Related papers: Bayesian inferences on covariant density functiona…
While the equation of state (EOS) of symmetric nuclear matter (SNM) at suprasaturation densities has been relatively well constrained from heavy-ion collisions, the EOS of high-density neutron-rich matter is still largely uncertain due to…
In this theoretical study, we report an investigation of the equations of state (EoSs) ofhyper-nuclear matter and its composition as a function of density within the framework of effective field theory motivated relativistic mean field…
We explore the parameter space of the semi-analytic galaxy formation model GALFORM, studying the constraints imposed by measurements of the galaxy stellar mass function (GSMF) and its evolution. We use the Bayesian Emulator method to…
We introduce the notion of a Bayesian analysis motivated `reliability' that gives a truer distinction of cusp-core and other halo-parameters (like mass-concentration) in an ensemble of observed galaxies. Our approach goes beyond the…
Coherent elastic neutrino-nucleus scattering (CE$\nu$NS) and other rare-event physics searches, like dark matter detection, have been especially furthered by increasing sensitivity to low-energy particle interactions. Experiments using…
We suggest a new Bayesian analysis (BA) using disjunct M-R constraints for extracting probability measures for cold, dense matter equations of state (EoS). One of the key issues of such an analysis is the question of a deconfinement…
A new density dependent effective baryon-baryon interaction has been recently derived from the quark-meson-coupling (QMC) model, offering impressive results in application to finite nuclei and dense baryon matter. This self-consistent,…
Cosmological constraints on the sum of neutrino masses and on the effective number of neutrino species in standard and non-standard scenarios are computed using the most recent available cosmological data. Our cosmological data sets include…
The internal structure of dark matter halos on sub-galactic scales remains a key open question, particularly in the context of the core-cusp problem. Ultra-faint dwarf galaxies (UFDs), owing to their extreme dark matter dominance, provide a…
Neutron stars can accumulate asymmetric dark matter (ADM) in their interiors, which affects the neutron star's measurable properties and makes compact objects prime targets to search for ADM. In this work, we use Bayesian inference to…
The scaling relation between stellar mass ($M_{*}$) and physical effective radius ($r_{e}$) has been well-studied using wide spectroscopic surveys. However, these surveys suffer from severe surface brightness incompleteness in the dwarf…
We extract cosmological information from the anisotropic power spectrum measurements from the recently completed Baryon Oscillation Spectroscopic Survey (BOSS), extending the concept of clustering wedges to Fourier space. Making use of new…
We evaluate the feasibility of Bose-Einstein condensate stars (BECS) as models for the interior of neutron stars. BECS are compact objects composed of bosons, formed through the spin-parallel pairing of neutrons. Here, we utilize the…
Given the incomplete sampling of spatial frequencies by radio interferometers, achieving precise restoration of astrophysical information remains challenging. To address this ill-posed problem, compressive sensing(CS) provides a robust…
Gravitational waves from merging binary neutron stars carry characteristic information about their astrophysical properties, including masses and tidal deformabilities, that are needed to infer their radii. In this study, we use Bayesian…
We studied the properties of dark matter admixed-neutron stars (DMANS), considering fermionic dark matter (DM) that interacts gravitationally with hadronic matter (HM). Using relativistic mean-field equations of state (EoSs) for both…
At present, the only experimental access to the properties of cold, dense strongly interacting matter is provided by astrophysical observations. Neutron stars are the only known systems in the Universe that reach densities several times…
The swift progression of machine learning (ML) has not gone unnoticed in the realm of statistical mechanics. ML techniques have attracted attention by the classical density-functional theory (DFT) community, as they enable discovery of…
We derive constraints on cosmological parameters and tests of dark energy models from the combination of baryon acoustic oscillation (BAO) measurements with cosmic microwave background (CMB) and Type Ia supernova (SN) data. We take…
We propose a new Bayesian framework to infer the neutron star equation of state (EOS) from mass and radius observations and neutron matter theory by defining priors that directly parameterize mass-radius space instead of pressure-energy…