Related papers: On The Non-Gaussian Errors in High-z Supernovae Ty…

The Genetic Algorithm is a heuristic that can be used to produce model independent solutions to an optimization problem, thus making it ideal for use in cosmology and more specifically in the analysis of type Ia supernovae data. In this…

We use the two-point correlation function of the extrema points (peaks and valleys) in the COBE Differential Microwave Radiometers (DMR) 2-year sky maps as a test for non-Gaussian temperature distribution in the cosmic microwave background…

Machine learning has increasingly gained more popularity with its incredibly powerful ability to make predictions or calculated suggestions for large amounts of data. We apply the machine learning classification to 85,613,922 objects in the…

In this paper, we analyze the potential variation of the gravitational constant $G$ using data from strong gravitational lensing systems and Type Ia supernovae. Testing $G(z)$ parameterizations where $G(z) = G_0(1 + G_1z)$ and $G(z) = G_0(1…

The velocity distributions of stellar tracers in general exhibit weak non-Gaussianity encoding information on the orbital composition of a galaxy and the underlying potential. The standard solution for measuring non-Gaussianity involves…

Identifying anomalous patterns in real-world data is essential for understanding where, when, and how systems deviate from their expected dynamics. Yet methods that separately consider the anomalousness of each individual data point have…

This paper presents a systematic literature review focusing on the application of machine learning techniques for deriving observational constraints in cosmology. The goal is to evaluate and synthesize existing research to identify…

The actual knowledge of the structure and future evolution of our universe is based on the use of cosmological models, which can be tested through the so-called 'probes', namely astrophysical phenomena, objects or structures with peculiar…

Gaussian universality results assert that the properties of many estimators remain unchanged when the input data are replaced by Gaussians. Such results have gained popularity in high-dimensional statistics and machine learning, as…

This paper develops Kolmogorov-type maximal inequalities for sums of Negative Binomial random variables under both independence and dependence structures. For independent heterogeneous Negative Binomial variables we derive sharp Markov-type…

The analysis of record-breaking events is of interest in fields such as climatology, hydrology or anthropology. In connection with the record occurrence, we propose three distribution-free statistics for the changepoint detection problem.…

Observations of high redshift supernovae imply an accelerating Universe which can only be explained by an unusual energy component such as vacuum energy or quintessence. To assess the ability of current and future supernova data to…

Observations of distant type Ia supernovae (SNe Ia), used as standard candles, support the notion that the Cosmos is filled with a mysterious form of energy, the dark energy. The constraints on cosmological parameters derived from data of…

We describe methods used to validate data from the Y.T. Lee Array for Microwave Background Anisotropy (AMiBA), an interferometric array designed to measure the Sunyaev-Zel'dovich effect and the anisotropy of the Cosmic Microwave Background…

The observed delay-time distribution (DTD) of Type-Ia supernovae (SNe Ia) is a valuable probe of SN Ia progenitors and physics, and of the role of SNe Ia in cosmic metal enrichment. The SN Ia rate in galaxy clusters as a function of cluster…

We probe the systematic uncertainties from 113 Type Ia supernovae (SNIa) in the Pan-STARRS1 (PS1) sample along with 197 SN Ia from a combination of low-redshift surveys. The companion paper by Rest et al. (2013) describes the photometric…

The absolute-magnitude distributions of seven supernova types are presented. The data used here were primarily taken from the Asiago Supernova Catalogue, but were supplemented with additional data. We accounted for both foreground and…

Observational data for type Ia supernovae, shows that the expansion of the universe is accelerated. This accelerated expansion can be described by a cosmological constant or by dark energy models like quintessence. An interesting question…

The peculiar motions of galaxies are powerful cosmological probes that trace the growth of structures and the distribution of matter in the universe, providing a means to investigate the nature of dark energy and test gravity on…

We confront the predictions of different quintessence models with recent measurements of the luminosity distance from two sets of supernovae type Ia. In particular, we consider the 157 SNe Ia in the Gold dataset with z<1.7, and the more…