Constraining modified gravity and growth with weak lensing
Bibliographic record
Abstract
The idea that we live in a Universe undergoing a period of acceleration is a new, yet strongly held, notion in cosmology. As this can, potentially, be explained with a modification to general relativity, we look at current cosmological data with the purpose of testing gravity. First, we constrain a phenomenological model [modified Dvali Gabadadze Porrati (mDGP)] motivated by a possible extra dimension. This is characterized by a parameter α which interpolates between α= 0[lambda cold dark matter (LCDM)] and α= 1 (the DGP model). In addition, we analyse general signatures of modified gravity given by the growth parameter γ and power spectrum parameter Σ. We utilize large angular scale (θ > 30 arcmin) weak lensing data (Canada–France–Hawaii Telescope Legacy Survey wide) in order to work in the more linear regime and then add, in combination, baryon acoustic oscillations (BAOs) and supernovae. We subsequently show that current weak-lensing data are not yet capable of constraining either model in isolation. However, we demonstrate that even at present this probe is highly beneficial, for in combination with BAOs and Supernovae we obtain α < 0.58 and 0.91 at 1σ and 2σ, respectively. Without the lensing data, no constraint is possible. This corresponds to a disfavouring of the flat DGP braneworld model at over 2σ. We highlight these are insensitive to potential systematics in the lensing data such as an underestimation of the shear at high redshift. For the growth signature γ, we show that, in combination, these probes do not yet have sufficient constraining power. Finally, we look beyond these present capabilities and demonstrate that Euclid, a future weak-lensing survey, will deeply probe the nature of gravity. A 1σ error of 0.104 is found for α(lmax= 500) whereas for the general modified signatures we forecast 1σ errors of 0.045 for γ and 0.25 for Σ0(lmax= 500), which is further tightened to 0.038 for γ and 0.069 for Σ0(lmax= 10 000).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".