Download lean/OAI/NumberTheory/Jacobsthal/Analysis/CompactSmallCountErrors.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/Jacobsthal/Analysis/CompactSmallCountErrors.lean
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curl -L -o CompactSmallCountErrors.lean https://huggingface.co/datasets/roseking/openAI-math-dataset/resolve/main/lean/OAI/NumberTheory/Jacobsthal/Analysis/CompactSmallCountErrors.lean
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| import OAI.NumberTheory.Jacobsthal.Estimates.LargeGapCountErrors | |
| namespace OAI | |
| namespace Erdos970 | |
| open scoped _root_.Erdos970 | |
| namespace NumberTheoryLean.CompactSmallCountErrors | |
| open FinitePathGeometry PrimeHistories PrimeBinMembership ReferenceAdmission StrongSourceFamilies | |
| open ActualCountErrorEdges ActualCountErrorMass SourcePrimeProductData | |
| open LogarithmicBinPartition ErdosInverseCounts | |
| open ErdosPrimeInputs.PrimePrefixMass ErdosPrimeInputs.PrimePrefixTail | |
| theorem uniform_compact_small_count_errors (K d : ℝ) (hK : 3 ≤ K) (hd : 0 < d) : | |
| ∃ C B₀ w₀ : ℝ,0 < C ∧ 3 ≤ B₀ ∧ 1 < w₀ ∧ ∀ B w top : ℝ,B₀ ≤ B → w₀ ≤ w → | |
| w < top → Real.log B ≤ d*Real.log w → ∀ z : Node, | |
| z.side=.even → 199/100 ≤ z.ratio → z.ratio ≤ 23/10 → Consistent z → z.cutoff=B → z.closed=true → w^B=top → | |
| ∀ Y : ℕ,0 < Y → ∀ residue : ℕ → ℕ,∀ eps : ℝ,0 ≤ eps → ∀ F : Finset (List ℕ), | |
| F ⊆ referencePrefixes w (sourcePrimeSet w top) z.side z.gap → | |
| (∀ ps∈F,(terminal w z ps).gap ≤ K ∧ | |
| |wordCountError Y (LargePrimeDeletion.cutoffPrimes ⌊w⌋₊) residue (SmallSieveFinite.smallEuler ⌊w⌋₊) ps| ≤ eps) → | |
| (B^2/((Y:ℝ)*SmallSieveFinite.smallEuler ⌊w⌋₊))*(∑ ps∈F, | |
| |(modulusCount Y (LargePrimeDeletion.cutoffPrimes ⌊w⌋₊) residue ps.prod:ℝ)- | |
| ((Y:ℝ)/(ps.prod:ℝ))*SmallSieveFinite.smallEuler ⌊w⌋₊|) ≤ C*eps := by | |
| obtain ⟨C,B₀,W,hC,hB₀,hW,hMass⟩ := uniform_source_family_mass K d hK hd | |
| refine ⟨C,B₀,max W 2,hC,hB₀,hW.trans_le (le_max_left _ _),?_⟩ | |
| intro B w top hB hw₀ htop hcomp z hi h199 h23 hz hcut hclosed hpower Y hY residue eps heps F hF hGood | |
| have hw : 1 < w := hW.trans_le ((le_max_left _ _).trans hw₀) | |
| have hw2 : 2 ≤ w := (le_max_right _ _).trans hw₀ | |
| have hV : 0 < SmallSieveFinite.smallEuler ⌊w⌋₊ := | |
| (inv_pos.mpr (zero_lt_one.trans hw)).trans_le (SmallSieveFinite.smallEuler_floor_ge_inv w hw2) | |
| have hp : ∀ ps∈F,0 < ps.prod := fun ps hps => (reference_word_product_data hw htop z.side z.gap ps (hF hps)).1 | |
| rw [finite_count_error_weight B Y _ residue _ hY hV F hp] | |
| have he : (∑ ps∈F,prefixWeight ps*|wordCountError Y (LargePrimeDeletion.cutoffPrimes ⌊w⌋₊) residue | |
| (SmallSieveFinite.smallEuler ⌊w⌋₊) ps|) ≤ (∑ ps∈F,prefixWeight ps)*eps := by | |
| rw [Finset.sum_mul] | |
| apply Finset.sum_le_sum | |
| intro ps hps | |
| exact mul_le_mul_of_nonneg_left (hGood ps hps).2 (prefixWeight_nonneg ps) | |
| have hsum := hMass B w top hB ((le_max_left _ _).trans hw₀) htop hcomp z hi h199 h23 hz hcut hclosed hpower F hF | |
| (fun ps hps => (hGood ps hps).1) | |
| have hh := mul_le_mul_of_nonneg_left he (sq_nonneg B) | |
| have hc := mul_le_mul_of_nonneg_right hsum heps | |
| nlinarith | |
| end NumberTheoryLean.CompactSmallCountErrors | |
| end Erdos970 | |
| end OAI | |