The VIMOS Public Extragalactic Redshift Survey (VIPERS)

Torre, S. de la; Guzzo, L.; Peacock, J. A.; Branchini, E.; Iovino, A.; Granett, B. R.; Abbas, U.; Adami, C.; Arnouts, S.; Bel, J.; Bolzonella, M.; Bottini, D.; Cappi, A.; Coupon, J.; Cucciati, O.; Davidzon, I.; Lucia, G. De; Fritz, A.; Franzetti, P.; Fumana, M.; Garilli, B.; Ilbert, O.; Krywult, J.; Brun, V. Le; Fèvre, O. Le; Maccagni, D.; Małek, K.; Marulli, F.; McCracken, H. J.; Moscardini, L.; Paioro, L.; Percival, Will J.; Polletta, M.; Pollo, A.; Schlagenhaufer, H.; Scodeggio, M.; Tasca, L.; Tojeiro, Rita; Vergani, D.; Zanichelli, A.; Burden, A.; Porto, C. Di; Marchetti, A.; Marinoni, C.; Mellier, Y.; Monaco, Pierluigi; Nichol, R. C.; Phleps, S.; Wolk, M.; Zamorani, G.

doi:10.1051/0004-6361/201321463

Cited by 288 publications

(122 citation statements)

References 76 publications

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“…[54], the WiggleZ [55], the SDSS LRG [56], the BOSS CMASS [57], the 6dFGRS [58], and the VIPERS [59]. For the measured values of RSD, we refer …”

Section: Data and The Methodologymentioning

confidence: 99%

“…We examine the interacting scenario both for the constant and dynamical nature of the dark-energy equation of state. Finally, we constrain both the interacting scenarios using the latest observational data from different astronomical sources, namely, the cosmic microwave background radiation [46,47], baryon acoustic oscillations distance measurements [48][49][50], joint light curve analysis from Supernovae Type Ia [51], weak lensing [52,53], redshift space distortion data [54][55][56][57][58][59], and finally the Hubble parameter measurements from cosmic chronometers [60] plus the local Hubble constant [61]. We note that the use of several observational data provides better and tight constraints on the models.…”

Section: Introductionmentioning

confidence: 99%

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Novel approach toward the large-scale stable interacting dark-energy models and their astronomical bounds

2017

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Stability analysis of interacting dark-energy models generally divides its parameters space into two regions, (i) w x ≥ −1 and ξ ≥ 0 and (ii) w x ≤ −1 and ξ ≤ 0, where w x is the dark-energy equation of state and ξ is the coupling strength of the interaction. Because of this separation, crucial information about the cosmology and phenomenology of these models may be lost. In a recent study, it has been shown that one can unify the two regions with a coupling function that depends on the dark-energy equation of state. In this work, we introduce a new coupling function that also unifies the two regions of the parameter space and generalizes the previous proposal. We analyze this scenario considering the equation of state of dark energy to be either constant or dynamical. We study the cosmology of such models and constrain both scenarios with the use of the latest astronomical data from both the background evolution as well as large-scale structures. Our analysis shows that a nonzero value of the coupling parameter ξ as well as the dark-energy equation of state other than −1 are allowed. However, within 1σ confidence level, ξ ¼ 0 and the darkenergy equation of state equal to −1 are compatible with the current data. In other words, the observational data allow a very small but nonzero deviation from the Λ cosmology; however, within the 1σ confidence region, the interacting models can mimic the Λ cosmology. In fact, we observe that the models both at the background and perturbative levels are very hard to distinguish from each other and from Λ cosmology as well. Finally, we offer a rigorous analysis on the current tension on H 0 , allowing different regions of the dark-energy equation of state, which shows that interacting dark-energy models reasonably solve the current tension on H 0 .

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“…[54], the WiggleZ [55], the SDSS LRG [56], the BOSS CMASS [57], the 6dFGRS [58], and the VIPERS [59]. For the measured values of RSD, we refer …”

Section: Data and The Methodologymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Novel approach toward the large-scale stable interacting dark-energy models and their astronomical bounds

2017

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“…The 2PCF of PDR-1 galaxies and the first constraints on the growth rate from redshift-space distortions are presented in a parallel paper (de la Torre et al 2013). A measurement of Ω M using a novel clustering statistic is given in Bel et al (2013).…”

Section: The Vipers Surveymentioning

confidence: 99%

“…This represents a reasonable, though not optimal, approximation at r p 20 h −1 Mpc , where r p is the direction perpendicular to the line-of-sight, and facilitates the comparison with previous studies. A more detailed interpretation of these data using halo occupation distribution (HOD) modelling is deferred to a future work (see also de la Torre et al 2013).…”

Section: Introductionmentioning

confidence: 99%

The VIMOS Public Extragalactic Redshift Survey (VIPERS)

Marulli

Bolzonella

Branchini

et al. 2013

A&A

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Aims. We investigate the dependence of galaxy clustering on luminosity and stellar mass in the redshift range 0.5 < z < 1.1, using the first ∼55 000 redshifts from the VIMOS Public Extragalactic Redshift Survey (VIPERS). Methods. We measured the redshift-space two-point correlation functions (2PCF), ξ(s) and ξ(r p , π) , and the projected correlation function, w p (r p ), in samples covering different ranges of B-band absolute magnitudes and stellar masses. We considered both threshold and binned galaxy samples, with median B-band absolute magnitudes −21.6 M B − 5 log (h) −19.5 and median stellar masses 9.8 log (M [h −2 M ]) 10.7. We assessed the real-space clustering in the data from the projected correlation function, which we model as a power law in the range 0.2 < r p [h −1 Mpc ] < 20. Finally, we estimated the galaxy bias as a function of luminosity, stellar mass, and redshift, assuming a flat Λ cold dark matter model to derive the dark matter 2PCF. Results. We provide the best-fit parameters of the power-law model assumed for the real-space 2PCF -the correlation length, r 0 , and the slope, γ -as well as the linear bias parameter, as a function of the B-band absolute magnitude, stellar mass, and redshift. We confirm and provide the tightest constraints on the dependence of clustering on luminosity at 0.5 < z < 1.1. We prove the complexity of comparing the clustering dependence on stellar mass from samples that are originally flux-limited and discuss the possible origin of the observed discrepancies. Overall, our measurements provide stronger constraints on galaxy formation models, which are now required to match, in addition to local observations, the clustering evolution measured by VIPERS galaxies between z = 0.5 and z = 1.1 for a broad range of luminosities and stellar masses.

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“…The data set used in this paper are those of the early science data release of VIPERS data as described in Guzzo et al (2013); see also de la Torre et al (2013), Fritz et al (2013), Marulli et al (2013), Bel et al (2013), and Davidzon et al (2013). This data will be publicly available in fall 2013 as the VIPERS Public Data Release 1 (PDR-1) catalogue.…”

Section: Spectroscopic Data Vipers Surveymentioning

confidence: 99%

The VIMOS Public Extragalactic Redshift Survey (VIPERS)

Małek

Solarz

Pollo

et al. 2013

A&A

Self Cite

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Aims. The aim of this work is to develop a comprehensive method for classifying sources in large sky surveys and to apply the techniques to the VIMOS Public Extragalactic Redshift Survey (VIPERS). Using the optical (u * , g , r , i ) and near-infrared (NIR) data (z , K s ), we develop a classifier, based on broad-band photometry, for identifying stars, active galactic nuclei (AGNs), and galaxies, thereby improving the purity of the VIPERS sample. Methods. 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 to classifying stars, AGNs, and galaxies and applied this classification to the VIPERS data. We trained the SVM using spectroscopically confirmed sources from the VIPERS and VVDS surveys. Results. 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 97% accuracy in the classification of galaxies, 97% for stars, and 95% for AGNs in the 5-dimensional colour space. In the test of 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, hence increasing the security of measurements for almost 4900 objects. Conclusions. 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.

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The VIMOS Public Extragalactic Redshift Survey (VIPERS)

Cited by 288 publications

References 76 publications

Novel approach toward the large-scale stable interacting dark-energy models and their astronomical bounds

Novel approach toward the large-scale stable interacting dark-energy models and their astronomical bounds

The VIMOS Public Extragalactic Redshift Survey (VIPERS)

The VIMOS Public Extragalactic Redshift Survey (VIPERS)

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