{
  "abstract": "Title\n\nTDH-CRAH-AI-Σ (TDH-Causal Reorganization & Accumulation Hub): An Advanced Architectural Variant for Multi-Scale Feedback, Tensor-Driven Causation, and Entropic Governance Boundaries\n\nVersion\n\n2.0 - (Math extended)\n\nAuthors\n\nThai, Dinh Hau (TDH)\n\n(Thái Đình Hầu (Vietnamese name))\n\n(Pen-names: TDH, or Thomas H. D. Thai, Thomas Thai, Thoriel-TDH)\n\nAffiliation\n\nIndependent Researcher\n\n(Scientifically Theoretical Architect)\n\nDate of Publication\n\n2026-10-24\n\nDescription/Abstract\n\nThis work presents an advanced mathematical and structural divergence of the TDH-CRAH-AI-Σ framework, explicitly designed to elevate its initial pre-formal systems paradigm into an independently viable operational model within the Combined Intangible and Tangible Verse (CIT-Verse).\n\nWhile parallel repository deposits (such as DOI: 10.5281/zenodo.23288373) focus on basic computational procedural loop execution, this isolated Version 2.0-Math-Extended treatise provides a comprehensive text-driven formalization of the system's underlying mathematical operators. This manuscript introduces multi-scale history tensor equations for causal accumulation within the Causal Reorganization and Accumulation Hub (CRAH), non-linear coupled field aggregations for cognitive module summation (Σ), and explicit entropic boundary minimization constraints for the internal housekeeping governance system (Gov).\n\nIncluded in this repository are complete, warning-free LaTeX source assets, publication-grade math formatting blocks, and a native Python simulation script that computationally verifies system telemetry stabilization parameters post-transition without requiring centralized top-down control loops. This framework functions as an organizational systems paradigm designed to complement existing computational and physical laws.\n\nKeywords\n\nTDH Theory\n\nTDH-CRAH-AI-Sigma (Causal Reorganization & Accumulation Hub)\n\nCIT-Verse (Combined Intangible & Tangible -Verse)\n\nMulti-Scale Feedback Mechanics\n\nTensor-Driven Causation\n\nCausal Reorganization and Accumulation Hub (CRAH)\n\nHousekeeping Governance (Gov)\n\nEntropic Boundary Constraints\n\nPython Loop Simulation\n\nMatrix Stabilization Function\n\nCognitive Architecture\n\nDecentralized Emergence\n\nLicense\n\nCreative Commons Attribution 4.0 International (CC BY 4.0)",
  "abstract_shown": true,
  "affiliations": [
    "Private Researcher"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 1,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Hau Dinh Thai",
      "orcid": "0009-0001-2276-7953"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/3gddbbk3ver5x.bib",
  "cited_by": 0,
  "doi": "10.5281/zenodo.23624739",
  "fulltext_url": null,
  "id": "3gddbbk3ver5x",
  "issns": [],
  "landing_url": "https://zenodo.org/records/23624739",
  "language": "eng",
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [],
  "openalex": null,
  "pdf_url": "https://zenodo.org/api/records/23624739/files/tdh_CRAH_%CE%A3_.pdf/content",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-24",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/3gddbbk3ver5x.ris",
  "sources": [
    {
      "first_seen": "2026-11-07T12:20:36Z",
      "native_id": "23624739",
      "source": "zenodo",
      "url": "https://zenodo.org/records/23624739"
    }
  ],
  "subjects": [],
  "title": "TDH-CRAH-AI-Σ (TDH-Causal Reorganization & Accumulation Hub): An Advanced Architectural Variant for Multi-Scale Feedback, Tensor-Driven Causation, and Entropic Governance Boundaries (Version 2.0 - Math Extended)",
  "title_text": "TDH-CRAH-AI-Σ (TDH-Causal Reorganization & Accumulation Hub): An Advanced Architectural Variant for Multi-Scale Feedback, Tensor-Driven Causation, and Entropic Governance Boundaries (Version 2.0 - Math Extended)",
  "type": "preprint",
  "updated_at": "2026-11-07T12:20:36Z",
  "url": "https://research.draconitic.com/paper/3gddbbk3ver5x",
  "venue": "Zenodo",
  "versions": []
}