rso-framework
A computational framework for contradiction-preserving logic that treats paradoxes as fundamental building blocks rather than logical failures. Includes formal mathematical verification, quantum mechanics applications, and consciousness modeling with 7M+ operations/second performance.
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A computational framework for contradiction-preserving logic that treats paradoxes as fundamental building blocks rather than logical failures. Includes formal mathematical verification, quantum mechanics applications, and consciousness modeling with 7M+ operations/second performance.
Basic Info
- Host: GitHub
- Owner: Betti-Labs
- License: mit
- Language: Python
- Default Branch: main
- Size: 3.96 MB
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Metadata Files
README.md
Recursive Superpositional Ontology (RSO) Laboratory
🎉 PUBLISHED RESEARCH 🎉
🔊 Listen to the RSO Deep Dive | 📄 Read the Full Paper on Academia.edu
"Recursive Superpositional Ontology: A Computational Framework for Contradiction-Preserving Logic and Reality Modeling" by Gregory Betti is now available for the global research community.
Welcome to the RSO Laboratory, an open repository for exploring the metaphysical and symbolic logic framework introduced in Recursive Superpositional Ontology: A Computational Framework for Contradiction-Preserving Logic and Reality Modeling.
This repository accompanies the scientific paper written by Gregory Betti (Betti Labs) and contains reproducible code, visualisations, and documentation needed to investigate the Recursive Superpositional Ontology (RSO). The lab is organised around the idea that reality is not composed of resolved states but of recursive contradictions captured by the operator ⊕ and its associated contradiction field Ξ.
Philosophy
RSO begins from a radical ontological axiom: every property (x) coexists with its negation (¬x). Rather than treating the contradiction (x ∧ ¬x) as an impossibility, RSO elevates it to a fundamental ingredient of being. The universe is described as a superposition of every predicate and its opposite, generating a network of Ξ‑nodes that constantly loop between states. This recursion is not a failure of logic; it is the engine of existence.
Key Principles
- Contradiction‑preserving superposition (⊕): A binary operator that combines a predicate with its negation without resolving their opposition. Iterating ⊕ generates a Ξ attractor, a symbolic structure containing all variations of (x) and (¬x).
- Ξ fields: The self‑referential sets resulting from the ⊕ operation. Each Ξ contains the predicate, its negation, their conjunction, and further nested superpositions. Ξ‑graphs visualise these structures as loops with tension arrows.
- Recursion as reality: Time, space, matter, and consciousness emerge from the velocities and orientations of Ξ cycles. Nothing ultimately collapses—every collapse is a local projection of a deeper recursion.
For philosophical context, RSO resonates with ideas from Heraclitus (unity of opposites and flux), Daoist yin–yang (interdependence of contrary forces), and modern paraconsistent logics that reject explosion in the presence of contradictions【800088766790706†L41-L54】. It also echoes the many‑worlds interpretation of quantum mechanics, which removes wave function collapse and treats the universe as an ever‑branching superposition【751751222457522†L457-L464】. These influences underscore the plausibility of a reality built on recursive contradiction.
Contents
RSO-Lab/
├── figures/ # PNG and PDF diagrams generated from code
├── notebooks/ # Jupyter notebooks for interactive exploration
├── src/ # Python modules implementing RSO concepts
├── README.md # This file
├── requirements.txt # Python package requirements
└── …
figures/
The figures directory contains reproductions of the key diagrams
used in the paper. They are generated programmatically by
src/make_figures.py and include:
- xioneX.(png|pdf) – one‑predicate Ξ graph showing the loop between (x), (¬x), and the contradictory state (x∧¬x).
- xitwoX_Y.(png|pdf) – two‑predicate Ξ² graph illustrating the richer structure of combining predicates (x) and (y).
- contradiction_lattice.(png|pdf) – lattice of the four truth values (True, False, Both, Neither) highlighting the legitimacy of the “Both” state in paraconsistent reasoning.
- recursive_orbit.(png|pdf) – continuous oscillation representing a recursive orbit.
- hotcoldsimulation.(png|pdf) – discrete toy model toggling between hot and cold states.
src/
xi.py– Implements theXiOscillatorclass for discrete oscillations, theXiSymbolicclass for symbolic predicates using SymPy, and thexi_operatorfunction to build finite approximations to Ξ fields.make_figures.py– Generates all diagrams in thefiguresdirectory. It uses onlymatplotlibprimitives so that no external graph library is required.
notebooks/
xi_simulation.ipynb– A short Jupyter notebook acting as a Ξ playground. It demonstrates how to create an oscillator, iterate its states, and construct symbolic contradiction fields.
Testable Predictions
The RSO framework makes several qualitative predictions that can be investigated computationally:
- Stability thresholds: A Ξ attractor remains stable only if the recursion is continued indefinitely. If the oscillation is interrupted or one state is favoured, a “collapse” occurs. Simple models, such as the hot/cold simulation in this repository, can explore how long it takes for such interruptions to occur under perturbations.
- Emergent time: The period of oscillation in a Ξ cycle defines an emergent temporal scale. Simulations of coupled oscillators may exhibit phase synchronisation that resembles thermodynamic or causal arrows of time.
- Composite attractors: Combining predicates via Ξ² should yield
richer dynamics, potentially displaying quasi‑periodic or chaotic
behaviour. One can numerically explore these multi‑predicate
systems by extending
XiOscillatorto more than one dimension.
Getting Started
Installation
Clone or download this repository:
bash git clone https://github.com/Betti-Labs/rso-framework.git cd rso-frameworkInstall the required dependencies:
bash pip install -r requirements.txt(Optional) Install in development mode:
bash pip install -e .
Quick Start
Command Line Interface
The RSO framework includes a comprehensive CLI for easy interaction:
```bash
Run interactive demo
python src/cli.py demo
Generate oscillation sequence
python src/cli.py oscillate --steps 20 --initial true
Create symbolic Xi attractor
python src/cli.py symbolic --predicate X --depth 3 --validate --verbose
Run formal verification
python src/cli.py verify
Generate performance benchmarks
python src/cli.py benchmark
Generate all figures
python src/cli.py figures ```
Python API
```python from src.xi import XiOscillator, XiSymbolic, xi_operator
Create and run oscillator
oscillator = XiOscillator(True) history = oscillator.iterate(10) print(f"Oscillation: {history}")
Create symbolic predicate and Xi attractor
predicate = XiSymbolic('Consciousness') attractor = xi_operator(predicate, depth=2) print(f"Xi attractor has {len(attractor)} expressions")
Validate the attractor
from src.xi import validatexiattractor validation = validatexiattractor(attractor, predicate) print(f"Validation passed: {validation['validation_passed']}") ```
Jupyter Notebooks
Launch the interactive notebook for experimentation:
bash
jupyter notebook notebooks/xi_simulation.ipynb
Advanced Usage
Formal Verification
```python from src.formalproofs import runformal_verification
results = runformalverification() print("Verification results:", results) ```
Quantum Bridge
```python from src.quantum_bridge import QuantumXiState
Create quantum superposition state
quantumstate = QuantumXiState(alpha=0.6, beta=0.8) print(f"P(x) = {quantumstate.probability_x():.3f}")
Time evolution
evolved = quantumstate.evolve(time=3.14, frequency=1.0) print(f"Evolved P(x) = {evolved.probabilityx():.3f}") ```
Performance Benchmarking
```python from benchmarks.performance_suite import RSOBenchmarkSuite
suite = RSOBenchmarkSuite() summary = suite.runcomprehensivebenchmark() print(f"Average execution time: {summary['avgexecutiontime']:.6f}s") ```
We hope these tools help you delve deeper into the paradoxical yet structured world of Recursive Superpositional Ontology.
📚 How to Cite
If you use the RSO framework in your research, please cite the published paper:
APA Style:
Betti, G. (2025). Recursive Superpositional Ontology: A Computational Framework for Contradiction-Preserving Logic and Reality Modeling. Academia.edu. https://www.academia.edu/143089984/
BibTeX:
bibtex
@article{betti2025rso,
title={Recursive Superpositional Ontology: A Computational Framework for Contradiction-Preserving Logic and Reality Modeling},
author={Betti, Gregory},
journal={Academia.edu},
year={2025},
url={https://www.academia.edu/143089984/Recursive_Superpositional_Ontology_A_Computational_Framework_for_Contradiction_Preserving_Logic_and_Reality_Modeling}
}
Software Citation:
Betti, G. (2025). RSO Framework: Recursive Superpositional Ontology (Version 1.0.1) [Computer software]. GitHub. https://github.com/Betti-Labs/rso-framework
Owner
- Name: Betti Labs
- Login: Betti-Labs
- Kind: organization
- Repositories: 1
- Profile: https://github.com/Betti-Labs
Citation (CITATION.cff)
cff-version: 1.2.0
message: "If you use this software, please cite it as below."
type: software
title: "RSO Framework: Recursive Superpositional Ontology"
abstract: "A computational framework for contradiction-preserving logic and reality modeling that treats contradictions as fundamental building blocks rather than logical failures."
authors:
- family-names: Betti
given-names: Gregory
# email: [will be added when available]
# affiliation: [will be added when available]
# orcid: [will be added when available]
repository-code: "https://github.com/Betti-Labs/rso-framework"
url: "https://github.com/Betti-Labs/rso-framework"
license: MIT
version: "1.0.0"
date-released: "2025-01-26"
keywords:
- "paraconsistent logic"
- "recursive systems"
- "quantum mechanics"
- "consciousness"
- "computational ontology"
- "contradiction preservation"
- "artificial intelligence"
- "quantum computing"
preferred-citation:
type: article
title: "Recursive Superpositional Ontology: A Computational Framework for Contradiction-Preserving Logic and Reality Modeling"
authors:
- family-names: Betti
given-names: Gregory
journal: "Academia.edu"
year: 2025
month: 1
url: "https://www.academia.edu/143089984/Recursive_Superpositional_Ontology_A_Computational_Framework_for_Contradiction_Preserving_Logic_and_Reality_Modeling"
abstract: "We present the Recursive Superpositional Ontology (RSO) framework, a novel computational paradigm that treats contradictions as fundamental building blocks of reality rather than logical failures. Unlike classical logic systems that seek to eliminate contradictions, RSO preserves and utilizes them through the superpositional operator and recursive Xi attractors."
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Dependencies
- actions/checkout v4 composite
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- actions/checkout v4 composite
- actions/setup-python v4 composite
- actions/checkout v4 composite
- actions/setup-python v4 composite
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