lenstronomy-metals-notebooks
Tutorials for using lenstronomy on light-weighted data, such as metallicities. Paper coming soon! Link to be put here!
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Repository
Tutorials for using lenstronomy on light-weighted data, such as metallicities. Paper coming soon! Link to be put here!
Basic Info
- Host: GitHub
- Owner: astrobenji
- License: gpl-3.0
- Language: Jupyter Notebook
- Default Branch: main
- Size: 422 KB
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- Stars: 1
- Watchers: 1
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Metadata Files
README.md
lenstronomy-metals-notebooks
A compliment Jupyter notebook to Metha et al. 2024
Hello researcher! I'm Benji Metha, one of the developers for Lenstronomy's tracer module. This Notebook contains a tutorial for using lenstronomy on light-weighted galaxy data, such as metallicity maps.
To make it work, you need three things:
- Observations of the light distribution of the system (It's also fine to use a bright emission line, such as Hα).
- Observations of the 2D metallicity distribution of the system (or another light-weighted property of the galaxy, such as velocity or stellar age), with uncertainties at all points.
- An estimate of the point spread function of the telescope.
This approach offers two benefits over a traditional approach: Firstly, it corrects for the effects of PSF smearing. Secondly, it allows asymmetric models to be fit to metallicity profiles that do not appear to be radially symmetric.
For more details on the lenstronomy package and for citation purposes, you can find the two lenstronomy introductory papers here:
https://ui.adsabs.harvard.edu/abs/2018PDU....22..189B/abstract
https://ui.adsabs.harvard.edu/abs/2021JOSS....6.3283B/abstract
To install lenstronomy, which contains the tracer module that this tutorial covers, follow https://github.com/lenstronomy.
If you have any questions, please reach out! I am friendly and approachable!
methab (at) student.unimelb.edu.au
:)
Owner
- Name: Benjamin Metha
- Login: astrobenji
- Kind: user
- Company: University of Melbourne
- Repositories: 1
- Profile: https://github.com/astrobenji
Studying a PhD in Astronomy at the University of Melbourne. Programming is supposed to be fun!
Citation (CITATION.cff)
# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!
cff-version: 1.2.0
title: lenstronomy_tracer_module
message: >-
If you use this software, please cite it using the
metadata from this file.
type: software
authors:
- given-names: Benjamin Andrew
family-names: Metha
email: methab@student.unimelb.edu.au
affiliation: University of Melbourne
orcid: 'https://orcid.org/0000-0002-8632-6049'
- given-names: Simon
family-names: Birrer
orcid: 'https://orcid.org/0000-0003-3195-5507'
affiliation: Stony Brook University
email: simon.birrer@stonybrook.edu
identifiers:
- type: doi
value: 10.1093/rasti/rzae010
description: 'https://doi.org/10.1093/rasti/rzae010'
- type: url
value: 'https://arxiv.org/abs/2403.08175'
description: "\tarXiv:2403.08175"
abstract: >-
Historically, metallicity profiles of galaxies have been
modelled using a radially symmetric, two-parameter linear
model, which reveals that most galaxies are more
metal-rich in their central regions than their outskirts.
However, this model is known to yield inaccurate results
when the point-spread function (PSF) of a telescope is
large. Furthermore, a radially symmetric model cannot
capture asymmetric structures within a galaxy. In this
work, we present an extension of the popular
forward-modelling python package LENSTRONOMY, which allows
the user to overcome both of these obstacles. We
demonstrate the new features of this code base through two
illustrative examples on simulated data. First, we show
that through forward modelling, LENSTRONOMY is able to
recover accurately the metallicity gradients of galaxies,
even when the PSF is comparable to the size of a galaxy,
as long as the data is observed with a sufficient number
of pixels. Additionally, we demonstrate how LENSTRONOMY is
able to fit irregular metallicity profiles to galaxies
that are not well-described by a simple surface brightness
profile. This opens up pathways for detailed
investigations into the connections between morphology and
chemical structure for galaxies at cosmological distances
using the transformative capabilities of JWST. Our code is
publicly available and open source, and can also be used
to model spatial distributions of other galaxy properties
that are traced by its surface brightness profile
keywords:
- Software
- Data Methods
- 'ISM: abundances'
- 'galaxies: abundance'
license: CC-BY-4.0