The formation of satellite galaxies and their associated black holes

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Estimating the Mass of the Local Group using Machine Learning Applied to Numerical Simulations

We revisit the estimation of the combined mass of the Milky Way and Andromeda (M31), which dominate the mass of the Local Group. We make use of an ensemble of 30,190 halo pairs from the Small MultiDark simulation, assuming a $\Lambda$CDM (Cosmological Constant with Cold Dark Matter) cosmology, to investigate the relationship between the bound mass and parameters characterising the orbit of the binary and their local environment with the aid of machine learning methods (artificial neural networks, ANN). Results from the ANN are most successful when information about the velocity shear is provided, which demonstrates the flexibility of machine learning to model physical phenomena and readily incorporate new information as it becomes available. The resulting estimate for the Local Group mass, when shear information is included, is $4.9 \times 10^{12} M_\odot$, with an error of $\pm0.8 \times 10^{12} M_\odot$ from the 68% uncertainty in observables, and a 68% confidence interval of $^{+1.3}_{-1.4} \times 10^{12}M_\odot$ from the intrinsic scatter from the differences between the model and simulation masses. We also consider a recently reported large transverse velocity of M31 relative to the Milky Way, and produce an alternative mass estimate of $3.6\pm0.3\pm1.4 \times 10^{12}M_\odot$. Although different methods predict similar values for the most likely mass of the LG, application of ANN compared to the Timing Argument reduces the scatter in the log mass by over half when tested on samples from the simulation.Comment: 20 pages, 6 figures, 5 table

The spin alignment of galaxies with the large-scale tidal field in hydrodynamic simulations

The correlation between the spins of dark matter halos and the large-scale structure (LSS) has been studied in great detail over a large redshift range, while investigations of galaxies are still incomplete. Motivated by this point, we use the state-of-the-art hydrodynamic simulation, Illustris-1, to investigate mainly the spin--LSS correlation of galaxies at redshift of $z=0$. We mainly find that the spins of low-mass, blue, oblate galaxies are preferentially aligned with the slowest collapsing direction ($e_3$) of the large-scale tidal field, while massive, red, prolate galaxy spins tend to be perpendicular to $e_3$. The transition from a parallel to a perpendicular trend occurs at $\sim10^{9.4} M_{\odot}/h$ in the stellar mass, $\sim0.62$ in the g-r color, and $\sim0.4$ in triaxiality. The transition stellar mass decreases with increasing redshifts. The alignment was found to be primarily correlated with the galaxy stellar mass. Our results are consistent with previous studies both in N-body simulations and observations. Our study also fills the vacancy in the study of the galaxy spin--LSS correlation at $z=0$ using hydrodynamical simulations and also provides important insight to understand the formation and evolution of galaxy angular momentum.Comment: 9 pages, 6 figures, 1 table. Accepted for publication in ApJ, match the proof versio