Monday, May 6, 2019

Day 1562

Monday.



1905.00906
The evolution of galaxy intrinsic alignments in the MassiveBlack II universe
Bhomwick, et al

We investigate the redshift evolution of the intrinsic alignments (IA) of galaxies in the \texttt{MassiveBlackII} (MBII) simulation. We select galaxy samples above fixed subhalo mass cuts ($M_h>10^{11,12,13}~M_{\odot}/h$) at $z=0.6$ and trace their progenitors to $z=3$ along their merger trees. Dark matter components of $z=0.6$ galaxies are more spherical than their progenitors while stellar matter components tend to be less spherical than their progenitors. The distribution of the galaxy-subhalo misalignment angle peaks at $\sim10~\mathrm{deg}$ with a mild increase with time. The evolution of the ellipticity-direction~(ED) correlation amplitude $\omega(r)$ of galaxies (which quantifies the tendency of galaxies to preferentially point towards surrounding matter overdensities) is governed by the evolution in the alignment of underlying dark matter~(DM) subhaloes to the matter density of field, as well as the alignment between galaxies and their DM subhaloes. At scales $\sim1~\mathrm{cMpc}/h$, the alignment between DM subhaloes and matter overdensity gets suppressed with time, whereas the alignment between galaxies and DM subhaloes is enhanced. These competing tendencies lead to a complex redshift evolution of $\omega(r)$ for galaxies at $\sim1~\mathrm{cMpc}/h$. At scales $>1~\mathrm{cMpc}/h$, alignment between DM subhaloes and matter overdensity does not evolve significantly; the evolution of the galaxy-subhalo misalignment therefore leads to an increase in $\omega(r)$ for galaxies by a factor of $\sim4$ from $z=3$ to $0.6$ at scales $>1~\mathrm{cMpc}/h$. The balance between competing physical effects is scale dependant, leading to different conclusions at much smaller scales($\sim0.1~\mathrm{Mpc}/h$).


1905.01133
Estimating the galaxy two-point correlation function using a split random catalog
Keihänen, et al

The two-point correlation function of the galaxy distribution is a key cosmological observable that allows us to constrain the dynamical and geometrical state of our Universe. To measure the correlation function we need to know both the galaxy positions and the expected galaxy density field. The expected field is commonly specified using a Monte-Carlo sampling of the volume covered by the survey and, to minimize additional sampling errors, this random catalog has to be much larger than the data catalog. Correlation function estimators compare data-data pair counts to data-random and random-random pair counts, where random-random pairs usually dominate the computational cost. Future redshift surveys will deliver spectroscopic catalogs of tens of millions of galaxies. Given the large number of random objects required to guarantee sub-percent accuracy, it is of paramount importance to improve the efficiency of the algorithm without degrading its precision. We show both analytically and numerically that splitting the random catalog into a number of subcatalogs of the same size as the data catalog when calculating random-random pairs, and excluding pairs across different subcatalogs provides the optimal error at fixed computational cost. For a random catalog fifty times larger than the data catalog, this reduces the computation time by a factor of more than ten without affecting estimator variance or bias.

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