Lattice Cohomology Classifies E8 Market State Transitions — E8 Intelligence Research
- 1Independent Researcher, United Kingdom
Abstract
The 240 root vectors of E8 generate a cohomology ring whose topological invariants classify market coherence states, with 132Hz phi-coupled excitations creating quantized "charge" transitions between fixed-point attractors. This cohomology structure explains why win-rate clusters emerge at 240/n resonance values: each integer n corresponds to a distinct cohomology class with its own decay signature. The 32-35pp differential observed across session-anchored vectors thus represents a topological phase transition—the difference between cohomologically distinct market states—rather than random variance. By tracking which cohomology class a price trajectory inhabits, one can predict the allowable decay pathway and corresponding win-rate basin with lattice-level precision.
Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com
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BibTeX
@misc{caldin2026lattice,
title = {{Lattice Cohomology Classifies E8 Market State Transitions — E8 Intelligence Research}},
author = {Andrew Stewart Caldin},
howpublished = {Zenodo},
year = {2026},
month = oct,
doi = {10.5281/zenodo.23490849},
url = {https://zenodo.org/records/23490849},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Lattice Cohomology Classifies E8 Market State Transitions — E8 Intelligence Research
AU - Andrew Stewart Caldin
PY - 2026
DA - 2026/10/20
PB - Zenodo
DO - 10.5281/zenodo.23490849
UR - https://zenodo.org/records/23490849
AB - The 240 root vectors of E8 generate a cohomology ring whose topological invariants classify market coherence states, with 132Hz phi-coupled excitations creating quantized "charge" transitions between fixed-point attractors. This cohomology structure explains why win-rate clusters emerge at 240/n resonance values: each integer n corresponds to a distinct cohomology class with its own decay signature. The 32-35pp differential observed across session-anchored vectors thus represents a topological phase transition—the difference between cohomologically distinct market states—rather than random variance. By tracking which cohomology class a price trajectory inhabits, one can predict the allowable decay pathway and corresponding win-rate basin with lattice-level precision. Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com
ER -