Cosmological tests of Everpresent Λ
Bibliographic record
Abstract
Abstract Everpresent Λ is a cosmological scenario in which the observed cosmological ‘constant’ Λ fluctuates between positive and negative values with a vanishing mean, and with a magnitude comparable to the critical density at any epoch. In accord with a longstanding heuristic prediction of causal set theory, it postulates that Λ is a stochastic function of cosmic time that will vary from one realization of the scenario to another. Herein, we consider two models of ‘dark energy’ that exhibit these features. Via Monte Carlo Markov chains, we explore the space of cosmological parameters and the set of stochastic realizations of these models, finding that Everpresent Λ can fit current cosmological observations as well as the ΛCDM model does. Furthermore, it removes the observational tensions that ΛCDM experiences in relation to low redshift measurements of the Hubble constant, and to the baryonic acoustic oscillations (BAO) in Lyman- α forest at –3. It does not, however, help significantly with the early growth of ultramassive black holes, or with the Lithium problem in Big Bang nucleosynthesis. Future measurements of ‘dark energy’ at high redshifts will further test the viability of Everpresent Λ as an alternative to the ΛCDM cosmology.
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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 | 0.004 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".