We present a new photometric typing technique for normal type Ia supernovae (SNe~Ia) and peculiar SNe~Ia such as SN~1991bg-like, type Iax and super-Chandrasekhar SNe~Ia. This photometric classifier allows the identification of exclusively normal SNe~Ia (with a purity above 99% and an efficiency greater than 80%) in current and future large wide field surveys for cosmological studies.

I present first results from the algorithm we developed to photometrically classify the Supernovae discovered by the Supernova Diversity and Rate Evolution (SUDARE). The classification outcome is compared with that of the public available code SNANA.

The Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) project performed its five year formal survey since Sep. 2012, already fulfilled the pilot survey and the 1st two years general survey with an output - spectroscopic data archive containing more than 4.1 million observations. One of the scientific objectives of the project is for better understanding the structure and evolution of the Milky Way. Thus, credible derivation of the physical properties of the stars plays a key role for the exploration. We developed and implemented the LAMOST stellar parameter pipeline (LASP) which can automatically determine the fundamental stellar atmospheric parameters (effective temperature Teff, surface gravity log g, metallicity [Fe/H], radial velocity Vr) for late A, FGK type stars observed during the survey. An overview of the LASP, including the strategy, the algorithm and the process is presented in this work.

For SDSS quasar data (2005) we have truncated data structure whereas for the survey of 2007 the data is no longer truncated. This calls for development or use of completely different statistical methodology to study the data for the evolution of the same objects like quasars. These different methodologies suggest different interpretation for a particular phenomenon in nature. This leads to the issue of validation of the data. More intriguing and challenging issue crops up as, given all of the data, what can be said about the laws of physics that have been operating over the universe? Over here we have used the concept of Neural Network to model the relationship between redshift and apparent magnitude.

From the galaxy power spectrum in redshift space, we derive semi-analytical results on the generic degeneracy of galaxy clustering measurements. Defining the observables A = Gbσ8 and R = Gfσ8, (being G the growth function, b the bias, f the growth rate, and σ8 the amplitude of the power spectrum), we perform a Fisher matrix formalism to forecast the expected precision of these quantities for a Euclid-like survey. Among the results we found that galaxy surveys have generically a slightly negative correlation between A and R, and they can always measure R about 3.7 to 4.7 times better than A.

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.

The Hard X-ray Modulation Telescope (HXMT) is a Chinese space telescope mission. It is scheduled for launch in 2015. The telescope will perform an all-sky survey in hard X-ray band (1 - 250 keV), a series of deep imaging observations of small sky regions as well as pointed observations. In this work we present a conceptual method to reconstruct light curves from HXMT imaging observation directly, in order to monitor time-varying objects such as GRB, AXP and SGR in hard X-ray band with HXMT imaging observations.

The success of many cosmological surveys in the near future is highly grounded on the quality of their photometry. The Javalambre-PAU Astrophysical Survey (J-PAS) will image more than 8500 deg2 of the Northern Sky Hemisphere in 54 narrow + 2 medium/broad optical bands plus Sloan u, g and r bands. The main goal of J-PAS is to provide the best constrains on the cosmological parameters before the arrival of projects like Euclid or LSST. To achieve this goal the uncertainty in photo-z cannot be larger than 0.3% for several millions of galaxies and this is highly dependent on the photometric accuracy.

The photometric calibration of J-PAS will imply the intensive use of huge amounts of data and the use of statistical tools is unavoidable. Here, we present some of the key steps in the photometric calibration of J-PAS that will demand a suitable statistical approach.

We quantify the statistical evidence of the relation between the inferred morphology and the emission-line activity type of galaxies for a large sample of galaxies. We compare the distribution of the inferred morphologies of galaxies of different dominant activity types, showing that the difference in the median morphological type between the samples of different activity types is significant. We also test the significance of the difference in the mean morphological type between all the activity-type samples using an ANOVA model with a modified Tukey test that takes into account heteroscedasticity and the unequal sample sizes. We show this test in the form of simultaneous confidence intervals for all pairwise comparisons of the mean morphological types of the samples. Using this test, scarcely applied in astronomy, we conclude that there are statistically significant differences in the inferred morphologies of galaxies of different dominant activity types.

We discuss different methods to separate high- from low-redshift galaxies based on a combination of spectroscopic and photometric observations. Our baseline scenario is the Hobby-Eberly Telescope Dark Energy eXperiment (HETDEX) survey, which will observe several hundred thousand Lyman Alpha Emitting (LAE) galaxies at 1.9 < z < 3.5, and for which the main source of contamination is [OII]-emitting galaxies at z < 0.5. Additional information useful for the separation comes from empirical knowledge of LAE and [OII] luminosity functions and equivalent width distributions as a function of redshift. We consider three separation techniques: a simple cut in equivalent width, a Bayesian separation method, and machine learning algorithms, including support vector machines. These methods can be easily applied to other surveys and used on simulated data in the framework of survey planning.

We investigate how galaxies in VIPERS (the VIMOS Public Extragalactic Redshift Survey) inhabit the cosmological density field by examining the correlations across the observable parameter space of galaxy properties and clustering strength. The high-dimensional analysis is made manageable by the use of group-finding and regression tools. We find that the major trends in galaxy properties can be explained by a single parameter related to stellar mass. After subtracting this trend, residual correlations remain between galaxy properties and the local environment pointing to complex formation dependencies. As a specific application of this work we build subsamples of galaxies with specific clustering properties for use in cosmological tests.

We match the XMM-Newton 3XMMi-DR4 catalog with the Sloan Digital Sky Survey (SDSS) Data Release 10 and the United Kingdom Infrared Deep Sky Survey (UKIDSS) Data Release 9. Based on this X-ray/optical/infrared catalog, we probe the distribution of various types of X-ray emitters in the multidimensional parameter space. It is found that quasars, galaxies and stars have some kind distribution rule, especially for stars. The result shows that only using the X-ray/optical features, stars are difficult to discriminate from galaxies and quasars, the added information from infrared band is very helpful to improve the classification result of any classifier. Comparing the classification accuracy of random forests with that of rotation forests, rotation forests show better performance.

Euclid is the next ESA mission devoted to cosmology. It aims at observing most of the extragalactic sky, studying both gravitational lensing and clustering over ~15,000 square degrees. The mission is expected to be launched in year 2020 and to last six years. The sheer amount of data of different kinds, the variety of (un)known systematic effects and the complexity of measures require efforts both in sophisticated simulations and techniques of data analysis. We review the mission main characteristics, some aspects of the the survey and highlight some of the areas of interest to this meeting.

The Euclid space mission proposes to survey 15000 square degrees of the extragalactic sky during 6 years, with a step-and-stare technique. The scheduling of observation sequences is driven by the primary scientific objectives, spacecraft constraints, calibration requirements and physical properties of the sky. We present the current reference implementation of the Euclid survey and on-going work on survey optimization.

Theories beyond the Standard Model and General Relativity predict a violation of the Weak Equivalence Principle (WEP) just below the current best experimental upper limits. MICROSCOPE (Micro-Satellite à traînée Compensée pour l'Observation du Principe d'Equivalence) will allow us to lower them by two orders of magnitude, and maybe to detect a WEP violation. However, analyzing the MICROSCOPE data will be challenging, mostly because of missing data and a colored noise burrying the signal of interest. In this communication, we apply an inpainting technique to simulated MICROSCOPE data and show that inpainting will help detect a WEP violation signal.

The evidence for the acceleration of the universe shows that canonical theories of cosmology and particle physics are incomplete, and that new physics is out there, waiting to be discovered. Forthcoming high-resolution ultra-stable spectrographs will play a key role in this quest for new physics. Here we focus on astrophysical tests of the stability of nature's fundamental couplings, and by taking existing VLT data as a starting point we discuss how forthcoming improvements (in particular with the E-ELT) will impact on fundamental cosmology.

This work studies the behavior of entropy in recent cosmological models that start with an initial de Sitter expansion phase, go through the conventional radiation and matter dominated eras to be followed by a final de Sitter epoch. In spite of their seemingly similarities (observationally they are close to the Λ-CDM model), different models deeply differ in their physics. The second law of thermodynamics encapsulates the underlying microscopic, statistical description, and hence we investigate it in the present work. Our study reveals that the entropy of the apparent horizon plus that of matter and radiation inside it, increases and is a concave function of the scale factor. Thus thermodynamic equilibrium is approached in the last de Sitter era, and this class of models is thermodynamically correct. Cosmological models that do not approach equilibrium appear in conflict with the second law of thermodynamics. (Based on Mimoso & Pavon 2013)

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.

This paper is concerned with a meteoroid shape estimation technique based on statistical laws of distribution for fragment masses. The idea is derived from the experiments that show that brittle fracturing produces multiple fragments of size lesser than or equal to the least dimension of the body. The number of fragments depends on fragment masses as a power law with exponential cutoff. The scaling exponent essentially indicates the initial form of the fragmented body. We apply the technique of scaling analysis to the empirical data on the mass distributions for Košice, Almahata Sitta and Bassikounou meteorites.

We analyze the cross-correlation function of the soft and hard X-rays of the atoll source 4U 1636-53 with RXTE data. The results show that the cross-correlations evolve along the different branches of the color-color diagram. At the lower left banana states, we have both positive and ambiguous correlations, and positive correlations are dominant for the lower banana and the upper banana states. The anti-correlation is detected at the top of the upper banana states. The cross-correlations of two atoll sources 4U 1735-44 and 4U 1608-52 have been studied in previous work, and the anti-correlations are detected at the lower left banana or the top of the upper banana states. Our results show that, in the 4U 1636-53, the distribution of the cross-correlations in the color-color diagram is similar to those of 4U 1735-44 and 4U 1608-52, and confirm further that the distribution of cross-correlations in color-color diagram could be correlated with the luminosity of the source.