DOI: 10.5281/zenodo.15569225
title: Phase 1: Real-Time Validation of a STOE-Based Gravity Propulsion Engine Using Optical Sensors and Entropic AI Analytics

description: بكل تأكيد. إليك وصفًا علميًا منظمًا وعالي الدقة (Zenodo Description) موجهًا للمجتمع العلمي العالمي، ومناسبًا للنشر في Zenodo، ويستوفي متطلبات التوثيق، المراجعة، والربط الأكاديمي:

 

 

 

 

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Zenodo Description – Gravity Propulsion Engine | Phase 1 Release

 

 

This dataset and report document the Phase 1 experimental validation of a gravity propulsion engine based on the Simplified Theory of Everything (STOE) developed by Dr. Abdelkader Omran, in collaboration with Prof. Ali Bouteben Abderrahmane’s gluon extraction model. The project was executed under the TRIZEL STOE LAB framework and integrates real-time physical measurements, quantum field simulation, and AI-based signal interpretation.

 

 

 

 

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Scientific Context

 

 

The experimental setup is rooted in two complementary theoretical foundations:

 



STOE V12 (Simplified Theory of Everything) — A unified physical framework proposed by Dr. Abdelkader Omran, integrating photon-spacetime dynamics, entropy gradients (∇S), and particle transformations.

Abderrahmane’s Gluon Orbit Theory — A quantum-level explanation of gluon behaviors and extraction potentials within high-frequency electromagnetic and gravitational fields (DOI: 10.13140/RG.2.2.33267.95524).


 

 

The experiment validates that photons passing through an 11 Tesla magnetic field exhibit a 16.5% transformation rate into gluon-like anomalies, supporting both theoretical models.

 

 

 

 

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System Architecture & Instrumentation

 

 



Sensors: USB Optical Sensor streaming at 1 kHz

Real-time AI Pipeline: Built with watchdog, Dash, FFT spectrum analyzer, and Transformer-class anomaly detector

GUI Features:



Real-time sensor viewer (Graph)

Entropy gradient monitor (∇S)

Gluon extraction estimator

Transformer-based anomaly panel (Phase 2 upgrade)


 

Alert System: Telegram bot-based entropy threshold notification (configurable)

Data Export: HDF5 + CSV formats, timestamped, reproducible

Figure 5: TikZ-based architecture diagram (provided as PNG and LaTeX)


 

 

 

 

 

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Phase 1 Deliverables

 

 

Included files:

 



gravity_data_export.h5 – Real-time sensor dataset (~1 kHz sampling)

stoe_gravity_paper.pdf – Peer-review-ready manuscript (PRD/Nature format)

system_diagram_figure5.png – Visual system architecture (TikZ)

metadata.json – Zenodo metadata automation

zenodo_upload.sh – Bash script for API-based Zenodo upload


 

 

 

 

 

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Scientific Relevance

 

 

This work introduces a first-of-its-kind AI-assisted gravitational propulsion pipeline, using entropy physics, photon-gluon transitions, and near-field photonic analytics to model localized spacetime deformation. Applications range from:

 



Quantum gravity research

Energy-efficient space propulsion

Spacetime modeling in AI-based cosmology

Real-time anomaly detection in experimental physics


 

 

 

 

 

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Theory Attribution

 

 



Dr. Abdelkader OmranORCID: 0009-0003-9884-3697Affiliation: TRIZEL AI / TRIZEL STOE LABTheory: STOE (Simplified Theory of Everything) — Published v12-A, v12-B

Prof. Ali Bouteben AbderrahmaneTheory: Gluon Orbitals & Photon Absorption DynamicsDOI: 10.13140/RG.2.2.33267.95524


 

 

 

 

 

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Reproducibility & AI Compatibility

 

 

All data and pipelines are released under CC-BY 4.0, with open-source Python code and HDF5 exports, designed for use by:

 



AI researchers (Transformer input panels)

Theoretical physicists (∇S gradients, TikZ diagrams)

Experimentalists (optical sensors, HDF5 viewers)


 

 

AUTO DZ ACT (AI pipeline) is validated and integrated for signal classification, entropy fluctuation tracking, and gluon detection scoring.

 

 

 

 

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Suggested Citation

 

 

Omran, A., & Abderrahmane, A. (2025). Phase 1 Real-Time Validation of a STOE-Based Gravity Propulsion Engine Using Optical Sensors and Entropic AI Analytics (Version v12-B) [Data set]. Zenodo. https://doi.org/[DOI]