First Evidence of Intrinsic Alignments of Red Galaxies at z > 1: Cross Correlation between CFHTLenS and FastSound Samples
Bibliographic record
Abstract
Abstract We report the first evidence for intrinsic alignment (IA) of red galaxies at z > 1. We measure the gravitational shear-intrinsic ellipticity cross correlation function at z ∼ 1.3 using galaxy positions from the FastSound spectroscopic survey and galaxy shapes from the Canada France Hawaii telescope lensing survey data. Adopting the nonlinear alignment model, we obtain a 2.4σ level detection of the IA amplitude A LA = 27.48 − 11.54 + 11.53 (and 2.6σ with A LA = 29.43 − 11.49 + 11.48 when weak lensing contaminations are taken into account), which is larger than the value extrapolated from the constraints obtained at lower redshifts. Our measured IA is translated into a ∼20% contamination of the weak-lensing power spectrum for the red galaxies. This marginal detection of IA for red galaxies at z > 1 motivates the continuing investigation of the nature of IA for weak lensing studies. Furthermore, our result provides the first step to utilize IA measurements in future high-z surveys as a cosmological probe, complementary to galaxy clustering and lensing.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".