import Mathlib.Algebra.BigOperators.Fin import Mathlib.Algebra.Order.BigOperators.Expect import Mathlib.Data.Fin.Tuple.Basic import Mathlib.Data.Fintype.Pi import Mathlib.Basic.Real.Basic import Mathlib.Tactic.FieldSimp import Mathlib.Tactic.Linarith import Mathlib.Tactic.NormNum import Mathlib.Tactic.Positivity import Mathlib.Tactic.Ring namespace OAI namespace BinPackingGames.Foundations.PCP.LazySmoothing open scoped BigOperators def bitCount {n : ℕ} (tape : Fin n → Bool) : ℕ := ∑ i, if tape i then 1 else 0 noncomputable def binomialMean (n : ℕ) (g : ℕ → ℝ) : ℝ := Finset.univ.expect (fun tape : Fin n → Bool => g (bitCount tape)) def splitTape (n : ℕ) : (Fin (n + 1) → Bool) ≃ (Bool × (Fin n → Bool)) where toFun x := (x 0, fun i => x i.succ) invFun x := Fin.cases x.1 x.2 left_inv x := by funext i exact Fin.cases rfl (fun _ => rfl) i right_inv _ := rfl theorem bitCount_succ {n : ℕ} (x : Fin (n + 1) → Bool) : bitCount x = (if x 0 then 1 else 0) + bitCount (fun i => x i.succ) := by exact Fin.sum_univ_succ _ theorem mean_congr {n : ℕ} {f g : ℕ → ℝ} (h : ∀ k, f k = g k) : binomialMean n f = binomialMean n g := by unfold binomialMean exact Finset.expect_congr rfl (fun x _ => h (bitCount x)) @[simp] theorem mean_const (n : ℕ) (c : ℝ) : binomialMean n (fun _ => c) = c := Fintype.expect_const c theorem mean_add (n : ℕ) (f g : ℕ → ℝ) : binomialMean n (fun k => f k + g k) = binomialMean n f + binomialMean n g := Finset.expect_add_distrib _ _ _ theorem mean_sub (n : ℕ) (f g : ℕ → ℝ) : binomialMean n (fun k => f k - g k) = binomialMean n f - binomialMean n g := Finset.expect_sub_distrib _ _ _ theorem mean_mul (n : ℕ) (c : ℝ) (f : ℕ → ℝ) : binomialMean n (fun k => c * f k) = c * binomialMean n f := by exact (Finset.mul_expect Finset.univ (fun x : Fin n → Bool => f (bitCount x)) c).symm @[simp] theorem mean_zero (g : ℕ → ℝ) : binomialMean 0 g = g 0 := by simp [binomialMean, bitCount] theorem expect_bool (f : Bool → ℝ) : Finset.univ.expect f = (f false + f true) / 2 := by rw [Finset.expect_eq_sum_div_card] simp [Fintype.univ_bool, add_comm] theorem mean_succ (n : ℕ) (g : ℕ → ℝ) : binomialMean (n + 1) g = (binomialMean n g + binomialMean n (fun k => g (k + 1))) / 2 := by unfold binomialMean rw [Fintype.expect_equiv (splitTape n) (fun x => g (bitCount x)) (fun x => g ((if x.1 then 1 else 0) + bitCount x.2)) (fun x => congrArg g (bitCount_succ x))] rw [← Finset.univ_product_univ, Finset.expect_product, expect_bool] simp [Nat.add_comm] def score (n k : ℕ) : ℝ := (n : ℝ) - 2 * (k : ℝ) noncomputable def scoreMean (n : ℕ) (g : ℕ → ℝ) : ℝ := binomialMean n (fun k => score n k * g k) @[simp] theorem scoreMean_zero (g : ℕ → ℝ) : scoreMean 0 g = 0 := by simp [scoreMean, score] theorem scoreMean_succ (n : ℕ) (g : ℕ → ℝ) : scoreMean (n + 1) g = ((scoreMean n g + binomialMean n g) + (scoreMean n (fun k => g (k + 1)) - binomialMean n (fun k => g (k + 1)))) / 2 := by unfold scoreMean rw [mean_succ] have h₁ : (fun k => score (n + 1) k * g k) = (fun k => score n k * g k + g k) := by funext k simp only [score, Nat.cast_add, Nat.cast_one] ring have h₂ : (fun k => score (n + 1) (k + 1) * g (k + 1)) = (fun k => score n k * g (k + 1) - g (k + 1)) := by funext k simp only [score, Nat.cast_add, Nat.cast_one] ring rw [h₁, h₂, mean_add, mean_sub] theorem score_identity (n : ℕ) (g : ℕ → ℝ) : scoreMean (n + 1) g = ((n : ℝ) + 1) / 2 * (binomialMean n g - binomialMean n (fun k => g (k + 1))) := by induction n generalizing g with | zero => simp [scoreMean_succ]; ring | succ n ih => rw [scoreMean_succ, ih g, ih (fun k => g (k + 1))] simp only [mean_succ, Nat.cast_add, Nat.cast_one] ring theorem score_mean_zero (n : ℕ) : binomialMean n (score n) = 0 := by cases n with | zero => simp [score] | succ n => have h := score_identity n (fun _ => 1) simpa [scoreMean] using h theorem score_second_moment (n : ℕ) : binomialMean n (fun k => score n k ^ 2) = (n : ℝ) := by cases n with | zero => simp [score] | succ n => have h := score_identity n (score (n + 1)) have hd : binomialMean n (score (n + 1)) - binomialMean n (fun k => score (n + 1) (k + 1)) = 2 := by rw [← mean_sub] calc _ = binomialMean n (fun _ => 2) := by apply mean_congr intro k simp only [score, Nat.cast_add, Nat.cast_one] ring _ = 2 := mean_const _ _ rw [hd] at h simpa [scoreMean, pow_two] using h theorem score_difference (n : ℕ) (g : ℕ → ℝ) : scoreMean (n + 1) g = ((n : ℝ) + 1) * (binomialMean n g - binomialMean (n + 1) g) := by rw [score_identity, mean_succ] ring theorem adjacent_difference_sq (n : ℕ) (g : ℕ → ℝ) (hg : ∀ k, 0 ≤ g k ∧ g k ≤ 1) : 4 * ((n : ℝ) + 1) * (binomialMean n g - binomialMean (n + 1) g) ^ 2 ≤ 1 := by have hc : binomialMean (n + 1) (fun k => score (n + 1) k * (g k - 1 / 2)) = scoreMean (n + 1) g := by calc _ = binomialMean (n + 1) (fun k => score (n + 1) k * g k - (1 / 2) * score (n + 1) k) := by apply mean_congr intro k ring _ = scoreMean (n + 1) g := by rw [mean_sub, mean_mul, score_mean_zero] simp [scoreMean] have hv : binomialMean (n + 1) (fun k => (g k - 1 / 2) ^ 2) ≤ 1 / 4 := by apply Finset.expect_le Finset.univ_nonempty intro tape _ have h₀ := (hg (bitCount tape)).1 have h₁ := (hg (bitCount tape)).2 have hp := mul_nonneg h₀ (sub_nonneg.mpr h₁) nlinarith have hcs : (binomialMean (n + 1) (fun k => score (n + 1) k * (g k - 1 / 2))) ^ 2 ≤ binomialMean (n + 1) (fun k => score (n + 1) k ^ 2) * binomialMean (n + 1) (fun k => (g k - 1 / 2) ^ 2) := Finset.expect_mul_sq_le_sq_mul_sq Finset.univ _ _ rw [hc, score_difference, score_second_moment] at hcs have hn : 0 < (n : ℝ) + 1 := by positivity have hm := mul_le_mul_of_nonneg_left hv (le_of_lt hn) simp only [Nat.cast_add, Nat.cast_one] at hcs apply (mul_le_mul_iff_left₀ hn).mp nlinarith theorem adjacent_difference_le (n : ℕ) (g : ℕ → ℝ) (hg : ∀ k, 0 ≤ g k ∧ g k ≤ 1) (r : ℝ) (hr : 0 < r) (hrn : r ^ 2 ≤ 4 * ((n : ℝ) + 1)) : |binomialMean n g - binomialMean (n + 1) g| ≤ 1 / r := by have hs := adjacent_difference_sq n g hg have hd := sq_nonneg (binomialMean n g - binomialMean (n + 1) g) have hh := mul_le_mul_of_nonneg_right hrn hd rw [le_div_iff₀ hr] have ha := sq_abs (binomialMean n g - binomialMean (n + 1) g) have hp : 0 ≤ |binomialMean n g - binomialMean (n + 1) g| * r := mul_nonneg (abs_nonneg _) (le_of_lt hr) nlinarith [sq_nonneg (|binomialMean n g - binomialMean (n + 1) g| * r - 1)] theorem mean_shift_le (n d : ℕ) (g : ℕ → ℝ) (hg : ∀ k, 0 ≤ g k ∧ g k ≤ 1) (r : ℝ) (hr : 0 < r) (hrn : r ^ 2 ≤ 4 * ((n : ℝ) + 1)) : |binomialMean (n + d) g - binomialMean n g| ≤ (d : ℝ) / r := by induction d with | zero => simp | succ d ih => have hrnd : r ^ 2 ≤ 4 * ((n + d : ℕ) + 1 : ℝ) := by push_cast have : (0 : ℝ) ≤ d := Nat.cast_nonneg _ linarith have ha := adjacent_difference_le (n + d) g hg r hr hrnd rw [abs_sub_comm] at ha calc _ ≤ |binomialMean (n + d + 1) g - binomialMean (n + d) g| + |binomialMean (n + d) g - binomialMean n g| := abs_sub_le _ _ _ _ ≤ 1 / r + (d : ℝ) / r := add_le_add ha ih _ = ((d + 1 : ℕ) : ℝ) / r := by push_cast; ring theorem mean_ordered_difference_le (m n : ℕ) (hmn : m ≤ n) (g : ℕ → ℝ) (hg : ∀ k, 0 ≤ g k ∧ g k ≤ 1) (r : ℝ) (hr : 0 < r) (hrm : r ^ 2 ≤ 4 * ((m : ℝ) + 1)) : |binomialMean n g - binomialMean m g| ≤ ((n - m : ℕ) : ℝ) / r := by simpa [Nat.add_sub_of_le hmn] using mean_shift_le m (n - m) g hg r hr hrm theorem mean_window_le (N M m : ℕ) (hlo : N - M ≤ m) (hhi : m ≤ N + M) (g : ℕ → ℝ) (hg : ∀ k, 0 ≤ g k ∧ g k ≤ 1) (r : ℝ) (hr : 0 < r) (hbase : r ^ 2 ≤ 4 * (((N - M : ℕ) : ℝ) + 1)) : |binomialMean m g - binomialMean N g| ≤ (M : ℝ) / r := by by_cases hmN : m ≤ N · have hrm : r ^ 2 ≤ 4 * ((m : ℝ) + 1) := by have : ((N - M : ℕ) : ℝ) ≤ (m : ℝ) := by exact_mod_cast hlo linarith have h := mean_ordered_difference_le m N hmN g hg r hr hrm rw [abs_sub_comm] at h refine h.trans (div_le_div_of_nonneg_right ?_ (le_of_lt hr)) have : N - m ≤ M := by omega exact_mod_cast this · have hNm : N ≤ m := Nat.le_of_lt (Nat.lt_of_not_ge hmN) have hrN : r ^ 2 ≤ 4 * ((N : ℝ) + 1) := by have : ((N - M : ℕ) : ℝ) ≤ (N : ℝ) := by exact_mod_cast Nat.sub_le N M linarith have h := mean_ordered_difference_le N m hNm g hg r hr hrN refine h.trans (div_le_div_of_nonneg_right ?_ (le_of_lt hr)) have : m - N ≤ M := by omega exact_mod_cast this theorem square_window_le (q M m : ℕ) (hq : 1 ≤ q) (hM : 1 ≤ M) (hlo : (4 * q * M) ^ 2 - M ≤ m) (hhi : m ≤ (4 * q * M) ^ 2 + M) (g : ℕ → ℝ) (hg : ∀ k, 0 ≤ g k ∧ g k ≤ 1) : |binomialMean m g - binomialMean ((4 * q * M) ^ 2) g| ≤ 1 / (4 * (q : ℝ)) := by have hqR : (1 : ℝ) ≤ q := by exact_mod_cast hq have hMR : (1 : ℝ) ≤ M := by exact_mod_cast hM have hR : (4 : ℝ) * M ≤ ((4 * q * M : ℕ) : ℝ) := by push_cast nlinarith have hRM : (M : ℝ) ≤ (((4 * q * M : ℕ) : ℝ)) ^ 2 := by nlinarith have hMN : M ≤ (4 * q * M) ^ 2 := by exact_mod_cast hRM have hr : (0 : ℝ) < ((4 * q * M : ℕ) : ℝ) := by linarith have hb : (((4 * q * M : ℕ) : ℝ)) ^ 2 ≤ 4 * (((((4 * q * M) ^ 2 - M : ℕ)) : ℝ) + 1) := by rw [Nat.cast_sub hMN, Nat.cast_pow] nlinarith have h := mean_window_le ((4 * q * M) ^ 2) M m hlo hhi g hg ((4 * q * M : ℕ) : ℝ) hr hb have he : (M : ℝ) / ((4 * q * M : ℕ) : ℝ) = 1 / (4 * (q : ℝ)) := by push_cast have hq0 : (q : ℝ) ≠ 0 := by linarith have hM0 : (M : ℝ) ≠ 0 := by linarith field_simp rw [he] at h exact h theorem modal_transfer (q M m : ℕ) (hq : 1 ≤ q) (hM : 1 ≤ M) (hlo : (4 * q * M) ^ 2 - M ≤ m) (hhi : m ≤ (4 * q * M) ^ 2 + M) (g : ℕ → ℝ) (hg : ∀ k, 0 ≤ g k ∧ g k ≤ 1) (hmodal : 1 / (q : ℝ) ≤ binomialMean ((4 * q * M) ^ 2) g) : 1 / (2 * (q : ℝ)) ≤ binomialMean m g := by have h := square_window_le q M m hq hM hlo hhi g hg have hqR : (0 : ℝ) < q := by exact_mod_cast (Nat.zero_lt_of_lt hq) have hrec : 0 < 1 / (q : ℝ) := one_div_pos.mpr hqR have he₁ : 1 / (4 * (q : ℝ)) = (1 / (q : ℝ)) / 4 := by ring have he₂ : 1 / (2 * (q : ℝ)) = (1 / (q : ℝ)) / 2 := by ring rw [he₁] at h rw [he₂] have hl := (abs_le.mp h).1 linarith end BinPackingGames.Foundations.PCP.LazySmoothing end OAI