Swampland conjectures constraints on dark energy from a highly curved field space
Bibliographic record
Abstract
We study the interplay of the trans-Planckian censorship conjecture (TCC) and the swampland distance conjecture (SDC) in the context of multifield dark energy in a curved field space. In this scenario, the phase of accelerated expansion is realized as nongeodesic motion in a highly curved field space, reminiscent of models developed in the context of inflation. The model features a stable attractor solution with near constant equation of state w ≃ − 1 , and predicts that the current era of accelerated expansion is eternal. The latter implies an eventual conflict with the TCC, which holds that the duration of any epoch of cosmic acceleration is bounded by the requirement that the large-scale observable universe is blind to Planck-scale early universe physics. This tension can be resolved by an interplay with the distance conjecture: for suitable parameter values, the apparent violation of the TCC occurs well after the fields have traversed a Planckian distance. The SDC then predicts a breakdown of the effective field theory before the TCC can be violated. We derive the constraints on the model arising from the SDC + TCC and the de Sitter conjecture. We demonstrate that the model can be consistent with both swampland conjectures and observational data from Planck 2018 and the Dark Energy Spectroscopic Instrument. Published by the American Physical Society 2024
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".