The Serendipitous Axiodilaton: A Self-Consistent Recombination-Era Solution to the Hubble Tension
Bibliographic record
Abstract
Axio-dilaton cosmology provides a minimal benchmark model for both Dark Matter (DM) and Dark Energy (DE) that is well motivated by fundamental physics. The axion and dilaton arise as pseudo-Goldstone modes of symmetries that predict particle masses depend on the dilaton, and therefore to evolve cosmologically, leading to correlated modifications of recombination physics, the sound horizon, and late-time expansion and growth histories. We confront this model with Planck 2018 temperature, polarisation, and lensing data, SPT-3G high-$\ell$ measurements, DESI DR2 BAO, and Pantheon$+$ supernovae, assuming that the axion makes up all of the dark matter and that the dilaton plays the role of a dark energy field. We find that it fits the data somewhat better than $Λ$CDM cosmology, with the $χ^2$ lowered by $\simeq 7$ for three additional parameters, and significantly raises the inferred Hubble constant to $H_0 \simeq 69.2\,\mathrm{km\,s^{-1}\,Mpc^{-1}}$, reducing the Hubble tension to $\lesssim 3σ$ and thereby allowing a joint fit of CMB and SH0ES data. The model fits this enlarged data set as well as the $w_0w_a$ model with an electron mass modified by hand at recombination, though it does so with calculable dynamics. Axio-dilaton self-interactions robustly fake a phantom equation of state in DESI measurements. There is a sting: cosmology prefers dilaton-matter couplings $|\mathbf{g}|\sim 10^{-2}$-$10^{-1}$, which are large enough to have been detected in solar-system tests of General Relativity. These results show how axio-dilatons can provide a viable cosmology preferred by current data at surprisingly large couplings, within a framework that links dark energy, dark matter, and time-dependent particle masses in a coherent way. They suggest both new observable signals and new theoretical directions, aimed at resolving the apparent inconsistency with non-cosmological observations.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".