Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userClustering of Extremely Red Objects in Elais-N1 from the UKIDSS DXS with optical photometry from Pan-STARRS1 and Subaru
384
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
We measure the angular clustering of 33 415 extremely red objects (EROs) in the Elais-N1 field covering 5.33 deg$^{2}$, which cover the redshift range $z=0.8$ to $2$. This sample was made by merging the UKIDSS Deep eXtragalactic Survey (DXS) with the optical Subaru and Pan-STARRS PS1 datasets. We confirm the existence of a clear break in the angular correlation function at $sim 0.02^{circ}$ corresponding to $1 h^{-1}$ Mpc at $zsim1$. We find that redder or brighter EROs are more clustered than bluer or fainter ones. Halo Occupation Distribution (HOD) model fits imply that the average mass of dark matter haloes which host EROs is over $10^{13} h^{-1} M_{odot}$ and that EROs have a bias ranging from 2.7 to 3.5. Compared to EROs at $zsim1.1$, at $zsim1.5$ EROs have a higher bias and fewer are expected to be satellite galaxies. Furthermore, EROs reside in similar dark matter haloes to those that host $10^{11.0} M_{odot}<M_{*}<10^{11.5} M_{odot}$ galaxies. We compare our new measurement and HOD fits with the predictions of the GALFORM semi-analytical galaxy formation model. Overall, the clustering predicted by GALFORM gives an encouraging match to our results. However, compared to our deductions from the measurements, GALFORM puts EROs into lower mass haloes and predicts that a larger fraction of EROs are satellite galaxies. This suggests that the treatment of gas cooling may need to be revised in the model. Our analysis illustrates the potential of clustering analyses to provide observational constraints on theoretical models of galaxy formation.
rate research
Read More
Deep, wide, near-infrared imaging surveys provide an opportunity to study the clustering of various galaxy populations at high redshift on the largest physical scales. We have selected $1<z<2$ extremely red objects (EROs) and $1<z<3$ distant red galaxies (DRGs) in SA22 from the near-infrared photometric data of the UKIDSS Deep eXtragalactic Survey (DXS) and $gri$ optical data from CTIO covering 3.3~deg$^2$. This is the largest contiguous area studied to sufficient depth to select these distant galaxies to date. The angular two-point correlation functions and the real space correlation lengths of each population are measured and show that both populations are strongly clustered and that the clustering cannot be parameterised with a single power law. The correlation function of EROs shows a double power law with the inflection at $sim$ 0.6$$--1.2$$ (0.6--1.2~h$^{-1}$~Mpc). The bright EROs ($K<18.8$) show stronger clustering on small scales but similar clustering on larger scales, whereas redder EROs show stronger clustering on all scales. Clustering differences between EROs that are old passively evolved galaxies (OGs) and dusty star-forming galaxies (DGs), on the basis of their $J-K$ colour, are also investigated. The clustering of $r-K$ EROs are compared with that of $i-K$ EROs and the differences are consistent with their expected redshift distributions. The correlation function of DRGs is also well described by a double power law and consistent with previous studies once the effects of the broader redshift distribution our selection of DRGs returns are taken into account. We also perform the same analysis on smaller sub-fields to investigate the impact of cosmic variance on the derived clustering properties. Currently this study is the most representative measurement of the clustering of massive galaxies at $z>1$ on large scales.
The Pan-STARRS1 survey is currently obtaining imaging in 5 bands (grizy) for the $3pi$ steradian survey, one of the largest optical surveys ever conducted. The finished survey will have spatially varying depth, due to the survey strategy. This paper presents a method to correct galaxy number counts and galaxy clustering for this potential systematic based on a simplified signal to noise measurement. A star and galaxy separation method calibrated using realistic synthetic images is also presented, along with an approach to mask bright stars. By using our techniques on a ~69 sq. degree region of science verification data this paper shows PS1 measurements of the two point angular correlation function as a function of apparent magnitude agree with measurements from deeper, smaller surveys. Clustering measurements appear reliable down to a magnitude limit of rps<22.5. Additionally, stellar contamination and false detection issues are discussed and quantified. This work is the second of two papers which pave the way for the exploitation of the full $3pi$ survey for studies of large scale structure.
Context. A lot of photometric data is produced by surveys such as Pan-STARRS, LONEOS, WISE or Catalina. These data are a rich source of information about the physical properties of asteroids. There are several possible approaches for utilizing these data. Lightcurve inversion is a typical method that works with individual asteroids. Our approach in this paper is statistical when we focused on large groups of asteroids like dynamical families and taxonomic classes, and the data were not sufficient for individual models. Aims. Our aim was to study the distributions of shape elongation $b/a$ and the spin axis latitude $beta$ for various subpopulations of asteroids and to compare our results, based on Pan-STARRS1 survey, with statistics previously done using different photometric data (Lowell database, WISE data). Methods. We use the LEADER algorithm to compare the $b/a$ and $beta$ distributions for different subpopulations of asteroids. The algorithm creates a cumulative distributive function (CDF) of observed brightness variations, and computes the $b/a$ and $beta$ distributions using analytical basis functions that yield the observed CDF. A variant of LEADER is used to solve the joint distributions for synthetic populations to test the validity of the method. Results. When comparing distributions of shape elongation for groups of asteroids with different diameters $D$, we found that there are no differences for $D < 25$ km. We also constructed distributions for asteroids with different rotation periods and revealed that the fastest rotators with $P = 0 - 4$ h are more spheroidal than the population with $P = 4 - 8$ h.
We construct a sample of extremely red objects (EROs) within the UKIDSS Ultra Deep Survey by combining the Early Data Release with optical data from the Subaru/XMM-Newton Deep Field. We find a total of 3715 objects over 2013 sq. arcmin with R-K>5.3 and K<=20.3, which is a higher surface density than found by previous studies. This is partly due to our ability to use a small aperture in which to measure colours, but is also the result of a genuine overdensity of objects compared to other fields. We separate our sample into passively-evolving and dusty star-forming galaxies using their RJK colours and investigate their radio properties using a deep radio map. The dusty population has a higher fraction of individually-detected radio sources and a higher mean radio flux density among the undetected objects, but the passive population has a higher fraction of bright radio sources, suggesting that AGNs are more prevalent among the passive ERO population.
We present a study of the classification of z ~1 extremely red objects (EROs), using a combination of HST/ACS, Spitzer/IRAC, and ground-based images of the COSMOS field. Our sample includes about 5300 EROs with i-Ks>2.45 (AB, equivalently I-Ks=4 in Vega) and Ks<=21.1 (AB). For EROs in our sample, we compute, using the ACS F814W images, their concentration, asymmetry, as well as their Gini coefficient and the second moment of the brightest 20% of their light. Using those morphology parameters and the Spitzer/IRAC [3.6]-[8.0] color, the spectral energy distribution (SED) fitting method, we classify EROs into two classes: old galaxies (OGs) and young, dusty starburst galaxies (DGs). We found that the fraction of OGs and DGs in our sample is similar, about 48 percentages of EROs in our sample are OGs, and 52 percentages of them are DGs. To reduce the redundancy of these three different classification methods, we performed a principal component analysis on the measurements of EROs, and find that morphology parameters and SEDs are efficient in segregating OGs and DGs. The [3.6]-[8.0] color, which depends on reddening, redshift, and photometric accuracy, is difficult to separate EROs around the discriminating line between starburst and elliptical. We investigate the dependence of the fraction of EROs on their observational properties, and the results suggest that DGs become increasingly important at fainter magnitudes, redder colors, and higher redshifts.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
