Intrinsic alignments of galaxies in the MassiveBlack-II simulation: analysis of two-point statistics

TL;DR

This work uses the MassiveBlack-II hydrodynamic simulation to quantify intrinsic galaxy alignments via GI-type statistics, focusing on ED and w_{g+} while testing inertia-tensor definitions and the impact of mass, redshift, color, and central/satellite status. The analysis demonstrates stronger alignments for more massive galaxies, mild redshift evolution, and a robust agreement with non-linear alignment predictions in the two-halo regime, while revealing a scale-dependent 1-halo bias not captured by NLA at small scales. The results provide practical IA templates and scaling relations for LSST/Euclid, showing MB-II can reproduce observed trends (e.g., LRG-like amplitudes) and offering predictions for future weak-lensing surveys. Overall, the paper highlights the necessity of careful shape definitions, confirms color dependence is modest, and underscores the differing IA behavior of centrals versus satellites as encapsulated by the halo model.

Abstract

The intrinsic alignment of galaxies with the large-scale density field is an important astrophysical contaminant in upcoming weak lensing surveys. We present detailed measurements of the galaxy intrinsic alignments and associated ellipticity-direction (ED) and projected shape ($w_{g+}$) correlation functions for galaxies in the cosmological hydrodynamic MassiveBlack-II (MB-II) simulation. We carefully assess the effects on galaxy shapes, misalignment of the stellar component with the dark matter shape and two-point statistics of iterative weighted (by mass and luminosity) definitions of the (reduced and unreduced) inertia tensor. We find that iterative procedures must be adopted for a reliable measurement of the reduced tensor but that luminosity versus mass weighting has only negligible effects. Both ED and $w_{g+}$ correlations increase in amplitude with subhalo mass (in the range of $10^{10} - 6.0\times 10^{14}h^{-1}M_{\odot}$), with a weak redshift dependence (from $z=1$ to $z=0.06$) at fixed mass. At $z \sim 0.3$, we predict a $w_{g+}$ that is in reasonable agreement with SDSS LRG measurements and that decreases in amplitude by a factor of $\sim 5$--18 for galaxies in the LSST survey. We also compared the intrinsic alignments of centrals and satellites, with clear detection of satellite radial alignments within their host halos. Finally, we show that $w_{g+}$ (using subhalos as tracers of density) and $w_{δ+}$ (using dark matter density) predictions from the simulations agree with that of non-linear alignment models (NLA) at scales where the 2-halo term dominates in the correlations (and tabulate associated NLA fitting parameters). The 1-halo term induces a scale dependent bias at small scales which is not modeled in the NLA model.

Figures (27)

• Figure 1: Normalized histograms of 3D axis ratios of dark matter component in subhalos using different definitions of inertia tensor in mass bins M1, M2 and M3 at $z=0.3$. The number of galaxies are $38768$, $8438$, and $267$ respectively in mass bins M1, M2 and M3. Top:$q~(b/a)$; Bottom:$s~(c/a)$.
• Figure 2: Normalized histograms of 3D axis ratios of stellar matter component in subhalos using different definitions of inertia tensor in mass bins M1, M2 and M3 at $z=0.3$. Top:$q~(b/a)$; Bottom:$s~(c/a)$.
• Figure 3: Normalized histograms of misalignment angles between the major axes of 3D shapes defined by the dark matter and stellar matter component in subhalos using different definitions of inertia tensor, in mass bins (M1, M2, and M3) at $z=0.3$. Note that for uniformly distributed misalignment angles in 3D, the probability distribution is proportional to $\sin{\theta}$.
• Figure 4: ED correlation function, $\omega(r)$, for the 3D shapes of stellar matter obtained using different definitions of inertia tensor in subhalos selected by a mass threshold. The top panel, shows the ED correlation function and the bottom panel shows the ratio of the signals obtained using iterative reduced inertia tensor with the unweighted inertia tensor. Note that in the top panel, the lines labeled Unweighted and Unweighted (Iterative); Reduced and Reduced (Iterative) are close enough that they cannot be easily distinguished. Left:$M > 10^{11}h^{-1}M_{\odot}$ ($24648$ galaxies); Middle:$M > 10^{12.0}h^{-1}M_{\odot}$ ($2947$ galaxies); Right:$M > 10^{13.0}h^{-1}M_{\odot}$ ($267$ galaxies) at $z=0.3$.
• Figure 5: $w_{g+}$ correlation function for the projected (2D) shapes of stellar matter obtained using different definitions of inertia tensor in subhalos selected by a mass threshold at $z=0.3$. The top panel, shows the $w_{g+}$ correlation function and the bottom panel shows the ratio of the signals obtained using iterative reduced inertia tensor with the unweighted inertia tensor. Note that in the top panel, the lines labeled Unweighted and Unweighted (Iterative) are close enough that they cannot be easily distinguished. Left:$M > 10^{11}h^{-1}M_{\odot}$; Middle:$M > 10^{12.0}h^{-1}M_{\odot}$; Right:$M > 10^{13.0}h^{-1}M_{\odot}$.