This page provides step-by-step instructions to independently replicate our computational results using the Odlyzko zero datasets.Энэ хуудас Одлызкогийн zeros датасет ашиглан тооцооллын үр дүнг бие даан хуулбарлах алхам алхмаар зааварчилгаа өгнө.
Download from our repository or directly from Odlyzko's site:Манай репозитороос эсвэл Одлызкогийн сайтаас шууд татна:
zeros1.txt — 100,000 zeros, T ≈ 10¹² zeros_ht.txt — 10,000 zeros, T ≈ 10¹³ zeros6.txt — 1,000,000 zeros, T ≈ 10¹²
pip install numpy scipy matplotlib pandas
import numpy as np
from scipy import stats
# Load zeros
zeros = np.loadtxt('zeros1.txt')
T = zeros.mean()
# Compute normalized spacing
tau = np.log(T / (2 * np.pi))
spacings = np.diff(zeros) * tau / (2 * np.pi)
# Primes to test
primes = [2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37]
# Compute A(p) — covariance amplitude
results = []
for p in primes:
phase = np.cos(2 * np.pi * np.log(p) * zeros[:-1] / tau)
r, pval = stats.pearsonr(spacings, phase)
results.append((p, r))
print(f"p={p:3d} r={r:.4f}")
Dataset r value Bootstrap Status zeros1 0.6847 UNSTABLE preliminary zeros_ht 0.5113 UNSTABLE preliminary zeros6 0.4509 MODERATE preliminary
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