Related papers: Applying the BF method on the DESI evidence for dy…
We determine constraints on spatially-flat tilted dynamical dark energy XCDM and $\phi$CDM inflation models by analyzing Planck 2015 cosmic microwave background (CMB) anisotropy data and baryon acoustic oscillation (BAO) distance…
In this paper, we perform a forecast analysis to test the capacity of future baryon acoustic oscillation (BAO) and cosmic microwave background (CMB) experiments to constrain phenomenological interacting dark energy models using the Fisher…
We consider an Early Dark Energy (EDE) cosmological model, and perform an analysis which takes into account both background and perturbation effects via the parameters $c^{2}_{\rm eff}$ and $c^{2}_{\rm vis}$, representing effective sound…
Strong lensing of gravitational waves can produce several detectable images as repeated events in the upcoming observing runs, which can be detected with the posterior overlap analysis (Bayes factor). The choice of the binary black hole…
Tensor decompositions play a crucial role in numerous applications related to multi-way data analysis. By employing a Bayesian framework with sparsity-inducing priors, Bayesian Tensor Ring (BTR) factorization offers probabilistic estimates…
End-to-end simulations play a key role in the analysis of any high-sensitivity CMB experiment, providing high-fidelity systematic error propagation capabilities unmatched by any other means. In this paper, we address an important issue…
We perform extensive Monte Carlo simulations to systematically compare the frequentist and Bayesian treatments of the Lomb--Scargle periodogram. The goal is to investigate whether the Bayesian period search is advantageous over the…
In this study, we investigate the oscillatory dark energy model $w_{\sin}\mathrm{CDM}$ based on the DESI BAO data together with OHD, Pantheon Plus, and SH0ES measurements. We examine how the DESI data influence the dark energy…
The ratio of Bayesian evidences is a popular tool in cosmology to compare different models. There are however several issues with this method: Bayes' ratio depends on the prior even in the limit of non-informative priors, and Jeffrey's…
In the framework of general relativity, dark energy was proposed to explain the cosmic acceleration. A pivotal inquiry in cosmology is to determine whether dark energy is the cosmological constant, and if not, the challenge lies in…
Quintessence scalar fields are a natural candidate for evolving dark energy. Unlike the phenomenological $w_0w_a$ parameterization of the dark energy equation of state, they cannot accommodate the phantom regime of dark energy $w(z) < -1$,…
To constrain cosmological parameters, one often makes a joint analysis with different combinations of observational data sets. In this paper we take the figure of merit (FoM) for Dark Energy Task Force fiducial model (CPL model) to estimate…
We present cosmological results from the measurement of clustering of galaxy, quasar and Lyman-$\alpha$ forest tracers from the first year of observations with the Dark Energy Spectroscopic Instrument (DESI Data Release 1). We adopt the…
We perform a comprehensive study of a class of dark energy models - scalar field models where the effective potential can be described by a polynomial series - exploring their dynamical behavior using the method of flow equations that has…
In this paper, we assemble a catalog of 118 strong gravitational lensing systems from SLACS, BELLS, LSD and SL2S surveys and use them to constrain the cosmic equation of state. In particular we consider two cases of dark energy…
As wide-field surveys yield increasingly precise data, multiprobe analyses offer significant advantages. In this work, we use our previously developed framework for jointly analyzing cosmic microwave background (CMB) and large-scale…
We present a unified Bayesian assessment of model comparison and data-set consistency for LCDM (cold dark matter plus a cosmological constant) and minimal extensions (neutrino mass, spatial curvature, constant or evolving dark energy) using…
The use of the baryonic acoustic oscillations (BAO) datasets offers a unique opportunity to connect the early universe and the late one. In this proceeding, we discuss recent results that used a marginalised likelihood to remove the…
Bayesian and frequentist methods differ in many aspects, but share some basic optimality properties. In practice, there are situations in which one of the methods is more preferred by some criteria. We consider the case of inference about a…
There is a rich literature proposing methods and establishing asymptotic properties of Bayesian variable selection methods for parametric models, with a particular focus on the normal linear regression model and an increasing emphasis on…