Related papers: Understanding Data Better with Bayesian and Global…
In the last two decades, Bayesian inference has become commonplace in astronomy. At the same time, the choice of algorithms, terminology, notation, and interpretation of Bayesian inference varies from one sub-field of astronomy to the next,…
The discussion of cosmological parameters used to be a source of embarrassment to cosmologists. Today, measurements of the cosmological parameters are leading the way into the era of precision cosmology. The CMB temperature is measured to…
In an era of large spectroscopic surveys of stars and big data, sophisticated statistical methods become more and more important in order to infer fundamental stellar parameters such as mass and age. Bayesian techniques are powerful methods…
Consistent experiment data are crucial to adjust parameters of physics models and to determine best estimates of observables. However, often experiment data are not consistent due to unrecognized systematic errors. Standard methods of…
The goal of this thesis is twofold; introduce the fundamentals of Bayesian inference and computation focusing on astronomical and cosmological applications, and present recent advances in probabilistic computational methods developed by the…
Tensions between cosmological parameters derived through different channels can be a genuine signature of new physics that $\Lambda$CDM as the standard model is not able to reproduce, in particular in the missing consistency between…
We investigate the possibility of measuring the Hubble constant, the fractional energy density components and the equation of state parameter of the ``dark energy'' using lensed multiple images of high-redshift supernovae. With future…
The inconsistency between experiments in the measurements of the local Universe expansion rate, the Hubble constant, suggests unknown systematics in the existing experiments or new physics. Gravitational-wave standard sirens, a method to…
We present a Bayesian algorithm to combine optical imaging of unresolved objects from distinct epochs and observation platforms for orbit determination and tracking. By propagating the non-Gaussian uncertainties we are able to optimally…
Theoretical models for structure formation with Gaussian initial fluctuations have been worked out in considerable detail and compared with observations on various scales. It is on nonlinear scales $\lsim 10 \ h^{-1}\ {\rm Mpc}$ that the…
Gravitational waves observation with electromagnetic counterparts provides an approach to measure the Hubble constant which is also known as the bright siren method. Great hope has been put into this method to arbitrate the Hubble tension.…
After the discovery of the gravitational waves and the observation of neutrinos of cosmic origin, we have entered a new and exciting era where cosmic rays, neutrinos, photons and gravitational waves will be used simultaneously to study the…
Bayesian model selection methods provide a self-consistent probabilistic framework to test the validity of competing scenarios given a set of data. We present a case study application to strong gravitational lens parametric models. Our goal…
Context. Time delay lensing is a powerful tool to measure the Hubble constant $H_0$. In order to obtain an accurate estimate of $H_0$ from a sample of time delay strong lenses, however, it is necessary to have a very good knowledge of the…
Direct observations of the Hubble rate, from cosmic chronometers and the radial baryon acoustic oscillation scale, can out-perform supernovae observations in understanding the expansion history, because supernovae observations need to be…
We present a method to compute the probability distribution function of the (true) Hubble constant and the age of the universe, given the estimate of the Hubble constant in our nearby galaxy samples. Our method takes into account both the…
Cosmological parameter uncertainties are often stated assuming a particular model, neglecting the model uncertainty, even when Bayesian model selection is unable to identify a conclusive best model. Bayesian model averaging is a method for…
Despite the tremendous advance of observational cosmology, the value of the Hubble constant ($H_0$) is still controversial (the so called ``Hubble tension'') because of the inconsistency between local/late-time measurements and those…
We present a unified Bayesian framework to jointly constrain the Hubble constant $H_0$ and the post-Newtonian parameter $\gamma$, a key probe of deviations from general relativity, using the population characteristics of strongly lensed…
With the use of simulated supernova catalogs, we show that the statefinder parameters turn out to be poorly and biased estimated by standard cosmography. To this end, we compute their standard deviations and several bias statistics on…