Galaxy morphology in the rich cluster Abell 2390

We have analysed images of the field of A2390 obtained with the CFHT and HST. The analysis fits models to bulge and disk components to several hundred galaxies, with about equal samples from the cluster and field. We also have assessed and graded asymmetries in the images. The cluster galaxies are compared in different cluster locations and also compared with field galaxies. We find that the central old population galaxies are bulge-dominated, while disk systems have young populations and are found predominantly in the outer cluster. S0 and bulgy disk galaxies are found throughout, but concentrate in regions of substructure. Disks of cluster blue galaxies are generally brighter and smaller than those in the field. We find that the cluster members have a higher proportion of interacting galaxies than the field sample. Interactions in the cluster and in the field, as well as cluster infall, appear to inhibit star-formation in galaxies.Comment: 20 pages including 10 of tables, plus 7 figures; To appear in the Astronomical Jorurna

De-noising of galaxy optical spectra with autoencoders

Optical spectra contain a wealth of information about the physical properties and formation histories of galaxies. Often though, spectra are too noisy for this information to be accurately retrieved. In this study, we explore how machine learning methods can be used to de-noise spectra and increase the amount of information we can gain without having to turn to sample averaging methods such as spectral stacking. Using machine learning methods trained on noise-added spectra - SDSS spectra with Gaussian noise added - we investigate methods of maximising the information we can gain from these spectra, in particular from emission lines, such that more detailed analysis can be performed. We produce a variational autoencoder (VAE) model, and apply it on a sample of noise-added spectra. Compared to the flux measured in the original SDSS spectra, the model values are accurate within 0.3-0.5 dex, depending on the specific spectral line and S/N. Overall, the VAE performs better than a principle component analysis (PCA) method, in terms of reconstruction loss and accuracy of the recovered line fluxes. To demonstrate the applicability and usefulness of the method in the context of large optical spectroscopy surveys, we simulate a population of spectra with noise similar to that in galaxies at z = 0.1 observed by the Dark Energy Spectroscopic Instrument (DESI). We show that we can recover the shape and scatter of the MZR in this ‘DESI-like’ sample, in a way that is not possible without the VAE-assisted de-noising

De-noising of galaxy optical spectra with autoencoders

Optical spectra contain a wealth of information about the physical properties and formation histories of galaxies. Often though, spectra are too noisy for this information to be accurately retrieved. In this study, we explore how machine learning methods can be used to de-noise spectra and increase the amount of information we can gain without having to turn to sample averaging methods such as spectral stacking. Using machine learning methods trained on noise-added spectra - SDSS spectra with Gaussian noise added - we investigate methods of maximising the information we can gain from these spectra, in particular from emission lines, such that more detailed analysis can be performed. We produce a variational autoencoder (VAE) model, and apply it on a sample of noise-added spectra. Compared to the flux measured in the original SDSS spectra, the model values are accurate within 0.3-0.5 dex, depending on the specific spectral line and S/N. Overall, the VAE performs better than a principle component analysis (PCA) method, in terms of reconstruction loss and accuracy of the recovered line fluxes. To demonstrate the applicability and usefulness of the method in the context of large optical spectroscopy surveys, we simulate a population of spectra with noise similar to that in galaxies at $z = 0.1$ observed by the Dark Energy Spectroscopic Instrument (DESI). We show that we can recover the shape and scatter of the MZR in this "DESI-like" sample, in a way that is not possible without the VAE-assisted de-noising.Comment: 14 pages, 10 figures, 6 tables, accepted for publication in MNRA

The GALEX Arecibo SDSS Survey. VI. Second Data Release and Updated Gas Fraction Scaling Relations

We present the second data release from the GALEX Arecibo SDSS Survey (GASS), an ongoing large Arecibo program to measure the HI properties for an unbiased sample of ~1000 galaxies with stellar masses greater than 10^10 Msun and redshifts 0.025<z<0.05. GASS targets are selected from the Sloan Digital Sky Survey (SDSS) spectroscopic and Galaxy Evolution Explorer (GALEX) imaging surveys, and are observed until detected or until a gas mass fraction limit of a few per cent is reached. This second data installment includes new Arecibo observations of 240 galaxies, and marks the 50% of the complete survey. We present catalogs of the HI, optical and ultraviolet parameters for these galaxies, and their HI-line profiles. Having more than doubled the size of the sample since the first data release, we also revisit the main scaling relations of the HI mass fraction with galaxy stellar mass, stellar mass surface density, concentration index, and NUV-r color, as well as the gas fraction plane introduced in our earlier work.Comment: 30 pages, 12 figures. Accepted for publication in A&A. Version with complete Appendix A available at http://www.mpa-garching.mpg.de/GASS/pubs.php . GASS released data can be found at http://www.mpa-garching.mpg.de/GASS/data.ph

Star formation in the cluster CLG0218.3-0510 at z=1.62 and its large-scale environment: the infrared perspective

The galaxy cluster CLG0218.3-0510 at z=1.62 is one of the most distant galaxy clusters known, with a rich muti-wavelength data set that confirms a mature galaxy population already in place. Using very deep, wide area (20x20 Mpc) imaging by Spitzer/MIPS at 24um, in conjunction with Herschel 5-band imaging from 100-500um, we investigate the dust-obscured, star-formation properties in the cluster and its associated large scale environment. Our galaxy sample of 693 galaxies at z=1.62 detected at 24um (10 spectroscopic and 683 photo-z) includes both cluster galaxies (i.e. within r <1 Mpc projected clustercentric radius) and field galaxies, defined as the region beyond a radius of 3 Mpc. The star-formation rates (SFRs) derived from the measured infrared luminosity range from 18 to 2500 Ms/yr, with a median of 55 Ms/yr, over the entire radial range (10 Mpc). The cluster brightest FIR galaxy, taken as the centre of the galaxy system, is vigorously forming stars at a rate of 256$\pm$70 Ms/yr, and the total cluster SFR enclosed in a circle of 1 Mpc is 1161$\pm$96 Ms/yr. We estimate a dust extinction of about 3 magnitudes by comparing the SFRs derived from [OII] luminosity with the ones computed from the 24um fluxes. We find that the in-falling region (1-3 Mpc) is special: there is a significant decrement (3.5x) of passive relative to star-forming galaxies in this region, and the total SFR of the galaxies located in this region is lower (130 Ms/yr/Mpc2) than anywhere in the cluster or field, regardless of their stellar mass. In a complementary approach we compute the local galaxy density, Sigma5, and find no trend between SFR and Sigma5. However, we measure an excess of star-forming galaxies in the cluster relative to the field by a factor 1.7, that lends support to a reversal of the SF-density relation in CLG0218.Comment: accepted for publication in MNRAS. v2: minor correction

Clinical Judgment Analysis

SUMMARY Judgment is central to the practice of medicine and occurs between making clinical observations and taking clinical decisions. Clinical judgment analysis has developed as a method of making statistically firm models of doctors' judgments. Computed models reveal the differential importance attached to items of clinical, social, or other data which are determinants of clinical decisions. These models can both reveal the causes of conflicts of judgment and may help resolve them in a way that unaided discussion cannot. Revealing experts' models to students speeds learning of diagnostic skills. Clinical judgment analysis offers a method of probing the judgments not just of students and doctors but also of patients who have shown systematic differences in their perceptions of risk and benefit. The power and relevance of clinical trials can be improved by the consistent application of judgment policies generated from both the trialists and those who will use their result

The Far-Infrared, UV and Molecular Gas Relation in Galaxies up to z=2.5

We use the infrared excess (IRX) FIR/UV luminosity ratio to study the relation between the effective UV attenuation (A_IRX) and the UV spectral slope (beta) in a sample of 450 1<z<2.5 galaxies. The FIR data is from very deep Herschel observations in the GOODS fields that allow us to detect galaxies with SFRs typical of galaxies with log(M)>9.3. Thus, we are able to study galaxies on and even below the main SFR-stellar mass relation (main sequence). We find that main sequence galaxies form a tight sequence in the IRX--beta plane, which has a flatter slope than commonly used relations. This slope favors a SMC-like UV extinction curve, though the interpretation is model dependent. The scatter in the IRX-beta plane, correlates with the position of the galaxies in the SFR-M plane. Using a smaller sample of galaxies with CO gas masses, we study the relation between the UV attenuation and the molecular gas content. We find a very tight relation between the scatter in the IRX-beta plane and the specific attenuation (S_A), a quantity that represents the attenuation contributed by the molecular gas mass per young star. S_A is sensitive to both the geometrical arrangement of stars and dust, and to the compactness of the star forming regions. We use this empirical relation to derive a method for estimating molecular gas masses using only widely available integrated rest-frame UV and FIR photometry. The method produces gas masses with an accuracy between 0.12-0.16 dex in samples of normal galaxies between z~0 and z~1.5. Major mergers and sub-millimeter galaxies follow a different S_A relation.Comment: 11 pages, 6 pages appendix, 11 figures, accepted to Ap

Detection of Outflowing and Extraplanar Gas in Disks in an Assembling Galaxy Cluster at z=0.37

We detect ionized gas characteristics indicative of winds in three disk-dominated galaxies that are members of a super-group at z=0.37 that will merge to form a Coma-mass cluster. All three galaxies are IR-luminous (L_IR > 4 x 10^{10} L_sun, SFR >8 M_sun per year) and lie outside the X-ray cores of the galaxy groups. We find that the most IR-luminous galaxy has strong blue and redshifted emission lines with velocities of ~ +/-200 km/s and a third, blueshifted (~ 900 km/s) component. This galaxy's line-widths (Hb, [OIII]5007, [NII], Ha) correspond to velocities of 100-1000 km/s. We detect extraplanar gas in two of three galaxies with SFR > 8 M_sun per year whose orientations are approximately edge-on and which have IFU spaxels off the stellar disk. IFU maps reveal that the extraplanar gas extends to r_h ~ 10 kpc; [NII] and Ha line-widths correspond to velocities of ~200-400 km/s in the disk and decrease to ~50-150 km/s above the disk. Multi-wavelength observations indicate that the emission is dominated by star formation. Including the most IR-luminous galaxy we find that 18% of supergroup members with SFR > 8 M_sun per year show ionized gas characteristics indicative of outflows. This is a lower limit as showing that gas is outflowing in the remaining, moderately inclined, galaxies requires a non-trivial decoupling of contributions to the emission lines from rotational and turbulent motion. Ionized gas mass loss in these winds is ~0.1 M_sun per year for each galaxy, although the winds are likely to entrain significantly larger amounts of mass in neutral and molecular gas.Comment: 6 pages, 3 figures (slightly degraded in quality), accepted for publication in ApJ