scholarly journals Radio Galaxies as Large-Scale Cosmological Probes

1988 ◽  
Vol 130 ◽  
pp. 579-579
Author(s):  
J.A. Peacock ◽  
L. Miller ◽  
C.A. Collins ◽  
D. Nicholson ◽  
S. J. Lilly
Keyword(s):  
Large Scale ◽  
A Priori ◽  
Radio Galaxies ◽  
Elliptical Galaxies ◽  
Central Component ◽  
Selection Effects ◽  
Core Radius ◽  
Point Correlation ◽  
Point Correlation Function ◽  
Radio Power

We are working on an all-sky sample of radio-selected elliptical galaxies to provide a powerful probe of clustering & streaming velocities on 10–100 Mpc scales. Our eventual sample will have the limits (i) S>0.5 Jy at 1.4 GHz; (ii) 0.01<z<0.1; (iii) |b| >15°; about 400 galaxies satisfy these criteria. We are pursuing an optical programme to obtain (i) B & I CCD frames for all galaxies; (ii) spectra for the galaxies without accurate redshifts; this is now about 30% complete. Accurate optical luminosity indicators exist for radio galaxies, without needing to measure velocity dispersions (using the correlations with optical core radius and radio central-component luminosity: Hoessel 1980: Ap. J. 241, 493; Fabbiano et al. 1984: Ap. J. 277, 115). We therefore expect to provide an accurate test of the Rubin-Ford effect, and to extend such studies to higher redshift. We also have a preliminary result for the 3D two-point correlation function of radio galaxies (see Figure). This strong clustering signal is seen only from galaxies in the decade of radio power below the Fanaroff-Riley division. These objects are known a priori to lie in cluster environments of average Abell richness 0 (Longair & Seldner 1979: MNRAS 189, 433). This result therefore provides confirmation of a trend of clustering with richness independent of optical selection effects in choosing a cluster sample.

scholarly journals The Anglo-Australian Redshift Survey

1983 ◽  
Vol 104 ◽  
pp. 175-175
Author(s):  
J. Bean ◽  
G. Efstathiou ◽  
R. S. Ellis ◽  
B. A. Peterson ◽  
T. Shanks ◽  
...  
Keyword(s):  
Correlation Function ◽  
Luminosity Function ◽  
Large Scale ◽  
Peculiar Velocities ◽  
Point Correlation ◽  
Point Correlation Function ◽  
Redshift Survey ◽  
Density Inhomogeneities ◽  
The Universe

The aim of the survey is to sample a relatively large, randomly chosen volume of the Universe in order to study the large-scale distribution of galaxies using the two-point correlation function, the peculiar velocities between galaxy pairs and to provide an estimate of the galaxian luminosity function that is unaffected by density inhomogeneities and Virgo infall.

The Local Large-Scale Structure from HIPASS

2005 ◽  
Vol 216 ◽  
pp. 196-202
Author(s):  
Martin Zwaan ◽  
Martin Meyer ◽  
Rachel Webster ◽  
Lister Staveley-Smith
Keyword(s):  
Large Scale ◽  
Large Scale Structure ◽  
Scale Structure ◽  
Sky Survey ◽  
The Galaxy ◽  
Point Correlation ◽  
Point Correlation Function ◽  
Fisher Relation ◽  
Galaxy Population ◽  
Mass Functions

The HI Parkes All Sky Survey (HIPASS) offers a unique perspective on the galaxy population in the local universe. A catalogue of 4315 HI-selected galaxies has been extracted from the southern region of the survey (δ < +2°). This catalogue gives a clear view of the local large-scale structure and is used to study the two-point correlation function, the Tully-Fisher relation, and galaxy luminosity and mass functions. Some initial results are discussed here.

scholarly journals One- and two-point source statistics from the LOFAR Two-metre Sky Survey first data release

2020 ◽  
Vol 643 ◽  
pp. A100
Author(s):  
T. M. Siewert ◽  
C. Hale ◽  
N. Bhardwaj ◽  
M. Biermann ◽  
D. J. Bacon ◽  
...  
Keyword(s):  
Point Source ◽  
Flux Density ◽  
Large Scale ◽  
Value Added ◽  
Radio Sources ◽  
Sky Survey ◽  
Point Correlation ◽  
Point Correlation Function ◽  
The Universe ◽  
Density Threshold

Context. The LOFAR Two-metre Sky Survey (LoTSS) will eventually map the complete Northern sky and provide an excellent opportunity to study the distribution and evolution of the large-scale structure of the Universe. Aims. We test the quality of LoTSS observations through a statistical comparison of the LoTSS first data release (DR1) catalogues to expectations from the established cosmological model of a statistically isotropic and homogeneous Universe. Methods. We study the point-source completeness and define several quality cuts, in order to determine the count-in-cell statistics and differential source count statistics, and measure the angular two-point correlation function. We use the photometric redshift estimates, which are available for about half of the LoTSS-DR1 radio sources, to compare the clustering throughout the history of the Universe. Results. For the masked LoTSS-DR1 value-added source catalogue, we find a point-source completeness of 99% above flux densities of 0.8 mJy. The counts-in-cell statistic reveals that the distribution of radio sources cannot be described by a spatial Poisson process. Instead, a good fit is provided by a compound Poisson distribution. The differential source counts are in good agreement with previous findings in deep fields at low radio frequencies and with simulated catalogues from the SKA Design Study and the Tiered Radio Extragalactic Continuum Simulation. Restricting the value added source catalogue to low-noise regions and applying a flux density threshold of 2 mJy provides our most reliable estimate of the angular two-point correlation. Based on the distribution of photometric redshifts and the Planck 2018 best-fit cosmological model, the theoretically predicted angular two-point correlation between 0.1 deg and 6 deg agrees reasonably well with the measured clustering for the sub-sample of radio sources with redshift information. Conclusions. The deviation from a Poissonian distribution might be a consequence of the multi-component nature of a large number of resolved radio sources and/or of uncertainties on the flux density calibration. The angular two-point correlation function is < 10−2 at angular scales > 1 deg and up to the largest scales probed. At a 2 mJy flux density threshold and at a pivot angle of 1 deg, we find a clustering amplitude of A = (5.1 ± 0.6) × 10−3 with a slope parameter of γ = 0.74 ± 0.16. For smaller flux density thresholds, systematic issues are identified, which are most likely related to the flux density calibration of the individual pointings. We conclude that we find agreement with the expectation of large-scale statistical isotropy of the radio sky at the per cent level. The angular two-point correlation agrees well with the expectation of the cosmological standard model.

scholarly journals rascalc: a jackknife approach to estimating single- and multitracer galaxy covariance matrices

2019 ◽  
Vol 491 (3) ◽  
pp. 3290-3317 ◽  
Author(s):  
Oliver H E Philcox ◽  
Daniel J Eisenstein ◽  
Ross O’Connell ◽  
Alexander Wiegand
Keyword(s):  
Large Scale ◽  
Covariance Matrices ◽  
Scale Model ◽  
Data Sets ◽  
Data Set ◽  
Large Numbers ◽  
Large Scale Model ◽  
Point Correlation ◽  
Point Correlation Function ◽  
Single Input

ABSTRACT To make use of clustering statistics from large cosmological surveys, accurate and precise covariance matrices are needed. We present a new code to estimate large-scale galaxy two-point correlation function (2PCF) covariances in arbitrary survey geometries that, due to new sampling techniques, runs ∼104 times faster than previous codes, computing finely binned covariance matrices with negligible noise in less than 100 CPU-hours. As in previous works, non-Gaussianity is approximated via a small rescaling of shot noise in the theoretical model, calibrated by comparing jackknife survey covariances to an associated jackknife model. The flexible code, rascalc, has been publicly released, and automatically takes care of all necessary pre- and post-processing, requiring only a single input data set (without a prior 2PCF model). Deviations between large-scale model covariances from a mock survey and those from a large suite of mocks are found to be indistinguishable from noise. In addition, the choice of input mock is shown to be irrelevant for desired noise levels below ∼105 mocks. Coupled with its generalization to multitracer data sets, this shows the algorithm to be an excellent tool for analysis, reducing the need for large numbers of mock simulations to be computed.

scholarly journals Large-Scale Distribution of Galaxies with Different Luminosities

1987 ◽  
Vol 124 ◽  
pp. 363-366
Author(s):  
X. Y. Xia ◽  
Z. G. Deng ◽  
Y. Y. Zhou
Keyword(s):  
Large Scale ◽  
Absolute Magnitude ◽  
Power Indices ◽  
Apparent Magnitude ◽  
Clusters Of Galaxies ◽  
Intrinsic Properties ◽  
Complete Sample ◽  
Point Correlation ◽  
Point Correlation Function ◽  
Distant Region

Analyses for complete samples of galaxies and clusters of galaxies showed that the two-point correlation function of galaxy-galaxy and cluster-cluster have form of power law with power indices about −1.8 (Peebles, 1980; Bahcall and Soneira, 1983). Because the completeness of a sample means that we have observed completely the objects brighter than a given apparent magnitude in certain sky region. But, we know that a complete sample will be lack of faint objects at distant region. If we attempt to avoid the influences of any non-intrinsic properties on the analysis, we have to use the samples which are complete in certain interval of absolute magnitude.

scholarly journals The large-scale three-point correlation function of the SDSS BOSS DR12 CMASS galaxies

2017 ◽  
Vol 468 (1) ◽  
pp. 1070-1083 ◽  
Author(s):  
Zachary Slepian ◽  
Daniel J. Eisenstein ◽  
Florian Beutler ◽  
Chia-Hsun Chuang ◽  
Antonio J. Cuesta ◽  
...  
Keyword(s):  
Correlation Function ◽  
Large Scale ◽  
Point Correlation ◽  
Point Correlation Function

scholarly journals Detection of baryon acoustic oscillation features in the large-scale three-point correlation function of SDSS BOSS DR12 CMASS galaxies

2017 ◽  
Vol 469 (2) ◽  
pp. 1738-1751 ◽  
Author(s):  
Zachary Slepian ◽  
Daniel J. Eisenstein ◽  
Joel R. Brownstein ◽  
Chia-Hsun Chuang ◽  
Héctor Gil-Marín ◽  
...  
Keyword(s):  
Correlation Function ◽  
Large Scale ◽  
Acoustic Oscillation ◽  
Baryon Acoustic Oscillation ◽  
Point Correlation ◽  
Point Correlation Function
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