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Add lean source and binary files (part 126)
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import OAI.Probability.RandomSAT.ClauseProcess
namespace OAI
/-!
Finite Bernoulli-count expectations and integrated telescoping estimates.
-/
namespace FixedClauseThreshold
open Finset
noncomputable section
attribute [local instance] Classical.propDecidable
def binomialMean (p : ℝ) : ℕ → (ℕ → ℝ) → ℝ
| 0, f => f 0
| m + 1, f => (1 - p) * binomialMean p m f +
p * binomialMean p m (fun d => f (d + 1))
theorem binomialMean_congr {p : ℝ} {m : ℕ} {f g : ℕ → ℝ}
(h : ∀ d ≤ m, f d = g d) : binomialMean p m f = binomialMean p m g := by
induction m generalizing f g with
| zero => exact h 0 (by omega)
| succ m ih =>
simp only [binomialMean]
rw [ih (fun d hd => h d (by omega)), ih (fun d hd => h (d + 1) (by omega))]
theorem binomialMean_const (p c : ℝ) (m : ℕ) : binomialMean p m (fun _ => c) = c := by
induction m with
| zero => rfl
| succ m ih => simp only [binomialMean, ih]; ring
theorem binomialMean_add (p : ℝ) (m : ℕ) (f g : ℕ → ℝ) :
binomialMean p m (fun d => f d + g d) = binomialMean p m f + binomialMean p m g := by
induction m generalizing f g with
| zero => rfl
| succ m ih => simp only [binomialMean, ih]; ring
theorem binomialMean_sub (p : ℝ) (m : ℕ) (f g : ℕ → ℝ) :
binomialMean p m (fun d => f d - g d) = binomialMean p m f - binomialMean p m g := by
induction m generalizing f g with
| zero => rfl
| succ m ih => simp only [binomialMean, ih]; ring
theorem binomialMean_mul_const (p c : ℝ) (m : ℕ) (f : ℕ → ℝ) :
binomialMean p m (fun d => f d * c) = binomialMean p m f * c := by
induction m generalizing f with
| zero => rfl
| succ m ih => simp only [binomialMean, ih]; ring
theorem binomialMean_const_mul (p c : ℝ) (m : ℕ) (f : ℕ → ℝ) :
binomialMean p m (fun d => c * f d) = c * binomialMean p m f := by
simpa only [mul_comm] using binomialMean_mul_const p c m f
theorem binomialMean_sum {ι : Type*} (p : ℝ) (m : ℕ) (s : Finset ι) (f : ι → ℕ → ℝ) :
binomialMean p m (fun d => ∑ i ∈ s, f i d) = ∑ i ∈ s, binomialMean p m (f i) := by
induction s using Finset.induction_on with
| empty => simp [binomialMean_const]
| @insert i s hi ih =>
simp only [Finset.sum_insert hi, binomialMean_add, ih]
theorem binomialMean_mono {p : ℝ} {m : ℕ} (hp0 : 0 ≤ p) (hp1 : p ≤ 1)
{f g : ℕ → ℝ} (h : ∀ d ≤ m, f d ≤ g d) : binomialMean p m f ≤ binomialMean p m g := by
induction m generalizing f g with
| zero => exact h 0 (by omega)
| succ m ih =>
exact add_le_add
(mul_le_mul_of_nonneg_left (ih (fun d hd => h d (by omega))) (sub_nonneg.mpr hp1))
(mul_le_mul_of_nonneg_left (ih (fun d hd => h (d + 1) (by omega))) hp0)
theorem binomialMean_nonneg {p : ℝ} {m : ℕ} (hp0 : 0 ≤ p) (hp1 : p ≤ 1)
{f : ℕ → ℝ} (h : ∀ d ≤ m, 0 ≤ f d) : 0 ≤ binomialMean p m f := by
simpa only [binomialMean_const] using binomialMean_mono hp0 hp1 h
theorem binomialMean_id (p : ℝ) (m : ℕ) :
binomialMean p m (fun d => (d : ℝ)) = (m : ℝ) * p := by
induction m with
| zero => simp [binomialMean]
| succ m ih =>
simp only [binomialMean, Nat.cast_add, Nat.cast_one, binomialMean_add,
binomialMean_const, ih]
ring
theorem binomialMean_monotone_trials {p : ℝ} (hp0 : 0 ≤ p) (hp1 : p ≤ 1)
{f : ℕ → ℝ} (hf : Monotone f) : Monotone (fun m => binomialMean p m f) := by
apply monotone_nat_of_le_succ
intro m
have h := binomialMean_mono (m := m) hp0 hp1 (f := f) (g := fun d => f (d + 1))
(fun d _ => hf (by omega))
change _ ≤ (1 - p) * _ + p * _
nlinarith
theorem uniformMean_binomialMean {α : Type*} [Fintype α]
(p : ℝ) (m : ℕ) (f : ℕ → α → ℝ) :
uniformMean (fun a => binomialMean p m (fun d => f d a)) =
binomialMean p m (fun d => uniformMean (f d)) := by
induction m generalizing f with
| zero => rfl
| succ m ih =>
simp only [binomialMean, uniformMean_add, uniformMean_const_mul, ih]
theorem sum_shift_difference_le (P : ℕ → ℝ) (hP0 : ∀ j, 0 ≤ P j)
(hP1 : ∀ j, P j ≤ 1) (l b : ℕ) :
∑ j ∈ Finset.range l, (P j - P (j + b)) ≤ (b : ℝ) := by
have h1 := Finset.sum_range_add P l b
have h2 := Finset.sum_range_add P b l
have hid : (∑ j ∈ Finset.range l, (P j - P (j + b))) =
∑ j ∈ Finset.range b, (P j - P (j + l)) := by
rw [Finset.sum_sub_distrib, Finset.sum_sub_distrib]
have hc : l + b = b + l := Nat.add_comm _ _
simp only [Nat.add_comm l] at h1
simp only [Nat.add_comm b] at h2
rw [hc] at h2
linarith
rw [hid]
calc
_ ≤ ∑ _j ∈ Finset.range b, (1 : ℝ) := by
apply Finset.sum_le_sum
intro j _
linarith [hP0 (j + l), hP1 j]
_ = b := by simp
theorem sum_two_shift_difference_le (P : ℕ → ℝ) (hP0 : ∀ j, 0 ≤ P j)
(hP1 : ∀ j, P j ≤ 1) (l a b : ℕ) :
∑ j ∈ Finset.range l, (P (j - a) - P (j + b)) ≤ (a : ℝ) + b := by
have h1 := sum_shift_difference_le (fun j => P (j - a))
(fun j => hP0 _) (fun j => hP1 _) l a
simp only [Nat.add_sub_cancel] at h1
have h2 := sum_shift_difference_le P hP0 hP1 l b
have he : (∑ j ∈ Finset.range l, (P (j - a) - P (j + b))) =
(∑ j ∈ Finset.range l, (P (j - a) - P j)) +
∑ j ∈ Finset.range l, (P j - P (j + b)) := by
rw [← Finset.sum_add_distrib]
apply Finset.sum_congr rfl
intro j _
ring
rw [he]
linarith
def replacementDifference (P : ℕ → ℝ) (g j d : ℕ) : ℝ :=
P (j - d) - P (j + (g - 1) * d)
theorem replacementDifference_mono {P : ℕ → ℝ} (hP : Antitone P) (g j : ℕ) :
Monotone (replacementDifference P g j) := by
intro d e hde
apply sub_le_sub
· exact hP (Nat.sub_le_sub_left hde j)
· exact hP (Nat.add_le_add_left (Nat.mul_le_mul_left _ hde) j)
theorem replacementDifference_sum_le {P : ℕ → ℝ}
(hP0 : ∀ j, 0 ≤ P j) (hP1 : ∀ j, P j ≤ 1) {g : ℕ} (hg : 1 ≤ g) (l d : ℕ) :
∑ j ∈ Finset.range l, replacementDifference P g j d ≤ (g : ℝ) * d := by
have h := sum_two_shift_difference_le P hP0 hP1 l d ((g - 1) * d)
have he : (d : ℝ) + ((g - 1) * d : ℕ) = (g : ℝ) * d := by
rw [Nat.cast_mul, Nat.cast_sub hg]
push_cast
ring
simpa only [replacementDifference, he] using h
theorem binomial_replacement_sum_le {p : ℝ} (hp0 : 0 ≤ p) (hp1 : p ≤ 1)
{P : ℕ → ℝ} (hP : Antitone P) (hP0 : ∀ j, 0 ≤ P j) (hP1 : ∀ j, P j ≤ 1)
{g : ℕ} (hg : 1 ≤ g) (M : ℕ) :
∑ j ∈ Finset.range (M + 1), binomialMean p j (replacementDifference P g j) ≤
(g : ℝ) * (M : ℝ) * p := by
calc
_ ≤ ∑ j ∈ Finset.range (M + 1), binomialMean p M (replacementDifference P g j) := by
apply Finset.sum_le_sum
intro j hj
have hjM : j ≤ M := by simpa only [Finset.mem_range, Nat.lt_succ_iff] using hj
exact binomialMean_monotone_trials hp0 hp1 (replacementDifference_mono hP g j) hjM
_ = binomialMean p M (fun d => ∑ j ∈ Finset.range (M + 1),
replacementDifference P g j d) := (binomialMean_sum _ _ _ _).symm
_ ≤ binomialMean p M (fun d => (g : ℝ) * d) :=
binomialMean_mono hp0 hp1 (fun d _ => replacementDifference_sum_le hP0 hP1 hg _ d)
_ = _ := by rw [binomialMean_const_mul, binomialMean_id]; ring
end
end FixedClauseThreshold
end OAI