ShapePipe: A new shape measurement pipeline and weak-lensing application to UNIONS/CFIS data
Bibliographic record
Abstract
Context. The Ultraviolet Near-Infrared Optical Northern Survey (UNIONS) is an ongoing collaboration that will provide the largest deep photometric survey of the northern sky in four optical bands to date. As part of this collaboration, the Canada-France Imaging Survey (CFIS) is observing r -band data with an average seeing of 0.65 arcsec, which is complete to magnitude 24.5 and thus ideal for weak-lensing studies. Aims. We perform the first weak-lensing analysis of CFIS r -band data over an area spanning 1700 deg 2 of the sky. We create a catalogue with measured shapes for 40 million galaxies, corresponding to an effective density of 6.8 galaxies per square arcminute, and demonstrate a low level of systematic biases. This work serves as the basis for further cosmological studies that will use the full UNIONS survey of 4800 deg 2 when completed. Methods. Here we present S HAPE P IPE , a newly developed weak-lensing pipeline. This pipeline makes use of state-of-the-art methods such as N GMIX for accurate galaxy shape measurement. Shear calibration is performed with metacalibration. We carry out extensive validation tests on the point spread function (PSF) and on the galaxy shapes. In addition, we create realistic image simulations to validate the estimated shear. Results. We quantify the PSF model accuracy and show that the level of systematics is low as measured by the PSF residuals. Their effect on the shear two-point correlation function is sub-dominant compared to the cosmological contribution on angular scales < 100′. The additive shear bias is below 5 × 10 −4 , and the residual multiplicative shear bias is at most 10 −3 as measured on image simulations. Using complete orthogonal sets of E -/ B -mode integrals (COSEBIs), we show that there are no significant B -modes present in second-order shear statistics. We present convergence maps and see clear correlations of the E -mode with known cluster positions. We measure the stacked tangential shear profile around Planck clusters at a significance higher than 4 σ .
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.007 |
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".