Local Group Analogs in ΛCDM Cosmological Simulations

Abstract

We use semi-analytic galaxy catalogs based on two high-resolution cosmological N-body simulations, Millennium-WMAP7 and Millennium-II, to investigate the formation of the Local Group (LG) analogs. Unlike previous studies, we use the observed stellar masses to select the LG member (Milky Way (MW) and M31) analogs, and then impose constrains using the observed separation, isolation, and kinematics of the two main member galaxies. By comparing radial and low-ellipticity orbits between the MW and M31, we find higher tangential velocity results in higher total mass, which are 4.4 +2.4 −1.5 ×10 12 M and 6.6 +2.7 −1.5 ×10 12 M for radial and low-ellipticity orbits. The orbits also influence the individual mass distribution of MW and M31 analogs. For radial orbits, the typical host halo masses of the MW and M31 are 1.5 +1.4 −0.7 ×10 12 M and 2.5 +1.3 −1.1 ×10 12 M ; for low-ellipticity orbits, the masses are 2.5 +2.2 −1.4 ×10 12 M and 3.8 +2.8 −1.8 ×10 12 M . The LG is located primarily in filaments with tails extending toward higher densities up to δ ∼ 4.5. The dark matter velocity anisotropy parameters β of both the MW and M31 analogs are close to zero in the center, increasing to 0.2-0.3 at 50-80 kpc and decreasing slowly outward. The slope is much flatter than computed from the MW satellites, and the amplitude is smaller than traced by halo stars. Values of β from different tracers agree at ∼120 kpc where β ∼ 0.2. We also find that model predictions agree broadly with observations in the radial distribution and luminosity function of satellites around the MW and M31.

On the absence of backsplash analogues to NGC 3109 in the ΛCDM framework

“…This mass range covers the LG mass estimated in various ways, e.g. it is similar to the range reported by González et al (2014) and Zhai et al (2020) based on LG analogues in cosmological simulations with a similar separation and relative velocity to the MW-M31 system. The 1D timing argument analyses of Peñarrubia et al (2014) and Peñarrubia et al (2016) give values near the lower end of this range.…”

“…This might well explain the unusually low LG mass of (1.6 ± 0.2) × 10 12 M found in this manner by Kashibadze & Karachentsev (2018), with their table 4 indicating that their analysis included the NGC 3109 association. Zhai et al (2020) obtained a much higher timing argument mass of 4.4 +2.4 −1.5 × 10 12 M by searching cosmological simulations for analogues to the LG based on properties of the MW and M31 alone, especially with regards to their relative separation and velocity. This mass is in line with earlier results and simple analytic estimates neglecting information on LG galaxies other than the MW and M31 (Li & White 2008).…”

The mass of our Milky Way

“…Very recently, Zhai et al in 2020 [423] looked for MW-31 like systems in numerical simulations, and they found that higher tangential velocities correspond to higher total mass and also affect the individual mass distribution of MW and M31 analogs. The typical host halo mass of MW is 1.5 +1.…”

Implications of the Milky Way travel velocity for dynamical mass estimates of the Local Group

“…+ HST PM dataset. Zhai et al (2020) identified pairs of stellar analogs to the MW and M31, then applied a series of kinematic cuts on the separation, isolation, and velocities of the pair to determine Local Group analogs in two N -body cosmological simulations, Millenium-WMAP7 and MilleniumII. They find stellar and dynamical LG analogs on mostly radial orbits have total masses of 4.4 +2.4 −1.5 × 10 12 M , which is consistent with our findings for each dataset.…”

“…much smaller than LG scales) and then extrapolate, leading to mass-profile-dependent estimates of the total LG mass. Other techniques aim to more directly measure the mass of the Local Group en masse, for example looking for Local Group analogs in cosmological simulations based on stellar mass and kinematic criteria (e.g., Li & White 2008;González et al 2014;Hartl & Strigari 2021;Zhai et al 2020), by studying the kinematics of Local Volume galaxies (e.g., Diaz et al 2014;Peñarrubia et al 2014), or by applying machine learning (ML) techniques to hydrodynamic simulation data (e.g., McLeod et al 2017;Villanueva-Domingo et al 2021). One of the earliest methods utilized in this vein is the "Timing Argument," which uses the fact that the local group galaxies (most often the MW and M31) are bound and approaching pericenter in their relative orbit, but must have been close enough over cosmic time to not be pulled apart by the Hubble flow.…”