openAI-math-dataset / lean /OAI /NumberTheory /TwoPoint /Halasz /HalaszCollisionAbsorption.lean
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Add lean source and binary files (part 117)
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import OAI.NumberTheory.TwoPoint.Halasz.HalaszCollisionMoment
import OAI.NumberTheory.TwoPoint.Halasz.HalaszVinogradovProduct
namespace OAI
/-! Absorbing the contribution of repeated long coordinates by the
diagonal lower bound for the complete mean value. -/
namespace TwoPointCorrelations
lemma halasz_collision_algebra {k : ℕ} (hk : 0<k) {A B I C R : ℝ}
(hA : 0<A) (hB : 0<B) (hC : 0≤C) (hR : C^2<R)
(hdiag : R^k*B≤A) (hmoment : I^(2*k)≤A^(2*k-1)*B) : C*I<A := by
by_contra hn
have hAI : A≤C*I := le_of_not_gt hn
have hpow := pow_le_pow_left₀ hA.le hAI (2*k)
rw [mul_pow] at hpow
have ha : A^(2*k) ≤ C^(2*k)*A^(2*k-1)*B := by
calc
A^(2*k) ≤ C^(2*k)*I^(2*k) := hpow
_ ≤ C^(2*k)*(A^(2*k-1)*B) :=
mul_le_mul_of_nonneg_left hmoment (pow_nonneg hC _)
_ = _ := by ring
have hb := halasz_collision_power_absorb (by omega : 1≤2*k) hA ha
have hRpow : C^(2*k)<R^k := by
rw [pow_mul]
exact pow_lt_pow_left₀ hR (sq_nonneg C) (by omega)
have hstrict : C^(2*k)*B<R^k*B := mul_lt_mul_of_pos_right hRpow hB
linarith
theorem halasz_collision_moment_small {s k N : ℕ} (hs : 0<s) (hk : 2≤k)
{C : ℝ} (hC : 0≤C) (hN : C^2<N) :
C*halaszCollisionMoment s k N < (halaszVinogradovCount (s+k) k N:ℝ) := by
have hN0 : 0<N := by exact_mod_cast lt_of_le_of_lt (sq_nonneg C) hN
have hJs : 0<(halaszVinogradovCount s k N:ℝ) := by
exact_mod_cast lt_of_lt_of_le (Nat.pow_pos hN0) (halasz_vinogradov_count_lower s k N)
have hJ : 0<(halaszVinogradovCount (s+k) k N:ℝ) := by
exact_mod_cast lt_of_lt_of_le (Nat.pow_pos hN0)
(halasz_vinogradov_count_lower (s+k) k N)
have hdiag : (N:ℝ)^k*(halaszVinogradovCount s k N:ℝ) ≤
(halaszVinogradovCount (s+k) k N:ℝ) := by
exact_mod_cast (by simpa only [Nat.add_comm k s] using
halasz_vinogradov_diagonal_extension s k N)
exact halasz_collision_algebra (by omega : 0<k) hJ hJs hC hN hdiag
(halasz_collision_moment_bound hs hk N)
end TwoPointCorrelations
end OAI