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LeanPool.Erdos1196.FirstEntryRowTerm

First-entry row data #

This file packages the row-wise data for the first-entry contribution to the normalization constant. It introduces the threshold selecting admissible first jumps from a parent state m, the resulting tail sum, and the pairwise weights used later in the fiberwise reindexing of B_x.

Main definitions #

The least threshold satisfying both q ≥ Y and x ≤ m * q.

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    noncomputable def PrimitiveSetsAboveX.firstEntryTail (x Y m : ℕ) :

    The first-entry tail sum starting from a parent state m.

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      noncomputable def PrimitiveSetsAboveX.firstEntryPairWeight (x Y : ℕ) (mq : ℕ × ℕ) :

      The pairwise weight indexed by a parent state m and jump factor q for the first-entry contribution to B_x.

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      • One or more equations did not get rendered due to their size.
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        theorem PrimitiveSetsAboveX.entryThreshold_le_iff (x Y m q : ℕ) (hm : 0 < m) :
        entryThreshold x Y m ≤ q ↔ Y ≤ q ∧ x ≤ m * q

        The lower-threshold condition is exactly the conjunction q ≥ Y and x ≤ m * q.

        theorem PrimitiveSetsAboveX.firstEntryPairWeight_eq {x Y m q : ℕ} (hm1 : 1 ≤ m) (hmx : m < x) :

        For a parent state already known to satisfy 1 ≤ m < x, the pairwise first-entry weight is the corresponding scaled tail summand.

        theorem PrimitiveSetsAboveX.firstEntryPairWeight_row (x Y m : ℕ) :
        (fun (q : ℕ) => firstEntryPairWeight x Y (m, q)) = if 1 ≤ m ∧ m < x then fun (q : ℕ) => 1 / ↑m * if entryThreshold x Y m ≤ q then ArithmeticFunction.vonMangoldt q / (↑q * Real.log ↑(m * q) ^ 2) else 0 else fun (x : ℕ) => 0

        For a fixed parent state m, the first-entry row is either the scaled tail summand row when 1 ≤ m < x, or identically zero otherwise.