The nucleardatapy toolkit for simple access to experimental nuclear data, astrophysical observations, and theoretical predictions

Abstract

Systematic comparisons across theoretical predictions for the properties of dense matter, nuclear physics data, and astrophysical observations (also called meta-analyses) are performed. Existing predictions for symmetric nuclear and neutron matter properties are considered, and they are shown in this paper as an illustration of the present knowledge. Asymmetric matter is constructed assuming the isospin asymmetry quadratic approximation. It is employed to predict the pressure at twice saturation energy-density based only on nuclear-physics constraints, and we find it compatible with the one from the gravitational-wave community. To make our meta-analysis transparent, updated in the future, and to publicly share our results, the Python toolkit \texttt{nucleardatapy} is described and released here. Hence, this paper accompanies \texttt{nucleardatapy}, which simplifies access to nuclear-physics data, including theoretical calculations, experimental measurements, and astrophysical observations. This Python toolkit is designed to easily provide data for: i) predictions for uniform matter (from microscopic or phenomenological approaches); ii) correlation among nuclear properties induced by experimental and theoretical constraints; iii) measurements for finite nuclei (nuclear chart, charge radii, neutron skins or nuclear incompressibilities, etc.) and hypernuclei (single particle energies); and iv) astrophysical observations. This toolkit provides data in a unified format for easy comparison and provides new meta-analysis tools. It will be continuously developed, and we expect contributions from the community in our endeavor.

Figures (59)

• Figure 1: FFG energy in NM ($\delta=1$) and in SM ($\delta=0$) (top) and FFG pressure in NM and SM (bottom) as a function of the density $n_\mathrm{nuc}$ (left) and the Fermi momentum $k_{F}$ (right). Lines (Symbols) show the relativistic (non-relativistic) FFG results. The nucleon mass is fixed to three constant values: $m_N$, $0.4m_N$, and $0.6m_N$. This figure is generated with matter_setupFFGNuc_plot.py.
• Figure 2: FFG EoS: pressure $p$ (top) and sound speed $(c_s/c)^2$ (bottom) for SM (solid blue lines) and NM (dashed yellow lines) function of the energy density $\epsilon$. Circles (lines) show the non-relativistic (relativistic) FFG results. This figure is generated with matter_setupFFGNuc_plot.py.
• Figure 3: Leptonic FFG: energy per particle for electrons (solid) and muons (dashed) (top) and pressure (bottom). We have considered three scenarios for muons: 10% of the electron density (yellow), 20% (green) and 50% (red). This figure is generated with matter_setupFFGLep_plot.py.
• Figure 4: Internal energy per nucleon in neutron matter (NM) $E_{\mathrm{NM}}^\mathrm{int}$ (top) and $E_{\mathrm{NM}}^\mathrm{int}$ over the non-relativistic free Fermi gas energy (bottom) as a function of the density (left) and the Fermi momentum (right) for the variational models (FP and APR) available in nuda toolkit. The reference band detailed in Sec. \ref{['sec:unif:band']} is also shown (pink area). We have applied here and in the next figures a selection of the models: all those passing through the reference band are shown in solid lines, the ones not passing through it in dashed lines. Since all models shown in this figure pass through the reference band, they are all shown with solid lines. Figure generated with matter_setupMicro_plot.py.
• Figure 5: Same as Fig. \ref{['fig:micro:var:e2a']} for BHF23 models with 2+3BF available in nuda toolkit. Figure generated with matter_setupMicro_plot.py.