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Preprint . 2026
License: CC BY NC ND
Data sources: ZENODO
ZENODO
Preprint . 2026
License: CC BY NC ND
Data sources: Datacite
ZENODO
Preprint . 2026
License: CC BY NC ND
Data sources: Datacite
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RENASCENT-Q: Extension of the TET–CVTL Theoretical Framework – Numerical Evidence for Retrocausal Negentropic Effects, Topological Lattice Stabilization, and Convergence Dynamics in Embodied Quantum Systems

Authors: Soliman, Simon;

RENASCENT-Q: Extension of the TET–CVTL Theoretical Framework – Numerical Evidence for Retrocausal Negentropic Effects, Topological Lattice Stabilization, and Convergence Dynamics in Embodied Quantum Systems

Abstract

This repository archives the preprint and supporting numerical resources for RENASCENT-Q, an advanced extension of the TET–CVTL theoretical framework. RENASCENT-Q investigates time-symmetric quantum dynamics in open systems, with a focus on retrocausal mechanisms capable of inducing local negentropic effects (damping parameter β ≈ φ⁻² ≈ 0.382) that counteract standard decoherence.Through custom Lindblad master equation integrations (using QuTiP for quantum simulations), the work demonstrates: Convergence of concurrence toward maximal entanglement (C → 1) and reduction of von Neumann entropy (S → 0) in two-qubit embodied systems under weak retrocausal feedback. Topological protection and lattice stabilization via anyon braiding (Fibonacci/Ising categories), Majorana zero modes (MZMs), and toric code thresholds. Scaling behavior of weak values in the two-state vector formalism (TSVF), showing power-law amplification beyond classical bounds. Ginzburg-Landau vortex dynamics and microtubule-nanowire interface models as potential substrates for room-temperature quantum coherence. The framework bridges quantum information, topological quantum computation, and quantum biology, offering testable predictions for extended Orch-OR-like models of consciousness and novel protocols toward radical biological longevity through sustained quantum effects and negentropic stabilization.Included materials: Compiled preprint PDF Full LaTeX source (.tex) with embedded simulation code listings Bibliography (BibTeX) All generated figures (concurrence trajectories, entropic plots, vortex snapshots, braiding schematics, weak-value scaling, MT-nanowire structures, etc.) Citation metadata (CITATION.cff) and CC BY-NC-ND 4.0 license The simulations are designed for reproducibility within the theoretical context; standalone Python scripts are not provided separately, as the listings in the LaTeX document preserve the exact computational narrative.This deposit preserves the numerical evidence and visual outputs of RENASCENT-Q (preprint dated February 2026) for long-term citability and open-science purposes, linked to the live GitHub repository at https://github.com/TETcollective/RENASCENT-Q." Tetcollective.org tetcollective@proton.me Quest'opera è rilasciata sotto licenza Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0). Non è consentito l'uso commerciale Non è permesso modificare l'opera né crearne versioni derivate Testo legale completo: https://creativecommons.org/licenses/by-nc-nd/4.0/

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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
Green