astroglam 0.1.0

A code to leverage ALMA and JWST data to infer the gas density, metallicity, and burstiness of galaxies.

General purpose and references

GLAM is a Python software that will allow you to derive the gas density, metallicity, and deviations from the Kennicutt-Schmidt relation of a galaxy with known star formation rate surface density (Sigma_SFR), known [CII] surface brightness, and known surface brightness of an ionized gas tracer (e.g. Halpha, [OIII]5007, [OIII]88um, ...). Details on the rationale, the model implementation, and on the equations are discussed in the following papers:

• Vallini et al. 2021
• Vallini et al. 2020
• Ferrara et al. 2019

Requirements

The code is tested for Python >3.9. It requires Pyneb, emcee, corner.

Acknowledging this code in Scientific Publications

@ARTICLE{Ferrara:2019,
       author = { {Ferrara}, A. and {Vallini}, L. and {Pallottini}, A. and {Gallerani}, S. and {Carniani}, S.
                 and {Kohandel}, M. and {Decataldo}, D. and {Behrens}, C.},
        title = "{A physical model for [C II] line emission from galaxies}",
      journal = {\mnras},
         year = 2019,
        month = oct,
       volume = {489},
       number = {1},
        pages = {1-12},
          doi = {10.1093/mnras/stz2031},
archivePrefix = {arXiv},
       eprint = {1908.07536},
 primaryClass = {astro-ph.GA},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2019MNRAS.489....1F},
   }

@ARTICLE{Vallini2021,
       author = {{Vallini}, L. and {Ferrara}, A. and {Pallottini}, A. and {Carniani}, S. and {Gallerani}, S.},
        title = "{High [OIII]/[CII] surface brightness ratios trace early starburst galaxies}",
      journal = {arXiv e-prints},
     keywords = {Astrophysics - Astrophysics of Galaxies},
         year = 2021,
        month = jun,
          eid = {arXiv:2106.05279},
        pages = {arXiv:2106.05279},
archivePrefix = {arXiv},
       eprint = {2106.05279},
 primaryClass = {astro-ph.GA},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2021arXiv210605279V},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System},
}

Funding

This work is supported by the ERC Advanced Grant INTERSTELLAR H2020/740120 (PI: Ferrara).

Part of the work of LV has been supported by funding from the EU Horizon 2020 research and innovation program under the Marie Sklodowska-Curie Grant agreement No. 746119.