Dark energy in the swampland
Bibliographic record
Abstract
In this article, we study the implications of string swampland criteria for dark energy in view of ongoing and future cosmological observations. If string theory should be the ultimate quantum gravity theory, there is evidence that exact de Sitter solutions with a positive cosmological constant cannot describe the fate of the late-time universe. Even though cosmological models with dark energy given by a scalar field $\ensuremath{\pi}$ evolving in time are not in direct tension with string theory, they have to satisfy the swampland criteria $|\mathrm{\ensuremath{\Delta}}\ensuremath{\pi}| c\ensuremath{\sim}\mathcal{O}(1)$, where $V$ is the scalar field potential. In view of the restrictive implications that the swampland criteria have on dark energy, we investigate the accuracy needed for future observations to tightly constrain standard dark-energy models. We find that current $3\text{\ensuremath{-}}\ensuremath{\sigma}$ constraints with $c\ensuremath{\lesssim}1.35$ are still well in agreement with the string swampland criteria. However, stage-4 surveys such as Euclid, LSST, and DESI, tightly constraining the equation of state $w(z)$, will start putting surviving quintessence models into tensions with the string swampland criteria by demanding $c<0.4$. We further investigate whether any idealized futuristic survey will ever be able to give a decisive answer to the question whether the cosmological constant would be preferred over a time-evolving dark-energy model within the swampland criteria. Hypothetical surveys with a reduction in the uncertainties by a factor of $\ensuremath{\sim}20$ compared to Euclid would be necessary to reveal strong tension between quintessence models obeying the string swampland criteria and observations by pushing the allowed values down to $c<0.1$. In view of such perspectives, there will be fundamental observational limitations with future surveys.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".