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Register a new userObserved versus modelled u,g,r,i,z-band photometry of local galaxies - Evaluation of model performance
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We test how well available stellar population models can reproduce observed u,g,r,i,z-band photometry of the local galaxy population (0.02<=z<=0.03) as probed by the SDSS. Our study is conducted from the perspective of a user of the models, who has observational data in hand and seeks to convert them into physical quantities. Stellar population models for galaxies are created by synthesizing star formations histories and chemical enrichments using single stellar populations from several groups (Starburst99, GALAXEV, Maraston2005, GALEV). The role of dust is addressed through a simplistic, but observationally motivated, dust model that couples the amplitude of the extinction to the star formation history, metallicity and the viewing angle. Moreover, the influence of emission lines is considered (for the subset of models for which this component is included). The performance of the models is investigated by: 1) comparing their prediction with the observed galaxy population in the SDSS using the (u-g)-(r-i) and (g-r)-(i-z) color planes, 2) comparing predicted stellar mass and luminosity weighted ages and metallicities, specific star formation rates, mass to light ratios and total extinctions with literature values from studies based on spectroscopy. Strong differences between the various models are seen, with several models occupying regions in the color-color diagrams where no galaxies are observed. We would therefore like to emphasize the importance of the choice of model. Using our preferred model we find that the star formation history, metallicity and also dust content can be constrained over a large part of the parameter space through the use of u,g,r,i,z-band photometry. However, strong local degeneracies are present due to overlap of models with high and low extinction in certain parts of color space.
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We introduce a new method to determine galaxy cluster membership based solely on photometric properties. We adopt a machine learning approach to recover a cluster membership probability from galaxy photometric parameters and finally derive a membership classification. After testing several machine learning techniques (such as Stochastic Gradient Boosting, Model Averaged Neural Network and k-Nearest Neighbors), we found the Support Vector Machine (SVM) algorithm to perform better when applied to our data. Our training and validation data are from the Sloan Digital Sky Survey (SDSS) main sample. Hence, to be complete to $M_r^* + 3$ we limit our work to 30 clusters with $z_{text{phot-cl}} le 0.045$. Masses ($M_{200}$) are larger than $sim 0.6times10^{14} M_{odot}$ (most above $3times10^{14} M_{odot}$). Our results are derived taking in account all galaxies in the line of sight of each cluster, with no photometric redshift cuts or background corrections. Our method is non-parametric, making no assumptions on the number density or luminosity profiles of galaxies in clusters. Our approach delivers extremely accurate results (completeness, C $sim 92%$ and purity, P $sim 87%$) within R$_{200}$, so that we named our code {bf RPM}. We discuss possible dependencies on magnitude, colour and cluster mass. Finally, we present some applications of our method, stressing its impact to galaxy evolution and cosmological studies based on future large scale surveys, such as eROSITA, EUCLID and LSST.
Our aim in this work is to answer, using simulated narrow-band photometry data, the following general question: What can we learn about galaxies from these new generation cosmological surveys? For instance, can we estimate stellar age and metallicity distributions? Can we separate star-forming galaxies from AGN? Can we measure emission lines, nebular abundances and extinction? With what precision? To accomplish this, we selected a sample of about 300k galaxies with good S/N from the SDSS and divided them in two groups: 200k objects and a template library of 100k. We corrected the spectra to $z = 0$ and converted them to filter fluxes. Using a statistical approach, we calculated a Probability Distribution Function (PDF) for each property of each object and the library. Since we have the properties of all the data from the {sc starlight}-SDSS database, we could compare them with the results obtained from summaries of the PDF (mean, median, etc). Our results shows that we retrieve the weighted average of the log of the galaxy age with a good error margin ($sigma approx 0.1 - 0.2$ dex), and similarly for the physical properties such as mass-to-light ratio, mean stellar metallicity, etc. Furthermore, our main result is that we can derive emission line intensities and ratios with similar precision. This makes this method unique in comparison to the other methods on the market to analyze photometry data and shows that, from the point of view of galaxy studies, future photometric surveys will be much more useful than anticipated.
SPECULOOS-South, an observatory composed of four independent 1m robotic telescopes, located at ESO Paranal, Chile, started scientific operation in January 2019. This Southern Hemisphere facility operates as part of SPECULOOS, an international network of 1m-class telescopes surveying for transiting terrestrial planets around the nearest and brightest ultra-cool dwarfs. To automatically and efficiently process the observations of SPECULOOS-South, and to deal with the specialised photometric requirements of ultra-cool dwarf targets, we present our automatic pipeline. This pipeline includes an algorithm for automated differential photometry and an extensive correction technique for the effects of telluric water vapour, using ground measurements of the precipitable water vapour. Observing very red targets in the near-infrared can result in photometric systematics in the differential lightcurves, related to the temporally-varying, wavelength-dependent opacity of the Earths atmosphere. These systematics are sufficient to affect the daily quality of the lightcurves, the longer time-scale variability study of our targets and even mimic transit-like signals. Here we present the implementation and impact of our water vapour correction method. Using the 179 nights and 98 targets observed in the I+z filter by SPECULOOS-South since January 2019, we show the impressive photometric performance of the facility (with a median precision of ~1.5 mmag for 30-min binning of the raw, non-detrended lightcurves) and assess its detection potential. We compare simultaneous observations with SPECULOOS-South and TESS, to show that we readily achieve high-precision, space-level photometry for bright, ultra-cool dwarfs, highlighting SPECULOOS-South as the first facility of its kind.
We report first science results from our new spectrometer, the 2nd generation z(Redshift) and Early Universe Spectrometer (ZEUS-2), recently commissioned on the Atacama Pathfinder Experiment telescope (APEX). ZEUS-2 is a submillimeter grating spectrometer optimized for detecting the faint and broad lines from distant galaxies that are redshifted into the telluric windows from 200 to 850 microns. It utilizes a focal plane array of transition-edge sensed bolometers, the first use of these arrays for astrophysical spectroscopy. ZEUS-2 promises to be an important tool for studying galaxies in the years to come due to its synergy with ALMA and its capabilities in the short submillimeter windows that are unique in the post Herschel era. Here we report on our first detection of the [CII] 158 $mu m$ line with ZEUS-2. We detect the line at z ~ 1.8 from H-ATLAS J091043.1-000322 with a line flux of $(6.44 pm 0.42) times 10^{-18} W m^{-2}$. Combined with its far-infrared luminosity and a new Herschel-PACS detection of the [OI] 63 $mu m $ line we model the line emission as coming from a photo-dissociation region with far-ultraviolet radiation field, $G approx 2 times 10^{4} G_{0}$, gas density, $n approx 1 times 10^{3} cm^{-3}$ and size between ~ 0.4 and 1 kpc. Based on this model, we conclude that H-ATLAS J091043.1-000322 is a high redshift analogue of a local ultra-luminous infrared galaxy, i.e. it is likely the site of a compact starburst due to a major merger. Further identification of these merging systems is important for constraining galaxy formation and evolution models.
We present ultraviolet through far-infrared surface brightness profiles for the 75 galaxies in the Spitzer Infrared Nearby Galaxies Survey (SINGS). The imagery used to measure the profiles includes GALEX UV data, optical images from KPNO, CTIO and SDSS, near-IR data from 2MASS, and mid- and far-infrared images from Spitzer. Along with the radial profiles, we also provide multi-wavelength asymptotic magnitudes and several non-parametric indicators of galaxy morphology: the concentration index (C_42), the asymmetry (A), the Gini coefficient (G) and the normalized second-order moment of the brightest 20% of the galaxys flux (M_20). Our radial profiles show a wide range of morphologies and multiple components (bulges, exponential disks, inner and outer disk truncations, etc.) that vary not only from galaxy to galaxy but also with wavelength for a given object. In the optical and near-IR, the SINGS galaxies occupy the same regions in the C_42-A-G-M_20 parameter space as other normal galaxies in previous studies. However, they appear much less centrally concentrated, more asymmetric and with larger values of G when viewed in the UV (due to star-forming clumps scattered across the disk) and in the mid-IR (due to the emission of Polycyclic Aromatic Hydrocarbons at 8.0 microns and very hot dust at 24 microns).
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