The Relation Between Quasar and Merging Galaxy Luminosity Functions and the Merger-Induced Star Formation Rate of the Universe

Using a model for self-regulated growth of black holes (BHs) in mergers involving gas-rich galaxies, we study the relationship between quasars and the population of merging galaxies and predict the merger-induced star formation rate density of the Universe. Mergers drive nuclear gas inflows, fueling starbursts and 'buried quasars' until accretion feedback expels the gas, rendering a briefly visible optical quasar. Star formation is shut down and accretion declines, leaving a passively evolving remnant with properties typical of red, elliptical galaxies. Based on evolution of these events in our simulations, we demonstrate that the observed statistics of merger rates, luminosity functions (LFs) and mass functions, SFR distributions, specific SFRs, quasar and quasar host galaxy LFs, and elliptical/red galaxy LFs are self-consistent and follow from one another as predicted by the merger hypothesis. We use our simulations to de-convolve both quasar and merging galaxy LFs to determine the birthrate of black holes of a given final mass and merger rates as a function of stellar mass. We use this to predict the merging galaxy LF in several observed wavebands, color-magnitude relations, mass functions, absolute and specific SFR distributions and SFR density, and quasar host galaxy LFs, as a function of redshift from z=0-6. We invert this and predict e.g. quasar LFs from observed merger LFs or SFR distributions. Our results agree well with observations, but idealized models of quasar lightcurves are ruled out by comparison of merger and quasar observations at >99.9% confidence. Using only observations of quasars, we estimate the contribution of mergers to the SFR density of the Universe even to high redshifts z~4.Comment: 26 pages, 15 figures, matches version accepted to Ap

AN ULTRA-FAINT GALAXY CANDIDATE DISCOVERED in EARLY DATA from the MAGELLANIC SATELLITES SURVEY

We report a new ultra-faint stellar system found in Dark Energy Camera data from the first observing run of the Magellanic Satellites Survey (MagLiteS). MagLiteS J0644-5953 (Pictor II or Pic II) is a low surface brightness (μ = 28.5+1 -1 mag arcsec-2 within its half-light radius) resolved overdensity of old and metal-poor stars located at a heliocentric distance of 45+5 -4 kpc. The physical size (r1/2 = 46+15 -11) and low luminosity (Mv = -3.2+0.4 -0.5 mag) of this satellite are consistent with the locus of spectroscopically confirmed ultra-faint galaxies. MagLiteS J0644-5953 (Pic II) is located 11.3+3.1 -0.9 kpc from the Large Magellanic Cloud (LMC), and comparisons with simulation results in the literature suggest that this satellite was likely accreted with the LMC. The close proximity of MagLiteS J0644-5953 (Pic II) to the LMC also makes it the most likely ultra-faint galaxy candidate to still be gravitationally bound to the LMC.Peer reviewe

The cosmic web for density perturbations of various scales

We follow the evolution of galaxy systems in numerical simulation. Our goal is to understand the role of density perturbations of various scales in the formation and evolution of the cosmic web. We perform numerical simulations with the full power spectrum of perturbations, and with spectrum cut at long wavelengths. Additionally, we have one model, where we cut the intermediate waves. We analyze the density field and study the void sizes and density field clusters in different models. Our analysis shows that the fine structure (groups and clusters of galaxies) is created by small-scale density perturbations of scale $\leq 8$ \Mpc. Filaments of galaxies and clusters are created by perturbations of intermediate scale from $\sim 8$ to $\sim 32$ \Mpc, superclusters of galaxies by larger perturbations. We conclude that the scale of the pattern of the cosmic web is determined by density perturbations of scale up to $\sim 100$ \Mpc. Larger perturbations do not change the pattern of the web, but modulate the richness of galaxy systems, and make voids emptier. The stop of the increase of the scale of the pattern of the cosmic web with increasing scale of density perturbations can probably be explained as the freezing of the web at redshift $z\simeq 0.7$.Comment: 12 pages, 7 figures, accepted for publication in Astronomy and Astrophysic

Star/galaxy separation at faint magnitudes: application to a simulated Dark Energy Survey

We address the problem of separating stars from galaxies in future large photometric surveys. We focus our analysis on simulations of the Dark Energy Survey (DES). In the first part of the paper, we derive the science requirements on star/galaxy separation, for measurement of the cosmological parameters with the gravitational weak lensing and large-scale structure probes. These requirements are dictated by the need to control both the statistical and systematic errors on the cosmological parameters, and by point spread function calibration. We formulate the requirements in terms of the completeness and purity provided by a given star/galaxy classifier. In order to achieve these requirements at faint magnitudes, we propose a new method for star/galaxy separation in the second part of the paper. We first use principal component analysis to outline the correlations between the objects parameters and extract from it the most relevant information. We then use the reduced set of parameters as input to an Artificial Neural Network. This multiparameter approach improves upon purely morphometric classifiers (such as the classifier implemented in SExtractor), especially at faint magnitudes: it increases the purity by up to 20 per cent for stars and by up to 12 per cent for galaxies, at i-magnitude fainter than 2

Unbound Particles in Dark Matter Halos

We investigate unbound dark matter particles in halos by tracing particle trajectories in a simulation run to the far future (a = 100). We find that the traditional sum of kinetic and potential energies is a very poor predictor of which dark matter particles will eventually become unbound from halos. We also study the mass fraction of unbound particles, which increases strongly towards the edges of halos, and decreases significantly at higher redshifts. We discuss implications for dark matter detection experiments, precision calibrations of the halo mass function, the use of baryon fractions to constrain dark energy, and searches for intergalactic supernovae.Comment: Significant improvements following referee suggestion

Photoactivate release of silver nanoparticles in cell membranemodels for bacterial control.

International audienceWe present a forward-modeling simulation framework designed to model the data products from the Dark Energy Survey (DES). This forward-model process can be thought of as a transfer function—a mapping from cosmological/astronomical signals to the final data products used by the scientists. Using output from the cosmological simulations (the Blind Cosmology Challenge), we generate simulated images (the Ultra Fast Image Simulator) and catalogs representative of the DES data. In this work we demonstrate the framework by simulating the 244 deg2 coadd images and catalogs in five bands for the DES Science Verification data. The simulation output is compared with the corresponding data to show that major characteristics of the images and catalogs can be captured. We also point out several directions of future improvements. Two practical examples—star-galaxy classification and proximity effects on object detection—are then used to illustrate how one can use the simulations to address systematics issues in data analysis. With clear understanding of the simplifications in our model, we show that one can use the simulations side-by-side with data products to interpret the measurements. This forward modeling approach is generally applicable for other upcoming and future surveys. It provides a powerful tool for systematics studies that is sufficiently realistic and highly controllable

Simulated Milky Way analogues: implications for dark matter direct searches

We study the implications of galaxy formation on dark matter direct detection using high resolution hydrodynamic simulations of Milky Way-like galaxies simulated within the eagle and apostle projects. We identify MilkyWay analogues that satisfy observational constraints on the Milky Way rotation curve and total stellar mass. We then extract the dark matter density and velocity distribution in the Solar neighbourhood for this set of Milky Way analogues, and use them to analyse the results of current direct detection experiments. For most Milky Way analogues, the event rates in direct detection experiments obtained from the best _t Maxwellian distribution (with peak speed of 223 { 289 km=s) are similar to those obtained directly from the simulations. As a consequence, the allowed regions and exclusion limits set by direct detection experiments in the dark matter mass and spin-independent cross section plane shift by a few GeV compared to the Standard Halo Model, at low dark matter masses. For each dark matter mass, the halo-to-halo variation of the local dark matter density results in an overall shift of the allowed regions and exclusion limits for the cross section. However, the compatibility of the possible hints for a dark matter signal from DAMA and CDMS-Si and null results from LUX and SuperCDMS is not improved

Mapping and simulating systematics due to spatially varying observing conditions in DES science verification data

Spatially varying depth and the characteristics of observing conditions, such as seeing, airmass, or sky background, are major sources of systematic uncertainties in modern galaxy survey analyses, particularly in deep multi-epoch surveys. We present a framework to extract and project these sources of systematics onto the sky, and apply it to the Dark Energy Survey (DES) to map the observing conditions of the Science Verification (SV) data. The resulting distributions and maps of sources of systematics are used in several analyses of DES–SV to perform detailed null tests with the data, and also to incorporate systematics in survey simulations. We illustrate the complementary nature of these two approaches by comparing the SV data with BCC-UFig, a synthetic sky catalog generated by forward-modeling of the DES–SV images. We analyze the BCC-UFig simulation to construct galaxy samples mimicking those used in SV galaxy clustering studies. We show that the spatially varying survey depth imprinted in the observed galaxy densities and the redshift distributions of the SV data are successfully reproduced by the simulation and are well-captured by the maps of observing conditions. The combined use of the maps, the SV data, and the BCC-UFig simulation allows us to quantify the impact of spatial systematics on N(z), the redshift distributions inferred using photometric redshifts. We conclude that spatial systematics in the SV data are mainly due to seeing fluctuations and are under control in current clustering and weak-lensing analyses. However, they will need to be carefully characterized in upcoming phases of DES in order to avoid biasing the inferred cosmological results. The framework presented here is relevant to all multi-epoch surveys and will be essential for exploiting future surveys such as the Large Synoptic Survey Telescope, which will require detailed null tests and realistic end-to-end image simulations to correctly interpret the deep, high-cadence observations of the sky

Mapping and simulating systematics due to spatially-varying observing conditions in DES Science Verification data

Spatially-varying depth and characteristics of observing conditions, such as seeing, airmass, or sky background, are major sources of systematic uncertainties in modern galaxy survey analyses, in particular in deep multi-epoch surveys. We present a framework to extract and project these sources of systematics onto the sky, and apply it to the Dark Energy Survey (DES) to map the observing conditions of the Science Verification (SV) data. The resulting distributions and maps of sources of systematics are used in several analyses of DES SV to perform detailed null tests with the data, and also to incorporate systematics in survey simulations. We illustrate the complementarity of these two approaches by comparing the SV data with the BCC-UFig, a synthetic sky catalogue generated by forward-modelling of the DES SV images. We analyse the BCC-UFig simulation to construct galaxy samples mimicking those used in SV galaxy clustering studies. We show that the spatially-varying survey depth imprinted in the observed galaxy densities and the redshift distributions of the SV data are successfully reproduced by the simulation and well-captured by the maps of observing conditions. The combined use of the maps, the SV data and the BCC-UFig simulation allows us to quantify the impact of spatial systematics on $N(z)$, the redshift distributions inferred using photometric redshifts. We conclude that spatial systematics in the SV data are mainly due to seeing fluctuations and are under control in current clustering and weak lensing analyses. The framework presented here is relevant to all multi-epoch surveys, and will be essential for exploiting future surveys such as the Large Synoptic Survey Telescope (LSST), which will require detailed null-tests and realistic end-to-end image simulations to correctly interpret the deep, high-cadence observations of the sky