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ea76aac | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 | import Mathlib
import OAI.Computability.MaxCut.Estimates.Dictator
namespace OAI
noncomputable section
namespace OptimalMaxCut.LongCode
open scoped BigOperators
open Finset OptimalMaxCut.Unweighted
namespace Law
variable {I : Type} [Fintype I]
/-- Downward rounding is performed BEFORE aggregation. Thus every output mass
has the same polynomially sized integer denominator; no product of all input
vertex degrees has to be represented as a unary integer. -/
noncomputable def gridWeight (P : ℕ) (a : ℚ) : ℚ := (⌊(P : ℚ) * a⌋₊ : ℚ) / P
theorem gridWeight_nonneg (P : ℕ) (a : ℚ) : 0 ≤ gridWeight P a := by
unfold gridWeight; positivity
theorem gridWeight_le (P : ℕ) (hP : 0 < P) (a : ℚ) (ha : 0 ≤ a) :
gridWeight P a ≤ a := by
have hPr : (0 : ℚ) < P := by exact_mod_cast hP
rw [gridWeight, div_le_iff₀ hPr]
simpa [mul_comm] using Nat.floor_le (mul_nonneg hPr.le ha)
theorem gridWeight_error (P : ℕ) (hP : 0 < P) (a : ℚ) :
a - gridWeight P a ≤ 1 / (P : ℚ) := by
have hPr : (0 : ℚ) < P := by exact_mod_cast hP
have h := Nat.lt_floor_add_one ((P : ℚ) * a)
unfold gridWeight
apply (le_div_iff₀ hPr).mpr
rw [sub_mul, div_mul_cancel₀ _ (ne_of_gt hPr)]
nlinarith
noncomputable def grid (p : Law I) (P : ℕ) (hP : 0 < P) : Law (Option I) where
weight
| none => 1 - ∑ i, gridWeight P (p.weight i)
| some i => gridWeight P (p.weight i)
nonneg
| none => by
have h := sum_le_sum (fun i (_ : i ∈ (univ : Finset I)) =>
gridWeight_le P hP (p.weight i) (p.nonneg i))
rw [p.total] at h
linarith
| some i => gridWeight_nonneg _ _
total := by simp [Fintype.sum_option]
theorem grid_average (p : Law I) (P : ℕ) (hP : 0 < P) (f : Option I → ℝ)
(hzero : f none = 0) :
(p.grid P hP).avg f = ∑ i, (gridWeight P (p.weight i) : ℝ) * f (some i) := by
simp only [avg, Fintype.sum_option, grid, hzero, mul_zero, zero_add]
theorem grid_average_bounds (p : Law I) (P : ℕ) (hP : 0 < P) (f : I → ℝ)
(hf0 : ∀ i, 0 ≤ f i) (hf1 : ∀ i, f i ≤ 1) :
let rounded := ∑ i, (gridWeight P (p.weight i) : ℝ) * f i
rounded ≤ p.avg f ∧ p.avg f - rounded ≤ Fintype.card I / (P : ℝ) := by
dsimp only
have hw (i : I) : (gridWeight P (p.weight i) : ℝ) ≤ (p.weight i : ℝ) := by
exact_mod_cast gridWeight_le P hP _ (p.nonneg i)
have he (i : I) : (p.weight i : ℝ) - (gridWeight P (p.weight i) : ℝ) ≤ 1 / (P : ℝ) := by
have hh : ((p.weight i - gridWeight P (p.weight i) : ℚ) : ℝ) ≤
((1 / (P : ℚ) : ℚ) : ℝ) := by exact_mod_cast gridWeight_error P hP (p.weight i)
simpa only [Rat.cast_sub, Rat.cast_div, Rat.cast_one, Rat.cast_natCast] using hh
constructor
· exact sum_le_sum (fun i _ => mul_le_mul_of_nonneg_right (hw i) (hf0 i))
· rw [avg, ← sum_sub_distrib]
calc
_ ≤ ∑ _ : I, 1 / (P : ℝ) := sum_le_sum (fun i _ => by
have h := mul_le_of_le_one_right (sub_nonneg.mpr (hw i)) (hf1 i)
nlinarith [he i])
_ = _ := by simp [div_eq_mul_inv]
end Law
/-- Lost mass becomes a loop, which is deleted by exactly the original
aggregation. It is never renormalized into non-loop edges. -/
noncomputable def roundedWeights {I : Type} [Fintype I] {N : ℕ}
(p : Law I) (endpoints : I → Fin N × Fin N) (v0 : Fin N)
(P : ℕ) (hP : 0 < P) : Fin N → Fin N → ℚ :=
aggregate ((p.grid P hP).push (fun
| none => (v0,v0)
| some i => endpoints i))
theorem roundedWeights_cut_error {I : Type} [Fintype I] {N : ℕ}
(p : Law I) (query : I → Fin N × Fin N) (v0 : Fin N)
(P : ℕ) (hP : 0 < P) (σ : Fin N → Bool) :
let w := aggregate (p.push query)
let w' := roundedWeights p query v0 P hP
weightedCut (fun u v => (w' u v : ℝ)) σ ≤ weightedCut (fun u v => (w u v : ℝ)) σ ∧
weightedCut (fun u v => (w u v : ℝ)) σ -
weightedCut (fun u v => (w' u v : ℝ)) σ ≤ Fintype.card I / (P : ℝ) := by
dsimp only
rw [aggregate_cut, Law.push_average, roundedWeights, aggregate_cut, Law.push_average,
Law.grid_average _ _ _ _ (by simp)]
exact Law.grid_average_bounds p P hP (fun i => if σ (query i).1 ≠ σ (query i).2 then 1 else 0)
(fun i => by split_ifs <;> norm_num) (fun i => by split_ifs <;> norm_num)
theorem roundedWeights_max_error {I : Type} [Fintype I] {N : ℕ}
(p : Law I) (query : I → Fin N × Fin N) (v0 : Fin N)
(P : ℕ) (hP : 0 < P) :
let w := aggregate (p.push query)
let w' := roundedWeights p query v0 P hP
weightedMax (fun u v => (w' u v : ℝ)) ≤ weightedMax (fun u v => (w u v : ℝ)) ∧
weightedMax (fun u v => (w u v : ℝ)) -
weightedMax (fun u v => (w' u v : ℝ)) ≤ Fintype.card I / (P : ℝ) := by
dsimp only
obtain ⟨σ, hσ⟩ := weightedMax_attained (fun u v =>
(roundedWeights p query v0 P hP u v : ℝ))
obtain ⟨τ, hτ⟩ := weightedMax_attained (fun u v => (aggregate (p.push query) u v : ℝ))
constructor
· have h := (roundedWeights_cut_error p query v0 P hP σ).1
exact hσ.symm.trans_le (h.trans (weightedCut_le_max _ _))
· have h := (roundedWeights_cut_error p query v0 P hP τ).2
have h' := weightedCut_le_max (fun u v => (roundedWeights p query v0 P hP u v : ℝ)) τ
rw [hτ] at h
linarith
end OptimalMaxCut.LongCode
end
end OAI
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