rmf 0.1.1

Relativistic Mean Field package for neutron star and nuclear matter equation of state

Relativistic Mean Field

1. Purpose

This project provides the code to compute the equation of state (EoS) using Relativistic Mean Field (RMF) Theory. It can automatically generate the RMF coupling constants [ $g_\sigma$, $g_\omega$, $g_\rho$, $g_2$, $g_3$, $\Lambda_v$, $c_3$] based on input saturation properties [ $n_0$, $E$/ $A$, $E_{sym}$, $K_0$, $J_0$, $M^\ast$/ $M_{_N}$, $J_0$]. Using these coupling constants, the code can compute the EoS for neutron star matter or symmetric nuclear matter.

2. Installation

Using Pip

pip install rmf

or

git clone [e-mail]:zzhu-astro/RMF.git; cd RMF
pip install .

Build from Scratch

Clone the Repository

git clone [e-mail]:zzhu-astro/RMF.git; cd RMF

Environment Variable

To compile the project, you must set the HOME_MF environment variable. If you are currently in the root directory of RMF (e.g. $HOME/RMF), you can run:

export HOME_MF=`pwd`

Configuration File

To ensure Makefile works correctly, you need to specify the configurations in the config file (e.g. $HOME/macos_clang-config.mk). An example can be found at $HOME_TOV\macos_clang-config.mk, where the Clang compiler, library paths, includes directories and flags are defined. Once your configuration file is ready, compile the project by running:

make CONFIG=macos_clang-config.mk python

Python Package

Then run:

pip install .

This will install the Python package and automatically copy the librmf.so shared library you just built into the package directory.

3. Dependencies

1. C++ compiler - gcc or clang++ is recommended
2. GSL
3. Python3.9 or newer
4. JAX (Automatic differentiation)

4. Related Publications

See the references below for more details on the Relativistic Mean Field model:

1. Zhenyu Zhu, Ang Li, Jinniu Hu, Hong Shen: https://arxiv.org/abs/2305.16058
2. Zhenyu Zhu, Ang Li, Tong Liu: https://arxiv.org/abs/2211.02007
3. Zhenyu Zhu, Ang Li: https://arxiv.org/abs/1802.07441