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: AstroPhot
message: >-
  Fitting Everything Everywhere All at Once in Astronomical
  Images
type: software
authors:
  - given-names: Connor
    family-names: Stone
    email: connorstone628@gmail.com
    affiliation: Université de Montréal
    orcid: 'https://orcid.org/0000-0002-9086-6398'
  - given-names: Stéphane
    family-names: Courteau
    affiliation: Queen's University
  - given-names: Jean-Charles
    family-names: Cuillandre
    affiliation: Université de Paris
    orcid: 'https://orcid.org/0000-0002-3263-8645'
  - given-names: Yashar
    family-names: Hezaveh
    affiliation: Univeristé de Montréal
    orcid: 'https://orcid.org/0000-0002-8669-5733'
  - orcid: 'https://orcid.org/0000-0003-3544-3939'
    given-names: Laurence
    family-names: Perreault-Levasseur
    affiliation: Université de Montréal
  - given-names: Nikhil
    family-names: Arora
    affiliation: New York University Abu Dhabi
    orcid: 'https://orcid.org/0000-0002-3929-9316'
identifiers:
  - type: doi
    value: 10.1093/mnras/stad2477
    description: MNRAS
repository-code: 'https://github.com/Autostronomy/AstroPhot'
url: 'https://autostronomy.github.io/AstroPhot/'
abstract: >-
  We present AstroPhot, a fast, powerful, and user-friendly
  Python based astronomical image photometry solver.
  AstroPhot incorporates automatic differentiation and GPU
  (or parallel CPU) acceleration, powered by the machine
  learning library PyTorch. Everything: AstroPhot can fit
  models for sky, stars, galaxies, PSFs, and more in a
  principled Chi^2 forward optimization, recovering Bayesian
  posterior information and covariance of all parameters.
  Everywhere: AstroPhot can optimize forward models on CPU
  or GPU; across images that are large, multi-band,
  multi-epoch, rotated, dithered, and more. All at once: The
  models are optimized together, thus handling overlapping
  objects and including the covariance between parameters
  (including PSF and galaxy parameters). A number of
  optimization algorithms are available including
  Levenberg-Marquardt, Gradient descent, and No-U-Turn MCMC
  sampling. With an object-oriented user interface,
  AstroPhot makes it easy to quickly extract detailed
  information from complex astronomical data for individual
  images or large survey programs.
keywords:
  - python
  - scientific computing
  - pytorch
  - photometry
  - astronomy
license: GPL-3.0
commit: 543dd68
version: 0.16.0
date-released: '2023-08-23'