The Automated Photometry Of Transients (AutoPhOT) pipeline
S. J. Brennan, M. Fraser

TL;DR
AutoPhOT is an automated, Python-based pipeline for rapid, high-quality photometry of astronomical transients, capable of various photometric methods and calibration, suitable for ground-based optical and infrared images.
Contribution
AutoPhOT introduces a fully automated, dependency-free pipeline that performs comprehensive photometry and calibration for transients, streamlining analysis with minimal human input.
Findings
AutoPhOT's photometry aligns with DAOPHOT results.
It accurately reproduces published transient light curves.
Supports calibration against survey catalogs or local standards.
Abstract
We present the Automated Photometry Of Transients (AutoPhOT) package, a novel automated pipeline that is designed for rapid, publication-quality photometry of astronomical transients. AutoPhOT is built from the ground up using Python 3 - with no dependencies on legacy software. Capabilities of AutoPhOT include aperture and point-spread-function photometry, template subtraction, and calculation of limiting magnitudes through artificial source injection. AutoPhOT is also capable of calibrating photometry against either survey catalogues, or using a custom set of local photometric standards, and is designed primarily for ground-based optical and infrared images. We show that both aperture and point-spread-function photometry from AutoPhOT is consistent with commonly used software, for example DAOPHOT, and also demonstrate that AutoPhOT can reproduce published light curves for a selection…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAstronomical Observations and Instrumentation · Astronomy and Astrophysical Research · Adaptive optics and wavefront sensing
