Related papers: Finding Universal Relations using Statistical Data…
We calculate total masses and radii of neutron stars (NS) for pure neutron matter and nuclear matter in beta-equilibrium. We apply a relativistic nuclear matter equation of state (EOS) derived from Dirac-Brueckner-Hartree-Fock (DBHF)…
We discuss deep learning inference for the neutron star equation of state (EoS) using the real observational data of the mass and the radius. We make a quantitative comparison between the conventional polynomial regression and the neural…
Binary neutron star mergers are studied using nonlinear 3+1 numerical relativity simulations and the analytical effective-one-body (EOB) model. The EOB model predicts quasiuniversal relations between the mass-rescaled gravitational wave…
We obtain a universal relation for the neutron star maximum mass arising from a particular combination of the saturation density ($n_0$), the effective mass ($m^*$), and (when present) the vector meson self-coupling constant ($\zeta$)…
Millisecond pulsars are rapidly rotating neutron stars where general relativity plays a strong role in the propagation of light from the neutron star to observer. The observed X-ray pulse shapes carry information on the mass, radius and…
We present a unified framework to derive fundamental stellar parameters by combining all available observational and theoretical information for a star. The algorithm relies on the method of Bayesian inference, which for the first time…
In this letter, we present a new, weakly model-dependent, test for ``standard" equations of state (EoS) models that disfavor sharp and strong phase-transitions, by using neutron star mass and radius observations. We show the radii of two…
The accurate classification of galaxies in large-sample astrophysical databases of galaxy clusters depends sensitively on the ability to distinguish between morphological types, especially at higher redshifts. This capability can be…
We use covariant density functional theory to obtain the equation of state (EoS) of matter in compact stars at non-zero temperature, including the full baryon octet as well as the $\Delta(1232)$ resonance states. Global properties of hot…
We present a neural network classification model for detecting the presence of hyperonic degrees of freedom in neutron stars. The models take radii and/or tidal deformabilities as input and give the probability for the presence of hyperons…
We exploit the great potential offered by Bayesian Neural Networks (BNNs) to directly decipher the internal composition of neutron stars (NSs) based on their macroscopic properties. By analyzing a set of simulated observations, namely NS…
Neutron star properties depend on both nuclear physics and astrophysical processes, and thus observations of neutron stars offer constraints on both large-scale astrophysics and the behavior of cold, dense matter. In this study, we use…
Multivariate correlation analysis plays a key role in various fields such as statistics and big data analytics. In this paper, it is presented a new non-parametric association measure between more than two variables based on the concept of…
We systematically study the observable properties of dark-matter admixed neutron stars, employing a realistic nuclear EOS in combination with self-interacting fermionic dark matter respecting constraints on the self-interaction cross…
Various statistical issues relevant to searches for new physics or to parameter determination in analyses of data in neutrino experiments are briefly discussed.
The distribution of masses for neutron stars is analyzed using the Bayesian statistical inference, evaluating the likelihood of proposed gaussian peaks by using fifty-four measured points obtained in a variety of systems. The results…
Accurate modeling of the neutron star crust is essential for interpreting multimessenger observations and constraining the nuclear equation of state (EoS). However, standard phenomenological EoS models often rely on heuristic extrapolations…
In recent years, modified gravity theories have gained significant attention as potential replacements for the general theory of relativity. Neutron stars, which are dense compact objects, provide ideal astrophysical laboratories for…
We use neutron star mass and radius measurements to constrain the spontaneous scalarization phenomenon in scalar-tensor theories using Bayesian analysis. Neutron star structures in this scenario can be significantly different from the case…
Correlation remains to be one of the most widely used statistical tools for assessing the strength of relationships between data series. This paper presents a novel compositional correlation method for detecting linear and nonlinear…