Modified Version of "Stardust": Composite Template Fitting Software

For the original version, please see here and Kokorev et al. 2021.

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This Modified stardust code allows AGN fluxes as additional constraints.

The original code fit the model SED F_model=F₁+F₂+F₃ to the data SED F_tot by minimizing ||F_tot - F_model||₂, where

  F₁=UV/Optical stellar light templates or Shen et al. 2016 quasar temperates
  F₂=AGN heated dust in the MIR
  F₃=IR dust reprocessed stellar light in the NIR-FIR

When total flux F_tot is decomposed into the point source (AGN) F_AGN and rest F_{host galaxy} by image decomposition, this modified code can include this additional constraint by providing F_AGN as AGN_EXTRA_BANDS_FILE and setting AGN_EXTRA_BANDS=1 in the config file (similar to setting EXTRA_BANDS_FILE and EXTRA_BANDS=1).

  When the stellar light templates are chosen, the code minimizes ||(F_tot-F_model)+(F_AGN - F₂)||₂.

  When the quasar templates are chosen, the code minimizes ||(F_tot-F_model)+(F_AGN - F₁ - F₂)||₂.

See descriptions: Tsukui, Wisnioski, Krumholz and Battisti, 2023

Usage

See here, for a quick example of how to use it and reproduce the result of Tsukui et al. 2023.

Contacts

Takafumi Tsukui: tsukuitk23@gmail.com

README of the original code below (The same requirements and installation apply)

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Stardust is a Python package designed to extract galaxy properties by fitting their multiwavelength data to a set of linearly combined templates.

This algorithm brings together three different families of templates:

1. UV+Optical emission from dust unobscured stellar light
2. AGN heated dust in the MIR
3. IR dust reprocessed stellar light in the NIR-FIR

One of the features of Stardust is that the template fitting does not rely on energy balance. As a result, the total luminosity of dust obscured and dust unobscured stellar light do not rely on each other, and it is possible to fit objects (e.g. SMGs) where the energy balance approach might not be necessarily applicable. A detailed description of Stardust and its first application is presented in Kokorev et al. 2021.

Requirements

python
python>=3.9.0
numpy
scipy
matplotlib
astropy
multiprocess
tqdm

Installation

For MacOS users, it is recommended to create a separate Python 3.6.10 environment with miniconda. See instructions here.

You can then pull Stardust and install it with pip.

$ git clone https://github.com/VasilyKokorev/stardust.git
$ cd stardust
$ pip install .

Usage

The primary use of this code is to extract the parameters from the infrared photometry. The program also has the ability to fit AGN and Stellar emission templates if the user desires to do so. It is recommended to use this code within a Jupyter notebook.

See here for a quick example of how to fit a catalogue.

An example dataset, a subset from the COSMOS Super-Deblended Catalogue 2 (Jin+18) along with the example configuration files are provided in the example folder.

See the quickstart guide and docs folder for more detailed instructions.

Acknowledgements

Filter curves are adopted from eazy-py by Gabe Brammer.

Troubleshooting

1. The module does not install: If you are on Linux, try using Python 3.9.1 instead.

Contacts

Vasily Kokorev: vasily.kokorev.astro@gmail.com / kokorev@astro.rug.nl