Download lean/OAI/NumberTheory/Ostmann/ZeroDensity/ArithmeticProgressionRows.lean from roseking/openAI-math-dataset: direct link, hf CLI and curl.
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curl -L -o ArithmeticProgressionRows.lean https://huggingface.co/datasets/roseking/openAI-math-dataset/resolve/main/lean/OAI/NumberTheory/Ostmann/ZeroDensity/ArithmeticProgressionRows.lean
2.57 kB
| import OAI.NumberTheory.Ostmann.ZeroDensity.ProgressionErrorRates | |
| namespace OAI | |
| /-! # Giant and bulk progression rows used in the arithmetic comparison -/ | |
| namespace Ostmann | |
| open Filter | |
| inductive ArithmeticProgressionRow | |
| | giant | |
| | bulk | |
| deriving DecidableEq | |
| namespace ArithmeticProgressionRow | |
| noncomputable def leftExponent : ArithmeticProgressionRow → ℝ | |
| | giant => 49 / 1000 | |
| | bulk => 39 / 10000 | |
| noncomputable def modulusExponent : ArithmeticProgressionRow → ℝ | |
| | giant => 12 / 1000 | |
| | bulk => 12 / 10000 | |
| noncomputable def errorExponent : ArithmeticProgressionRow → ℝ | |
| | giant => 18 / 1000 | |
| | bulk => 16 / 10000 | |
| theorem gaps (r : ArithmeticProgressionRow) : | |
| 0 < r.leftExponent ∧ 0 < r.modulusExponent ∧ | |
| r.errorExponent < r.leftExponent / 2 ∧ | |
| r.errorExponent < r.leftExponent - r.modulusExponent ∧ | |
| 0 < r.leftExponent - r.modulusExponent := by | |
| cases r <;> norm_num [leftExponent, modulusExponent, errorExponent] | |
| end ArithmeticProgressionRow | |
| /-- Exactly the two rows of the manuscript's progression table, with one | |
| exceptional character for all moduli in the row. The logarithmic interval | |
| estimate is proved from the published theta and Page inputs. -/ | |
| theorem PublishedProgressionInput.row_log_interval (P : PublishedProgressionInput) | |
| (r : ArithmeticProgressionRow) : | |
| ∀ᶠ L : ℝ in atTop, ∀ (q Q a : ℕ), 2 ≤ Q → 1 ≤ q → q ≤ Q → a.Coprime q → | |
| Real.log (Q : ℝ) ≤ Real.exp (r.modulusExponent * L) → | |
| ∀ s t : ℝ, 1 ≤ s → Real.exp (r.leftExponent * L) ≤ s → s ≤ t → t ≤ s + 1 → | |
| |reciprocalPrimeInterval q a (Real.exp s) (Real.exp t) - | |
| ∫ y in Set.Ioc s t, primeLogDensity (Nat.totient q) | |
| (pageCoefficient (pageAtModulus q (selectedPageZero P Q)) a) | |
| (pageBeta (pageAtModulus q (selectedPageZero P Q))) y| ≤ | |
| 2 * Real.exp (-Real.exp (r.errorExponent * L)) := by | |
| obtain ⟨ha, hμ, hδa, hδμ, haμ⟩ := r.gaps | |
| filter_upwards [P.log_interval_rate r.leftExponent r.modulusExponent r.errorExponent | |
| ha hδa hδμ haμ, | |
| eventually_ge_atTop (Real.log 4 / r.modulusExponent)] with L hL hLlarge | |
| intro q Q a hQ hq hqQ hcop hlog | |
| apply hL q Q a hQ hq hqQ hcop | |
| have hQ0 : (Q : ℝ) ≠ 0 := by exact_mod_cast (by omega : Q ≠ 0) | |
| rw [Real.log_mul (by norm_num : (4 : ℝ) ≠ 0) hQ0] | |
| have hm : Real.log 4 ≤ r.modulusExponent * L := by | |
| have h := (div_le_iff₀ hμ).mp hLlarge | |
| nlinarith | |
| have he := Real.add_one_le_exp (r.modulusExponent * L) | |
| linarith | |
| end Ostmann | |
| end OAI | |