From Planck Data to Planck Era: Observational Tests of Holographic Cosmology
Bibliographic record
Abstract
We test a class of holographic models for the very early Universe against cosmological observations and find that they are competitive to the standard cold dark matter model with a cosmological constant (ΛCDM) of cosmology. These models are based on three-dimensional perturbative superrenormalizable quantum field theory (QFT), and, while they predict a different power spectrum from the standard power law used in ΛCDM, they still provide an excellent fit to the data (within their regime of validity). By comparing the Bayesian evidence for the models, we find that ΛCDM does a better job globally, while the holographic models provide a (marginally) better fit to the data without very low multipoles (i.e., l≲30), where the QFT becomes nonperturbative. Observations can be used to exclude some QFT models, while we also find models satisfying all phenomenological constraints: The data rule out the dual theory being a Yang-Mills theory coupled to fermions only but allow for a Yang-Mills theory coupled to nonminimal scalars with quartic interactions. Lattice simulations of 3D QFTs can provide nonperturbative predictions for large-angle statistics of the cosmic microwave background and potentially explain its apparent anomalies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".