Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userThe VIMOS Public Extragalactic Redshift Survey (VIPERS). Hierarchical scaling and biasing
203
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
We investigate the higher-order correlation properties of the VIMOS Public Extragalactic Redshift Survey (VIPERS) to test the hierarchical scaling hypothesis at z~1 and the dependence on galaxy luminosity, stellar mass, and redshift. We also aim to assess deviations from the linearity of galaxy bias independently from a previously performed analysis of our survey (Di Porto et al. 2014). We have measured the count probability distribution function in cells of radii 3 < R < 10 Mpc/h, deriving $sigma_{8g}$, the volume-averaged two-,three-,and four-point correlation functions and the normalized skewness $S_{3g}$ and kurtosis $S_{4g}$ for volume-limited subsamples covering the ranges $-19.5 le M_B(z=1.1)-5log(h) le -21.0$, $9.0 < log(M*/M_{odot} h^{-2}) le 11.0$, $0.5 le z < 1.1$. We have thus performed the first measurement of high-order correlations at z~1 in a spectroscopic redshift survey. Our main results are the following. 1) The hierarchical scaling holds throughout the whole range of scale and z. 2) We do not find a significant dependence of $S_{3g}$ on luminosity (below z=0.9 $S_{3g}$ decreases with luminosity but only at 1{sigma}-level). 3) We do not detect a significant dependence of $S_{3g}$ and $S_{4g}$ on scale, except beyond z~0.9, where the dependence can be explained as a consequence of sample variance. 4) We do not detect an evolution of $S_{3g}$ and $S_{4g}$ with z. 5) The linear bias factor $b=sigma_{8g}/sigma_{8m}$ increases with z, in agreement with previous results. 6) We quantify deviations from the linear bias by means of the Taylor expansion parameter $b_2$. Our results are compatible with a null non-linear bias term, but taking into account other available data we argue that there is evidence for a small non-linear bias term.
rate research
Read More
The VIPERS galaxy survey has measured the clustering of $0.5<z<1.2$ galaxies, enabling a number of measurements of galaxy properties and cosmological redshift-space distortions (RSD). Because the measurements were made using one-pass of the VIMOS instrument on the Very Large Telescope (VLT), the galaxies observed only represent approximately 47% of the parent target sample, with a distribution imprinted with the pattern of the VIMOS slitmask. Correcting for the effect on clustering has previously been achieved using an approximate approach developed using mock catalogues. Pairwise inverse probability (PIP) weighting has recently been proposed by Bianchi & Percival to correct for missing galaxies, and we apply it to mock VIPERS catalogues to show that it accurately corrects the clustering for the VIMOS effects, matching the clustering measured from the observed sample to that of the parent. We then apply PIP-weighting to the VIPERS data, and fit the resulting monopole and quadrupole moments of the galaxy two-point correlation function with respect to the line-of-sight, making measurements of RSD. The results are close to previous measurements, showing that the previous approximate methods used by the VIPERS team are sufficient given the errors obtained on the RSD parameter.
Aims. Using the VIMOS Public Extragalactic Redshift Survey (VIPERS) we aim to jointly estimate the key parameters that describe the galaxy density field and its spatial correlations in redshift space. Methods. We use the Bayesian formalism to jointly reconstruct the redshift-space galaxy density field, power spectrum, galaxy bias and galaxy luminosity function given the observations and survey selection function. The high-dimensional posterior distribution is explored using the Wiener filter within a Gibbs sampler. We validate the analysis using simulated catalogues and apply it to VIPERS data taking into consideration the inhomogeneous selection function. Results. We present joint constraints on the anisotropic power spectrum as well as the bias and number density of red and blue galaxy classes in luminosity and redshift bins as well as the measurement covariances of these quantities. We find that the inferred galaxy bias and number density parameters are strongly correlated although these are only weakly correlated with the galaxy power spectrum. The power spectrum and redshift-space distortion parameters are in agreement with previous VIPERS results with the value of the growth rate $fsigma_8 = 0.38$ with 18% uncertainty at redshift 0.7.
Using an unconventional single line diagnostic that unambiguously identifies AGNs in composite galaxies we report statistical differences in the properties (stellar age, [OII] luminosity, colour) between active and inactive galaxies at 0.62<z<1.2 extracted from the VIMOS Public Extragalactic Redshift Survey (VIPERS). The nuclear activity is probed by the high-ionization [NeV] emission line and along with their parent samples, the galaxies are properly selected according to their stellar mass, redshift, and colour distributions. We report younger underlying stellar ages and higher [OII] luminosities of active galaxies in the green valley and in the blue cloud compared to control samples. We observe higher fractions of green galaxies hosting AGN activity at progressively bluer (r-K) colours. Depending on the location of the host galaxy in the NUVrK colour diagram we find higher AGN fractions in massive blue galaxies and in the least massive red galaxies, in agreement with the picture that black holes vary their properties when hosted in either star-forming or passive galaxies. Exactly where the fast quenching processes are expected to play a role, we identify a novel class of active galaxies in the blue cloud with signatures typical for a suddenly suppression of their star formation activity after a burst happening in the recent past. Their optical spectra resemble those of post-starburst galaxies, that would never be identified in a spectroscopic search using classical selection techniques. Broadly, these active galaxies selected on the [NeV] line are not commonly represented in shallow X-ray, mid-IR, or classical line diagnostics. If we consider that our results are limited by the shallow observational limits and rapid AGN variability, the impact of AGN feedback on galaxy formation and evolution may represent an important channel of fast-transiting galaxies moving to the red sequence.
The aim of this work is to develop a comprehensive method for classifying sources in large sky surveys and we apply the techniques to the VIMOS Public Extragalactic Redshift Survey (VIPERS). Using the optical (u*, g, r, i) and NIR data (z, Ks), we develop a classifier, based on broad-band photometry, for identifying stars, AGNs and galaxies improving the purity of the VIPERS sample. Support Vector Machine (SVM) supervised learning algorithms allow the automatic classification of objects into two or more classes based on a multidimensional parameter space. In this work, we tailored the SVM for classifying stars, AGNs and galaxies, and applied this classification to the VIPERS data. We train the SVM using spectroscopically confirmed sources from the VIPERS and VVDS surveys. We tested two SVM classifiers and concluded that including NIR data can significantly improve the efficiency of the classifier. The self-check of the best optical + NIR classifier has shown a 97% accuracy in the classification of galaxies, 97 for stars, and 95 for AGNs in the 5-dimensional colour space. In the test on VIPERS sources with 99% redshift confidence, the classifier gives an accuracy equal to 94% for galaxies, 93% for stars, and 82% for AGNs. The method was applied to sources with low quality spectra to verify their classification, and thus increasing the security of measurements for almost 4 900 objects. We conclude that the SVM algorithm trained on a carefully selected sample of galaxies, AGNs, and stars outperforms simple colour-colour selection methods, and can be regarded as a very efficient classification method particularly suitable for modern large surveys.
The characterisation of cosmic voids gives unique information about the large-scale distribution of galaxies, their evolution and the cosmological model. We identify and characterise cosmic voids in the VIMOS Public Extragalactic Redshift Survey (VIPERS) at redshift 0.55 < z < 0.9. A new void search method is developed based upon the identification of empty spheres that fit between galaxies. The method can be used to characterise the cosmic voids despite the presence of complex survey boundaries and internal gaps. We investigate the impact of systematic observational effects and validate the method against mock catalogues. We measure the void size distribution and the void-galaxy correlation function. We construct a catalogue of voids in VIPERS. The distribution of voids is found to agree well with the distribution of voids found in mock catalogues. The void-galaxy correlation function shows indications of outflow velocity from the voids.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
