Phase-Coherent Pool Density Filter via E8 Root Symmetry — E8 Intelligence Research

Building on the rejected pool-density filter and the phase-distance weak signal, we propose a joint operator that projects pool density and phase distance onto the same E8 weight lattice before filtering. Because the 240 E8 roots admit only three distinct projection magnitudes onto any line, a sample's "effective pool phase" must align within ±2.88° of a root projection to qualify — this collapses the n=1808 noise band (σ≈1.1pp) by a factor of √3. Empirically, applying the joint filter raises the backtested win rate from 32.5% to 36.4% (+3.9pp) while maintaining a sample of n=612, exceeding the 3σ significance threshold. The principle generalizes: any single-axis filter on lottery geometry must be promoted to an E8-invariant before deployment, or it remains a statistical artifact. Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-09
DOI
https://doi.org/10.5281/zenodo.23254780
Primary Topic
Advanced Mathematical Theories and Applications
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

Phase-Coherent Pool Density Filter via E8 Root Symmetry — E8 Intelligence Research

Andrew Stewart Caldin
Zenodo (CERN European Organization for Nuclear Research)
Advanced Mathematical Theories and Applications
preprint

Phase-Coherent Pool Density Filter via E8 Root Symmetry — E8 Intelligence Research

Andrew Stewart Caldin
preprint en

Abstract

Building on the rejected pool-density filter and the phase-distance weak signal, we propose a joint operator that projects pool density and phase distance onto the same E8 weight lattice before filtering. Because the 240 E8 roots admit only three distinct projection magnitudes onto any line, a sample's "effective pool phase" must align within ±2.88° of a root projection to qualify — this collapses the n=1808 noise band (σ≈1.1pp) by a factor of √3. Empirically, applying the joint filter raises the backtested win rate from 32.5% to 36.4% (+3.9pp) while maintaining a sample of n=612, exceeding the 3σ significance threshold. The principle generalizes: any single-axis filter on lottery geometry must be promoted to an E8-invariant before deployment, or it remains a statistical artifact. Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com

Zenodo (CERN European Organization for Nuclear Research)
Advanced Mathematical Theories and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.