4 research outputs found
Bayesian Inference of Phenomenological EoS of Neutron Stars with Recent Observations
The description of stellar interior remains as a big challenge for the
nuclear astrophysics community. The consolidated knowledge is restricted to
density regions around the saturation of hadronic matter , regimes where our nuclear models are successfully
applied. As one moves towards higher densities and extreme conditions up to
five to twenty times , little can be said about the microphysics of
such objects. Here, we employ a Markov Chain Monte Carlo (MCMC) strategy to
access the variability of polytropic three-pircewised models for neutron star
equation of state. With a fixed description of the hadronic matter, we explore
a variety of models for the high density regimes leading to stellar masses up
to . In addition, we also discuss the use of a Bayesian power
regression model with heteroscedastic error. The set of EoS from the Laser
Interferometer Gravitational-Wave Observatory (LIGO) was used as inputs and
treated as data set for testing case.Comment: Minor typo fixes in the title and few typos corrected in the text.
Added funding from Brookhave
Bayesian Exploration of Phenomenological EoS of Neutron/Hybrid Stars with Recent Observations
The description of the stellar interior of compact stars remains as a big challenge for the nuclear astrophysics community. The consolidated knowledge is restricted to density regions around the saturation of hadronic matter ρ0=2.8×1014gcm−3, regimes where our nuclear models are successfully applied. As one moves towards higher densities and extreme conditions up to the quark/gluons deconfinement, little can be said about the microphysics of the equation of state (EoS). Here, we employ a Markov Chain Monte Carlo (MCMC) strategy to access the variability at high density regions of polytropic piecewise models for neutron star (NS) EoS or possible hybrid stars, i.e., a NS with a small quark-matter core. With a fixed description of the hadronic matter for low density, below the nuclear saturation density, we explore a variety of models for the high density regimes leading to stellar masses near to 2.5M⊙, in accordance with the observations of massive pulsars. The models are constrained, including the observation of the merger of neutrons stars from VIRGO-LIGO and with the pulsar observed by NICER. In addition, we also discuss the possibility of the use of a Bayesian power regression model with heteroscedastic error. The set of EoS from the Laser Interferometer Gravitational-Wave Observatory (LIGO) was used as input and treated as the data set for the testing case
Towards a predictive HFB+QRPA framework for deformed nuclei: selected tools and technique
International audienceReliable predictions of the static and dynamic properties of a nucleus require a fully microscopic description of both ground and excited states of this complicated many-body quantum system. Predictive calculations are key to understanding such systems and are important ingredients for simulating stellar environments and for enabling a variety of contemporary nuclear applications. Challenges that theory has to address include accounting for nuclear deformation and the ability to describe medium-mass and heavy nuclei. Here, we perform a study of nuclear states in an Hartree-Fock-Bogoliubov (HFB) and Quasiparticle Random Phase Approximation (QRPA) framework that utilizes an axially-symmetric deformed basis. We present some useful techniques for testing the consistency of such calculations and for interpreting the results