PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
January 18, 20260 citationsOpen Access

Two-Energy Theory (TDE) v12.0: Dark Matter Yield as a Topological Branching Efficiency

View Full Paper
MSMichał Karol Surowiecki

Key Points

  • The research aims to define boundary conditions for the Two-Energy Theory (TDE) using the dark matter density ratio.
  • Established the cosmological dark matter-to-baryon density ratio using observational data.
  • Introduced topological resonance concepts in the TDE framework.
  • Defined a dimensionless topological barrier parameter to relate to the density ratio.
  • Set conditions for dark matter behavior during structure formation.
  • Mapped the Planck dark matter-to-baryon density ratio into a calibration target.
  • Established the topological barrier parameter value at approximately 1.68.
  • Provided falsification criteria for the dark matter regime under TDE.

Abstract

This chapter establishes an observationally anchored boundary condition for Two-Energy Theory (TDE) v12.0 using the cosmological dark-matter-to-baryon density ratio, Ωc/Ωb ≈ 5.36 (Planck 2018). In the TDE v12.0 interpretation, this ratio is not treated as a fit parameter but as the outcome of an early-Universe topological resonance of the Shadow Field χ into two channels: n = 1 (successful, baryonic topological knots) and n = 0 (unsuccessful, electromagnetically dark energy-localized configurations identified with dark matter). We introduce a minimal dimensionless “topological barrier” parameter, ΔStopo ≡ ln(Ωc/Ωb) ≈ 1.68, which directly maps the Planck ratio into a calibration target to be derived from χ microphysics in later work. The chapter specifies necessary conditions for the n = 0 sector to behave as cold dark matter (effective w ≈ 0 during structure formation), and provides explicit falsification criteria if such a regime cannot be realized or if ΔStopo cannot emerge from reasonable χ microphysics without ad hoc degrees of freedom. A reproducibility package (Python scripts and precomputed outputs) is included to independently verify all numerical anchors and plots.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Michał Karol Surowiecki (2026) studied this question.

synapsesocial.com/papers/696c7835eb60fb80d1396785https://doi.org/10.5281/zenodo.18267046
Ask AI
Helpful
Bookmark
Share
View Full Paper