PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
May 26, 20260 citationsOpen Access

Toroidal Closure-Cell Geometry for Planck-Normalized Dimensional Recurrence in the Quantized Dimensional Ledger

View Full Paper
JBJames D. BourassaZen-Noh (Japan)

Key Points

Key points are not available for this paper at this time.

Abstract

This preprint develops a toroidal closure-cell representation of the Quantized Dimensional Ledger persistence signature L³F². The construction interprets L³ as effective spatial occupancy and F² as two-cycle recurrence, represented by a compact toroidal recurrence candidate T₍, ₌ with winding data, sectoral data, effective occupancy volume, and recurrence frequencies. A toroidal QDC measure QDCT = VT omega₁ omega₂ is introduced, and physical persistence is defined by survival under a toroidal QDL closure functional. The paper emphasizes that the toroidal closure cell is not a material aether, classical medium, or claim that physical space contains literal toroidal objects. It is a closure-space representation of Planck-normalized dimensional recurrence. The work includes Planck-normalized anchors such as GM having dimensional form L³F², the Planck identity GMP = LP³ FP², and the reduced Compton-gravity threshold m_* = mP / sqrt (2). To connect the construction with established theoretical physics, the paper applies the closure-vector method to a representative Standard Model Effective Field Theory audit. Dimension-six Warsaw-basis operator classes are assigned reduced closure vectors, and selected anomalous-dimension structures are classified as closure-preserving, closure-compensated, or residual-forcing. The SMEFT section is not a completed full anomalous-dimension matrix audit; it is a reproducible criterion for testing whether known nonzero operator-mixing entries preserve declared closure vectors or require explicit Standard Model compensators. The paper is part of the QDL closure-admissibility program and is intended as a full archival version for Zenodo. Conditional extensions to particle-sector classification, vacuum filtering, mass-spectrum projections, and quantum-geometric state selection are identified as future tests rather than established results.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

James D. Bourassa (2026) studied this question.

synapsesocial.com/papers/6a177ad44f2b3115b0129b06https://doi.org/10.5281/zenodo.20401479
Ask AI
Helpful
Bookmark
Share
View Full Paper