Searching for scalar gravitational interactions in current and future cosmological data
Bibliographic record
Abstract
Modified gravity theories often contain a scalar field of gravitational strength which interacts with matter. We examine constraints on the range and the coupling strength of a scalar gravitational degree of freedom using a subset of current data that can be safely analyzed within the linear perturbation theory. Using a model-independent implementation of scalar-tensor theories in mgcamb in terms of two functions of the scale factor describing the mass and the coupling of the scalar degree of freedom, we derive constraints on the $f(R)$, generalized chameleon, symmetron and dilaton models. Since most of the large scale structure data available today is from relatively low redshifts, only a limited range of observed scales is in the linear regime, leading to relatively weak constraints. We then perform a forecast for a future large scale structure survey, such as the Large Synoptic Survey Telescope (LSST), which will map a significant volume at higher redshifts, and show that it will produce much stronger constraints on scalar interactions in specific models. We also perform a principal component analysis and find that future surveys should be able to provide tight constraints on several eigenmodes of the scalar mass evolution.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".