SpyDust 1.0.0

A code for modeling spinning dust radiation

SpyDust

SpyDust is an advanced Python package for modeling spinning dust radiation in astrophysical environments. Building upon previous models (the IDL SPDUST), SpyDust offers enhanced capabilities and corrections, making it a valuable tool for researchers in astrophysics and related fields.

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Features

• Comprehensive Grain Shape Modeling: Considers a wide range of grain geometries, providing corresponding grain dynamics, directional radiation fields, and angular momentum transports.

• Updated Physical Processes: Incorporates corrections and extensions, including updated expressions for the effects of electrical dipole radiation back-reaction and plasma drag on angular momentum dissipation.

• Parallisation: Functions can be run in parallel (implemented by mpi4py) by simply setting the corresponding keyword to True.

• SPDUST as is mode: Provides a submodule, SPDUST_as_is, which is exactly the full equivalent of the IDL spdust. Just in case the user wants to stick with the spdust simulation.

• Example notebooks: Provide some Jupyter notebooks to help users get started with this software package paper.

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Requirements

SpyDust requires Python 3.7 or higher (up to Python 3.9) and the following dependencies:

• numpy <= 2.0
• scipy
• numba
• logging
• mpi4py
• pandas

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Installation

You can install SpyDust using pip:

pip install SpyDust

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Usage

Import the package in your project and explore its functionalities for modeling spinning dust radiation. Data files required for computations are bundled with the package.

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Example usage:

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Resources

• Author: Zheng Zhang
• License: MIT License
• Paper: https://arxiv.org/abs/2412.03431 (Z Zhang and J Chluba 2024)

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History

• Version 1.0.0: Initial release of SpyDust, introducing comprehensive grain shape modeling, updated physical processes, and degeneracy analysis tools.

TODO (Future Versions)

• Get rid of numba. Use jax instead.
• Future upgrades will include features such as the SED fitting tool (based on perturbation statistics tools like moment expansion) and improve the treatment of the grain rotation distribution.

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Resources

• Author: Zheng Zhang
• License: MIT License
• Collaboration: SpyDust GitHub Collaboration
• ** Spdust Documentation**: We refer users to the website of spdust for better documentation of environmental parameters

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License

This project is licensed under the MIT License - see the LICENSE file for details.

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For a detailed understanding of the underlying models and theoretical background, refer to the publication: SpyDust: an improved and extended implementation for modeling spinning dust radiation.