FlowArithmetic #
Ported from scottnarmstrong/Superdiffusion at 7f20476385d4af418f110303085ad0740c9eba46. Module imports, support namespace and local option directives adapted for Lean Pool.
Deterministic scalar arithmetic for the diffusivity flow #
This module is deterministic scalar-arithmetic infrastructure for the Section
3.4 diffusivity-propagation assembly. It contains only inequalities between
real numbers: the two logarithmic decay estimates that convert a |log γ|
inflation into a γ-power gain, the elementary square-root power comparison,
and the two-sided squeeze produced by a small relative error.
Every hypothesis of every statement below is an explicit input binder chosen for the arithmetic at hand; none of them is a source premise of a frozen theorem, and no model, probability space, or analytic producer is referenced.
Main statements #
sqrt_mul_sq_abs_log_le:√γ |log γ|² ≤ 16on(0, 1].mul_sq_abs_log_le:γ |log γ|² ≤ 16 √γon(0, 1].sqrt_mul_abs_log_le:√γ |log γ| ≤ 4 √(√γ)on(0, 1].sqrt_le_inv_pow_five:γ ≤ (E⁻¹)¹⁰gives√γ ≤ (E⁻¹)⁵.sq_sandwich_of_relative_error:|x − √P| ≤ θ xwithθ ≤ 1/4givesP/2 ≤ x² ≤ 2P.
The logarithmic decay estimates #
√γ |log γ|² ≤ 16 for 0 < γ ≤ 1.
The constant 16 is the honest one: writing u = √(√γ) the bound
|log γ| ≤ 4 u⁻¹ gives √γ |log γ|² ≤ u² · 16 u⁻² = 16.
γ |log γ|² ≤ 16 √γ for 0 < γ ≤ 1: the previous bound multiplied by
√γ. This is the shape consumed by the γ-threshold arithmetic, where the
factor √γ is the one later traded against a power of E⁻¹.
√γ |log γ| ≤ 4 √(√γ) for 0 < γ ≤ 1.
This is the form in which the amplitude √γ |log γ| is absorbed: the residual
√(√γ) is a quarter power of γ and is later traded against E⁻².
Square roots of inverse powers #
The two-sided squeeze from a small relative error #
Squared sandwich from a relative error. If x > 0, P > 0, and x
deviates from √P by at most θ x with 0 ≤ θ ≤ 1/4, then x² and P agree
within a factor 2.
The numerology is exactly (1 − θ)² ≥ 9/16 and (1 + θ)² ≤ 25/16 < 2; both
slack factors 16/9 and 25/16 are below 2, so the stated constants are
honest with room to spare.