DataDoubleSlit

Quantum-inspired data interference simulator

DataDoubleSlit is a lightweight Python library that implements an analogy of the double-slit experiment for arbitrary data. It helps visualize and measure how two parallel interpretations of the same input can interfere before a decision is made.

Features

• Simple interface - a single DataDoubleSlit class with a run() method.
• Flexible input - accepts strings, Python lists, or NumPy arrays.
• Deterministic text mapping - string inputs are converted to waveforms through SHA-256-derived parameters, so the same text always produces the same pattern across interpreter sessions.
• Normalized score - returns an interference_score in the [0, 1] range.
• Optional observation - can sample collapse positions and optionally save a plot.
• Lightweight - depends only on numpy by default.

Installation

git clone https://github.com/Lutren/data-double-slit
cd data-double-slit
pip install .

Optional plotting support:

pip install .[plot]

Basic usage

from datadoubleslit import DataDoubleSlit

tool = DataDoubleSlit(screen_size=400)
result = tool.run(
    data="I want to build an autonomous functional matrix",
    slit_separation=2.0,
    observe=True,
    plot=True,
)

print(f"Interference score: {result.interference_score:.3f}")
print(result.collapse_positions[:5] if result.collapse_positions else None)
print(result.visualization_path)

File organization

File	Description
datadoubleslit.py	Core simulator implementation
tests/	Regression tests
README.md	English guide
README_ES.md	Spanish guide

License

MIT.