Download lean/OAI/NumberTheory/TwoPoint/Halasz/HalaszClassicalStep.lean from roseking/openAI-math-dataset: direct link, hf CLI and curl.
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https://huggingface.co/datasets/roseking/openAI-math-dataset/resolve/main/lean/OAI/NumberTheory/TwoPoint/Halasz/HalaszClassicalStep.lean
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hf download hf://datasets/roseking/openAI-math-dataset/lean/OAI/NumberTheory/TwoPoint/Halasz/HalaszClassicalStep.lean
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curl -L -o HalaszClassicalStep.lean https://huggingface.co/datasets/roseking/openAI-math-dataset/resolve/main/lean/OAI/NumberTheory/TwoPoint/Halasz/HalaszClassicalStep.lean
1.38 kB
| import OAI.NumberTheory.TwoPoint.Halasz.HalaszPrimeSupply | |
| namespace OAI | |
| /-! The classical mean-value step using a finite supply of primes. | |
| The absolute lower threshold for R comes only from Chebyshev's bounds. -/ | |
| namespace TwoPointCorrelations | |
| open Finset Filter | |
| open scoped Classical | |
| theorem halasz_classical_step : ∃ R₀ : ℕ, ∀ s k N R : ℕ, | |
| 0<s → 2≤k → (4*(k:ℝ)^2)^2<(N:ℝ) → k<R → N<R^k → | |
| R₀≤R → (2*(k^2*k)+1)^2≤R → | |
| halaszVinogradovCount (k+s) k N ≤ | |
| 2*(2*(k^2*k)+1)*((16*R)^(2*s)*((k^k*(16*R)^(k*(k-1)/2))* | |
| (N^k*halaszVinogradovCount s k (N/R+1)))) := by | |
| obtain ⟨R₀,hR₀⟩ := eventually_atTop.mp halasz_prime_supply_card | |
| refine ⟨R₀,?_⟩ | |
| intro s k N R hs hk hsize hkR hNR hR0 hmany | |
| have hroot : ((2*(k^2*k)+1:ℕ):ℝ)≤Real.sqrt (R:ℝ) := by | |
| apply Real.le_sqrt_of_sq_le | |
| exact_mod_cast hmany | |
| have hcard : 2*(k^2*k)+1≤(halaszPrimeSupply R).card := by | |
| exact_mod_cast hroot.trans (hR₀ R hR0) | |
| obtain ⟨P,hP,hPcard⟩ := exists_subset_card_eq hcard | |
| have hb : ∀ p∈P, p.Prime ∧ R≤p ∧ p≤16*R := by | |
| intro p hp | |
| have hh := halasz_prime_supply_mem (hP hp) | |
| exact ⟨hh.1,hh.2.1.le,hh.2.2⟩ | |
| have h := halasz_vinogradov_prime_recurrence hs hk hsize hkR hNR P hb | |
| (by rw [hPcard]; omega) | |
| simpa only [hPcard] using h | |
| end TwoPointCorrelations | |
| end OAI | |