Potential sources of contamination to weak lensing measurements: constraints from N-body simulations
Bibliographic record
Abstract
We investigate the expected correlation between the weak gravitational shear of distant galaxies and the orientation of foreground galaxies, through the use of numerical simulations. This shear–ellipticity correlation can mimic a cosmological weak lensing signal, and is potentially the limiting physical systematic effect for cosmology with future high-precision weak lensing surveys. We find that, if uncorrected, the shear–ellipticity correlation could contribute up to 10 per cent of the weak lensing signal on scales up to 20 arcmin, for lensing surveys with a median depth zm= 1. The most massive foreground galaxies are expected to cause the largest correlations, a result also seen in the Sloan Digital Sky Survey. We find that the redshift dependence of the effect is proportional to the lensing efficiency of the foreground, and this offers prospects for removal to high precision, although with some model dependence. The contamination is characterized by a weakly negative B mode, which can be used as a diagnostic of systematic errors. We also provide more accurate predictions for a second potential source of error, the intrinsic alignment of nearby galaxies. This source of contamination is less important, however, as it can be easily removed with distance information.
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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".