Improving on numerical simulations of nonlinear CMB anisotropies
Bibliographic record
Abstract
An Adaptative-Particle-Particle-Particle-Mesh code (HYDRA) plus a ray-tracing procedure was used in [1] to perform an exhaustive analysis of the weak lensing anisotropy. Other nonlinear Cosmic Microwave Background anisotropies, such as the Rees-Sciamaand the Sunyaev-Zel.dovicheffects are also being studied by using the same tools. Here we present some advances in our study of these nonlinear anisotropies. The primary advance is due to the use of better simulations with greater particle densities and appropriate softening, although other parameters have also been adjusted to get better estimates. Thus, we improve on a previous paper [2] where the Rees-Sciamaeffect was studied with Particle-Mesh simulations. We focus particular attention on the resolution improvement and its consequences.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".