204 citations · 1.1k across the 45 of their papers we have counts for
5 papers · 1 filter
Detecting Hyperons in neutron stars -- a machine learning approach
Valéria Carvalho, Márcio Ferreira, Constança Providência
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…
Hybrid Star Properties with NJL and MFTQCD Model: A Bayesian Approach
Milena Albino, Tuhin Malik, Márcio Ferreira +1
The composition of the core of neutron stars (NS) is still under debate. One possibility is that because of the high densities reached in their cores, matter could be deconfined in…
Constraining neutron star matter from the slope of the mass-radius curves
Márcio Ferreira, Constança Providência
We analyse the implications of information about local derivatives from the mass-radius diagram in neutron star matter. It is expected that the next generation of gravitational wav…
Detecting the third family of compact stars with normalizing flows
Valéria Carvalho, Márcio Ferreira, Constança Providência +1
We explore the anomaly detection framework based on Normalizing Flows (NF) models introduced in \cite{PhysRevC.106.065802} to detect the presence of a large (destabilising) dense m…
From NS observations to nuclear matter properties: a machine learning approach
Valéria Carvalho, Márcio Ferreira, Constança Providência
This study is devoted to the inference problem of extracting the nuclear matter properties directly from a set of mass-radius observations. We employ Bayesian neural networks (BNNs…