Weak Gravitational Lensing with COSMOS: Galaxy Selection and Shape Measurements
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Bibliographic record
Abstract
With a primary goal of conducting precision weak-lensing measurements from space, the COSMOS survey has imaged the largest contiguous area observed by Hubble Space Telescope to date, using the Advanced Camera for Surveys (ACS). This is the first paper in a series in which we describe our strategy for addressing the various technical challenges in the production of weak-lensing measurements from COSMOS data. We first construct a source catalog from 575 ACS/WFC tiles (1.64 deg2) subsampled at a pixel scale of 0.03''. Defects and diffraction spikes are carefully removed, leaving a total of 1.2 × 106 objects to a limiting magnitude of F814W = 26.5. This catalog is made publicly available. Multiwavelength follow-up observations of the COSMOS field provide photometric redshifts for 73% of the source galaxies in the lensing catalog. We analyze and discuss the COSMOS redshift distribution and show broad agreement with other surveys to z ~ 1. Our next step is to measure the shapes of galaxies and correct them for the distortion induced by the time-varying ACS point-spread function and for charge transfer efficiency (CTE) effects. Simulated images are used to derive the shear susceptibility factors that are necessary in transforming shape measurements into unbiased shear estimators. For every galaxy we derive a shape measurement error and utilize this quantity to extract the intrinsic shape noise of the galaxy sample. Interestingly, our results indicate that intrinsic shape noise varies little with size, magnitude, or redshift. Representing a number density of 66 galaxies per arcmin2, the final COSMOS weak-lensing catalog contains 3.9 × 105 galaxies with accurate shape measurements. The properties of the COSMOS weak-lensing catalog described throughout this paper will provide key input numbers for the preparation and design of next-generation wide field space missions.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it