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Record W4417251330 · doi:10.48550/arxiv.2504.07966

What it takes to solve the Hubble tension through scale-dependent modifications of the primordial power spectrum

2025· preprint· en· W4417251330 on OpenAlexfundno aff
Nanoom Lee, Matteo Braglia, Yacine Ali-Haïmoud

Bibliographic record

VenueArXiv.org · 2025
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicCosmology and Gravitation Theories
Canadian institutionsnot available
FundersYork UniversityJohns Hopkins University
KeywordsPlanckCosmic microwave backgroundHubble's lawSpectral densityMatter power spectrumBaryon acoustic oscillationsHubble volumeCOSMIC cancer databaseCosmologyIntensity mapping

Abstract

fetched live from OpenAlex

We investigate scale-dependent modifications to the primordial scalar power spectrum as potential solutions to the Hubble tension. We use the Fisher-bias formalism, recently adapted to examine perturbed recombination solutions to the Hubble tension, and extend its range of validity with an iterative method. We first analyze the Planck cosmic microwave background (CMB) anisotropy data, demonstrating the existence of modifications to the primordial power spectrum capable of fully resolving the tension between Planck and SH0ES. As a proof of concept, we interpret these solutions in terms of small, time-dependent variations in the first slow roll parameter or in the sound speed of curvature perturbations during a stage of primordial inflation. However, these solutions are associated with a low total matter density $Ω_m$, which makes them inconsistent with baryon acoustic oscillations (BAO) and uncalibrated supernovae (SNIa) data. When incorporating additional BOSS and PantheonPlus data, the solutions that reduce the Hubble tension tend to overfit Planck CMB data to compensate for the worsened fit to BAO and SNIa data, making them less compelling. These findings suggest that modifying the primordial power spectrum alone is unlikely to provide a robust resolution to the tension and highlight how the viability of such data-driven solutions depends on the specific datasets considered, emphasizing the role of future high-precision observations in further constraining possible resolutions to the tension.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.139
Threshold uncertainty score0.582

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.028
GPT teacher head0.291
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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