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ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
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UTMF v5.2 Synthetic Entropy-Trajectory Archive (FULL_DETAILS JSON + Raw Synthetic Datasets)

Authors: Strive, Jedi Markus;

UTMF v5.2 Synthetic Entropy-Trajectory Archive (FULL_DETAILS JSON + Raw Synthetic Datasets)

Abstract

This archive contains the complete synthetic dataset collection used for entropy-trajectory analysis within the UTMF v5.2 framework. The archive is organized into three components: 1. FULL_DETAILS JSON outputs (19 files) These files are complete UTMF v5.2 processing outputs generated after applying: jedi_mfdfa (multifractal analysis engine) UTMF v5.2 aggregation and metric computation Each JSON file contains: Subset-level results Mean DfD_fDf values Valid subset counts Full metric stack (TCI, MCI, TMCI) Engine version and SHA256 hash Dataset provenance Error logging (where applicable) All JSON files were produced using: MFDFA engine version: v5.2 Engine SHA256: ea690e6cca6fc2d6c5499833794d631d9d36d80da1f753f170521d97726ddbcc 2. Raw synthetic datasets This directory contains the original synthetic time series (NumPy .npy files) prior to UTMF processing. Each synthetic dataset: Matches the length of its corresponding empirical dataset Was generated under controlled synthetic models: white noise pink noise AR(1) phase randomization shuffle Lévy processes Brownian motion Was z-score normalized prior to analysis These raw files allow full reproducibility of all reported synthetic UTMF results. 3. Documentation Included documentation provides: Inventory of FULL_DETAILS JSON files Dataset summaries Processing metadata Reproducibility notes Provenance Synthetic datasets were generated using empirical dataset metadata obtained from: UTMF_v5.2_FULL_DETAILS_JSON_archive_6_runsDOI: https://doi.org/10.5281/zenodo.18529034 This synthetic archive is therefore directly reproducible from that upstream empirical archive under identical UTMF configuration. Purpose This archive supports research on: Synthetic universality classes in entropy-trajectory space Structural separation between empirical and synthetic datasets Curvature and entropy-geometry analysis Boundary behavior of QRNG datasets Robustness testing of UTMF metrics The archive enables complete independent replication of all synthetic experiments reported in the associated UTMF studies. Methodological Framework This archive was generated using the Unified Temporal-Measurement Framework (UTMF v5.2) and the jedi_mfdfa engine. Core references: UTMF-Core (software & paper) UTMF v5.2 (software & MFDFA stability paper) jedi_mfdfa (software & implementation paper) See the related identifiers for full DOI references.

Keywords

Multifractal Analysis MFDFA UTMF Fractal Entropy Entropy Geometry Synthetic Time Series Reproducible Research Fractal Asymmetry Kernel Emergence Depth Synthetic Controls Noise Models Universality Classes

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average