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Register a new userThe sum of the masses of the Milky Way and M31: a likelihood-free inference approach
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We use Density Estimation Likelihood-Free Inference, $Lambda$ Cold Dark Matter simulations of $sim 2M$ galaxy pairs, and data from Gaia and the Hubble Space Telescope to infer the sum of the masses of the Milky Way and Andromeda (M31) galaxies, the two main components of the Local Group. This method overcomes most of the approximations of the traditional timing argument, makes the writing of a theoretical likelihood unnecessary, and allows the non-linear modelling of observational errors that take into account correlations in the data and non-Gaussian distributions. We obtain an $M_{200}$ mass estimate $M_{rm MW+M31} = 4.6^{+2.3}_{-1.8} times 10^{12} M_{odot}$ ($68 %$ C.L.), in agreement with previous estimates both for the sum of the two masses and for the individual masses. This result is not only one of the most reliable estimates of the sum of the two masses to date, but is also an illustration of likelihood-free inference in a problem with only one parameter and only three data points.
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Dwarf galaxies are known to have remarkably low star formation efficiency due to strong feedback. Adopting the dwarf galaxies of the Milky Way as a laboratory, we explore a flexible semi-analytic galaxy formation model to understand how the feedback processes shape the satellite galaxies of the Milky Way. Using Markov-Chain Monte-Carlo, we exhaustively search a large parameter space of the model and rigorously show that the general wisdom of strong outflows as the primary feedback mechanism cannot simultaneously explain the stellar mass function and the mass--metallicity relation of the Milky Way satellites. An extended model that assumes that a fraction of baryons is prevented from collapsing into low-mass halos in the first place can be accurately constrained to simultaneously reproduce those observations. The inference suggests that two different physical mechanisms are needed to explain the two different data sets. In particular, moderate outflows with weak halo mass dependence are needed to explain the mass--metallicity relation, and prevention of baryons falling into shallow gravitational potentials of low-mass halos (e.g. pre-heating) is needed to explain the low stellar mass fraction for a given subhalo mass.
We present the first comparison between the lifetime star formation histories (SFHs) of M31 and Milky Way (MW) satellites. Using the Advanced Camera for Surveys aboard the Hubble Space Telescope, we obtained deep optical imaging of Andromeda II (M$_{V} = -$12.0; log(M$_{star}$/M$_{odot}$) $sim$ 6.7) and Andromeda XVI (M$_{V} = -$7.5; log(M$_{star}$/M$_{odot}$) $sim$ 4.9) yielding color-magnitude diagrams that extend at least 1 magnitude below the oldest main sequence turnoff, and are similar in quality to those available for the MW companions. And II and And XVI show strikingly similar SFHs: both formed 50-70% of their total stellar mass between 12.5 and 5 Gyr ago (z$sim$5-0.5) and both were abruptly quenched $sim$ 5 Gyr ago (z$sim$0.5). The predominance of intermediate age populations in And XVI makes it qualitatively different from faint companions of the MW and clearly not a pre-reionization fossil. Neither And II nor And XVI appears to have a clear analog among MW companions, and the degree of similarity in the SFHs of And II and And XVI is not seen among comparably faint-luminous pairs of MW satellites. These findings provide hints that satellite galaxy evolution may vary substantially among hosts of similar stellar mass. Although comparably deep observations of more M31 satellites are needed to further explore this hypothesis, our results underline the need for caution when interpreting satellite galaxies of an individual system in a broader cosmological context.
We present a suite of high-resolution cosmological zoom-in simulations to $z=4$ of a $10^{12},{rm M}_{odot}$ halo at $z=0$, obtained using seven contemporary astrophysical simulation codes widely used in the numerical galaxy formation community. Physics prescriptions for gas cooling, heating, and star formation, are similar to the ones used in our previous {it AGORA} disk comparison but now account for the effects of cosmological processes. In this work, we introduce the most careful comparison yet of galaxy formation simulations run by different code groups, together with a series of four calibration steps each of which is designed to reduce the number of tunable simulation parameters adopted in the final run. After all the participating code groups successfully completed the calibration steps, we reach a suite of cosmological simulations with similar mass assembly histories down to $z=4$. With numerical accuracy that resolves the internal structure of a target halo, we find that the codes overall agree well with one another in e.g., gas and stellar properties, but also show differences in e.g., circumgalactic medium properties. We argue that, if adequately tested in accordance with our proposed calibration steps and common parameters, the results of high-resolution cosmological zoom-in simulations can be robust and reproducible. New code groups are invited to join this comparison by generating equivalent models by adopting the common initial conditions, the common easy-to-implement physics package, and the proposed calibration steps. Further analyses of the simulations presented here will be in forthcoming reports from our Collaboration.
Studying our Galaxy, the Milky Way (MW), gives us a close-up view of the interplay between cosmology, dark matter, and galaxy formation. In the next decade our understanding of the MWs dynamics, stellar populations, and structure will undergo a revolution thanks to planned and proposed astrometric, spectroscopic and photometric surveys, building on recent advances by the Gaia astrometric survey. Together, these new efforts will measure three-dimensional positions and velocities and numerous chemical abundances for stars to the MWs edge and well into the Local Group, leading to a complete multidimensional view of our Galaxy. Studies of the multidimensional Milky Way beyond the Gaia frontier---from the edge of the Galactic disk to the edge of our Galaxys dark matter halo---will unlock new scientific advances across astrophysics, from constraints on dark matter to insights into galaxy formation.
Obtaining accurately calibrated redshift distributions of photometric samples is one of the great challenges in photometric surveys like LSST, Euclid, HSC, KiDS, and DES. We combine the redshift information from the galaxy photometry with constraints from two-point functions, utilizing cross-correlations with spatially overlapping spectroscopic samples. Our likelihood framework is designed to integrate directly into a typical large-scale structure and weak lensing analysis based on two-point functions. We discuss efficient and accurate inference techniques that allow us to scale the method to the large samples of galaxies to be expected in LSST. We consider statistical challenges like the parametrization of redshift systematics, discuss and evaluate techniques to regularize the sample redshift distributions, and investigate techniques that can help to detect and calibrate sources of systematic error using posterior predictive checks. We evaluate and forecast photometric redshift performance using data from the CosmoDC2 simulations, within which we mimic a DESI-like spectroscopic calibration sample for cross-correlations. Using a combination of spatial cross-correlations and photometry, we show that we can provide calibration of the mean of the sample redshift distribution to an accuracy of at least $0.002(1+z)$, consistent with the LSST-Y1 science requirements for weak lensing and large-scale structure probes.
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