相关论文: On The Non-Gaussian Errors in High-z Supernovae Ty…
We use the $\Delta_{\chi^2}$ statistic introduced in \cite{gup08,gup10} to study directional dependence, in the high-z supernovae data. This dependence could arise due to departures from the cosmological principle or from direction…
Type Ia supernovae have provided fundamental observational data in the discovery of the late acceleration of the expansion of the Universe in cosmology. However, this analysis has relied on the assumption of a Gaussian distribution for the…
The most detailed constraints on the accelerating expansion of the universe and details of nature of dark energy are derived from the high redshift supernova data, assuming that the errors in the measurements are Gaussian in nature. There…
Assuming the Central Limit Theorem, experimental uncertainties in any data set are expected to follow the Gaussian distribution with zero mean. We propose an elegant method based on Kolmogorov-Smirnov statistic to test the above; and apply…
Type Ia Supernovae hold great promise to measure the cosmic deceleration. The diversity observed among these explosions, however, complicates their ability to measure cosmological parameters considerably. The comparison of near and distant…
We examine three SNe Type Ia datasets: Union2.1, JLA and Panstarrs to check their consistency using cosmology blind statistical analyses as well as cosmological parameter fitting. We find that Panstarrs dataset is the most stable of the…
A great deal of effort is currently being devoted to understanding, estimating and removing systematic errors in cosmological data. In the particular case of type Ia supernovae, systematics are starting to dominate the error budget. Here we…
Cosmological parameter fitting remains crucial, especially with the abundance of available data. While many parameters have been tightly constrained, discrepancies-most notably the Hubble tension-persist between measurements obtained from…
Type Ia supernovae (SNe~Ia) are central to studies of cosmic expansion, under the assumption that their absolute magnitude $M_B$ does not evolve with redshift. Even small drifts in brightness can bias cosmological parameters such as $H_0$…
We present a calibration-independent test of the accelerated expansion of the universe using supernova type Ia data. The test is also model-independent in the sense that no assumptions about the content of the universe or about the…
We present a new measurement of the volumetric rate of Type Ia supernova up to a redshift of 1.7, using the Hubble Space Telescope (HST) GOODS data combined with an additional HST dataset covering the North GOODS field collected in 2004. We…
We propose a new statistic that has been designed to be used in situations where the intrinsic dispersion of a data set is not well known: The Crossing Statistic. This statistic is in general less sensitive than `chi^2' to the intrinsic…
Using the Hubble Space Telescope ACS imaging of the GOODS North and South fields during Cycles 11, 12, and 13, we derive empirical constraints on the delay-time distribution function for type Ia supernovae. We extend our previous analysis…
The data of type Ia supernovae observed by the High-z SN Search Team and Supernova Cosmology Project are analyzed in inhomogeneous cosmological models with a local void on scales of about 200 Mpc, to derive the best-fit values of model…
In this paper, we use three different kinds of observational data, including 130 strong gravitational lensing (SGL) systems, type Ia supernovae (SNeIa: Pantheon and Union2.1) and 31 Hubble parameter data points ($H(z)$) from cosmic…
Observational astronomy has shown significant growth over the last decade and has made important contributions to cosmology. A major paradigm shift in cosmology was brought about by observations of Type Ia supernovae. The notion that the…
We perform model-independent distance measurements on four Type Ia supernovae (SNe Ia) compilations (Pantheon, Pantheon+, DES-Dovekie, Union3) and compress each dataset into the values of $\log r_p(z)$ at eleven redshift knots, where…
The latest improvements in the scale and calibration of Type Ia supernovae catalogues allow us to constrain the specific nature and evolution of dark energy through its effect on the expansion history of the universe. We present the results…
The fitting of the observed redshifts and magnitudes of type Ia supernovae to what we would see in homogeneous cosmological models has led to constraints on cosmological parameters. However, in doing such fits it is assumed that the sampled…
Machine learning has become widely used in astronomy. Gaussian Process (GP) regression in particular has been employed a number of times to fit or re-sample supernova (SN) light-curves, however by their nature typical GP models are not…