2.trans
(mul_le_mul_of_nonneg_left (PosteriorCounting.size_prefix_bound hw H hr maps q _ t ω (hwpos ω) hm)
(by norm_num))
lemma Q_witness (hwpos:∀ ω,0<w ω) (t:ℕ) (ω:Ω)
(hm:∀ ρ,H t ρ=H t ω→maps t ρ=maps t ω) (v:Fin (Fintype.card (Vertex A L)))
(hq:0<Q A L hw H hr maps q hk t ω v):∃ y,y∈region A L maps t ω v:=by
have hh:=Q_mass A L hw H hr maps q hk hwpos t ω hm v
by_contra hn
have he:region A L maps t ω v=∅:=by
apply eq_empty_iff_forall_notMem.mpr
intro y hy
exact hn ⟨y,hy⟩
rw [he,sum_empty,mul_zero] at hh
linarith
omit [Fintype Y] in
lemma park_nonneg (hwpos:∀ ω,0<w ω) (t:ℕ) (ω:Ω) (v:Fin (Fintype.card (Vertex A L))):
0≤(travelTree A L).park (Q A L hw H hr maps q hk t ω) v:=by
apply sub_nonneg.mpr
exact Q_children A L hw H hr maps q hk hwpos t ω v
omit [Fintype Y] in
lemma park_le_Q (hwpos:∀ ω,0<w ω) (t:ℕ) (ω:Ω) (v:Fin (Fintype.card (Vertex A L))):
(travelTree A L).park (Q A L hw H hr maps q hk t ω) v≤Q A L hw H hr maps q hk t ω v:=by
apply sub_le_self
exact sum_nonneg fun u _=>Q_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:0<v.1.val):
(parent A L v).1.val=v.1.val-1:=by
simp only [parent,dite_eq_right (by omega:v.1.val≠0)]
omit [Fintype A] in
lemma take_parent (v:Vertex A L) {d:ℕ} (hd:d<v.1.val):
take A L (parent A L v) d (by rw [parent_depth A L v (by omega)]; omega)=
take A L v d hd.le:=by
rcases v with ⟨⟨e,he⟩,f⟩
cases e with
| zero=>exact 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,0<w ω) (t:ℕ) (ω:Ω)
(hm:∀ ρ,H t ρ=H t ω→maps t ρ=maps t ω)
(S:Finset (Fin (Fintype.card (Vertex A L)))) (d:ℕ) (y:Y) (r:ℝ)
(hd:∀ u∈S,d≤(numbering A L u).1.val)
(hwit:∀ u∈S,∃ z∈region A L maps t ω u,dist y z≤27*r)
(hdiam:∀ v:Fin (Fintype.card (Vertex A L)),(numbering A L v).1.val=d→
∀ a∈region A L maps t ω v,∀ b∈region A L maps t ω v,dist a b≤40*r):
(∑ u∈S,(travelTree A L).park (Q A L hw H hr maps q hk t ω) u)≤
72*Rounding.countingMass (PosteriorCounting.measure (w:=w) (H t) (q t) ω)
(univ.filter (fun z=>dist 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:0<depth A L v then some ((numbering A L v).2 ⟨depth A L v-1,by change depth A L v-1<depth A L v; omega⟩) else none
def band (d:ℕ) (a:A):Finset (Node A L):=
univ.filter (fun v=>depth 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:0<depth A L v:=by omega
simp only [lastKey,dite_eq_left hp,Option.some.injEq] at ha
have hi:=hy ⟨depth A L v-1,by change depth A L v-1<depth A L v; omega⟩
dsimp only at hi
have he:depth A L v-1=d:=by omega
rw [←ha,←hi,he]
lemma band_depth (d:ℕ) (a:A) {v:Node A L} (hv:v∈band A L d a):
(numbering A L v).1.val=d+1:=(mem_filter.mp hv).2.1
lemma band_disjoint {Y:Type} [Fintype Y] (maps:ℕ→Y→A) (d:ℕ) (a:A):
Set.PairwiseDisjoint (↑(band A L d a))
(fun v=>univ.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,0<w ω) (t:ℕ) (ω:Ω)
(hm:∀ ρ,H t ρ=H t ω→maps t ρ=maps t ω) (d:ℕ) (a:A):
bandMass A L ((travelTree A L).park (Q A L hw H hr maps q hk t ω)) d a≤
72*Rounding.countingMass (PosteriorCounting.measure (w:=w) (H t) (q t) ω)
(univ.filter (fun y=>maps 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<w ω)
variable (hr:∀ t ω ρ,H (t+1) ω=H (t+1) ρ→H t ω=H t ρ)
def process (d:ℕ) (a:A):KeySizeTracking.FilteredSizes w ((k:ℝ)+1):=
PosteriorSizes.process hw hwpos H hr (count maps q d a) (count_range maps q d a)
include hw hwpos hr
omit [Fintype A] [Fintype Y] in
lemma size_range (d:ℕ) (a:A) (t:ℕ) (ω:Ω):size (w:=w) H maps q d a t ω∈Set.Icc 1 ((k:ℝ)+1):=
(process H maps q hw hwpos hr d a).range t ω
omit [Fintype A] [Fintype Y] in
lemma reference_range (d:ℕ) (a:A) (t:ℕ) (ω:Ω):
reference (w:=w) H maps q d a t ω∈Set.Icc 1 ((k:ℝ)+1):=
KeySizeTracking.held_range (size_range H maps q hw hwpos hr d a) t ω
omit [Fintype A] [Fintype Y] in
lemma reference_pos (d:ℕ) (a:A) (t:ℕ) (ω:Ω):0<reference (w:=w) H maps q d a t ω:=
lt_of_lt_of_le (by norm_num) (reference_range H maps q hw hwpos hr d a t ω).1
omit [Fintype A] [Fintype Y] in
lemma reference_comparison (d:ℕ) (a:A) (t:ℕ) (ω:Ω):
(5/6:ℝ)*reference (w:=w) H maps q d a t ω≤ size (w:=w) H maps q d a t ω ∧
size (w:=w) H maps q d a t ω≤ (6/5:ℝ)*reference (w:=w) H maps q d a t ω:=
KeySizeTracking.held_accurate (fun t ω=>(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,0<w ω) (t:ℕ) (ω:Ω)
(hm:∀ ρ,H t ρ=H t ω→maps t ρ=maps t ω)
(sel:ℕ→Option A) (y:Y) {R τ:ℝ} (hR:0≤R) (hτ:2≤τ)
(hclose:∀ i a,sel i=some a→∀ z,maps t ω i z=a→
dist y z≤27*ParkedCoefficients.radius R τ i)
(hcells:∀ i a b,maps t ω i a=maps t ω i b→
dist a b≤40*ParkedCoefficients.radius R τ i) (j:ℕ):
ParkedCoefficients.tail
(selectedMass A L ((travelTree A L).park (Q A L hw H hr maps q hk t ω)) sel) L j≤
72*ParkedCoefficients.ballMass (PosteriorCounting.measure (w:=w) (H t) (q t) ω) y
(67*ParkedCoefficients.radius R τ j):=by
let p:Node A L→ℝ:=(travelTree A L).park (Q A L hw H hr maps q hk t ω)
let F:Finset (Node A L):=(Ico j L).biUnion (selectedBand A L sel)
let S:=F.filter (fun v=>0<p v)
have hn:∀ v,0≤p v:=park_nonneg A L hw H hr maps q hk hwpos t ω
have he:(∑ v∈F,p v)=(∑ v∈S,p v):=by
symm
apply sum_subset (filter_subset _ _)
intro v hv hvs
have hh:¬0<p v:=by simpa only [S,mem_filter,hv,true_and] using hvs
exact le_antisymm (le_of_not_gt hh) (hn v)
rw [selected_tail]
change (∑ v∈F,p v)≤_
rw [he]
have hd:∀ v∈S,j+1≤(numbering A L v).1.val:=by
intro v hv
obtain ⟨i,hi,hvi⟩:=mem_biUnion.mp (mem_filter.mp hv).1
have hvd:=selected_depth A L sel hvi
have hij:=(mem_Ico.mp hi).1
change j+1≤depth A L v
omega
have hwi:∀ v∈S,∃ z∈region A L maps t ω v,
dist y z≤27*ParkedCoefficients.radius R τ j:=by
intro v hv
obtain ⟨i,hi,hvi⟩:=mem_biUnion.mp (mem_filter.mp hv).1
have hp:0<Q A L hw H hr maps q hk t ω v:=
lt_of_lt_of_le (mem_filter.mp hv).2 (park_le_Q A L hw H hr maps q hk hwpos t ω v)
obtain ⟨z,hz⟩:=Q_witness A L hw H hr maps q hk hwpos t ω hm v hp
refine ⟨z,hz,?_⟩
unfold selectedBand at hvi
cases hs:sel i with
| none=>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,0<w ω) (t:ℕ) (ω:Ω)
(hm:∀ ρ,H t ρ=H t ω→maps t ρ=maps t ω)
(sel:ℕ→Option A) (y:Y) (u:ℕ→A→ℝ) {R τ:ℝ} (hR:0≤R) (hτ:2≤τ)
(hu:∀ i a,0<u i a)
(hnorm:∀ i a,1+Rounding.countingMass (PosteriorCounting.measure (w:=w) (H t) (q t) ω)
(univ.filter (fun z=>maps 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,0<den i:=by
intro i
dsimp [den,selectedDenominator]
cases hs:sel i with
| none=>simp 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,0<r d) (hk:1≤(k:ℝ))
abbrev Ω:=JointExperiment.Atom (k:=k) law hr
abbrev A:=LevelKeys.Key Y k
local instance keyDecEq : DecidableEq (A (Y:=Y) (k:=k)) := Classical.decEq _
def quota (t:ℕ) (ω:Ω (k:=k) law hr):PrefixTree.Node (A (Y:=Y) (k:=k)) L→ℝ:=
PrefixTree.Q _ L (weight_nonneg law hr) (history law hr) (history_refines law hr)
(maps law hr s) (hidden law hr s) hk t ω
def park (t:ℕ) (ω:Ω (k:=k) law hr):PrefixTree.Node (A (Y:=Y) (k:=k)) L→ℝ:=
(PrefixTree.travelTree _ L).park (quota s law hr hk t ω)
def band (t:ℕ) (ω:Ω (k:=k) law hr) (d:ℕ) (a:A (Y:=Y) (k:=k)):ℝ:=
PrefixTree.bandMass _ L (park s law hr hk t ω) d a
def size (d:ℕ) (a:A (Y:=Y) (k:=k)) (t:ℕ) (ω:Ω (k:=k) law hr):ℝ:=
KeyReferences.size (w:=weight law hr) (history law hr) (maps law hr s) (hidden law hr s) d a t ω
def reference (d:ℕ) (a:A (Y:=Y) (k:=k)) (t:ℕ) (ω:Ω (k:=k) law hr):ℝ:=
KeySizeTracking.held (size s law hr d a) t ω
lemma quota_nonneg (t:ℕ) (ω:Ω (k:=k) law hr) (v:PrefixTree.Node (A (Y:=Y) (k:=k)) L):
0≤quota s law hr hk t ω v:=
PrefixTree.Q_nonneg _ 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 v
lemma park_nonneg (t:ℕ) (ω:Ω (k:=k) law hr) (v:PrefixTree.Node (A (Y:=Y) (k:=k)) L):
0≤park s law hr hk t ω v:=
PrefixTree.park_nonneg _ 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 v
lemma band_nonneg (t:ℕ) (ω:Ω (k:=k) law hr) (d:ℕ) (a:A (Y:=Y) (k:=k)):
0≤band s law hr hk t ω d a:=PrefixTree.band_nonneg _ L (park_nonneg s law hr hk t ω) d a
lemma band_capacity (t:ℕ) (ω:Ω (k:=k) law hr) (d:ℕ) (a:A (Y:=Y) (k:=k)):
band s law hr hk t ω d a≤72*(size s law hr d a t ω-1):=by
have hm:∀ ρ,history law hr t ρ=history law hr t ω→maps law hr s t ρ=maps law hr s t ω:=
fun ρ h=>maps_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):
0<reference s law hr d a t ω:=by linarith [(reference_range s law hr d a t ω).1]
lemma reference_comparison (d:ℕ) (a:A (Y:=Y) (k:=k)) (t:ℕ) (ω:Ω (k:=k) law hr):
(5/6:ℝ)*reference s law hr d a t ω≤ size s law hr d a t ω ∧
size s law hr d a t ω≤ (6/5:ℝ)*reference s law hr d a t ω:=
KeyReferences.reference_comparison (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 coefficient_bounds (t:ℕ) (ω:Ω (k:=k) law hr) (d:ℕ) (a:A (Y:=Y) (k:=k)):
band s law hr hk t ω d a/reference s law hr d a t ω∈Set.Icc 0 ((6/5:ℝ)*72):=by
constructor
· exact div_nonneg (band_nonneg s law hr hk t ω d a) (reference_pos s law hr d a t ω).le
· apply (div_le_iff₀ (reference_pos s law hr d a t ω)).mpr
have hh:=band_capacity s law hr hk t ω d a
have hn:=(reference_comparison s law hr d a t ω).2
nlinarith
lemma quota_adapted (t:ℕ) (ω ρ:Ω (k:=k) law hr) (h:history law hr t ω=history law hr t ρ):
quota s law hr hk t ω=quota s law hr hk t ρ:=by
funext v
exact PrefixTree.Q_adapted _ L (weight_nonneg law hr) (history law hr) (history_refines law hr)
(maps law hr s) (hidden law hr s) hk t v ω ρ h
lemma band_adapted (t:ℕ) (ω ρ:Ω (k:=k) law hr) (h:history law hr t ω=history law hr t ρ):
band s law hr hk t ω=band s law hr hk t ρ:=by
unfold band park
rw [quota_adapted s law hr hk t ω ρ h]
lemma reference_adapted (d:ℕ) (a:A (Y:=Y) (k:=k)) (t:ℕ):
Adapted (history law hr t) (reference s law hr d a t):=
KeyReferences.reference_adapted (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
lemma size_mass_joint (d:ℕ) (a:A (Y:=Y) (k:=k)) (t:ℕ) (ω:Ω (k:=k) law hr):
size s law hr d a t ω=1+∑ y∈univ.filter (fun y=>maps 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
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