Extending MGCAMB tests of gravity to nonlinear scales
Bibliographic record
Abstract
Abstract Modified Growth with CAMB (MGCAMB) is a patch for the Einstein-Boltzmann solver CAMB for cosmological tests of gravity. Until now, MGCAMB was limited to scales well-described by linear perturbation theory. In this work, we extend the framework with a phenomenological model that can capture nonlinear corrections in a broad range of modified gravity theories. The extension employs the publicly available halo model reaction code ReACT, developed for modeling the nonlinear corrections to cosmological observables in extensions of the ΛCDM model. The nonlinear extension makes it possible to use a wider range of data from large scale structure surveys, without applying a linear scale cut. We demonstrate that, with the 3×2pt Dark Energy Survey data, we achieve a stronger constraint on the linear phenomenological functions μ and Σ, after marginalzing over the additional nonlinear parameter p 1 , compared to the case without the nonlinear extension and using a linear cut. The new version of MGCAMB is now forked with CAMB on GitHub allowing for compatibility with future upgrades.
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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".