相关论文: Toward unbiased estimations of the statefinder par…
The current accelerated expansion of the Universe remains ones of the most intriguing topics in modern cosmology, driving the search for innovative statistical techniques. Recent advancements in machine learning have significantly enhanced…
I present an analysis for fitting cosmological parameters from a Hubble Diagram of a standard candle with unknown intrinsic magnitude dispersion. The dispersion is determined from the data themselves, simultaneously with the cosmological…
Supernova cosmology without spectra will be an important component of future surveys such as LSST. This lack of supernova spectra results in uncertainty in the redshifts which, if ignored, leads to significantly biased estimates of…
Cosmography is used in cosmological data processing in order to constrain the kinematics of the universe in a model-independent way. In this paper, we first investigate the effect of the ultraviolet (UV) and X-ray relation of a quasar on…
Photometric redshift estimation is an indispensable tool of precision cosmology. One problem that plagues the use of this tool in the era of large-scale sky surveys is that the bright galaxies that are selected for spectroscopic observation…
Gravitational lensing will cause a dispersion in the Hubble diagram for high redshift sources. This effect will introduce a bias in the cosmological parameter determination using the distance-redshift relation for Type Ia supernovae. In…
When combining data sets to perform parameter inference, the results will be unreliable if there are unknown systematics in data or models. Here we introduce a flexible methodology, BACCUS: BAyesian Conservative Constraints and Unknown…
We develop a novel statistical strong lensing approach to probe the cosmological parameters by exploiting multiple redshift image systems behind galaxies or galaxy clusters. The method relies on free-form mass inversion of strong lenses and…
A method is presented for performing joint analyses of cosmological datasets, in which the weight assigned to each dataset is determined directly by it own statistical properties. The weights are considered in a Bayesian context as a set of…
Stage IV cosmological surveys will map the universe with unprecedented precision, reducing statistical uncertainties to levels where unmodelled systematics can significantly bias inference. In particular, photometric redshift (photo-z)…
Strong gravitational lensing by galaxy clusters is a fundamental tool to study dark matter and constrain the geometry of the Universe. Recently, the Hubble Space Telescope Frontier Fields programme has allowed a significant improvement of…
Recent observational analyses have suggested possible evidence of hemisphere asymmetry in cosmological datasets. Parameterizations of this kind place observers in a privileged position-specifically on the plane that divides the two…
In the context of cosmography approach and using the data of Hubble diagram for supernovae, quasars and gamma-ray bursts, we study some DE parametrizations and also the concordance $\Lambda$CDM universe. Using the different combinations of…
Phenomenological models are widely used in cosmology in relation to constraining different cosmological models, with two common examples being cosmographic expansions and modeling the equation-of-state parameter of dark energy. This work…
As an increasing number of well measured type Ia supernovae (SNe Ia) become available, the statistical uncertainty on w has been reduced to the same size as the systematic uncertainty. The statistical error will decrease further in the near…
We test the isotropy of the Hubble diagram. At small redshifts, this is possible without assumptions on the cosmic inventory and provides a fundamental test of the cosmological principle. At higher redshift we check for the self-consistency…
Local measurements of the Hubble constant ($H_0$) based on Cepheids e Type Ia supernova differ by $\approx 5 \sigma$ from the estimated value of $H_0$ from Planck CMB observations under $\Lambda$CDM assumptions. In order to better…
Gaussian processes provide a method for extracting cosmological information from observations without assuming a cosmological model. We carry out cosmography -- mapping the time evolution of the cosmic expansion -- in a model-independent…
A novel evolutionary method is introduced that can be used for constraining the parameters and theoretical models of Cosmology. The newly proposed algorithm, which is inherently parallel by design, is able to obtain the full potential of…
Cosmography has been referred to as a solution to the inverse scattering problem, which is reasonable since it allows us to calculate cosmological bounds from data samplers by performing an expansion of the cosmological observables around…