Coder Social home page Coder Social logo

chunhuangphy / eos_inference Goto Github PK

View Code? Open in Web Editor NEW
14.0 2.0 3.0 6.25 MB

An open-source package for neutron star whole workflow Bayesian nference constraining Neutron star EOS package

Home Page: https://chunhuangphy.github.io/EoS_inference/

License: MIT License

Python 6.61% Jupyter Notebook 93.24% Makefile 0.07% Batchfile 0.09%
astronomy baysian-inference equation-of-state neutron-star tov-solver

eos_inference's Introduction

About The Project

  1. Dealing with complex Relativistic Mean field (RMF) theory to generate Equation of State (EOS) of neutron star. (EOSgenerators Package)
  2. Solves the Tolman-Oppenheimer-Volkoff equation for a spherically symmetric compact object out of given equation of state of neutron star. (TOVsolver Package)
  3. Implementing Neutron state EOS inference by Nested Sampling, draw constraints from Nuclear experiments, Neutron star mass (and/or) radius observations (from X-ray timing and/or radio timing) (and/or) Tidal measurement from Gravitational wave detection. That all workflow is inside this folder. (InferenceWorkflow Package)

Project papers list based these package: (Please consider cite them, if you are using this package)

[1]. [Huang, C., Raaijmakers, G., Watts, A. L., Tolos, L., and Providência, C., “Constraining fundamental nuclear physics parameters using neutron star mass-radius measurements I: Nucleonic models”,Monthly Notices of the Royal Astronomical Society,2024, 10.1093/mnras/stae844,529, https://academic.oup.com/mnras/article/529/4/4650/7634362

- check this project website: https://chunhuangphy.github.io/EoS_inference/

CompactObject-TOV package website

Inlcudes

  1. Routine to check a valid equation of state input
  2. Return the mass, radius, and tidal deformability, and compute the corresponding speed of sound.
  3. Sample TOV solver Notebook, Sample RMF Equation of state solver Notebook and Sample Analysis Notebook on Equation of state Inference and tutorial on the github to show off what we can do currently and how to use our code. (please read them before you start to work on your own project, to familiar with the coding routine.)
  4. Test cases and documentation

v.1.3 new features:

  1. Added computation function of generating Relativistic mean field theory(RMF) model EOS functionality. Defined two files fastRMF_EOS and RMF_EOS, which the fastRMF_EOS is speed up by numba, which need gcc compiler, could be hard to implement in windows, so we leave the options for users.

v.1.5 new features:

  1. Added Whole workflow of Bayesian inference of neutron star equation of state. Include defining prior by InferenceWorkflow.prior, which included two types: flat distribution and gaussian type. Include defining liklihood generated from nuclear and astrophysical constraint.

Installation

Below are commands to install and update the package as well as a link to pypi.

  1. Install package
    pip install CompactObject-TOV
  2. Update package
    pip install CompactObject-TOV --upgrade

When you call the package, if you need to do EoS computation just

import EOSgenerators

if you need TOV solver, just

import TOVsolver

if you need to do Bayesian inference, just

import InferenceWorkflow

Physics notations

  1. CGS units is using here, for input quantity (equation of state): Pressure (P) and Energy density (rho). P is in $MeV/fm^{-3}$, same for rho. However, to omit a lot of the repeat of c,G. We set P as rescaled: (value in $MeV/fm^{-3}$)*G/c^4, for rho we have (value in $MeV/fm^{-3}$)*G/c^2
  2. Out put M in Mass of sun, radius in km, unit-less for spped of sound and tidal deformability.

License

Distributed under the MIT License. See LICENSE.txt for more information.

(back to top)

Contact

Project Link: [https://github.com/ChunHuangPhy/EoS_inference]

DOI

(back to top)

Acknowledgments

Use this space to list resources you find helpful and would like to give credit to. Here included a few of my favorites to kick things off! We would like to acknowledge the support of Code/Astro workshop to make this project happen, we all learned a lot from that 5 day intensive workshop.

Chun want to thank Professor Anna Watts, Dr. Geert Raaijmakers and Jeannie Kuijper for asistance on coding and help on providing me basic strategy of how to solve this problem.

(back to top)

eos_inference's People

Contributors

chunhuangphy avatar nwhitsett avatar osborn62 avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.