Nuclear Theory·nucl-th

Wednesday·March 23, 2022

10 papers—4 primary·6 cross-listed

01
Multicomponent relativistic dissipative fluid dynamics from the Boltzmann equation
Jan A. Fotakis🇩🇪 · Etele Molnár🇩🇪 · Harri Niemi🇩🇪 · Carsten Greiner🇩🇪 · Dirk H. Rischke🇩🇪
We derive multicomponent relativistic second-order dissipative fluid dynamics from the Boltzmann equations for a reactive mixture of $N_{spec}$ particle species with $N_{q}$ intrinsic quantum numbers (e.g. electric charge, baryon number, and strangeness) using the method of moments. We obtain the continuity equations for multiple conserved charges as well as the conservation equations for the total energy and momentum in the single-fluid approximation. These $4 + N_{q}$ conservation laws are closed by deriving the second-order equations of motion for the dissipative quantities in the $(10 + 4 N_{q})$ -moment approximation. The resulting fluid-dynamical equations are formally similar to those of a single-component system, but feature different thermodynamic relations and transport coefficients. We derive general relations for all transport coefficients and compute them explicitly in the ultrarelativistic limit.
nucl-thhep-phphysics.flu-dynPRD(2022)·54 citations
02
Confronting a set of Skyrme and $χ_{E F T}$ predictions for the crust of neutron stars
Guilherme Grams🇫🇷 · Jérôme Margueron🇫🇷 · Rahul Somasundaram🇫🇷 · Sanjay Reddy🇺🇸
With the improved accuracy of neutron star observational data, it is necessary to derive new equation of state where the crust and the core are consistently calculated within a unified approach. For this purpose we describe non-uniform matter in the crust of neutron stars employing a compressible liquid-drop model, where the bulk and the neutron fluid terms are given from the same model as the one describing uniform matter present in the core. We then generate a set of fifteen unified equations of state for cold catalyzed neutron stars built on realistic modelings of the nuclear interaction, which belongs to two main groups: the first one derives from the phenomenological Skyrme interaction and the second one from $χ_{E F T}$ Hamiltonians. The confrontation of these model predictions allows us to investigate the model dependence for the crust properties, and in particular the effect of neutron matter at low density. The new set of unified equations of state is available at the CompOSE repository.
nucl-thastro-ph.HEEPJA(2022)·23 citations
03
Hybrid stars and QCD phase transition with a NJL-like model
Bing-Jun Zuo🇨🇳 · Yong-Feng Huang🇨🇳 · Hong-Tao Feng🇨🇳
In this paper, we introduce a self-consistent mean field approximation to study the QCD phase transition and the structure of hybrid stars within the framework of NJL model. In our practice, a phenomenological parameter $α$ is introduced, which reflects the weights of "direct" channel and "exchange" channel under a finite chemical potential. The mass-radius relation is obtained by solving the Tolman-Oppenheimer-Volkoff equation using a crossover equation of state (EOS). We calculate the density distribution in a two solar-mass hybrid star to show the effects of different parameters. We also calculate the tidal Love number $k_{2}$ and the deformability $(Λ)$ . It is found that the stiffness of the EOS increases with $α$ , which allows us to obtain a hybrid star with a maximum mass of 2.40 solar-mass through our model. The observation of over 2.06 solar-mass neutron stars may indicates that the chiral transition may be a crossover on the whole $T - μ$ plane.
nucl-thastro-ph.HEPRD(2022)·6 citations
04
Machine learning light hypernuclei
Isaac Vidana🇮🇹
We employ a feed-forward artificial neural network to extrapolate at large model spaces the results of {\it ab-initio} hypernuclear No-Core Shell Model calculations for the $Λ$ separation energy $B_{Λ}$ of the lightest hypernuclei, $_{Λ}^{3}$ H, $_{Λ}^{4}$ H and $_{Λ}^{4}$ He, obtained in computationally accessible harmonic oscillator basis spaces using chiral nucleon-nucleon, nucleon-nucleon-nucleon and hyperon-nucleon interactions. The overfitting problem is avoided by enlarging the size of the input dataset and by introducing a Gaussian noise during the training process of the neural network. We find that a network with a single hidden layer of eight neurons is sufficient to extrapolate correctly the value of the $Λ$ separation energy to model spaces of size $N_{ma x} = 100$ . The results obtained are in agreement with the experimental data in the case of $_{Λ}^{3}$ H and the $0^{+}$ state of $_{Λ}^{4}$ He, although they are off of the experiment by about $0.3$ MeV for both the $0^{+}$ and $1^{+}$ states of $_{Λ}^{4}$ H and the $1^{+}$ state of $_{Λ}^{4}$ He. We find that our results are in excellent agreement with those obtained using other extrapolation schemes of the No-Core Shell Model calculations, showing this that an ANN is a reliable method to extrapolate the results of hypernuclear No-Core Shell Model calculations to large model spaces.
nucl-thNPA(2023)·12 citations

Affiliations

first authorsco-authorsvia INSPIRE

Multicomponent relativistic dissipative fluid dynamics from the Boltzmann equation

Confronting a set of Skyrme and χEFT​ predictions for the crust of neutron stars

Hybrid stars and QCD phase transition with a NJL-like model

Machine learning light hypernuclei

Affiliations

Confronting a set of Skyrme and $χ_{E F T}$ predictions for the crust of neutron stars