DOI: 10.5281/zenodo.16720010
title: RCFT/ULRC Protocol and Data Backlog (2022–2025): Regime Assignment, Audit Trail, Calibration History, and Multi-Domain Collapse Diagnostics

description: This document provides the complete protocol, audit log, and multi-domain application data for the RCFT/ULRC system (Recursive Collapse Field Theory / Unified Language of Recursive Collapse).

 

It includes canonical definitions, symbolic invariants, drift–fidelity–entropy–curvature equations, and regime classification logic used to assign system states into Stable, Watch, Collapse, or Critical conditions.

 

The dataset spans 2022–2025 and is designed for scientific publication, regulatory audit, and algorithmic implementation.

 

Key contents:

 



Full invariant definitions and thresholds

Cross-domain examples: environmental (EPA RadNet), biomedical (EEG, MIT-BIH), climate (NASA GISTEMP), power grid

Synthetic edge case tests (low-variance, noise, periodicity, outlier injection)

Handling of missing data (NaNs, gaps, hot restarts)

False positive/false negative audit review

Attribution logic for distinguishing spike vs. turbulence vs. hybrid collapse

Multi-variable analysis (e.g., concordance/discrepancy across channels)

Regime distribution histograms and non-event audit windows

Parameter update/calibration log with rationale per change


 

 

This file serves as the definitive supplement and empirical diagnostic reference for all RCFT/ULRC implementations through mid-2025. It is suitable for use in scientific journals, methods papers, compliance reports, and symbolic collapse engine deployment.

 

Cite this document using the DOI provided. For questions or integration support, contact the author.

 

Keywords:

RCFT, ULRC, symbolic collapse, audit log, protocol, regime classification, entropy, drift, fidelity, climate anomaly, EEG, power grid, data diagnostics, reproducibility, regulatory compliance, calibration
description: We formalize the empirical calibration of the Universal Mathematics & Collapse Platform (UMCP) using experimental data from polariton quantum fluids engineered to simulate the Hawking effect. All key measured variables, regime boundaries, and field invariants are mapped to UMCP diagnostic logic, providing a reference benchmark for cross-domain deployment. The protocol includes extracted equations, thresholds, and operational steps for regime assignment, invariant detection, and collapse boundary calibration. This work demonstrates how recent advances in analog gravity experiments can anchor and validate universal collapse diagnostics, expanding UMCP’s empirical foundation for both quantum and classical systems.

 

 

Paulus, C. (2025). Universal Mathematics & Collapse Platform (UMCP): Empirical Calibration via Hawking-Analog Polariton Fluids (1.0) [Data set]. Universal Mathematics & Collapse Platform (UMCP). https://doi.org/10.5281/zenodo.16623285
description: Key features:

 



Closed operational protocol for regime assignment in nanocrystal coalescence

Empirical calibration with direct mapping to observed data

Symbolic and mathematical translation via the UMCP/RCFT framework

Example numerical applications for direct laboratory use

Glossary of terms and definitions for reproducibility