import OAI.Probability.SATVariance.CappedUpper namespace OAI noncomputable section open MeasureTheory ProbabilityTheory namespace RandomKSAT open scoped Classical ENNReal lemma T_eq_min_natH_ae {n k : ℕ} (hkn : k ≤ n) (B : ℝ) : ∀ᵐ ω ∂streamLaw n k, T B ω = ((min (firstFailure ω).toNat (cap n B) : ℕ) : ℝ) := by filter_upwards [firstFailure_finite_ae hkn] with ω hω have he := ENat.natCast_toNat (ne_of_lt hω) by_cases h : (firstFailure ω).toNat ≤ cap n B · have hEN : firstFailure ω ≤ (cap n B : ℕ∞) := by rw [← he]; exact_mod_cast h simp only [T, min_eq_left hEN, min_eq_left h] · have hEN : (cap n B : ℕ∞) ≤ firstFailure ω := by rw [← he]; exact_mod_cast (le_of_not_ge h) simp only [T, min_eq_right hEN, min_eq_right (le_of_not_ge h), ENat.toNat_natCast] lemma cap_error_eq_nat_ae {n k : ℕ} (hkn : k ≤ n) (B : ℝ) : ∀ᵐ ω ∂streamLaw n k, (H ω-T B ω)^2 = (((firstFailure ω).toNat-cap n B : ℕ) : ℝ)^2 := by filter_upwards [T_eq_min_natH_ae hkn B] with ω hω rw [hω, H, ← Nat.cast_sub (Nat.min_le_left _ _)] congr 2 omega lemma natH_integral {n k : ℕ} (hkn : k ≤ n) (f : ℕ → ℝ) : (∫ ω, f (firstFailure ω).toNat ∂streamLaw n k) = ∑' m, ((streamLaw n k).map (fun ω => (firstFailure ω).toNat) {m}).toReal * f m := by let := streamLaw_probability n k hkn rw [← integral_map (measurable_natH n k).aemeasurable (measurable_of_countable f).aestronglyMeasurable] conv_lhs => rw [ ← Measure.sum_smul_dirac ((streamLaw n k).map (fun ω => (firstFailure ω).toNat)), integral_sum_dirac (fun _ => measure_ne_top _ _)] rfl lemma summable_sub_sq_geometric {q : ℝ} (hq : 0 ≤ q) (hq1 : q < 1) (M : ℕ) : Summable (fun m : ℕ => ((m-M : ℕ) : ℝ)^2*q^m) := by have hn : ‖q‖ < 1 := by simpa [Real.norm_eq_abs, abs_of_nonneg hq] using hq1 apply Summable.of_nonneg_of_le (fun m => by positivity) _ (summable_pow_mul_geometric_of_norm_lt_one 2 hn) intro m exact mul_le_mul_of_nonneg_right (pow_le_pow_left₀ (by positivity) (by exact_mod_cast Nat.sub_le m M) 2) (pow_nonneg hq m) lemma tsum_sub_sq_geometric {q : ℝ} (hq : 0 ≤ q) (hq1 : q < 1) (M : ℕ) : (∑' m : ℕ, ((m-M : ℕ) : ℝ)^2*q^m) = q^M * ∑' j : ℕ, (j : ℝ)^2*q^j := by have hs := summable_sub_sq_geometric hq hq1 M have he := hs.sum_add_tsum_nat_add M have hz : ∑ m ∈ Finset.range M, ((m-M : ℕ) : ℝ)^2*q^m = 0 := by apply Finset.sum_eq_zero intro m hm simp only [Nat.sub_eq_zero_of_le (le_of_lt (Finset.mem_range.mp hm)), Nat.cast_zero, ne_eq, OfNat.ofNat_ne_zero, not_false_eq_true, zero_pow, zero_mul] rw [hz, zero_add] at he rw [← he, ← tsum_mul_left] apply tsum_congr intro j rw [Nat.add_sub_cancel, pow_add] ring lemma cap_error_geom {n k : ℕ} (hk : 1 ≤ k) (hkn : k ≤ n) (B : ℝ) : (∫ ω : Stream n k, (H ω-T B ω)^2 ∂streamLaw n k) ≤ ((2 : ℝ)^n * (1-((2 : ℝ)^k)⁻¹)^(cap n B)) / (1-((2 : ℝ)^k)⁻¹) * ∑' j : ℕ, (j : ℝ)^2*(1-((2 : ℝ)^k)⁻¹)^j := by let q := 1-((2 : ℝ)^k)⁻¹ have hq : 0 < q := real_rate_pos hk have hq1 : q < 1 := real_rate_lt_one k rw [integral_congr_ae (cap_error_eq_nat_ae hkn B), natH_integral hkn (fun m => (((m-cap n B : ℕ) : ℝ)^2))] have hb (m : ℕ) := mul_le_mul_of_nonneg_right (natH_mass_bound hk hkn m) (sq_nonneg (((m-cap n B : ℕ) : ℝ))) have hs := (summable_sub_sq_geometric hq.le hq1 (cap n B)).mul_left ((2 : ℝ)^n/q) have ht : Summable (fun m : ℕ => ((streamLaw n k).map (fun ω => (firstFailure ω).toNat) {m}).toReal * (((m-cap n B : ℕ) : ℝ)^2)) := by apply Summable.of_nonneg_of_le (fun _ => by positivity) _ hs intro m calc _ ≤ (((2 : ℝ)^n/q)*q^m)*(((m-cap n B : ℕ) : ℝ)^2) := hb m _ = _ := by ring calc _ ≤ ∑' m : ℕ, ((2 : ℝ)^n/q)*((((m-cap n B : ℕ) : ℝ)^2)*q^m) := by apply ht.tsum_le_tsum _ hs intro m convert hb m using 1 dsimp [q] ring _ = _ := by rw [tsum_mul_left, tsum_sub_sq_geometric hq.le hq1]; dsimp [q]; ring lemma U_pos {k : ℕ} (hk : 1 ≤ k) : 0 < U k := by have hq := real_rate_pos hk have hq1 := real_rate_lt_one k exact div_pos (Real.log_pos (by norm_num)) (neg_pos.mpr (Real.log_neg hq hq1)) lemma cap_geometric_uniform {k : ℕ} (hk : 1 ≤ k) {B : ℝ} (hB : U k ≤ B) (n : ℕ) : (2 : ℝ)^n * (1-((2 : ℝ)^k)⁻¹)^(cap n B) ≤ (1-((2 : ℝ)^k)⁻¹)⁻¹ := by let q := 1-((2 : ℝ)^k)⁻¹ have hq : 0 < q := real_rate_pos hk have hl : Real.log q < 0 := Real.log_neg hq (real_rate_lt_one k) have ht : Real.log 2 ≤ B*(-Real.log q) := (div_le_iff₀ (by linarith)).mp hB have hf : B*n < (cap n B : ℝ)+1 := Nat.lt_floor_add_one _ apply (Real.log_le_log_iff (mul_pos (by positivity) (pow_pos hq _)) (inv_pos.mpr hq)).mp rw [Real.log_mul (by positivity) (ne_of_gt (pow_pos hq _)), Real.log_pow, Real.log_pow, Real.log_inv] have hh := mul_le_mul_of_nonneg_left ht (Nat.cast_nonneg n : (0 : ℝ) ≤ n) change _ ≤ -Real.log q nlinarith def bridgeC (k : ℕ) : ℝ := (1-((2 : ℝ)^k)⁻¹)⁻¹^2 * ∑' j : ℕ, (j : ℝ)^2*(1-((2 : ℝ)^k)⁻¹)^j lemma bridgeC_nonneg {k : ℕ} (hk : 1 ≤ k) : 0 ≤ bridgeC k := by unfold bridgeC exact mul_nonneg (sq_nonneg _) (tsum_nonneg (fun j => by positivity [real_rate_pos hk])) lemma cap_error_uniform {n k : ℕ} (hk : 1 ≤ k) (hkn : k ≤ n) {B : ℝ} (hB : U k ≤ B) : (∫ ω : Stream n k, (H ω-T B ω)^2 ∂streamLaw n k) ≤ bridgeC k := by have hq := real_rate_pos hk have hb := cap_error_geom hk hkn B have hz : 0 ≤ ∑' j : ℕ, (j : ℝ)^2*(1-((2 : ℝ)^k)⁻¹)^j := tsum_nonneg (fun _ => by positivity) have hh := mul_le_mul_of_nonneg_right ((div_le_div_iff_of_pos_right hq).mpr (cap_geometric_uniform hk hB n)) hz apply hb.trans convert hh using 1 dsimp [bridgeC] ring lemma variance_bridge.{u_1} {Ω : Type u_1} [MeasurableSpace Ω] {μ : Measure Ω} [IsProbabilityMeasure μ] {f g : Ω → ℝ} (hf : MemLp f 2 μ) (hg : MemLp g 2 μ) : variance f μ ≤ 2*variance g μ + 2*(∫ ω, (f ω-g ω)^2 ∂μ) := by let c := ∫ ω, g ω ∂μ have hfc := hf.sub (memLp_const c) have hgc := hg.sub (memLp_const c) have hfg := hf.sub hg have hv := variance_le_expectation_sq hfc.aestronglyMeasurable simp only [Pi.sub_apply, Pi.pow_apply] at hv change variance (fun ω => f ω-c) μ ≤ (∫ ω, (f ω-c)^2 ∂μ) at hv rw [variance_sub_const hf.aestronglyMeasurable] at hv have hm := integral_mono hfc.integrable_sq ((hgc.integrable_sq.const_mul 2).add (hfg.integrable_sq.const_mul 2)) (fun ω => by dsimp; nlinarith [sq_nonneg ((f ω-g ω)-(g ω-c))]) change (∫ ω, (f ω-c)^2 ∂μ) ≤ (∫ ω, 2*(g ω-c)^2+2*(f ω-g ω)^2 ∂μ) at hm have hgi : Integrable (fun ω => (g ω-c)^2) μ := hgc.integrable_sq have hfgi : Integrable (fun ω => (f ω-g ω)^2) μ := hfg.integrable_sq rw [integral_add (hgi.const_mul 2) (hfgi.const_mul 2), integral_const_mul, integral_const_mul, ← variance_eq_integral hg.aemeasurable] at hm exact hv.trans hm lemma H_variance_le_cap {n k : ℕ} (hk : 1 ≤ k) (hkn : k ≤ n) {B : ℝ} (hB : U k ≤ B) : variance (H : Stream n k → ℝ) (streamLaw n k) ≤ 2*variance (T B : Stream n k → ℝ) (streamLaw n k)+2*bridgeC k := by let := streamLaw_probability n k hkn exact (variance_bridge (H_memLp_two hk hkn) (T_memLp hkn B 2)).trans (by linarith [cap_error_uniform hk hkn hB]) lemma cap_variance_le_H {n k : ℕ} (hk : 1 ≤ k) (hkn : k ≤ n) {B : ℝ} (hB : U k ≤ B) : variance (T B : Stream n k → ℝ) (streamLaw n k) ≤ 2*variance (H : Stream n k → ℝ) (streamLaw n k)+2*bridgeC k := by let := streamLaw_probability n k hkn have hh := variance_bridge (T_memLp hkn B 2) (H_memLp_two hk hkn) have he : (∫ ω : Stream n k, (T B ω-H ω)^2 ∂streamLaw n k) = ∫ ω : Stream n k, (H ω-T B ω)^2 ∂streamLaw n k := by congr 1 funext ω ring rw [he] at hh exact hh.trans (by linarith [cap_error_uniform hk hkn hB]) theorem uncapped_variance_upper (k : ℕ) (hk : 3 ≤ k) : ∃ C : ℝ, 0 ≤ C ∧ ∀ n : ℕ, k ≤ n → variance (H : Stream n k → ℝ) (streamLaw n k) ≤ C*n*ell k n := by have hk1 : 1 ≤ k := by omega obtain ⟨C,hC,hv⟩ := capped_variance_upper k hk (U k) (U_pos hk1) refine ⟨2*C+2*bridgeC k, by positivity [bridgeC_nonneg hk1], fun n hkn => ?_⟩ have hh := H_variance_le_cap hk1 hkn (le_refl (U k)) have hn : (1 : ℝ) ≤ n := by exact_mod_cast (hk1.trans hkn) have he := ell_one_le k n (hk1.trans hkn) have hb := bridgeC_nonneg hk1 have hm : 1 ≤ (n : ℝ)*ell k n := by nlinarith have hm' := mul_le_mul_of_nonneg_left hm hb nlinarith [hv n hkn] end RandomKSAT end end OAI