REPRODUCING THE STELLAR MASS/HALO MASS RELATION IN SIMULATED ΛCDM GALAXIES: THEORY VERSUS OBSERVATIONAL ESTIMATES

We examine the present-day total stellar-to-halo mass (SHM) ratio as a function of halo mass for a new sample of simulated field galaxies using fully cosmological, Lambda CDM, high-resolution SPH + N-body simulations. These simulations include an explicit treatment of metal line cooling, dust and self-shielding, H-2-based star formation (SF), and supernova-driven gas outflows. The 18 simulated halos have masses ranging from a few times 10(8) to nearly 10(12) M-circle dot.At z = 0, our simulated galaxies have a baryon content and morphology typical of field galaxies. Over a stellar mass range of 2.2 x 10(3)-4.5 x 10(10) M-circle dot we find extremely good agreement between the SHM ratio in simulations and the present-day predictions from the statistical abundance matching technique presented in Moster et al. This improvement over past simulations is due to a number systematic factors, each decreasing the SHM ratios: (1) gas outflows that reduce the overall SF efficiency but allow for the formation of a cold gas component; (2) estimating the stellar masses of simulated galaxies using artificial observations and photometric techniques similar to those used in observations; and (3) accounting for a systematic, up to 30% overestimate in total halo masses in DM-only simulations, due to the neglect of baryon loss over cosmic times. Our analysis suggests that stellar mass estimates based on photometric magnitudes can underestimate the contribution of old stellar populations to the total stellar mass, leading to stellar mass errors of up to 50% for individual galaxies. These results highlight that implementing a realistic high density threshold for SF considerably reduces the overall SF efficiency due to more effective feedback. However, we show that in order to reduce the perceived tension between the SF efficiency in galaxy formation models and in real galaxies, it is very important to use proper techniques to compare simulations with observations.