ترغب بنشر مسار تعليمي؟ اضغط هنا

Statistical Properties of Bright Galaxies in the SDSS Photometric System

32   0   0.0 ( 0 )
 نشر من قبل Kazuhiro Shimasaku
 تاريخ النشر 2001
  مجال البحث فيزياء
والبحث باللغة English
 تأليف K. Shimasaku




اسأل ChatGPT حول البحث

We investigate the photometric properties of 456 bright galaxies using imaging data recorded during the commissioning phase of the Sloan Digital Sky Survey (SDSS). Morphological classification is carried out by correlating results of several human classifiers. Our purpose is to examine the statistical properties of color indices, scale lengths, and concentration indices as functions of morphology for the SDSS photometric system. We find that $u-g$, $g-r$, and $r-i$ colors of SDSS galaxies match well with those expected from the synthetic calculation of spectroscopic energy distribution of template galaxies and with those transformed from $UBVR_CI_C$ color data of nearby galaxies. The agreement is somewhat poor, however, for $i-z$ color band with a discrepancy of $0.1-0.2$ mag. With the aid of the relation between surface brightness and radius obtained by Kent (1985), we estimate the averages of the effective radius of early type galaxies and the scale length of exponential disks both to be 2.6 kpc for $L^*$ galaxies. We find that the half light radius of galaxies depends slightly on the color bands, consistent with the expected distribution of star-forming regions for late type galaxies and with the known color gradient for early type galaxies. We also show that the (inverse) concentration index, defined by the ratio of the half light Petrosian radius to the 90% light Petrosian radius, correlates tightly with the morphological type; this index allows us to classify galaxies into early (E/S0) and late (spiral and irregular) types, allowing for a 15-20% contamination from the opposite class compared with eye-classified morphology.



قيم البحث

اقرأ أيضاً

We analyze photometric data in SDSS-DR7 to infer statistical properties of faint satellites associated to isolated bright galaxies (M_r<-20.5) in the redshift range 0.03<z<0.1. The mean projected radial profile shows an excess of companions in the ph otometric sample around the primaries, with approximately a power law shape that extends up to ~700kpc. Given this overdensity signal, a suitable background subtraction method is used to study the statistical properties of the population of bound satellites, down to magnitude M_r=-14.5, in the projected radial distance range 100 < r_p/kpc < 3 R_{vir}. We have also considered a color cut consistent with the observed colors of spectroscopic satellites in nearby galaxies so that distant redshifted galaxies do not dominate the statistics. We have tested the implementation of this procedure using a mock catalog. We find that the method is effective in reproducing the true projected radial satellite number density profile and luminosity distributions, providing confidence in the results derived from SDSS data. The spatial extent of satellites is larger for bright, red primaries. Also, we find a larger spatial distribution of blue satellites. For the different samples analyzed, we derive the average number of satellites and their luminosity distributions down to M_r=-14.5. The mean number of satellites depends very strongly on host luminosity. Bright primaries (M_r<-21.5) host on average ~6 satellites with M_r<-14.5, while primaries with -21.5<M_r<-20.5 have less than 1 satellite per host. We provide Schechter function fits to the luminosity distributions of satellite galaxies with faint-end slopes -1.3+/-0.2. This shows that satellites of bright primaries lack an excess population of faint objects, in agreement with the results in the Milky Way and nearby galaxies.
We apply clustering-based redshift inference to all extended sources from the Sloan Digital Sky Survey photometric catalogue, down to magnitude r = 22. We map the relationships between colours and redshift, without assumption of the sources spectral energy distributions (SED). We identify and locate star-forming, quiescent galaxies, and AGN, as well as colour changes due to spectral features, such as the 4000 AA{} break, redshifting through specific filters. Our mapping is globally in good agreement with colour-redshift tracks computed with SED templates, but reveals informative differences, such as the need for a lower fraction of M-type stars in certain templates. We compare our clustering-redshift estimates to photometric redshifts and find these two independent estimators to be in good agreement at each limiting magnitude considered. Finally, we present the global clustering-redshift distribution of all Sloan extended sources, showing objects up to z ~ 0.8. While the overall shape agrees with that inferred from photometric redshifts, the clustering redshift technique results in a smoother distribution, with no indication of structure in redshift space suggested by the photometric redshift estimates (likely artifacts imprinted by their spectroscopic training set). We also infer a higher fraction of high redshift objects. The mapping between the four observed colours and redshift can be used to estimate the redshift probability distribution function of individual galaxies. This work is an initial step towards producing a general mapping between redshift and all available observables in the photometric space, including brightness, size, concentration, and ellipticity.
We present redshift probability distributions for galaxies in the SDSS DR8 imaging data. We used the nearest-neighbor weighting algorithm presented in Lima et al. 2008 and Cunha et al. 2009 to derive the ensemble redshift distribution N(z), and indiv idual redshift probability distributions P(z) for galaxies with r < 21.8. As part of this technique, we calculated weights for a set of training galaxies with known redshifts such that their density distribution in five dimensional color-magnitude space was proportional to that of the photometry-only sample, producing a nearly fair sample in that space. We then estimated the ensemble N(z) of the photometric sample by constructing a weighted histogram of the training set redshifts. We derived P(z) s for individual objects using the same technique, but limiting to training set objects from the local color-magnitude space around each photometric object. Using the P(z) for each galaxy, rather than an ensemble N(z), can reduce the statistical error in measurements that depend on the redshifts of individual galaxies. The spectroscopic training sample is substantially larger than that used for the DR7 release, and the newly added PRIMUS catalog is now the most important training set used in this analysis by a wide margin. We expect the primary source of error in the N(z) reconstruction is sample variance: the training sets are drawn from relatively small volumes of space. Using simulations we estimated the uncertainty in N(z) at a given redshift is 10-15%. The uncertainty on calculations incorporating N(z) or P(z) depends on how they are used; we discuss the case of weak lensing measurements. The P(z) catalog is publicly available from the SDSS website.
54 - Stefano Zibetti 2007
The presence of a diffuse stellar component in galaxy clusters has been established by a number of observational works in recent years. In this contribution I summarize our results (Zibetti et al. 2005) obtained by stacking SDSS images of 683 cluster s, selected with the maxBCG algorithm at 0.2< z <0.3. Thanks to our large sample and the advantages of image stacking applied to SDSS images, we are able to measure the systematic properties of the intracluster light (ICL) with very high accuracy. We find that the average surface brightness of the ICL ranges between 26 and 32 mag/arcsec^2, and constantly declines from 70 kpc cluster-centric distance (i.e. distance from the BCG) to 700 kpc. The fraction of diffuse light over the total light (including galaxies), monotonically declines from ~50 to <~5% over the same range of distances, thus showing that the ICL is more easily produced close to the bottom of a clusters potential well. Clusters lacking a bright BCG hardly build up a large amount of intracluster stellar component. The link between the growth of the BCG and the ICL is also suggested by the strong degree of alignment between these two components which is observed in clusters where the BCG displays a significant elongation. With the additional fact that the colors of the ICL are consistent with those of galaxies, all this appears to be evidence for IC stars being stripped from galaxies that suffer very strong tidal interactions in the center of clusters and eventually merge into the BCG. Our measurements also show that IC stars are a minor component of a clusters baryonic budget, representing only ~10% of the total optical emission within 500 kpc. Finally, we discuss some open issues that emerge from a comparison of the present results with other observations and recent theoretical modeling.
107 - P.A.A. Lopes 2007
In this work I discuss the necessary steps for deriving photometric redshifts for luminous red galaxies (LRGs) and galaxy clusters through simple empirical methods. The data used is from the Sloan Digital Sky Survey (SDSS). I show that with three ban ds only ({it gri}) it is possible to achieve results as accurate as the ones obtained by other techniques, generally based on more filters. In particular, the use of the $(g-i)$ color helps improving the final redshifts (especially for clusters), as this color monotonically increases up to $z sim 0.8$. For the LRGs I generate a catalog of $sim 1.5$ million objects at $z < 0.70$. The accuracy of this catalog is $sigma = 0.027$ for $z le 0.55$ and $sigma = 0.049$ for $0.55 < z le 0.70$. The photometric redshift technique employed for clusters is independent of a cluster selection algorithm. Thus, it can be applied to systems selected by any method or wavelength, as long as the proper optical photometry is available. When comparing the redshift listed in literature to the photometric estimate, the accuracy achieved for clusters is $sigma = 0.024$ for $z le 0.30$ and $sigma = 0.037$ for $030 < z le 0.55$. However, when considering the spectroscopic redshift as the mean value of SDSS galaxies on each cluster region, the accuracy is at the same level as found by other authors: $sigma = 0.011$ for $z le 0.30$ and $sigma = 0.016$ for $030 < z le 0.55$. The photometric redshift relation derived here is applied to thousands of cluster candidates selected elsewhere. I have also used galaxy photometric redshifts available in SDSS to identify groups in redshift space and then compare the redshift peak of the nearest group to each cluster redshift (ABRIDGED).
التعليقات
جاري جلب التعليقات جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا