arXiv subjects

Cristian A. Vega-Martínez

Publications and source records attributed to Cristian A. Vega-Martínez.

21 records · Page 2Linked to original sources

arXiv2017

MultiDark-Galaxies: data release and first results

We present the public release of the MultiDark-Galaxies: three distinct galaxy catalogues derived from one of the Planck cosmology MultiDark simulations (i.e. MDPL2, with a volume of (1 Gpc/$h$)$^{3}$ and mass resolution of $1.5 \times 10^{9} M_{\odot}/h$) by applying the semi-analytic models GALACTICUS, SAG, and SAGE to it. We compare the three models and their conformity with observational data for a selection of fundamental properties of galaxies like stellar mass function, star formation rate, cold gas fractions, and metallicities - noting that they sometimes perform differently reflecting model designs and calibrations. We have further selected galaxy subsamples of the catalogues by number densities in stellar mass, cold gas mass, and star formation rate in order to study the clustering statistics of galaxies. We show that despite different treatment of orphan galaxies, i.e. galaxies that lost their dark-matter host halo due to the finite mass resolution of the N-body simulation or tidal stripping, the clustering signal is comparable, and reproduces the observations in all three models - in particular when selecting samples based upon stellar mass. Our catalogues provide a powerful tool to study galaxy formation within a volume comparable to those probed by on-going and future photometric and redshift surveys. All model data consisting of a range of galaxy properties - including broad-band SDSS magnitudes - are publicly available.

astro-ph.GA↗

arXiv2017

nIFTy Cosmology: the clustering consistency of galaxy formation models

We present a clustering comparison of 12 galaxy formation models (including Semi-Analytic Models (SAMs) and Halo Occupation Distribution (HOD) models) all run on halo catalogues and merger trees extracted from a single ΛCDM N-body simulation. We compare the results of the measurements of the mean halo occupation numbers, the radial distribution of galaxies in haloes and the 2-Point Correlation Functions (2PCF). We also study the implications of the different treatments of orphan (galaxies not assigned to any dark matter subhalo) and non-orphan galaxies in these measurements. Our main result is that the galaxy formation models generally agree in their clustering predictions but they disagree significantly between HOD and SAMs for the orphan satellites. Although there is a very good agreement between the models on the 2PCF of central galaxies, the scatter between the models when orphan satellites are included can be larger than a factor of 2 for scales smaller than 1 Mpc/h. We also show that galaxy formation models that do not include orphan satellite galaxies have a significantly lower 2PCF on small scales, consistent with previous studies. Finally, we show that the 2PCF of orphan satellites is remarkably different between SAMs and HOD models. Orphan satellites in SAMs present a higher clustering than in HOD models because they tend to occupy more massive haloes. We conclude that orphan satellites have an important role on galaxy clustering and they are the main cause of the differences in the clustering between HOD models and SAMs.

astro-ph.GA↗

arXiv2015

Calibration of semi-analytic models of galaxy formation using Particle Swarm Optimization

We present a fast and accurate method to select an optimal set of parameters in semi-analytic models of galaxy formation and evolution (SAMs). Our approach compares the results of a model against a set of observables applying a stochastic technique called Particle Swarm Optimization (PSO), a self-learning algorithm for localizing regions of maximum likelihood in multidimensional spaces that outperforms traditional sampling methods in terms of computational cost. We apply the PSO technique to the SAG semi-analytic model combined with merger trees extracted from a standard $Λ$CDM N-body simulation. The calibration is performed using a combination of observed galaxy properties as constraints, including the local stellar mass function and the black hole to bulge mass relation. We test the ability of the PSO algorithm to find the best set of free parameters of the model by comparing the results with those obtained using a MCMC exploration. Both methods find the same maximum likelihood region, however the PSO method requires one order of magnitude less evaluations. This new approach allows a fast estimation of the best-fitting parameter set in multidimensional spaces, providing a practical tool to test the consequences of including other astrophysical processes in SAMs.

astro-ph.CO↗