The effect of imperfect models of point spread function anisotropy on cosmic shear measurements
Bibliographic record
Abstract
Current measurements of the weak lensing signal induced by large scale structure provide useful constraints on a range of cosmological parameters. However, the ultimate success of this technique depends on the accuracy with which one corrects for the effect of the point spread function (PSF), in particular the correction for the PSF anisotropy. With upcoming large weak lensing surveys, a proper understanding of residual systematics is necessary. In this paper, we examine the importance of the adopted model for the spacial variation of the PSF anisotropy using images of fields with a large number of stars. A wrong parametrization of the PSF anisotropy leads to a residual signal in the data, affecting the cosmic shear measurements. We use data taken with the Canada–France–Hawaii 12k (CFH12k) camera, and note that some of the results might not be valid for other instruments. We select a random subset of stars which are used to characterize the PSF and to correct the shapes of the remaining stars. The ellipticity correlation function of the residuals is studied to quantify the effect of residual PSF anisotropy on cosmic shear studies. In order to single out the effect of the parametrization, we assume a perfect method for the actual correction of galaxy shapes. The PSF anisotropy is typically modelled for each individual chip of a mosaic; consequently, the residuals are coherent on small scales. As a result, the systematic signal decreases rapidly with increasing angular scale. Separation of the signal into ‘E’ (curl free) and ‘B’ (curl) components can help to identify the presence of residual systematics, but in general, the amplitude of the ‘B’ mode is different from that of the ‘E’ mode. The study of fields with many stars can be beneficial in finding a proper description of the variation of PSF anisotropy, and consequently can help to improve the accuracy with which the cosmic shear signal can be measured significantly. We show that such an approach can lead to an appreciable reduction in systematics. The results suggest that the prospects for accurate measurements of the cosmic shear signal on scales larger than ∼10 arcmin are excellent.
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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 | 0.016 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".