We describe modifications to the joint stepwise maximum likelihood method of Cole (2011) in order to simultaneously fit the GAMA-II galaxy luminosity function (LF), corrected for radial density variations, and its evolution with redshift. The whole sample is reasonably well-fit with luminosity (Q) and density (P) evolution parameters Q, P ≈ 0.8, 1.7. Red galaxies show larger luminosity but smaller density evolution than blue galaxies, as expected.

Spectroscopic redshift surveys are an incredibly valuable tool in cosmology, allowing us to trace the distribution of galaxies as a function of distance and, thus, trace the evolution of structure formation in the Universe. However, estimating the redshifts from spectra with low signal-to-noise is difficult, and such data are often either discarded or require human classification of spectral lines to obtain the galaxy redshift. Darth Fader offers an automated method for estimating the redshifts of galaxies in the low signal-to-noise regime. Using a sophisticated, wavelet-based technique, galaxy spectra can be separated into continuum, line and noise components, and the lines can then be cross-correlated with template spectra in order to estimate the redshifts. Cross-matching of the identified lines then allows for a cleaning of the resulting catalogue, effectively removing the vast majority of erroneous redshift estimates and resulting in a highly pure, highly accurate redshift catalogue. Darth Fader allows us to effectively use low signal-to-noise galaxy spectra, and dramatically reduces the number of human hours required to do this, allowing spectroscopic surveys to probe deeper into the formation history of the Universe.

We present a Principal Component Analysis (PCA) of the V band light-curves of a sample of more than 100 nearby Core collapse supernovae (CC SNe) from [Anderson et al. (2014)]. We used different reference epochs in order to extract the common properties of these light-curves and searched for correlations to some physical parameters such as the burning of 56Ni, and morphological light-curve parameters such as the length of the plateau, the stretch of the light-curve, and the decrements in brightness after maximum and after the plateau. We also used these similarities to create SNe II light-curve templates that will be used in the future for standardize these objects and determine cosmological distances.

Mock galaxy catalogues are essential to the error analysis of cosmological measurements from big galaxy surveys covering thousands of square degrees in the sky, like BOSS, WiggleZ, DES, or Euclid. The PTHalos mock galaxy catalogues were used in the BOSS survey to analyse the BAO measurement from the CMASS (z∼ 0.57) and LOWZ (z∼ 0.32) galaxy samples, which provided the best estimate to date of the cosmic distance scale from galaxy surveys at these redshifts. We review the PTHalos mocks galaxy catalogues and their key contributions to these analyses.

The sufficient statistics of the one-point probability density function of the dark matter density field is worked out using cosmological perturbation theory and tested to the Millennium simulation density field. The logarithmic transformation is recovered for spectral index close to -1 as a special case of the family of power transformations. We then discuss how these transforms should be modified in the case of noisy tracers of the field and focus on the case of Poisson sampling. This gives us optimal local transformations to apply to galaxy survey data prior the extraction of the spectrum in order to capture most efficiently the information encoded in large scale structures.

The avalanche of data over the past 10-20 years has propelled cosmology into the “precision era”. The next challenge cosmology has to meet is to enter the era of accuracy. Because of the intrinsic nature of studying the Cosmos and the sheer amount of data available now and coming soon, the only way to meet this challenge is by developing suitable and specific statistical techniques. The road from precision Cosmology to accurate Cosmology goes through statistical Cosmology. I will outline some open challenges and discuss some specific examples.

Gaussianizing transformations are used statistically in many non-cosmological fields, but in cosmology, we are only starting to apply them. Here I explain a strategy of analyzing the 1-point function (PDF) of a spatial field, together with the ‘essential’ clustering statistics of the Gaussianized field, which are invariant to a local transformation. In cosmology, if the tracer sampling is sufficient, this achieves two important goals. First, it can greatly multiply the Fisher information, which is negligible on nonlinear scales in the usual δ statistics. Second, it decouples clustering statistics from a local bias description for tracers such as galaxies.

Radio interferometers suffer from the problem of missing information in their data, due to the gaps between the antennae. This results in artifacts, such as bright rings around sources, in the images obtained. Multiple deconvolution algorithms have been proposed to solve this problem and produce cleaner radio images. However, these algorithms are unable to correctly estimate uncertainties in derived scientific parameters or to always include the effects of instrumental errors. We propose an alternative technique called Bayesian Inference for Radio Observations (BIRO) which uses a Bayesian statistical framework to determine the scientific parameters and instrumental errors simultaneously directly from the raw data, without making an image. We use a simple simulation of Westerbork Synthesis Radio Telescope data including pointing errors and beam parameters as instrumental effects, to demonstrate the use of BIRO.

The recent immense volume of observation data has urged us to recognize solar features and to analyze their correlation with automation methods, and many of these automation methods are closely related to statistical methods. Author investigations the extensive literatures to sum up the function of statistical methods and their advantages in recognizing automatically solar features and analyzing their correlation. The review lists the results and summarizes conclusions of the investigations. The results and conclusions will be helpful to promote the further automation processing.

We present the first measurement of the correlation between the map of the CMB lensing potential derived from the Planck nominal mission data and z ≳ 1.5 galaxies detected by Herschel-ATLAS (H-ATLAS) survey covering about 550 deg2. We detect the cross-power spectrum with a significance of ∼ 8.5σ, ruling out the absence of correlation at 9σ. We check detection with a number of null tests. The amplitude of cross-correlation and the galaxy bias are estimated using joint analysis of the cross-power spectrum and the galaxy survey auto-spectrum, which allows to break degeneracy between these parameters. The estimated galaxy bias is consistent with previous estimates of the bias for the H-ATLAS data, while the cross-correlation amplitude is higher than expected for a ΛCDM model. The content of this work is to appear in a forthcoming paper Bianchini, et al. (2014).

We discuss a selection of semi-numerical simulations of reionization whose analysis investigates the effect of small absorbing systems, neutral hydrogen within galaxies and the efficiency with which galaxies produce X-rays. We focus on the consequences for both observing the 21–cm 1-point statistics and their interpretation.

The statistical properties of the temperature anisotropies and polarization of the of cosmic microwave background (CMB) radiation offer a powerful probe of the physics of the early universe. In recent works a statistical procedure based upon the calculation of the kurtosis and skewness of the data in patches of CMB sky-sphere has been proposed and used to investigate the large-angle deviation from Gaussianity in WMAP maps. Here we briefly address the question as to how this analysis of Gaussianity is modified if the foreground-cleaned Planck maps are considered. We show that although the foreground-cleaned Planck maps present significant deviation from Gaussianity of different degrees when a less severe mask is used, they become consistent with Gaussianity, as detected by our indicators, when masked with the union mask U73.

The extraction of foreground and CMB maps from multi-frequency observations relies mostly on the different frequency behavior of the different components. Existing Bayesian methods additionally make use of a Gaussian prior for the CMB whose correlation structure is described by an unknown angular power spectrum. We argue for the natural extension of this by using non-trivial priors also for the foreground components. Focusing on diffuse Galactic foregrounds, we propose a log-normal model including unknown spatial correlations within each component and cross-correlations between the different foreground components. We present case studies at low resolution that demonstrate the superior performance of this model when compared to an analysis with flat priors for all components.

Using the 3D information provided by photometric or spectroscopic weak lensing surveys, it has become possible in the last few years to address the problem of mapping the matter density contrast in three dimensions from gravitational lensing. We recently proposed a new non linear sparsity based reconstruction method allowing for high resolution reconstruction of the over-density. This new technique represents a significant improvement over previous linear methods and opens the way to new applications of 3D weak lensing density reconstruction. In particular, we demonstrate that for the first time reconstructed over-density maps can be used to detect and characterise galaxy clusters in mass and redshift.

It is now common practice to constrain cosmological parameters using supernovae (SNe) catalogues constructed from several different surveys. Before performing such a joint analysis, however, one should check that parameter constraints derived from the individual SNe surveys that make up the catalogue are mutually consistent. We describe a statistically-robust mutual consistency test, which we calibrate using simulations, and apply it to each pairwise combination of the surveys making up, respectively, the UNION2 catalogue and the very recent JLA compilation by Betoule et al. We find no inconsistencies in the latter case, but conclusive evidence for inconsistency between some survey pairs in the UNION2 catalogue.

Similarly to gravitational lensing effects like cosmic shear, cosmological γ-ray emission too is to some extent a tracer of the distribution of dark matter (DM) in the Universe. Intervening DM structures source gravitational lensing distortions of distant galaxy images, and those same galaxies can emit γ rays, either because they host astrophysical sources, or directly by particle DM annihilations or decays occurring in the galactic halo. If such γ rays exhibit correlation with the cosmic shear signal, this will provide novel information on the composition of the extragalactic γ-ray background.

Cosmic string interactions often result in the formation of cosmic string loops that detach from the long string network and radiate their energy in the form of gravitational waves. Loop production occurs copiously throughout the cosmological evolution of a cosmic string network and the superimposition of their emissions gives rise to a stochastic gravitational In this essay, we briefly review our recent work on the stochastic gravitational wave background generated by cosmic string networks and introduce a set of numerical and analytical tools for the computation of this background.

Extreme value statistics (EVS) is applied to the pixelized distribution of galaxy luminosities in the Sloan Digital Sky Survey (SDSS). We analyze the DR8 Main Galaxy Sample (MGS) as well as the Luminous Red Galaxy Sample (LRGS). A non-parametric comparison of the EVS of the luminosities with the Fisher-Tippett-Gumbel distribution (limit distribution for independent variables distributed by the Press-Schechter law) indicates a good agreement provided uncertainties arising both from the finite size of the samples and from the sample size distribution are accounted for. This effectively rules out the possibility of having a finite maximum cutoff luminosity.

Peak statistics from weak gravitational lensing have been shown to be a promising tool for cosmology. Here we propose a new approach to predict weak lensing peak counts. For an arbitrary cosmology, we draw dark matter halos from the halo mass function, and calculate the number of peaks from the projected halo mass distribution. This procedure is much faster than time-consuming N-body simulations. By comparing these “fast simulations” to N-body runs, we find that the peak abundance is in very good agreement. Furthermore, our model is able to discriminate cosmologies with different sets of parameters, using high signal-to-noise peaks (≳ 4). This encourages us to examine the optimal combinations of parameters to this approach in the future.

The Gaussian Kinematic Formula (GKF, see Adler and Taylor (2007,2011)) is an extremely powerful tool allowing for explicit analytic predictions of expected values of Minkowski functionals under realistic experimental conditions for cosmological data collections. In this paper, we implement Minkowski functionals on multipoles and needlet components of CMB fields, thus allowing a better control of cosmic variance and extraction of information on both harmonic and real domains; we then exploit the GKF to provide their expected values on spherical maps, in the presence of arbitrary sky masks, and under nonGaussian circumstances.