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Register a new userPhotometric redshift galaxies as tracers of the filamentary network
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Galaxy filaments are the dominant feature in the overall structure of the cosmic web. The study of the filamentary web is an important aspect in understanding galaxy evolution and the evolution of matter in the Universe. A map of the filamentary structure is an adequate probe of the web. We propose that photometric redshift galaxies are significantly positively associated with the filamentary structure detected from the spatial distribution of spectroscopic redshift galaxies. The catalogues of spectroscopic and photometric galaxies are seen as point-process realisations in a sphere, and the catalogue of filamentary spines is proposed to be a realisation of a random set in a sphere. The positive association between these sets was studied using a bivariate $J-$function, which is a summary statistics studying clustering. A quotient $D$ was built to estimate the distance distribution of the filamentary spine to galaxies in comparison to the distance distribution of the filamentary spine to random points in $3-$dimensional Euclidean space. This measure gives a physical distance scale to the distances between filamentary spines and the studied sets of galaxies. The bivariate $J-$function shows a statistically significant clustering effect in between filamentary spines and photometric redshift galaxies. The quotient $D$ confirms the previous result that smaller distances exist with higher probability between the photometric galaxies and filaments. The trend of smaller distances between the objects grows stronger at higher redshift. Additionally, the quotient $D$ for photometric galaxies gives a rough estimate for the filamentary spine width of about $1$~Mpc. Photometric redshift galaxies are positively associated with filamentary spines detected from the spatial distribution of spectroscopic galaxies.
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Optical emission is detected from filaments around the central galaxies of clusters of galaxies. These filaments have lengths of tens of kiloparsecs. The emission is possibly due to heating caused by the dissipation of mechanical energy and by cosmic ray induced ionisation. CO millimeter and submillimeter line emissions as well as H$_{2}$ infrared emission originating in such filaments surrounding NGC~1275, the central galaxy of the Perseus cluster, have been detected. Our aim is to identify those molecular species, other than CO, that may emit detectable millimeter and submillimeter line features arising in these filaments, and to determine which of those species will produce emissions that might serve as diagnostics of the dissipation and cosmic ray induced ionisation. The time-dependent UCL photon-dominated region modelling code was used in the construction of steady-state models of molecular filamentary emission regions at appropriate pressures, for a range of dissipation and cosmic ray induced ionisation rates and incident radiation fields.HCO$^+$ and C$_2$H emissions will potentially provide information about the cosmic ray induced ionisation rates in the filaments. HCN and, in particular, CN are species with millimeter and submillimeter lines that remain abundant in the warmest regions containing molecules. Detections of the galaxy cluster filaments in HCO$^{+}$, C$_{2}$H, and CN emissions and further detections of them in HCN emissions would provide significant constraints on the dissipation and cosmic ray induced ionisation rates.
Even 10 billion years ago, the cores of the first galaxy clusters are often found to host a characteristic population of massive galaxies with already suppressed star formation. Here we search for distant cluster candidates at z~2 using massive passive galaxies as tracers. With a sample of ~40 spectroscopically confirmed passive galaxies at 1.3<z<2.1, we tune photometric redshifts of several thousands passive sources in the full 2 sq.deg. COSMOS field. This allows us to map their density in redshift slices, probing the large scale structure in the COSMOS field as traced by passive sources. We report here on the three strongest passive galaxy overdensities that we identify in the redshift range 1.5<z<2.5. While the actual nature of these concentrations is still to be confirmed, we discuss their identification procedure, and the arguments supporting them as candidate galaxy clusters (likely mid-10^13 M_sun range). Although this search approach is likely biased towards more evolved structures, it has the potential to select still rare, cluster-like environments close to their epoch of first appearance, enabling new investigations of the evolution of galaxies in the context of structure growth.
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 individual 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.
We present a determination of the effects of including galaxy morphological parameters in photometric redshift estimation with an artificial neural network method. Neural networks, which recognize patterns in the information content of data in an unbiased way, can be a useful estimator of the additional information contained in extra parameters, such as those describing morphology, if the input data are treated on an equal footing. We use imaging and five band photometric magnitudes from the All-wavelength Extended Groth Strip International Survey. It is shown that certain principal components of the morphology information are correlated with galaxy type. However, we find that for the data used the inclusion of morphological information does not have a statistically significant benefit for photometric redshift estimation with the techniques employed here. The inclusion of these parameters may result in a trade-off between extra information and additional noise, with the additional noise becoming more dominant as more parameters are added.
Of the many ways of detecting high redshift galaxies, the selection of objects due to their redshifted Ly-alpha emission has become one of the most successful. But what types of galaxies are selected in this way? Until recently, Ly-alpha emitters were understood to be small star-forming galaxies, possible building-blocks of larger galaxies. But with increased number of observations of Ly-alpha emitters at lower redshifts, a new picture emerges. Ly-alpha emitters display strong evolution in their properties from higher to lower redshift. It has previously been shown that the fraction of ultra-luminous infrared galaxies (ULIRGs) among the Ly-alpha emitters increases dramatically between redshift three and two. Here, the fraction of AGN among the LAEs is shown to follow a similar evolutionary path. We argue that Ly-alpha emitters are not a homogeneous class of objects, and that the objects selected with this method reflect the general star forming and active galaxy populations at that redshift. Ly-alpha emitters should hence be excellent tracers of galaxy evolution in future simulations and modeling.
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