The Fine-Structure Constant from Discrete Hodge Theory

Preprint (February 2026). We present a self-contained derivation of the electromagnetic fine-structure constant within a discrete Hodge-theoretic framework. Starting from d^2 = 0 and explicit additional structural assumptions, we obtain the parameter chain (z, k, Q, N, δ) = (4, 1/√2, 2/3, 3, 2/9) and compute α^{-1} = 137.0359 (0.79 ppm) at second order. Each step is explicitly labeled by type (T: theorem, S: structural identification, M: model-level, T|conditional). Falsification criteria are stated. Reproducibility: all calculations can be verified without proprietary software. Human–machine workflow (disclosure): during development, an internal analytics engine (AQEA CRONOS) was used for exploratory searches and consistency checks across candidate relations. Large language models were used as non-author assistants for editorial and algebraic cross-checking; this does not constitute formal machine-checked proof.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-02-13
DOI
https://doi.org/10.5281/zenodo.18629771
Primary Topic
Benford’s Law and Fraud Detection
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Fine-Structure Constant from Discrete Hodge Theory

Sayed Amir Karim
Zenodo (CERN European Organization for Nuclear Research)
Benford’s Law and Fraud Detection
article

The Fine-Structure Constant from Discrete Hodge Theory

Sayed Amir Karim
article en

Abstract

Preprint (February 2026). We present a self-contained derivation of the electromagnetic fine-structure constant within a discrete Hodge-theoretic framework. Starting from d^2 = 0 and explicit additional structural assumptions, we obtain the parameter chain (z, k, Q, N, δ) = (4, 1/√2, 2/3, 3, 2/9) and compute α^{-1} = 137.0359 (0.79 ppm) at second order. Each step is explicitly labeled by type (T: theorem, S: structural identification, M: model-level, T|conditional). Falsification criteria are stated. Reproducibility: all calculations can be verified without proprietary software. Human–machine workflow (disclosure): during development, an internal analytics engine (AQEA CRONOS) was used for exploratory searches and consistency checks across candidate relations. Large language models were used as non-author assistants for editorial and algebraic cross-checking; this does not constitute formal machine-checked proof.

Zenodo (CERN European Organization for Nuclear Research)
Peace, Justice and strong institutions
Openalex Percentile: Top 58%
Benford’s Law and Fraud Detection
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.