Improved correction of VIPERS angular selection effects in clustering measurements

AbstractClustering estimates in galaxy redshift surveys need to account and correct for the way targets are selected from the general population, as to avoid biasing the measured values of cosmological parameters. The VIMOS Public Extragalactic Redshift Survey (VIPERS) is no exception to this, involving slit collisions and masking effects. Pushed by the increasing precision of the measurements, e.g. of the growth rate f, we have been re-assessing these effects in detail. We present here an improved correction for the two-point correlation function, capable to recover the amplitude of the monopole of the two-point correlation function ξ(r) above 1 h-1 Mpc to better than 2

Augmenting photometric redshift estimates using spectroscopic nearest neighbours

As a consequence of galaxy clustering, close galaxies observed on the plane of the sky should be spatially correlated with a probability that is inversely proportional to their angular separation. In principle, this information can be used to improve photometric redshift estimates when spectroscopic redshifts are available for some of the neighbouring objects. Depending on the depth of the survey, however, this angular correlation is reduced by chance projections. In this work, we implement a deep-learning model to distinguish between apparent and real angular neighbours by solving a classification task. We adopted a graph neural network architecture to tie together photometry, spectroscopy, and the spatial information between neighbouring galaxies. We trained and validated the algorithm on the data of the VIPERS galaxy survey, for which photometric redshifts based on spectral energy distribution are also available. The model yields a confidence level for a pair of galaxies to be real angular neighbours, enabling us to disentangle chance superpositions in a probabilistic way. When objects for which no physical companion can be identified are excluded, all photometric redshift quality metrics improve significantly, confirming that their estimates were of lower quality. For our typical test configuration, the algorithm identifies a subset containing ~75% high-quality photometric redshifts, for which the dispersion is reduced by as much as 50% (from 0.08 to 0.04), while the fraction of outliers reduces from 3% to 0.8%. Moreover, we show that the spectroscopic redshift of the angular neighbour with the highest detection probability provides an excellent estimate of the redshift of the target galaxy, comparable to or even better than the corresponding template-fitting estimate.Comment: 9 pages, 12 figures, matching the accepted version. NezNet is available at https://github.com/tos-1/NezNe

Attractancy of Racemic Disparlure and Certain Analogues to Male Gypsy Moths and the Effect of Trap Placement

Traps hung on small trees of 3-8 cm diam and baited with racemic epoxides, hydrocarbons and other analogues related to racemic cis-7,8-epoxy-2-methyloctadecane (disparlure) resulted in male Lymantria dispar L. (gypsy moth) catches statistically indistinguishable from those of unbaited traps. Only (±)-disparlure yielded trap catches statistically above the level of unbaited traps. However, trap placement on trees of ca. 0.5 m diam produced appreciable trap catches, even in unbaited trap

Average luminosity distance in inhomogeneous universes

The paper studies the correction to the distance modulus induced by inhomogeneities and averaged over all directions from a given observer. The inhomogeneities are modeled as mass-compensated voids in random or regular lattices within Swiss-cheese universes. Void radii below 300 Mpc are considered, which are supported by current redshift surveys and limited by the recently observed imprint such voids leave on CMB. The averaging over all directions, performed by numerical ray tracing, is non-perturbative and includes the supernovas inside the voids. Voids aligning along a certain direction produce a cumulative gravitational lensing correction that increases with their number. Such corrections are destroyed by the averaging over all directions, even in non-randomized simple cubic void lattices. At low redshifts, the average correction is not zero but decays with the peculiar velocities and redshift. Its upper bound is provided by the maximal average correction which assumes no random cancelations between different voids. It is described well by a linear perturbation formula and, for the voids considered, is 20% of the correction corresponding to the maximal peculiar velocity. The average correction calculated in random and simple cubic void lattices is severely damped below the predicted maximal one after a single void diameter. That is traced to cancellations between the corrections from the fronts and backs of different voids. All that implies that voids cannot imitate the effect of dark energy unless they have radii and peculiar velocities much larger than the currently observed. The results obtained allow one to readily predict the redshift above which the direction-averaged fluctuation in the Hubble diagram falls below a required precision and suggest a method to extract the background Hubble constant from low redshift data without the need to correct for peculiar velocities.Comment: 34 pages, 21 figures, matches the version accepted in JCA

The VIMOS Public Extragalactic Redshift Survey (VIPERS). Never mind the gaps: comparing techniques to restore homogeneous sky coverage

[Abridged] Non-uniform sampling and gaps in sky coverage are common in galaxy redshift surveys, but these effects can degrade galaxy counts-in-cells and density estimates. We carry out a comparison of methods that aim to fill the gaps to correct for the systematic effects. Our study is motivated by the analysis of the VIMOS Extragalactic Redshift Survey (VIPERS), a flux-limited survey (i<22.5) based on one-pass observations with VIMOS, with gaps covering 25% of the surveyed area and a mean sampling rate of 35%. Our findings are applicable to other surveys with similar observing strategies. We compare 1) two algorithms based on photometric redshift, that assign redshifts to galaxies based on the spectroscopic redshifts of the nearest neighbours, 2) two Bayesian methods, the Wiener filter and the Poisson-Lognormal filter. Using galaxy mock catalogues we quantify the accuracy of the counts-in-cells measurements on scales of R=5 and 8 Mpc/h after applying each of these methods. We also study how they perform to account for spectroscopic redshift error and inhomogeneous and sparse sampling rate. We find that in VIPERS the errors in counts-in-cells measurements on R<10 Mpc/h scales are dominated by the sparseness of the sample. All methods underpredict by 20-35% the counts at high densities. This systematic bias is of the same order as random errors. No method outperforms the others. Random and systematic errors decrease for larger cells. We show that it is possible to separate the lowest and highest densities on scales of 5 Mpc/h at redshifts 0.5<z<1.1, over a large volume such as in VIPERS survey. This is vital for the characterisation of cosmic variance and rare populations (e.g, brightest galaxies) in environmental studies at these redshifts.Comment: 17 pages, 13 figures, accepted for publication in A&A (revised version after minor revision and language editing

Measuring the growth rate of structure around cosmic voids

Using an algorithm based on searching for empty spheres we identified 245 voids in the VIMOS Public Extragalactic Redshift Survey (VIPERS). We show how by modelling the anisotropic void-galaxy cross correlation function we can probe the growth rate of structure

Looking the void in the eyes - the kSZ effect in LTB models

As an alternative explanation of the dimming of distant supernovae it has recently been advocated that we live in a special place in the Universe near the centre of a large void described by a Lemaitre-Tolman-Bondi (LTB) metric. The Universe is no longer homogeneous and isotropic and the apparent late time acceleration is actually a consequence of spatial gradients in the metric. If we did not live close to the centre of the void, we would have observed a Cosmic Microwave Background (CMB) dipole much larger than that allowed by observations. Hence, until now it has been argued, for the model to be consistent with observations, that by coincidence we happen to live very close to the centre of the void or we are moving towards it. However, even if we are at the centre of the void, we can observe distant galaxy clusters, which are off-centre. In their frame of reference there should be a large CMB dipole, which manifests itself observationally for us as a kinematic Sunyaev-Zeldovich (kSZ) effect. kSZ observations give far stronger constraints on the LTB model compared to other observational probes such as Type Ia Supernovae, the CMB, and baryon acoustic oscillations. We show that current observations of only 9 clusters with large error bars already rule out LTB models with void sizes greater than approximately 1.5 Gpc and a significant underdensity, and that near future kSZ surveys like the Atacama Cosmology Telescope, South Pole Telescope, APEX telescope, or the Planck satellite will be able to strongly rule out or confirm LTB models with giga parsec sized voids. On the other hand, if the LTB model is confirmed by observations, a kSZ survey gives a unique possibility of directly reconstructing the expansion rate and underdensity profile of the void.Comment: 20 pages, 9 figures, submitted to JCA

The VIMOS Public Extragalactic Redshift Survey (VIPERS). Exploring the dependence of the three-point correlation function on stellar mass and luminosity at 0.5<z<1.1

The three-point correlation function (3PCF) is a powerful probe to investigate the clustering of matter in the Universe in a complementary way with respect to lower-order statistics, providing additional information with respect to the two-point correlation function and allowing us to shed light on biasing, nonlinear processes, and deviations from Gaussian statistics. In this paper, we analyse the first data release of the VIMOS Public Extragalactic Redshift Survey (VIPERS), determining the dependence of the three-point correlation function on luminosity and stellar mass at $z=[0.5,1.1]$. We exploit the VIPERS Public Data Release 1, consisting of more than 50,000 galaxies with B-band magnitudes in the range $-21.6\lesssim M_{\rm B}-5\log(h)\lesssim-19.9$ and stellar masses in the range $9.8\lesssim\log(M_\star[h^{-2}\,M_\odot])\lesssim 10.7$. We measure both the connected 3PCF and the reduced 3PCF in redshift space, probing different configurations and scales, in the range $2.5<r\,$[Mpc/h]$<20$. We find a significant dependence of the reduced 3PCF on scales and triangle shapes, with stronger anisotropy at larger scales ($r\sim10$ Mpc/h) and an almost flat trend at smaller scales, $r\sim2.5$ Mpc/h. Massive and luminous galaxies present a larger connected 3PCF, while the reduced 3PCF is remarkably insensitive to magnitude and stellar masses in the range we explored. These trends, already observed at low redshifts, are confirmed for the first time to be still valid up to $z=1.1$, providing support to the hierarchical scenario for which massive and bright systems are expected to be more clustered. The possibility of using the measured 3PCF to provide independent constraints on the linear galaxy bias $b$ has also been explored, showing promising results in agreement with other probes.Comment: 12 pages, 11 figures, 2 tables, accepted for publication in A&

The VIMOS Public Extragalactic Redshift Survey (VIPERS): PCA-based automatic cleaning and reconstruction of survey spectra

Identifying spurious reduction artefacts in galaxy spectra is a challenge for large surveys. We present an algorithm for identifying and repairing residual spurious features in sky-subtracted galaxy spectra with application to the VIPERS survey. The algorithm uses principal component analysis (PCA) applied to the galaxy spectra in the observed frame to identify sky line residuals imprinted at characteristic wavelengths. We further model the galaxy spectra in the rest-frame using PCA to estimate the most probable continuum in the corrupted spectral regions, which are then repaired. We apply the method to 90,000 spectra from the VIPERS survey and compare the results with a subset where careful editing was performed by hand. We find that the automatic technique does an extremely good job in reproducing the time-consuming manual cleaning and does it in a uniform and objective manner across a large data sample. The mask data products produced in this work are released together with the VIPERS second public data release (PDR-2).Comment: Find the VIPERS data release at http://vipers.inaf.i