Download lean/OAI/NumberTheory/TwoPoint/Walks/BlockTestNormalization.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/Walks/BlockTestNormalization.lean
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hf download hf://datasets/roseking/openAI-math-dataset/lean/OAI/NumberTheory/TwoPoint/Walks/BlockTestNormalization.lean
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curl -L -o BlockTestNormalization.lean https://huggingface.co/datasets/roseking/openAI-math-dataset/resolve/main/lean/OAI/NumberTheory/TwoPoint/Walks/BlockTestNormalization.lean
542 Bytes
| import Mathlib.Analysis.SpecialFunctions.Pow.Real | |
| import Mathlib.Tactic | |
| namespace OAI | |
| /-! Separate the retained block test's main term from its exceptional | |
| fraction before applying the boundary-error estimate. -/ | |
| namespace TwoPointCorrelations | |
| lemma block_test_normalization (L K T G R S M l δ : ℝ) | |
| (hL : L ≠ 0) (hM : M ≠ 0) : | |
| l * ((3 * R) * (l * (2 * M * S)) + (M * (2 * K * T) * G) * δ) / | |
| (2 * L * M) = | |
| 3 * l ^ 2 * S * R / L + l * (K / L * G * T) * δ := by | |
| field_simp | |
| end TwoPointCorrelations | |
| end OAI | |