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Expansion as Boundary Printing: One Printer for Inflation, Dark Energy and Dark Matter, and a Primordial-Tensor Null

David Elliman · Neuro-Symbolic Ltd · 8 July 2026

DOI: 10.5281/zenodo.21251719

Abstract

Cosmic expansion reframed not as a stretching metric but as Holographic Boundary Crystallization — printing fresh zero-entropy cells at the causal horizon to keep the patch under its Bekenstein bound, with inflation and dark energy the same printer at different clock rates. Three results. The scalar sector reduces to a local single-clock queue-balance theorem in which saturated constant-H printing locks the colour-restoring channel load (N_shell·α₀⁴ = C_F = 4/3), giving the sharp candidate A_s = (3/4)α₀⁴ = 2.13×10⁻⁹, within 1σ of Planck, conditional on the channel-lock and spatial-whitening identities. The tensor sector is sharply different: the printer is a scalar process whose graviton — the substrate's transverse shear phonon — is absent at the pre-rigid printing front, giving a primordial-tensor null, r_linear = 0, with only a scalar-induced floor r_induced ∼ 2×10⁻⁹ (no observable B-modes). And the boot cooling law is the printer's own dilution of frustration, Ḟ = −nHF, not a freely chosen anneal. Tiered honestly — the scalar form, the amplitude candidate, and the tensor-null mechanism are robust within stated premises, while CMB completion and absolute dark-sector normalisation retain named gates. Falsifiable by any B-mode detection at r ∼ 10⁻³–10⁻¹·⁴; every number is reproduced by a short self-checking program.

Keywords

cosmic expansioninflationdark energyholographyBekenstein bound

How to cite

Elliman, D. (2026). Expansion as Boundary Printing: One Printer for Inflation, Dark Energy and Dark Matter, and a Primordial-Tensor Null. Neuro-Symbolic Ltd technical report. https://doi.org/10.5281/zenodo.21251719

@techreport{elliman2026boundaryprinting,
  author      = {Elliman, David},
  title       = {Expansion as Boundary Printing: One Printer for Inflation, Dark Energy and Dark Matter, and a Primordial-Tensor Null},
  institution = {Neuro-Symbolic Ltd},
  year        = {2026},
  doi         = {10.5281/zenodo.21251719},
  url         = {https://neusym.ai/papers/boundary_printing/}
}

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