zcm-collapse-model 1.0.2

Math-only implementation of the Zeta Collapse Model (ZCM). System architecture and database are patent-pending and not included.

Zeta Collapse Model (ZCM) – Math Library

This repository contains the math-only implementation of the Zeta Collapse Model (ZCM):
a deterministic framework for collapsing high-entropy data using radar-band logic inspired by the spectral behaviour of the Riemann zeta function.

⚠️ Important:
This repository includes only the mathematical components of ZCM.
The ZCM database architecture, selector engine, radar-band orchestration, and system-level design are patent-pending and are not included here.

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✨ What is ZCM?

The Zeta Collapse Model is a deterministic collapse method that:

• Defines radar bands to isolate stable signal regions.
• Applies harmonic / interval logic to reduce chaotic candidate sets.
• Uses simple zeta-derived metrics (e.g., basic_zeta_metric) for illustration.
• Requires no machine learning, no statistics, and no probability.

This math library is intentionally minimal and demonstrates the foundational ideas behind ZCM collapse behaviour.

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📦 Included in this repo

Math modules

• zcm/radar_bands.py
  Radar band definitions and filtering logic.

• zcm/collapse.py
  A simple deterministic collapse using a single radar band.

• zcm/zeta_metrics.py
  Toy zeta-related metrics (for examples only).

• zcm/__init__.py
  Public API surface.

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🧠 Example usage

from zcm import collapse_by_radar_band

candidates = [3, 6, 8, 15, 18, 39]

survivors = collapse_by_radar_band(
    candidates=candidates,
    center=15,
    radius=5
)

print(survivors)
# → [8, 15, 18]

## 📩 Contact

For collaboration, licensing, or access to ZCM’s system architecture:

**Alex Veldman**   
GitHub: https://github.com/alexvm35  
ResearchGate: https://www.researchgate.net/

## 📚 Related Work

The Zeta Collapse Model (ZCM) sits in a broader landscape of research exploring
spectral, harmonic, or zeta-function–based mechanisms for dimensional reduction
and state collapse.

A closely related theoretical work is:

**Stander, M. & Wallis, B. (2023).  
"Deriving Measurement Collapse Using Zeta Function Regularisation."**  
arXiv: 2303.0054  
https://arxiv.org/abs/2303.0054

Their approach derives quantum measurement collapse using zeta-function
regularisation and thermodynamic arguments. While ZCM is *not* a quantum collapse
theory, both frameworks share the idea of using zeta-spectral structure to
reduce high-entropy systems into stable surviving states.

ZCM generalises this idea into a **deterministic, computation-oriented collapse
filter** that applies to numerical data, candidate sets, token streams, and
signal processing pipelines.