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https://github.com/3fon3fonov/migration_ns

https://github.com/3fon3fonov/migration_ns

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Repository

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  • Host: GitHub
  • Owner: 3fon3fonov
  • Language: Fortran
  • Default Branch: main
  • Size: 1.51 MB
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Created 12 months ago · Last pushed 9 months ago
Metadata Files
Readme

README.md

Planet Migration with Nested Sampling

Overview

This project implements planet migration simulations using nested sampling via Dynesty. It explores the parameter space efficiently to model planetary migration scenarios and fits observational data using Bayesian inference.

Features

  • Simulates planet migration dynamics (e.g., swift_symba)
  • Uses Dynesty for dynamic nested sampling to infer posterior distributions
  • Supports optional parallelization for performance gains
  • Generates corner plots of posterior distributions and sampling diagnostics

Dependencies

Install the necessary Python packages via pip:

bash pip install numpy scipy matplotlib emcee corner dynesty pathos dill

You'll also need an installed Fortran compiler (gfortran) for the migration integrators (swift_symba, etc.).

File Structure

  • compute_mig_nest.py: Main script for running migration nested sampling
  • dynesty_2_0/: Forked Dynesty sampler code
  • swift/: Compiled Fortran integrator libraries (e.g. libswift.a)
  • examples/: Sample configurations and run scripts
  • README.md: This documentation

Usage

Run the main sampling script:

bash python3 compute_mig_nest.py

By default, this will execute migration models with nested sampling. You can configure:

  • Input parameters via command-line flags or configuration files
  • Sampling options (number of live points, stopping criteria)
  • Parallel settings using pathos.ProcessPool

Output includes posterior sample files and optional corner plots.

References

  • Speagle, J. S. (2020). DYNESTY: a dynamic nested sampling package for estimating Bayesian posteriors and evidences. MNRAS, 493(3), 3132–3158. doi:10.1093/mnras/staa278
  • Swift integrator code documentation

License

Open-source under the MIT License. Contributions and issues are welcome.

About

Developed by Trifon Trifonov.

Owner

  • Name: Trifon Trifonov
  • Login: 3fon3fonov
  • Kind: user
  • Location: Germany
  • Company: MPIA Heidelberg

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