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Prediction note

A Primordial-Tensor Null from Boundary Printing: Pre-registering r_linear=0 and a Scalar-Induced Floor

David Elliman · Neuro-Symbolic Ltd · 30 June 2026

DOI: 10.5281/zenodo.21062226

Abstract

A short, dated prediction from the boundary-printing branch: a primordial-tensor null, r_linear = 0. In this branch inflation is not a smooth de Sitter stretching of an existing metric but the printing of fresh boundary cells by a scalar counting process — and a scalar source has no transverse-traceless part, so the spin-2 projector annihilates it at linear order. The often-quoted r ∼ 2×10⁻⁹ is therefore not a primordial squeezed-tensor amplitude but only the expected second-order scalar-induced floor, r_induced = C_SIGW·A_s ≃ 2.13×10⁻⁹ (with C_SIGW an external radiation-transfer coefficient, not a fitted substrate parameter), far below any near-term reach. The prediction-grade near-term claim is a null: no primordial B-mode detection at r ≳ 10⁻³ after dust, lensing and systematics — a clean kill switch, since a robust signal at that level (LiteBIRD, CMB-S4) would force a squeezed-graviton vacuum and refute the boundary-printer branch. The note also pre-commits the post-hoc rules: the denominator, the one-bit printer premise, and A_s = (3/4)α₀⁴ cannot be retuned after the data arrive, and a hidden squeezed-graviton vacuum would be a new branch, not this one.

Keywords

primordial gravitational wavestensor-to-scalar ratioB-modescosmic microwave backgroundinflation

How to cite

Elliman, D. (2026). A Primordial-Tensor Null from Boundary Printing: Pre-registering r_linear=0 and a Scalar-Induced Floor. Neuro-Symbolic Ltd technical report. https://doi.org/10.5281/zenodo.21062226

@techreport{elliman2026primordialtensorprediction,
  author      = {Elliman, David},
  title       = {A Primordial-Tensor Null from Boundary Printing: Pre-registering r_linear=0 and a Scalar-Induced Floor},
  institution = {Neuro-Symbolic Ltd},
  year        = {2026},
  doi         = {10.5281/zenodo.21062226},
  url         = {https://neusym.ai/papers/primordial_tensor_prediction}
}

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