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Published November 1, 2023 | Published
Journal Article Open

The Farmer: A Reproducible Profile-fitting Photometry Package for Deep Galaxy Surveys

Abstract

While space-borne optical and near-infrared facilities have succeeded in delivering a precise and spatially resolved picture of our Universe, their small survey area is known to underrepresent the true diversity of galaxy populations. Ground-based surveys have reached comparable depths but at lower spatial resolution, resulting in source confusion that hampers accurate photometry extractions. What once was limited to the infrared regime has now begun to challenge ground-based ultradeep surveys, affecting detection and photometry alike. Failing to address these challenges will mean forfeiting a representative view into the distant Universe. We introduce The Farmer: an automated, reproducible profile-fitting photometry package that pairs a library of smooth parametric models from The Tractor with a decision tree that determines the best-fit model in concert with neighboring sources. Photometry is measured by fitting the models on other bands leaving brightness free to vary. The resulting photometric measurements are naturally total, and no aperture corrections are required. Supporting diagnostics (e.g., χ 2) enable measurement validation. As fitting models is relatively time intensive, The Farmer is built with high-performance computing routines. We benchmark The Farmer on a set of realistic COSMOS-like images and find accurate photometry, number counts, and galaxy shapes. The Farmer is already being utilized to produce catalogs for several large-area deep extragalactic surveys where it has been shown to tackle some of the most challenging optical and near-infrared data available, with the promise of extending to other ultradeep surveys expected in the near future. The Farmer is available to download from GitHub (https://github.com/astroweaver/the_farmer) and Zenodo (https://doi.org/10.5281/zenodo.8205817).

Copyright and License

Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.

Acknowledgement

The authors thank Dustin Lang, Charles Steinhardt, Keith Horne, and Ranga-Ram Chary for helpful discussions.

Funding

The Cosmic Dawn Center (DAWN) is funded by the Danish National Research Foundation under grant No. 140. S.T., G.B., and J.W. acknowledge support from the European Research Council (ERC) consolidator grant funding scheme (project ConTExt, grant No. 648179). O.I. acknowledges the funding of the French Agence Nationale de la Recherche for the project "SAGACE." H.J.McC. acknowledges support from the PNCG. I.D. has received funding from the European Union's Horizon 2020 research and innovation program under the Marie SkÅ‚odowska-Curie grant agreement No. 896225. This research is partially funded by the Joint Survey Processing effort at IPAC/Caltech through NASA grant NNN12AA01C. The HST COSMOS program was supported through NASA grant HST-GO-09822. More information on the COSMOS survey is available at https://cosmos.astro.caltech.edu. This work used the CANDIDE computer system at the Institut d'Astrophysique de Paris supported by grants from the PNCG and the DIM-ACAV and maintained by S. Rouberol.

Code Availability

Software: numpy (van der Walt et al. 2011), matplotlib (Hunter 2007), astropy (Astropy Collaboration et al. 20132018), Source Extractor (Bertin & Arnouts 1996), PSFEx (Bertin 2013), SWarp (Bertin 2010), GalSim (Rowe et al. 2015), and The Tractor (Lang et al. 2016a).

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Additional details

Created:
September 3, 2024
Modified:
September 3, 2024