The Subaru FMOS galaxy redshift survey (FastSound). V. Intrinsic alignments of emission-line galaxies at <i>z</i> ∼ 1.4
Bibliographic record
Abstract
Abstract Intrinsic alignments (IA), the coherent alignment of intrinsic galaxy orientations, can be a source of a systematic error of weak lensing surveys. The redshift evolution of IA also contains information about the physics of galaxy formation and evolution. This paper presents the first measurement of IA at high redshift, z ∼ 1.4, using the spectroscopic catalog of blue star-forming galaxies of the FastSound redshift survey, with the galaxy shape information from the Canada–Hawaii–France telescope lensing survey. The IA signal is consistent with zero with power-law amplitudes fitted to the projected correlation functions for density–shape and shape–shape correlation components, Aδ+ = −0.0071 ± 0.1340 and A++ = −0.0505 ± 0.0848, respectively. These results are consistent with those obtained from blue galaxies at lower redshifts (e.g., $A\,_{\delta +}=0.0035_{-0.0389}^{+0.0387}$ and $A_{++}=0.0045_{-0.0168}^{+0.0166}$ at z = 0.51 from the WiggleZ survey). The upper limit of the constrained IA amplitude corresponds to a few percent contamination to the weak-lensing shear power spectrum, resulting in systematic uncertainties on the cosmological parameter estimations by −0.052 &lt; Δσ8 &lt; 0.039 and −0.039 &lt; ΔΩm &lt; 0.030.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".