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Register a new userGalaxy Zoo: an unusual new class of galaxy cluster
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We have identified a new class of galaxy cluster using data from the Galaxy Zoo project. These clusters are rare, and thus have apparently gone unnoticed before, despite their unusual properties. They appear especially anomalous when the morphological properties of their component galaxies are considered. Their identification therefore depends upon the visual inspection of large numbers of galaxies, a feat which has only recently been made possible by Galaxy Zoo, together with the Sloan Digital Sky Survey. We present the basic properties of our cluster sample, and discuss possible formation scenarios and implications for cosmology.
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We investigate the effect of dust on spiral galaxies by measuring the inclination-dependence of optical colours for 24,276 well-resolved SDSS galaxies visually classified in Galaxy Zoo. We find clear trends of reddening with inclination which imply a total extinction from face-on to edge-on of 0.7, 0.6, 0.5 and 0.4 magnitudes for the ugri passbands. We split the sample into bulgy (early-type) and disky (late-type) spirals using the SDSS fracdeV (or f_DeV) parameter and show that the average face-on colour of bulgy spirals is redder than the average edge-on colour of disky spirals. This shows that the observed optical colour of a spiral galaxy is determined almost equally by the spiral type (via the bulge-disk ratio and stellar populations), and reddening due to dust. We find that both luminosity and spiral type affect the total amount of extinction, with disky spirals at M_r ~ -21.5 mags having the most reddening. This decrease of reddening for the most luminous spirals has not been observed before and may be related to their lower levels of recent star formation. We compare our results with the latest dust attenuation models of Tuffs et al. We find that the model reproduces the observed trends reasonably well but overpredicts the amount of u-band attenuation in edge-on galaxies. We end by discussing the effects of dust on large galaxy surveys and emphasize that these effects will become important as we push to higher precision measurements of galaxy properties and their clustering.
We study the spectroscopic properties and environments of red spiral galaxies found by the Galaxy Zoo project. By carefully selecting face-on, disk dominated spirals we construct a sample of truly passive disks (not dust reddened, nor dominated by old stellar populations in a bulge). As such, our red spirals represent an interesting set of possible transition objects between normal blue spirals and red early types. We use SDSS data to investigate the physical processes which could have turned these objects red without disturbing their morphology. Red spirals prefer intermediate density regimes, however there are no obvious correlations between red spiral properties and environment - environment alone is not sufficient to determine if a spiral will become red. Red spirals are a small fraction of spirals at low masses, but are a significant fraction at large stellar masses - massive galaxies are red independent of morphology. We confirm that red spirals have older stellar popns and less recent star formation than the main spiral population. While the presence of spiral arms suggests that major star formation cannot have ceased long ago, we show that these are not recent post-starbursts, so star formation must have ceased gradually. Intriguingly, red spirals are ~4 times more likely than normal spirals to host optically identified Seyfert or LINER, with most of the difference coming from LINERs. We find a curiously large bar fraction in the red spirals suggesting that the cessation of star formation and bar instabilities are strongly correlated. We conclude by discussing the possible origins. We suggest they may represent the very oldest spiral galaxies which have already used up their reserves of gas - probably aided by strangulation, and perhaps bar instabilities moving material around in the disk.
We investigate a class of rapidly growing emission line galaxies, known as Green Peas, first noted by volunteers in the Galaxy Zoo project because of their peculiar bright green colour and small size, unresolved in SDSS imaging. Their appearance is due to very strong optical emission lines, namely [O III] 5007 A, with an unusually large equivalent width of up to ~1000 A. We discuss a well-defined sample of 251 colour-selected objects, most of which are strongly star forming, although there are some AGN interlopers including 8 newly discovered narrow Line Seyfert 1 galaxies. The star-forming Peas are low mass galaxies (M~10^8.5 - 10^10 M_sun) with high star formation rates (~10 M_sun/yr), low metallicities (log[O/H] + 12 ~ 8.7) and low reddening (E(B-V) < 0.25) and they reside in low density environments. They have some of the highest specific star formation rates (up to ~10^{-8} yr^{-1}) seen in the local Universe, yielding doubling times for their stellar mass of hundreds of Myrs. The few star-forming Peas with HST imaging appear to have several clumps of bright star-forming regions and low surface density features that may indicate recent or ongoing mergers. The Peas are similar in size, mass, luminosity and metallicity to Luminous Blue Compact Galaxies. They are also similar to high redshift UV-luminous galaxies, e.g., Lyman-break galaxies and Lyman-alpha emitters, and therefore provide a local laboratory with which to study the extreme star formation processes that occur in high-redshift galaxies. Studying starbursting galaxies as a function of redshift is essential to understanding the build up of stellar mass in the Universe.
Analysis of galaxies with overlapping images offers a direct way to probe the distribution of dust extinction and its effects on the background light. We present a catalog of 1990 such galaxy pairs selected from the Sloan Digital Sky Survey (SDSS) by volunteers of the Galaxy Zoo project. We highlight subsamples which are particularly useful for retrieving such properties of the dust distribution as UV extinction, the extent perpendicular to the disk plane, and extinction in the inner parts of disks. The sample spans wide ranges of morphology and surface brightness, opening up the possibility of using this technique to address systematic changes in dust extinction or distribution with galaxy type. This sample will form the basis for forthcoming work on the ranges of dust distributions in local disk galaxies, both for their astrophysical implications and as the low-redshift part of a study of the evolution of dust properties. Separate lists and figures show deep overlaps, where the inner regions of the foreground galaxy are backlit, and the relatively small number of previously-known overlapping pairs outside the SDSS DR7 sky coverage.
This paper presents the first results from a new citizen science project: Galaxy Zoo Supernovae. This proof of concept project uses members of the public to identify supernova candidates from the latest generation of wide-field imaging transient surveys. We describe the Galaxy Zoo Supernovae operations and scoring model, and demonstrate the effectiveness of this novel method using imaging data and transients from the Palomar Transient Factory (PTF). We examine the results collected over the period April-July 2010, during which nearly 14,000 supernova candidates from PTF were classified by more than 2,500 individuals within a few hours of data collection. We compare the transients selected by the citizen scientists to those identified by experienced PTF scanners, and find the agreement to be remarkable - Galaxy Zoo Supernovae performs comparably to the PTF scanners, and identified as transients 93% of the ~130 spectroscopically confirmed SNe that PTF located during the trial period (with no false positive identifications). Further analysis shows that only a small fraction of the lowest signal-to-noise SN detections (r > 19.5) are given low scores: Galaxy Zoo Supernovae correctly identifies all SNe with > 8{sigma} detections in the PTF imaging data. The Galaxy Zoo Supernovae project has direct applicability to future transient searches such as the Large Synoptic Survey Telescope, by both rapidly identifying candidate transient events, and via the training and improvement of existing machine classifier algorithms.
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