Search

We investigate the main tensions within the current standard model of cosmology from the perspective of the main statistics of cosmic voids, using the final BOSS DR12 data set. For this purpose, we present the first estimate of the S8 ≡ σ8 Ωm/0.3 and H0 parameters obtained from void number counts and shape distortions. To analyze void counts we relied on an extension of the popular volume-conserving model for the void size function, tailored to the application on data, including geometric and dynamic distortions. We calibrated the two nuisance parameters of this model with the official BOSS Collaboration mock catalogs and propagated their uncertainty through the statistical analysis of the BOSS void number counts. The constraints from void shapes come from the study of the geometric distortions of the stacked void-galaxy cross-correlation function. In this work we focus our analysis on the Ωm − σ8 and Ωm − H0 parameter planes and derive the marginalized constraints S8 = 0.813−0.068+0.093 and H0 = 67.3−9.1+10.0 km s−1 Mpc−1, which are fully compatible with constraints from the literature. These results are expected to notably improve in precision when analyzed jointly with independent probes and will open a new viewing angle on the rising cosmological tensions in the near future. [ABSTRACT FROM AUTHOR]

We present ICAROGW 2.0, a pure python code developed to infer the astrophysical and cosmological population properties of noisy, heterogeneous, and incomplete observations. The code has mainly been developed for compact binary coalescence (CBC) population inference with gravitational wave (GW) observations. It contains several models for the masses, spins, and redshift of CBC distributions and it is able to infer population distributions, as well as the cosmological parameters and possible general relativity deviations at cosmological scales. Here, we present the theoretical and computational foundations of ICAROGW 2.0 and describe how the code can be employed for population and cosmological inference using (i) only GWs, (ii) GWs and galaxy surveys, and (iii) GWs with electromagnetic counterparts. We discuss the code performance on GPUs, finding a gain in computation time of about two orders of magnitude when more than 100 GW events are involved in the analysis. We have validated the code by re-analyzing GW population and cosmological studies, finding very good agreement with previous results. [ABSTRACT FROM AUTHOR]

Context. Pressure profiles are sensitive probes of the thermodynamic conditions and the internal structure of galaxy clusters. The intra-cluster gas resides in hydrostatic equilibrium within the dark-matter gravitational potential. However, this equilibrium may be perturbed; for example, as a consequence of thermal energy losses, feedback, and non-thermal pressure supports. Accurate measures of the gas pressure over cosmic time are crucial for constraining cluster evolution as well as the contributions from astrophysical processes. Aims. In this work we present a novel algorithm for deriving the pressure profiles of galaxy clusters from the Sunyaev-Zeldovich (SZ) signal measured on a combination of Planck and South Pole Telescope (SPT) observations. The synergy of the two instruments makes it possible to track the profiles on a wide range of spatial scales. We exploited the sensitivity of the Planck High-Frequency Instrument to the larger scales in order to observe the faint peripheries, and took advantage of the higher spatial resolution of SPT to solve the innermost regions. Methods. We developed a two-step pipeline to take advantage of the specifications of each instrument. We first performed a component separation on the two data sets separately in order to remove the background (CMB) and foreground (Galactic emission) contaminants. We then jointly fitted a parametric pressure profile model on a combination of Planck and SPT data. Results. We validated our technique on a sample of six CHEX-MATE clusters detected by SPT. We compare the results of the SZ analysis with profiles derived from X-ray observations with XMM-Newton. We find excellent agreement between these two independent probes of the gas pressure structure. [ABSTRACT FROM AUTHOR]

Context. Weak lensing mass-mapping is a useful tool for accessing the full distribution of dark matter on the sky, but because of intrinsic galaxy ellipticies, finite fields, and missing data, the recovery of dark matter maps constitutes a challenging, ill-posed inverse problem. Aims. We introduce a novel methodology that enables the effcient sampling of the high-dimensional Bayesian posterior of the weak lensing mass-mapping problem, relying on simulations to define a fully non-Gaussian prior. We aim to demonstrate the accuracy of the method to simulated fields, and then proceed to apply it to the mass reconstruction of the HST/ACS COSMOS field. Methods. The proposed methodology combines elements of Bayesian statistics, analytic theory, and a recent class of deep generative models based on neural score matching. This approach allows us to make full use of analytic cosmological theory to constrain the 2pt statistics of the solution, to understand any differences between this analytic prior and full simulations from cosmological simulations, and to obtain samples from the full Bayesian posterior of the problem for robust uncertainty quantification. Results. We demonstrate the method in the TNG simulations and find that the posterior mean significantly outperfoms previous methods (Kaiser-Squires, Wiener filter, Sparsity priors) both for the root-mean-square error and in terms of the Pearson correlation. We further illustrate the interpretability of the recovered posterior by establishing a close correlation between posterior convergence values and the S/N of the clusters artificially introduced into a field. Finally, we apply the method to the reconstruction of the HST/ACS COSMOS field, which yields the highest-quality convergence map of this field to date. Conclusions. We find the proposed approach to be superior to previous algorithms, scalable, providing uncertainties, and using a fully non-Gaussian prior. [ABSTRACT FROM AUTHOR]

We present a set of maps classifying regions of the sky according to their information gain potential as quantified by Fisher information. These maps can guide the optimal retrieval of relevant physical information with targeted cosmological searches. Specifically, we calculated the response of observed cosmic structures to perturbative changes in the cosmological model and we charted their respective contributions to Fisher information. Our physical forward-modeling machinery transcends the limitations of contemporary analyses based on statistical summaries to yield detailed characterizations of individual 3D structures. We demonstrate this advantage using galaxy counts data and we showcase the potential of our approach by studying the information gain of the Coma cluster. We find that regions in the vicinity of the filaments and cluster core, where mass accretion ensues from gravitational infall, are the most informative with regard to our physical model of structure formation in the Universe. Hence, collecting data in those regions would be most optimal for testing our model predictions. The results presented in this work are the first of their kind to elucidate the inhomogeneous distribution of cosmological information in the Universe. This study paves a new way forward for the performance of efficient targeted searches for the fundamental physics of the Universe, where search strategies are progressively refined with new cosmological data sets within an active learning framework. [ABSTRACT FROM AUTHOR]

We performed an internal-consistency test of the KiDS+VIKING-450 (KV450) cosmic shear analysis with a colour-based split of source galaxies. Utilising the same measurements and calibrations for both sub-samples, we inspected the characteristics of the shear measurements and the performance of the calibration pipelines. On the modelling side, we examined the observational nuisance parameters, specifically those for the redshift calibration and intrinsic alignments, using a Bayesian analysis with dedicated test parameters. We verified that the current nuisance parameters are sufficient for the KV450 data to capture residual systematics, with slight deviations seen in the second and the third redshift tomographic bins. Our test also showcases the degeneracy between the inferred amplitude of intrinsic alignments and the redshift uncertainties in low redshift tomographic bins. The test is rather insensitive to the background cosmology and, therefore, can be implemented before any cosmological inference is made. [ABSTRACT FROM AUTHOR]

We present a new shear calibration method based on machine learning. The method estimates the individual shear responses of the objects from the combination of several measured properties on the images using supervised learning. The supervised learning uses the true individual shear responses obtained from copies of the image simulations with different shear values. On simulated GREAT3 data, we obtain a residual bias after the calibration compatible with 0 and beyond Euclid requirements for a signal-to-noise ratio > 20 within ∼15 CPU hours of training using only ∼105 objects. This efficient machine-learning approach can use a smaller data set because the method avoids the contribution from shape noise. The low dimensionality of the input data also leads to simple neural network architectures. We compare it to the recently described method Metacalibration, which shows similar performances. The different methods and systematics suggest that the two methods are very good complementary methods. Our method can therefore be applied without much effort to any survey such as Euclid or the Vera C. Rubin Observatory, with fewer than a million images to simulate to learn the calibration function. [ABSTRACT FROM AUTHOR]

Mapping the behaviour of dark energy is a pressing task for observational cosmology. Phenomenological classification divides dynamical dark energy models into freezing and thawing, depending on whether the dark energy equation of state is approaching or moving away from w = p/p = -1. Moreover, in realistic dynamical dark energy models the dynamical degree of freedom is expected to couple to the electromagnetic sector, leading to variations of the fine-structure constant α. We discuss the feasibility of distinguishing between the freezing and thawing classes of models with current and forthcoming observational facilities and using a parametrisation of the dark energy equation of state, which can have either behaviour, introduced by Mukhanov as fiducial paradigm. We illustrate how freezing and thawing models lead to different redshift dependencies of α, and use a combination of current astrophysical observations and local experiments to constrain this class of models, improving the constraints on the key coupling parameter by more than a factor of two, despite considering a more extended parameter space than the one used in previous studies. We also briefly discuss the improvements expected from future facilities and comment on the practical limitations of this class of parametrisations. In particular, we show that sufficiently sensitive data can distinguish between freezing and thawing models, at least if one assumes that the relevant parameter space does not include phantom dark energy models. [ABSTRACT FROM AUTHOR]

The two-point correlation function of the galaxy distribution is a key cosmological observable that allows us to constrain the dynamical and geometrical state of our Universe. To measure the correlation function we need to know both the galaxy positions and the expected galaxy density field. The expected field is commonly specified using a Monte-Carlo sampling of the volume covered by the survey and, to minimize additional sampling errors, this random catalog has to be much larger than the data catalog. Correlation function estimators compare data–data pair counts to data–random and random–random pair counts, where random–random pairs usually dominate the computational cost. Future redshift surveys will deliver spectroscopic catalogs of tens of millions of galaxies. Given the large number of random objects required to guarantee sub-percent accuracy, it is of paramount importance to improve the efficiency of the algorithm without degrading its precision. We show both analytically and numerically that splitting the random catalog into a number of subcatalogs of the same size as the data catalog when calculating random–random pairs and excluding pairs across different subcatalogs provides the optimal error at fixed computational cost. For a random catalog fifty times larger than the data catalog, this reduces the computation time by a factor of more than ten without affecting estimator variance or bias. [ABSTRACT FROM AUTHOR]

There has been recent interest in the cosmological consequences of energy-momentum-powered gravity models, in which the matter side of Einstein's equations is modified by the addition of a term proportional to some power, n, of the energy-momentum tensor, in addition to the canonical linear term. In this work we treat these models as phenomenological extensions of the standard ΛCDM, containing both matter and a cosmological constant. We also quantitatively constrain the additional model parameters using low redshift background cosmology data that are specifically from Type Ia supernovas and Hubble parameter measurements. We start by studying specific cases of these models with fixed values of n, which lead to an analytic expression for the Friedmann equation; we discuss both their current constraints and how the models may be further constrained by future observations of Type Ia supernovas for WFIRST complemented by measurements of the redshift drift by the ELT. We then consider and constrain a more extended parameter space, allowing n to be a free parameter and considering scenarios with and without a cosmological constant. These models do not solve the cosmological constant problem per se. Nonetheless these models can phenomenologically lead to a recent accelerating universe without a cosmological constant at the cost of having a preferred matter density of around ΩM ∼ 0.4 instead of the usual ΩM ∼ 0.3. Finally we also briefly constrain scenarios without a cosmological constant, where the single component has a constant equation of state which needs not be that of matter; we provide an illustrative comparison of this model with a more standard dynamical dark energy model with a constant equation of state. [ABSTRACT FROM AUTHOR]

The treatment of unknown foreground contaminations will be one of the major challenges for galaxy clustering analyses of coming decadal surveys. These data contaminations introduce erroneous large-scale effects in recovered power spectra and inferred dark matter density fields. In this work, we present an effective solution to this problem in the form of a robust likelihood designed to account for effects due to unknown foreground and target contaminations. Conceptually, this robust likelihood marginalizes over the unknown large-scale contamination amplitudes. We showcase the effectiveness of this novel likelihood via an application to a mock SDSS-III data set subject to dust extinction contamination. In order to illustrate the performance of our proposed likelihood, we infer the underlying dark-matter density field and reconstruct the matter power spectrum, being maximally agnostic about the foregrounds. The results are compared to those of an analysis with a standard Poissonian likelihood, as typically used in modern large-scale structure analyses. While the standard Poissonian analysis yields excessive power for large-scale modes and introduces an overall bias in the power spectrum, our likelihood provides unbiased estimates of the matter power spectrum over the entire range of Fourier modes considered in this work. Further, we demonstrate that our approach accurately accounts for and corrects the effects of unknown foreground contaminations when inferring three-dimensional density fields. Robust likelihood approaches, as presented in this work, will be crucial to control unknown systematic error and maximize the outcome of the decadal surveys. [ABSTRACT FROM AUTHOR]

We present a large-scale Bayesian inference framework to constrain cosmological parameters using galaxy redshift surveys, via an application of the Alcock-Paczyński (AP) test. Our physical model of the non-linearly evolved density field, as probed by galaxy surveys, employs Lagrangian perturbation theory (LPT) to connect Gaussian initial conditions to the final density field, followed by a coordinate transformation to obtain the redshift space representation for comparison with data. We have implemented a Hamiltonian Monte Carlo sampler to generate realisations of three-dimensional (3D) primordial and present-day matter fluctuations from a non-Gaussian LPT-Poissonian density posterior given a set of observations. This hierarchical approach encodes a novel AP test, extracting several orders of magnitude more information from the cosmic expansion compared to classical approaches, to infer cosmological parameters and jointly reconstruct the underlying 3D dark matter density field. The novelty of this AP test lies in constraining the comoving-redshift transformation to infer the appropriate cosmology which yields isotropic correlations of the galaxy density field, with the underlying assumption relying purely on the geometrical symmetries of the cosmological principle. Such an AP test does not rely explicitly on modelling the full statistics of the field. We verified in depth via simulations that this renders our test robust to model misspecification. This leads to another crucial advantage, namely that the cosmological parameters exhibit extremely weak dependence on the currently unresolved phenomenon of galaxy bias, thereby circumventing a potentially key limitation. This is consequently among the first methods to extract a large fraction of information from statistics other than that of direct density contrast correlations, without being sensitive to the amplitude of density fluctuations. We perform several statistical efficiency and consistency tests on a mock galaxy catalogue, using the SDSS-III survey as template, taking into account the survey geometry and selection effects, to validate the Bayesian inference machinery implemented. [ABSTRACT FROM AUTHOR]

We present a new method to estimate shear measurement bias in image simulations that significantly improves the precision with respect to current techniques. Our method is based on measuring the shear response for individual images. We generated sheared versions of the same image to measure how the galaxy shape changes with the small applied shear. This shear response is the multiplicative shear bias for each image. In addition, we also measured the individual additive bias. Using the same noise realizations for each sheared version allows us to compute the shear response at very high precision. The estimated shear bias of a sample of galaxies is then the average of the individual measurements. The precision of this method leads to an improvement with respect to previous methods concerned with the precision of estimates of multiplicative bias since our method is not affected by noise from shape measurements, which until now has been the dominant uncertainty. As a consequence, the method does not require shape-noise suppression for a precise estimation of shear multiplicative bias. Our method can be readily used for numerous applications such as shear measurement validation and calibration, reducing the number of necessary simulated images by a few orders of magnitude to achieve the same precision. [ABSTRACT FROM AUTHOR]

We explore the use of the cosmic infrared background (CIB) as a tracer of the large scale structures for cross-correlating with the cosmic microwave background (CMB) and exploit the integrated Sachs–Wolfe (ISW) effect. We used an improved linear CIB model from our previous work and derived the theoretical CIB×ISW cross-correlation for different Planck HFI frequencies (217, 353, 545 and 857 GHz) and IRAS (3000 GHz). As expected, we predict a positive cross-correlation between the CIB and the CMB whose amplitude decreases rapidly at small scales. We perform a signal-to-noise ratio (S/N) analysis of the predicted cross-correlation. In the ideal case when the cross-correlation is obtained over 70% (40%) of the sky without residual contaminants (e.g. galactic dust) in maps, the S/N ranges from 4.2 to 5.6 (3.2 to 4.3); the highest S/N comes from 857 GHz. A Fisher matrix analysis shows that an ISW signal detected with a S/N this high on the 40% sky can considerably improve the constraints on the cosmological parameters; constraints on the equation of state of the dark energy especially are improved by 80%. We then performed a more realistic analysis considering the effect of residual galactic dust contamination in CIB maps. We calculated the dust power spectra for different frequencies and sky fractions that dominate the CIB power spectra at the lower multipoles we are interested in. Considering a conservative 10% residual level of galactic dust in the CIB power spectra, we observe that the S/N drops drastically, which makes it very challenging to detect the ISW. To determine the capability of current maps to detect the ISW effect through this method, we measured the cross-correlation of the CIB and the CMB Planck maps on the so-called GASS field, which covers an area of ∼11% in the southern hemisphere. We find that with such a small sky fraction and the dust residuals in the CIB maps, we do not detect any ISW signal, and the measured cross-correlation is consistent with zero. To avoid degrading the S/N for the ISW measurement by more than 10% on the 40% sky, we find that the dust needs to be cleaned up to the 0.01% level on the power spectrum. [ABSTRACT FROM AUTHOR]

Being observed only one billion years after the Big Bang, z ∼ 7 quasars are a unique opportunity for exploring the early Universe. However, only two z ∼ 7 quasars have been discovered in near-infrared surveys: the quasars ULAS J1120+0641 and ULAS J1342+0928 at z = 7.09 and z = 7.54, respectively. The rarity of these distant objects, combined with the difficulty of distinguishing them from the much more numerous population of Galactic low-mass stars, requires using efficient selection procedures. The Canada-France High-z Quasar Survey in the Near Infrared (CFHQSIR) has been carried out to search for z ∼ 7 quasars using near-infrared and optical imaging from the Canada-France Hawaii Telescope (CFHT). Our data consist of ∼130 deg2 of Wide-field Infrared Camera (WIRCam) Y-band images up to a 5σ limit of YAB ∼ 22.4 distributed over the Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) Wide fields. After follow-up observations in J band, a first photometric selection based on simple colour criteria led us to identify 36 sources with measured high-redshift quasar colours. However, we expect to detect only ∼2 quasars in the redshift range 6.8 < z < 7.5 down to a rest-frame absolute magnitude of M1450 = −24.6. With the motivation of ranking our high-redshift quasar candidates in the best possible way, we developed an advanced classification method based on Bayesian formalism in which we model the high-redshift quasars and low-mass star populations. The model includes the colour diversity of the two populations and the variation in space density of the low-mass stars with Galactic latitude, and it is combined with our observational data. For each candidate, we compute the probability of being a high-redshift quasar rather than a low-mass star. This results in a refined list of the most promising candidates. Our Bayesian selection procedure has proven to be a powerful technique for identifying the best candidates of any photometrically selected sample of objects, and it is easily extendable to other surveys. [ABSTRACT FROM AUTHOR]

We introduce a new test to study the cosmological principle with galaxy clusters. Galaxy clusters exhibit a tight correlation between the luminosity and temperature of the X-ray-emitting intracluster medium. While the luminosity measurement depends on cosmological parameters through the luminosity distance, the temperature determination is cosmology-independent. We exploit this property to test the isotropy of the luminosity distance over the full extragalactic sky, through the normalization a of the LX-T scaling relation and the cosmological parameters Ωm and H0. To this end, we use two almost independent galaxy cluster samples: the ASCA Cluster Catalog (ACC) and the XMM Cluster Survey (XCS-DR1). Interestingly enough, these two samples appear to have the same pattern for a with respect to the Galactic longitude. More specifically, we identify one sky region within l ∼ (-15°; 90°) (Group A) that shares very different best-fit values for the normalization of the LX-T relation for both ACC and XCS-DR1 samples. We use the Bootstrap and Jackknife methods to assess the statistical significance of these results. We find the deviation of Group A, compared to the rest of the sky in terms of a, to be ∼2:7σ for ACC and ∼3:1σ for XCS-DR1. This tension is not significantly relieved after excluding possible outliers and is not attributed to different redshift (z), temperature (T), or distributions of observable uncertainties. Moreover, a redshift conversion to the cosmic microwave background (CMB) frame does not have an important impact on our results. Using also the HIFLUGCS sample, we show that a possible excess of cool-core clusters in this region, is not able to explain the obtained deviations. Furthermore, we tested for a dependence of the results on supercluster environment, where the fraction of disturbed clusters might be enhanced, possibly affecting the LX-T relation. We indeed find a trend in the XCS-DR1 sample for supercluster members to be underluminous compared to field clusters. However, the fraction of supercluster members is similar in the different sky regions, so this cannot explain the observed differences, either. Constraining Ωm and H0 via the redshift evolution of LX-T and the luminosity distance via the flux-luminosity conversion, we obtain approximately the same deviation amplitudes as for a. It is interesting that the general observed behavior of Ωm for the sky regions that coincide with the CMB dipole is similar to what was found with other cosmological probes such as supernovae Ia. The reason for this behavior remains to be identified. [ABSTRACT FROM AUTHOR]

This paper presents the Planck 2015 likelihoods, statistical descriptions of the 2-point correlationfunctions of the cosmic microwave background (CMB) temperature and polarization fluctuations that account for relevant uncertainties, both instrumental and astrophysical in nature. They are based on the same hybrid approach used for the previous release, i.e., a pixel-based likelihood at low multipoles (l< 30) and a Gaussian approximation to the distribution of cross-power spectra at higher multipoles. The main improvements are the use of more and better processed data and of Planck polarization information, along with more detailed models of foregrounds and instrumental uncertainties. The increased redundancy brought by more than doubling the amount of data analysed enables further consistency checks and enhanced immunity to systematic effects. It also improves the constraining power of Planck, in particular with regard to small-scale foreground properties. Progress in the modelling of foreground emission enables the retention of a larger fraction of the sky to determine the properties of the CMB, which also contributes to the enhanced precision of the spectra. Improvements in data processing and instrumental modelling further reduce uncertainties. Extensive tests establish the robustness and accuracy of the likelihood results, from temperature alone, from polarization alone, and from their combination. For temperature, we also perform a full likelihood analysis of realistic end-to-end simulations of the instrumental response to the sky, which were fed into the actual data processing pipeline; this does not reveal biases from residual low-level instrumental systematics. Even with the increase in precision and robustness, the ΛCDM cosmological model continues to offer a very good fit to the Planck data. The slope of the primordial scalar fluctuations, ns, is confirmed smaller than unity at more than 5s from Planck alone. We further validate the robustness of the likelihood results against specific extensions to the baseline cosmology, which are particularly sensitive to data at high multipoles. For instance, the effective number of neutrino species remains compatible with the canonical value of 3.046. For this first detailed analysis of Planck polarization spectra, we concentrate at high multipoles on the E modes, leaving the analysis of the weaker B modes to future work. At low multipoles we use temperature maps at all Planck frequencies along with a subset of polarization data. These data take advantage of Planck's wide frequency coverage to improve the separation of CMB and foreground emission. Within the baseline ?CDM cosmology this requires τ = 0.078 ± 0.019 for the reionization optical depth, which is significantly lower than estimates without the use of high-frequency data for explicit monitoring of dust emission. At high multipoles we detect residual systematic errors in E polarization, typically at the μK² level; we therefore choose to retain temperature information alone for high multipoles as the recommended baseline, in particular for testing non-minimal models. Nevertheless, the high-multipole polarization spectra from Planck are already good enough to enable a separate high-precision determination of the parameters of the ?CDM model, showing consistency with those established independently from temperature information alone. [ABSTRACT FROM AUTHOR]

We test the statistical isotropy and Gaussianity of the cosmic microwave background (CMB) anisotropies using observations made by the Planck satellite. Our results are based mainly on the full Planck mission for temperature, but also include some polarization measurements. In particular, we consider the CMB anisotropy maps derived from the multi-frequency Planck data by several component-separation methods. For the temperature anisotropies, we find excellent agreement between results based on these sky maps over both a very large fraction of the sky and a broad range of angular scales, establishing that potential foreground residuals do not affect our studies. Tests of skewness, kurtosis, multi-normality, N-point functions, and Minkowski functionals indicate consistency with Gaussianity, while a power deficit at large angular scales is manifested in several ways, for example low map variance. The results of a peak statistics analysis are consistent with the expectations of a Gaussian random field. The "Cold Spot" is detected with several methods, including map kurtosis, peak statistics, and mean temperature profile. We thoroughly probe the large-scale dipolar power asymmetry, detecting it with several independent tests, and address the subject of a posteriori correction. Tests of directionality suggest the presence of angular clustering from large to small scales, but at a significance that is dependent on the details of the approach. We perform the first examination of polarization data, finding the morphology of stacked peaks to be consistent with the expectations of statistically isotropic simulations. Where they overlap, these results are consistent with the Planck 2013 analysis based on the nominal mission data and provide our most thorough view of the statistics of the CMB fluctuations to date. [ABSTRACT FROM AUTHOR]

Maps of cosmic microwave background (CMB) temperature and polarization from the 2015 release of Planck data provide the highest quality full-sky view of the surface of last scattering available to date. This enables us to detect possible departures from a globally isotropic cosmology. We present the first searches using CMB polarization for correlations induced by a possible non-trivial topology with a fundamental domain that intersects, or nearly intersects, the last-scattering surface (at comoving distance χrec), both via a direct scan for matched circular patterns at the intersections and by an optimal likelihood calculation for specific topologies. We specialize to flat spaces with cubic toroidal (T3) and slab (T1) topologies, finding that explicit searches for the latter are sensitive to other topologies with antipodal symmetry. These searches yield no detection of a compact topology with a scale below the diameter of the last-scattering surface. The limits on the radius Ri of the largest sphere inscribed in the fundamental domain (at log-likelihood ratio Δln L > -5 relative to a simply-connected flat Planck best-fit model) are: Ri > 0.97 χrec for the T3 cubic torus; and Ri > 0.56 χrec for the T1 slab. The limit for the T3 cubic torus from the matched-circles search is numerically equivalent, Ri > 0.97 χrec at 99% confidence level from polarization data alone. We also perform a Bayesian search for an anisotropic global Bianchi VIIh geometry. In the non-physical setting, where the Bianchi cosmology is decoupled from the standard cosmology, Planck temperature data favour the inclusion of a Bianchi component with a Bayes factor of at least 2.3 units of log-evidence. However, the cosmological parameters that generate this pattern are in strong disagreement with those found from CMB anisotropy data alone. Fitting the induced polarization pattern for this model to the Planck data requires an amplitude of -0.10 ± 0.04 compared to the value of +1 if the model were to be correct. In the physically motivated setting, where the Bianchi parameters are coupled and fitted simultaneously with the standard cosmological parameters, we find no evidence for a Bianchi VIIh cosmology and constrain the vorticity of such models to (ω/H)0 < 7:6 × 10-10 (95% CL). [ABSTRACT FROM AUTHOR]

In this paper, we develop a full statistical method for the pairwise velocity estimator previously proposed, and apply Cosmicflows-2 catalogue to this method to constrain cosmology. We first calculate the covariance matrix for line-of-sight velocities for a given catalogue, and then simulate the mock full-sky surveys from it, and then calculate the variance for the pairwise velocity field. By applying the 8315 independent galaxy samples and compressed 5224 group samples from Cosmicflows-2 catalogue to this statistical method, we find that the joint constraint on Ωm0.6h and s8 is completely consistent with the WMAP 9-year and Planck 2015 best-fitting cosmology. Currently, there is no evidence for the modified gravity models or any dynamic dark energy models from this practice, and the error-bars need to be reduced in order to provide any concrete evidence against/to support ΛCDM cosmology. [ABSTRACT FROM AUTHOR]

Context. Future large scale cosmological surveys will provide huge data sets whose analysis requires efficient data compression. In particular, the calculation of accurate covariances is extremely challenging with an increasing number of observables used in the statistical analysis. Aims. The primary aim of this paper is to introduce a formalism for achieving efficient data compression, based on a local expansion of the observables around a fiducial cosmological model. We specifically apply and test this approach for the case of cosmic shear statistics. In addition, we study how well band powers can be obtained from measuring shear correlation functions over a finite interval of separations. Methods. We demonstrate the performance of our approach, using a Fisher analysis on cosmic shear tomography described in terms of E-/B-mode separating statistics (COSEBIs). Results. We show that our data compression is highly effective in extracting essentially the full cosmological information from a strongly reduced number of observables. Specifically, the number of observables needed decreases by at least one order of magnitude relative to the COSEBIs, which already compress the data substantially compared to the shear two-point correlation functions. The efficiency appears to be affected only slightly if a highly inaccurate covariance is used for defining the compressed data vector, showing the robustness of the method. In addition, we show the strong limitations on the possibility of constructing top-hat filters in Fourier space, for which the real-space analog has a finite support, yielding strong bounds on the accuracy of band power estimates. Conclusions. We conclude that efficient data compression is achievable and that the number of compressed data points depends on the number of model parameters. Furthermore, a band convergence power spectrum inferred from a finite angular range cannot be accurately estimated. The error on an estimated band power is larger for a narrower filter and a narrower angular range, which for relevant cases can be as large as 10% for βl/l ~ 0.1. [ABSTRACT FROM AUTHOR]

The new cosmic microwave background (CMB) temperature maps from Planck provide the highest-quality full-sky view of the surface of last scattering available to date. This allows us to detect possible departures from the standard model of a globally homogeneous and isotropic cosmology on the largest scales. We search for correlations induced by a possible non-trivial topology with a fundamental domain intersecting, or nearly intersecting, the last scattering surface (at comoving distance χrec), both via a direct search for matched circular patterns at the intersections and by an optimal likelihood search for specific topologies. For the latter we consider flat spaces with cubic toroidal (T3), equal-sided chimney (T2) and slab (T1) topologies, three multi-connected spaces of constant positive curvature (dodecahedral, truncated cube and octahedral) and two compact negative-curvature spaces. These searches yield no detection of the compact topology with the scale below the diameter of the last scattering surface. For most compact topologies studied the likelihood maximized over the orientation of the space relative to the observed map shows some preference for multi-connected models just larger than the diameter of the last scattering surface. Since this effect is also present in simulated realizations of isotropic maps, we interpret it as the inevitable alignment of mild anisotropic correlations with chance features in a single sky realization; such a feature can also be present, in milder form, when the likelihood is marginalized over orientations. Thus marginalized, the limits on the radius Ri of the largest sphere inscribed in topological domain (at log-likelihood-ratio ΔlnL > -5 relative to a simply-connected flat Planck best-fit model) are: in a flat Universe, Ri > 0:92χrec for the T3 cubic torus; Ri > 0:71χrec for the T2 chimney; Ri > 0:50χrec for the T1 slab; and in a positively curved Universe, Ri > 1:03χrec for the dodecahedral space; Ri > 1:0χrec for the truncated cube; and Ri > 0:89χrec for the octahedral space. The limit for a wider class of topologies, i.e., those predicting matching pairs of back-to-back circles, among them tori and the three spherical cases listed above, coming from the matched-circles search, is Ri > 0:94χrec at 99% confidence level. Similar limits apply to a wide, although not exhaustive, range of topologies. We also perform a Bayesian search for an anisotropic global Bianchi VIIh geometry. In the non-physical setting where the Bianchi cosmology is decoupled from the standard cosmology, Planck data favour the inclusion of a Bianchi component with a Bayes factor of at least 1.5 units of log-evidence. Indeed, the Bianchi pattern is quite effcient at accounting for some of the large-scale anomalies found in Planck data. However, the cosmological parameters that generate this pattern are in strong disagreement with those found from CMB anisotropy data alone. In the physically motivated setting where the Bianchi parameters are coupled and fitted simultaneously with the standard cosmological parameters, we find no evidence for a Bianchi VIIh cosmology and constrain the vorticity of such models to (ω/H)0 < 8:1 × 10-10 (95% confidence level). [ABSTRACT FROM AUTHOR]

In light of the tension between cosmological parameters from Planck cosmic microwave background and galaxy clusters, we revised the Planck analysis of the YSZ-mass calibration to allow evolution to be determined by the data instead of being imposed as an external constraint. Our analysis uses the very same data and Malmquist bias corrections as used by the Planck team in order to emphasize that differences in the results come from differences in the assumptions. The evolution derived from 71 calibrating clusters, with 0.05 < z < 0.45, is proportional to E2.5 ± 0.4(z), so inconsistent with the self-similar evolution (E2/3) assumed by previous analyses. When allowing for evolution, the slope of YSZ-mass relation turns out to be 1.51 ± 0.07, which is shallower by 4.8σ than the value derived when assuming self-similar evolution, introducing a mass-dependent bias. The non-self-similar evolution of YSZ has to be accounted for in analyses aimed to establish the biases of Planck masses. [ABSTRACT FROM AUTHOR]

Some peculiar features found in the angular distribution of the cosmic microwave background (CMB) measured by the Wilkinson Microwave Anisotropy Probe (WMAP) deserve further investigation. Among these peculiar features is the quadrant asymmetry, which is likely related to the north-south asymmetry. In this paper, we aim to extend the analysis of the quadrant asymmetry in the ⋀CDM framework to the Planck foreground-cleaned maps, using the mask provided by Planck team. We compute the two-point correlation function (TPCF) from each quadrant of the Planck CMB sky maps, and compare the result with 1000 Monte Carlo (MC) simulations generated assuming the ⋀CDM best-fit power spectrum. We detect the presence of an excess of power in the southeastern quadrant (SEQ) and a significant lack of power in the northeastern quadrant (NEQ) in the Planck data. Asymmetries between the SEQ and the other three quadrants (southwestern quadrant (SWQ), northwestern quadrant (NWQ), and NEQ) are each in disagreement with an isotropic sky at a 95% confidence level. Furthermore, by rotating the Planck temperature sky map with respect to z direction, we showed the rotation angle where the TPCF of the SEQ has its maximal power. Our analysis of the Planck foreground-cleaned maps shows that there is an excess of power in the TPCF in the SEQ and a significant lack of power in the NEQ when compared with simulations. This asymmetry is anomalous when considering the ⋀CDM framework. [ABSTRACT FROM AUTHOR]

We explore the 2013 Planck likelihood function with a high-precision multi-dimensional minimizer (Minuit). This allows a refinement of the ΛCDM best-fit solution with respect to previously-released results, and the construction of frequentist confidence intervals using profile likelihoods. The agreement with the cosmological results from the Bayesian framework is excellent, demonstrating the robustness of the Planck results to the statistical methodology. We investigate the inclusion of neutrino masses, where more significant differences may appear due to the non-Gaussian nature of the posterior mass distribution. By applying the Feldman-Cousins prescription, we again obtain results very similar to those of the Bayesian methodology. However, the profile-likelihood analysis of the cosmic microwave background (CMB) combination (Planck+WP+highL) reveals a minimum well within the unphysical negative-mass region. We show that inclusion of the Planck CMB-lensing information regularizes this issue, and provide a robust frequentist upper limit ∑ mν ≤ 0.26 eV (95% confidence) from the CMB+lensing+BAO data combination. [ABSTRACT FROM AUTHOR]

Context. Research over the past three decades has revolutionized cosmology while supporting the standard cosmological model. However, the cosmological principle of Universal homogeneity and isotropy has always been in question, since structures as large as the survey size have always been found each time the survey size has increased. Until 2013, the largest known structure in our Universe was the Sloan Great Wall, which is more than 400 Mpc long located approximately one billion light years away. Aims. Gamma-ray bursts (GRBs) are the most energetic explosions in the Universe. As they are associated with the stellar endpoints of massive stars and are found in and near distant galaxies, they are viable indicators of the dense part of the Universe containing normal matter. The spatial distribution of GRBs can thus help expose the large scale structure of the Universe. Methods. As of July 2012, 283 GRB redshifts have been measured. Subdividing this sample into nine radial parts, each containing 31 GRBs, indicates that the GRB sample having 1.6 < z < 2.1 differs significantly from the others in that 14 of the 31 GRBs are concentrated in roughly 1/8 of the sky. A two-dimensional Kolmogorov-Smirnov test, a nearest-neighbour test, and a Bootstrap Point-Radius Method explore the significance of this clustering. Results. All tests used indicate that there is a statistically significant clustering of the GRB sample at 1.6 < z < 2.1. Furthermore, this angular excess cannot be entirely attributed to known selection biases, making its existence due to chance unlikely. Conclusions. This huge structure lies ten times farther away than the Sloan Great Wall, at a distance of approximately ten billion light years. The size of the structure defined by these GRBs is about 2000-3000 Mpc, or more than six times the size of the largest known object in the Universe, the Sloan Great Wall. [ABSTRACT FROM AUTHOR]

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', Ks), 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. [ABSTRACT FROM AUTHOR]

Context. Although there is currently a debate over the significance of the claimed large-scale anomalies in the cosmic microwave background (CMB), their existence is not totally dismissed. In parallel to the debate over their statistical significance, recent work has also focussed on masks and secondary anisotropies as potential sources of these anomalies. Aims. In this work we investigate simultaneously the impact of the method used to account for masked regions as well as the impact of the integrated Sachs-Wolfe (ISW) effect, which is the large-scale secondary anisotropy most likely to affect the CMB anomalies. In this sense, our work is an update of previous works. Our aim is to identify trends in CMB data from different years and with different mask treatments. Methods. We reconstruct the ISW signal due to 2 Micron All-Sky Survey (2MASS) and NRAO VLA Sky Survey (NVSS) galaxies, effectively reconstructing the low-redshift ISW signal out to z ~ 1.We account for regions of missing data using the sparse inpainting technique. We test sparse inpainting of the CMB, large scale structure and ISW and find that it constitutes a bias-free reconstruction method suitable to study large-scale statistical isotropy and the ISW effect. Results. We focus on three large-scale CMB anomalies: the low quadrupole, the quadrupole/octopole alignment, and the octopole planarity. After sparse inpainting, the low quadrupole becomes more anomalous, whilst the quadrupole/octopole alignment becomes less anomalous. The significance of the low quadrupole is unchanged after subtraction of the ISW effect, while the trend amongst the CMB maps is that both the low quadrupole and the quadrupole/octopole alignment have reduced significance, yet other hypotheses remain possible as well (e.g. exotic physics). Our results also suggest that both of these anomalies may be due to the quadrupole alone. While the octopole planarity significance is reduced after inpainting and after ISW subtraction, however, we do not find that it was very anomalous to start with. [ABSTRACT FROM AUTHOR]

In this brief paper we revisit the Fisher information content of cosmological power spectra or two-point functions of Gaussian fields in order to comment on the assumption of Gaussian estimators and the use of parameter-dependent covariance matrices for parameter inference in the context of precision cosmology. Even though the assumption of a Gaussian likelihood is motivated by the central limit theorem, we discuss that it leads to Fisher information content that violates the Cramér-Rao bound if used consistently, owing to independent but artificial information from the parameter-dependent covariance matrix. At any fixed multipole, this artificial term is shown to become dominant in the case of a large number of correlated fields.While the distribution of the estimators does indeed tend to a Gaussian with a large number of modes, it is shown, however, that its Fisher information content does not, in the sense that their covariance matrix never carries independent information content, precisely because of the non-Gaussian shape of the distribution. In this light, we discuss the use of parameter-dependent covariance matrices with Gaussian likelihoods for parameter inference from two-point statistics. As a rule of thumb, Gaussian likelihoods should always be used with a covariance matrix fixed in parameter space, since only this guarantees that conservative information content is assigned to the observables, and at the same time, prevents biases appearing. [ABSTRACT FROM AUTHOR]

Aims. We present a stand-alone software (named EXSdetect) for the detection of extended sources in X-ray images. Our goal is to provide a flexible tool capable of detecting extended sources down to the lowest flux levels attainable within instrumental limitations, while maintaining robust photometry, high completeness, and low contamination, regardless of source morphology. EXSdetect was developed mainly to exploit the ever-increasing wealth of archival X-ray data, but is also ideally suited to explore the scientific capabilities of future X-ray facilities, with a strong focus on investigations of distant groups and clusters of galaxies. Methods. EXSdetect combines a fast Voronoi tessellation code with a friends-of-friends algorithm and an automated deblending procedure. The values of key parameters are matched to fundamental telescope properties such as angular resolution and instrumental background. In addition, the software is designed to permit extensive tests of its performance via simulations of a wide range of observational scenarios. Results. We applied EXSdetect to simulated data fields modeled to realistically represent the Swift X-ray Cluster Survey (SXCS), which is based on archival data obtained by the X-ray telescope onboard the Swift satellite.We achieve more than 90% completeness for extended sources comprising at least 80 photons in the 0.5-2 keV band, a limit that corresponds to 10-14 erg cm-2 s-1 for the deepest SXCS fields. This detection limit is comparable to the one attained by the most sensitive cluster surveys conducted with much larger X-ray telescopes. While evaluating the performance of EXSdetect, we also explored the impact of improved angular resolution and discuss the ideal properties of the next generation of X-ray survey missions. [ABSTRACT FROM AUTHOR]

Estimates of cosmological parameters using galaxy clusters have the scatter in the observable at a given mass as a fundamental parameter. This work computes the amplitude of the scatter for a newly introduced mass proxy, the product of the cluster total luminosity times the mass-to-light ratio, usually referred as stellar mass. The analysis of 12 galaxy clusters with excellent total masses shows a tight correlation between the stellar mass, or stellar fraction, and total mass within r500 with negligible intrinsic scatter: the 90% upper limit is 0.06 dex, the posterior mean is 0.027 dex. This scatter is similar to the one of best-determined mass proxies, such as YX, i.e. the product of X-ray temperature, and gas mass. The size of the cluster sample used to determine the intrinsic scatter is small, as in previous works proposing low-scatter proxies because very accurate masses are needed to infer very small values of intrinsic scatter. Three-quarters of the studied clusters have lgM ≲ 14 M☉, which is advantageous from a cosmological perspective because these clusters are far more abundant than more massive clusters. At the difference of other mass proxies such as YX, stellar mass can be determined with survey data up to at least z = 0.9 using upcoming optical near-infrared surveys, such as DES and Euclid, or even with currently available surveys, covering however smaller solid angles. On the other end, the uncertainty about the predicted mass of a single cluster is large, 0.21 to 0.32 dex, depending on cluster richness. This is largely because the proxy itself has ≈0.10 dex errors for clusters of lg M ≲ 14 M☉ mass. [ABSTRACT FROM AUTHOR]

Context. Intriguing features in the angular distribution of the cosmic microwave background (CMB), such as the north-south asymmetry, were reported in the one- and three-year Wilkinson Microwave Anisotropy Probe (WMAP) data and should be studied in detail. We investigate some of these asymmetries in the CMB temperature angular distribution considering the ΛCDM model in the three, five, and seven year WMAP data. Aims. We aim to analyze the four quadrants of the internal linear combination (ILC) CMB maps using three different Galactic cuts: the WMAP KQ85 mask, a ∣b∣ < 10° Galactic cut, and the WMAP KQ85 mask + ∣b∣ < 10° Galactic cut. Methods. We used the two-point angular correlation function (TPCF) in the WMAP maps for each of their quadrants. The same procedure was performed for 1000 Monte Carlo (MC) simulations that were produced using the WMAP team ΛCDM best-fit power spectrum. In addition, we changed the quadrupole and octopole amplitudes obtained from the ΛCDM model spectrum. We changed this to fit the quadrupole and octopole amplitudes to their observable values from the WMAP data. We repeated the analysis for the 1000 simulations of this modified ΛCDM model, hereafter MΛCDM. Results. Our analysis showed asymmetries between the southeastern quadrant (SEQ) and the other quadrants (southwestern quad- rant (SWQ), northeastern quadrant (NEQ) and northwestern quadrant (NWQ)). Over all WMAP ILC maps, the probability for the occurrence of the SEQ-NEQ, SEQ-SWQ and SEQ-NWQ asymmetries varies from 0.1% (SEQ-NEQ) to 8.5% (SEQ-SWQ) using the KQ85 mask and the KQ85 mask + ∣b∣ < 10° Galactic cut, respectively. We also calculated the probabilities for the MΛCDM using only the KQ85 mask and found no significant differences in the results. Moreover, the cold spot region located in the SEQ quadrant was covered with masks of 5, 10 and 15 degrees radius and again the results remained unchanged. Furthermore, this analysis was repeated for random regions in the SEQ quadrant with a 15-degree mask and the SEQ quadrant still remained asymmetric with respect to the other quadrants of the CMB map. Conclusions. We found an excess of power in the TPCF at scales > 100 degrees in the SEQ with respect to the other quadrants that is independent of the Galactic cut used. Moreover, we tested a possible relation between the cold spot and the SEQ excess of power and found no evidence for it. Finally, we could not find any specific region within the SEQ that might be considered responsible for the quadrant asymmetry. [ABSTRACT FROM AUTHOR]

We report the detection, with a high level of confidence, of coherent outflows around voids found in the seventh data release of the Sloan Digital Sky Survey (SDSS DR7). In particular, we developed a robust ≺∣cos θ∣≻ statistical test to quantify the strength of redshiftspace distortions (RSD) associated with extended coherent velocity fields. We consistently find that the vector that joins void centers with galaxies that lie in shells around them is more likely to be perpendicular to the line-of-sight than parallel to it. This effect is clear evidence for the existence of outflows in the vicinity of voids. We show that the RSD exist for a wide range of void radius and shell thickness, but they are more evident in the largest voids in our sample. For instance, we find that the ≺∣cos θ∣≻ for galaxies located in shells within 2 h-1Mpc from the edge of voids larger than 15 h-1Mpc deviates 3.81σ from uniformity. The measurements presented in this work provide useful information to constrain cosmological parameters, in particular Ωm and σ8. [ABSTRACT FROM AUTHOR]

Context. Weak gravitational lensing is an ideal probe of the dark universe. In recent years, several linear methods have been developed to reconstruct the density distribution in the Universe in three dimensions, making use of photometric redshift information to determine the radial distribution of lensed sources. Aims. We aim to address three key problems seen in these methods; namely, the bias in the redshifts of detected objects, the line-ofsight smearing seen in reconstructions, and the damping of the amplitude of the reconstruction relative to the underlying density. We also aim to detect structures at higher redshifts than have previously been achieved, and to improve the line-of-sight resolution of our reconstructions. Methods. We considered the problem under the framework of compressed sensing (CS). Under the assumption that the data are sparse or compressible in an appropriate dictionary, we constructed a robust estimator and employ state-of-the-art convex optimisation methods to reconstruct the density contrast. For simplicity in implementation, and as a proof of concept of our method, we reduced the problem to one dimension, considering the reconstruction along each line of sight independently. We also assumed an idealised survey in which the redshifts of sources are known. Results. Despite the loss of information inherent in our one-dimensional implementation, we demonstrate that our method is able to accurately reproduce cluster haloes up to a redshift of zd = 1.0, deeper than state-of-the-art linear methods. We directly compare our method with these linear methods, and demonstrate minimal radial smearing and redshift bias in our reconstructions, as well as a reduced damping of the reconstruction amplitude as compared to the linear methods. In addition, the CS framework allows us to consider an underdetermined inverse problem, thereby allowing us to reconstruct the density contrast at finer resolution than the input data. Conclusions. The CS approach allows us to recover the density distribution more accurately than current state-of-the-art linear methods. Specifically, it addresses three key problem areas inherent in linear methods. Moreover, we are able to achieve superresolution and increased high-redshift sensitivity in our reconstructions. [ABSTRACT FROM AUTHOR]

Context. Active galactic nuclei (AGN) emit radiation over a wide range of wavelengths, with a peak of emission in the far-UV region of the electromagnetic spectrum, a spectral region that is historically difficult to observe. Aims. Using optical, GALEX UV, and XMM-Newton data we derive the spectral energy distribution (SED) from the optical/UV to X-ray regime of a sizeable sample of AGN. The principal motivation is to investigate the relationship between the optical/UV emission and the X-ray emission and provide bolometric corrections to the hard X-ray (2-10 keV) energy range, kbol, the latter being a fundamental parameter in current physical cosmology. Methods. We construct and study the X-ray to optical SED of a sample of 195 X-ray selected Type 1 AGN belonging to the XMM-Newton bright serendipitous survey (XBS). The optical-UV luminosity was computed using data from the Sloan Digital Sky Survey (SDSS), from our own dedicated optical spectroscopy and the satellite GALaxy evolution EXplorer (GALEX), while the X-ray luminosity was computed using XMM-Newton data. Because it covers a wide range of redshift (0.03 < z ≲2.2), X-ray luminosities (41.8 < log L[2-10] keV < 45.5 erg/s) and because it is composed of "bright objects", this sample is ideal for this kind of investigation. Results. We confirm a highly significant correlation between the accretion disc luminosity Ldisc and the hard X-ray luminosity L[2-10] keV, in the form Ldisc ∝ LΔ [2-10] keV, where Δ = 1.18 ± 0.05. We find a very shallow dependence of kbol on the X-ray luminosity with respect to the broad distribution of values of kbol. We find a correlation between kbol and the hard X-ray photon index Γ2-10 keV and a tight correlation between the optical-to-X-ray spectral index αox and kbol, so we conclude that both Γ2-10 keV and αox can be used as a proxy for kbol. [ABSTRACT FROM AUTHOR]