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.

https://github.com/betti-labs/rso-framework

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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.

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  • Host: GitHub
  • Owner: Betti-Labs
  • License: mit
  • Language: Python
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README.md

Recursive Superpositional Ontology (RSO) Laboratory

GitHub Pages Academia.edu License: MIT Python 3.8+

🎉 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 the XiOscillator class for discrete oscillations, the XiSymbolic class for symbolic predicates using SymPy, and the xi_operator function to build finite approximations to Ξ fields.
  • make_figures.py – Generates all diagrams in the figures directory. It uses only matplotlib primitives 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:

  1. 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.
  2. 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.
  3. 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 XiOscillator to more than one dimension.

Getting Started

Installation

  1. Clone or download this repository: bash git clone https://github.com/Betti-Labs/rso-framework.git cd rso-framework

  2. Install the required dependencies: bash pip install -r requirements.txt

  3. (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

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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requirements.txt pypi
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