The WiggleZ Dark Energy Survey: Direct constraints on blue galaxy intrinsic alignments at intermediate redshifts

TL;DR

This study delivers the first direct measurement of intrinsic alignments for blue galaxies at intermediate redshift ($z\sim0.6$) by correlating WiggleZ spectroscopic redshifts with SDSS shape measurements. The authors find null detections for both GI and II correlations, setting upper limits on contamination to cosmic shear that are robust against extrapolation from low-redshift results. They test simple power-law and non-linear alignment (NLA) models, obtaining tight constraints on the alignment amplitude $C_1$ and allowing a redshift-evolution parameter $\eta_{other}$, which remain consistent with zero within uncertainties. By combining WiggleZ with SDSS blue-galaxy constraints, they show that intrinsic alignments of blue galaxies contribute negligibly to $\sigma_8$ biases in CFHTLS-like surveys, marking an important step toward preserving cosmological information in future weak-lensing analyses, while highlighting the need for red-galaxy constraints and consideration of alternative alignment scenarios.

Abstract

Correlations between the intrinsic shapes of galaxy pairs, and between the intrinsic shapes of galaxies and the large-scale density field, may be induced by tidal fields. These correlations, which have been detected at low redshifts (z<0.35) for bright red galaxies in the Sloan Digital Sky Survey (SDSS), and for which upper limits exist for blue galaxies at z~0.1, provide a window into galaxy formation and evolution, and are also an important contaminant for current and future weak lensing surveys. Measurements of these alignments at intermediate redshifts (z~0.6) that are more relevant for cosmic shear observations are very important for understanding the origin and redshift evolution of these alignments, and for minimising their impact on weak lensing measurements. We present the first such intermediate-redshift measurement for blue galaxies, using galaxy shape measurements from SDSS and spectroscopic redshifts from the WiggleZ Dark Energy Survey. Our null detection allows us to place upper limits on the contamination of weak lensing measurements by blue galaxy intrinsic alignments that, for the first time, do not require significant model-dependent extrapolation from the z~0.1 SDSS observations. Also, combining the SDSS and WiggleZ constraints gives us a long redshift baseline with which to constrain intrinsic alignment models and contamination of the cosmic shear power spectrum. Assuming that the alignments can be explained by linear alignment with the smoothed local density field, we find that a measurement of σ_8 in a blue-galaxy dominated, CFHTLS-like survey would be contaminated by at most +/-0.02 (95% confidence level, SDSS and WiggleZ) or +/-0.03 (WiggleZ alone) due to intrinsic alignments. [Abridged]

Figures (12)

• Figure 1: Top: Solid black, dashed red, and long-dashed blue lines show the fraction of WiggleZ galaxies in the 09h, 11h, and 15h fields (respectively) that have high-quality shape measurements in SDSS, as a function of $r$-band apparent model magnitude. The arbitrarily-normalised, hatched magenta curve drawn with dotted lines shows the apparent magnitude distribution of the full WiggleZ sample. Bottom: Similar to the top, but as a function of redshift. The local minimum in the good shape fraction at $z \approx 0.3$ is created by the strong correlation of galaxy luminosity with redshift in the WiggleZ sample, with the result that galaxies at lower redshifts have preferentially smaller effective radii, which more than offsets the larger apparent size due to the lower redshift. The tail of good shapes at $z > 1$ is partially due to the redshift blunder rate in the WiggleZ sample, which is about $3\%$ at $z = 0.6$ but rises steeply at $z > 1$ to almost $50\%$2009MNRAS.395..240B.
• Figure 2: Top: Projected GI cross-correlation signal $w_{g+}(r_p)$, multiplied by $r_p^{0.8}$. Results are shown for each field separately: 09h (black solid line with hexagonal points); 11h (red dashed line with crosses); and 15h (blue dot-short dashed line with solid squares). Points at a given value of $r_p$ are slightly horizontally offset for clarity. Bottom: Same as the top, but for the II cross-correlation signal $w_{++}(r_p)$.
• Figure 3: Top: Projected GI cross-correlation signal $w_{g+}(r_p)$, multiplied by $r_p^{0.8}$. Results are shown averaged over all regions, for the two redshift subsamples. Points at a given value of $r_p$ are slightly horizontally offset for clarity. Bottom: Same as the top, but for the II cross-correlation signal $w_{++}(r_p)$.
• Figure 4: Top: Projected GI cross-correlation signal $w_{g+}(r_p)$, multiplied by $r_p^{0.8}$. Results are shown averaged over all regions, for the two values of $\Pi_\mathrm{max}$. Points at a given value of $r_p$ are slightly horizontally offset for clarity. Bottom: Same as the top, but for the II cross-correlation signal $w_{++}(r_p)$.
• Figure 5: Top: Projected GI cross-correlation signal $w_{g+}(r_p)$ and the systematics test $w_{g\times}(r_p)$ (as indicated on the plot), multiplied by $r_p^{0.8}$. Results are shown averaged over all regions. Points at a given value of $r_p$ are slightly horizontally offset for clarity. Bottom: Same as the top, but for the II auto-correlation signals $w_{++}(r_p)$ and $w_{\times\times}(r_p)$, and their systematics test, the cross-correlation $w_{+ \times}(r_p)$.