activity
20182020
collaborators

5 papers

nucl-th2020

Structure of Quark Star: A Comparative Analysis of Bayesian Inference and Neural Network Based Modeling

Silvia Traversi, Prasanta Char

In this work, we compare two powerful parameter estimation methods namely Bayesian inference and Neural Network based learning to study the quark matter equation of state with cons…

astro-ph.HE2020

Bayesian Inference of Dense Matter Equation of State within Relativistic Mean Field Models using Astrophysical Measurements

Silvia Traversi, Prasanta Char, Giuseppe Pagliara

We present a Bayesian analysis to constrain the equation of state of dense nucleonic matter by exploiting the available data from symmetric nuclear matter at saturation and from ob…

astro-ph.HE2019

Merger of compact stars in the two-families scenario

Roberto De Pietri, Alessandro Drago, Alessandra Feo +4

We analyse the phenomenological implications of the two-families scenario on the merger of compact stars. That scenario is based on the coexistence of both hadronic stars and stran…

astro-ph.HE2018

The merger of two compact stars: a tool for dense matter nuclear physics

Alessandro Drago, Giuseppe Pagliara, Sergei B. Popov +2

We discuss the different signals, in gravitational and electromagnetic waves, emitted during the merger of two compact stars. We will focus in particular on the possible contraints…

astro-ph.HE2018

A multi-messenger analysis of neutron star mergers

Alessandro Drago, Giuseppe Pagliara, Silvia Traversi

The merger of two neutron stars is a very complex process. In order to disentangle the various steps through which it takes place it is mandatory to examine all the signals we can…