Metadata-Version: 2.5
Name: axiomize-quantum-skills-2.0
Version: 1.2.0
Summary: Axiomize 2.0: scientific modeling engine plus quantum-inspired multi-branch reasoning and Model IR selection
Project-URL: Homepage, https://github.com/Furox-Art/axiomize-quantum-skills-2.0
Project-URL: Repository, https://github.com/Furox-Art/axiomize-quantum-skills-2.0
Project-URL: Issues, https://github.com/Furox-Art/axiomize-quantum-skills-2.0/issues
Project-URL: Documentation, https://furox-art.github.io/axiomize-quantum-skills-2.0/
Author-email: Furox-Art <177975472+Furox-Art@users.noreply.github.com>
License-Expression: MIT
License-File: LICENSE
Keywords: agent-skills,bayesian,calibration,causal-inference,decision-making,finite-elements,first-principles,llm-agents,mathematical-modeling,model-ir,model-selection,modeling,multi-branch-reasoning,optimization,quantum-inspired,reasoning,reproducibility,scientific-computing,simulation,uncertainty-quantification
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=3.10
Requires-Dist: casadi>=3.6
Requires-Dist: control>=0.10
Requires-Dist: cvxpy>=1.5
Requires-Dist: matplotlib>=3.7
Requires-Dist: networkx>=3.0
Requires-Dist: numpy>=1.24
Requires-Dist: scipy>=1.10
Requires-Dist: statsmodels>=0.14
Requires-Dist: sympy>=1.12
Requires-Dist: z3-solver<5,>=4.13; sys_platform == 'darwin'
Requires-Dist: z3-solver>=4.12; sys_platform != 'darwin'
Provides-Extra: dev
Requires-Dist: mypy>=1.10; extra == 'dev'
Requires-Dist: pytest>=8.0; extra == 'dev'
Requires-Dist: ruff>=0.4; extra == 'dev'
Provides-Extra: full
Requires-Dist: jax>=0.4; extra == 'full'
Requires-Dist: pymc>=5.0; extra == 'full'
Provides-Extra: playground
Requires-Dist: gradio>=4.0; extra == 'playground'
Requires-Dist: pandas>=1.5; extra == 'playground'
Description-Content-Type: text/markdown

# Axiomize Quantum Skills - 2.0  
  
Current package line: **1.2.0**  
  
![License](https://img.shields.io/badge/license-MIT-blue)  
![Python](https://img.shields.io/badge/python-3.10%2B-informational)  
![CI](https://github.com/Furox-Art/axiomize-quantum-skills-2.0/actions/workflows/ci.yml/badge.svg)  
[![PyPI](https://img.shields.io/pypi/v/axiomize-quantum-skills-2.0)](https://pypi.org/project/axiomize-quantum-skills-2.0/)  
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This is what happens when you combine a scientific modeling engine with a reasoning system that refuses to commit to the first plausible answer.  
  
Most AI tools give you one answer and move on. This one keeps multiple hypotheses alive, tests them against evidence, kills the weak ones, and only collapses to a conclusion when the data actually supports it.  
  
## The two pieces  
  
**Axiomize** handles the scientific modeling: explicit equations, dimensional analysis, sensitivity studies, reproducible exports.  
  
**Quantum Reasoning** handles the thinking: multi-branch exploration, evidence-based pruning, adaptive compute allocation. It's not quantum computing-it's just a metaphor for keeping possibilities open until you have real evidence.  
  
Together they let you build models where the reasoning process is as rigorous as the math.  
  
## Common use cases

- Explore several competing **mathematical models** before committing to one formulation.
- Combine **multi-branch AI reasoning** with parameter estimation, sensitivity analysis, and uncertainty quantification.
- Compare hypotheses using quantitative evidence instead of selecting the first plausible answer.
- Build reproducible scientific workflows that preserve both the **reasoning trace and mathematical model**.
- Apply quantum-inspired branch exploration to scientific modeling, model selection, planning, and decision support.

## Quick start  
  
```bash  
pip install axiomize-quantum-skills-2.0  
# or  
npx axiomize-quantum  
```  
  
## Why I merged them  
  
I had the modeling engine and the reasoning skill as separate projects for a while. But every time I used one, I wanted the other. Building a model requires exploring multiple formulations. Reasoning about evidence requires quantitative checks. They belong together.  
  
## License  
  
MIT. 
