Photometry Pipeline Documentation

Introduction

The Photometry Pipeline (PP) is a Python software package for automated photometric analysis of imaging data from small to medium-sized observatories. It uses Source Extractor and SCAMP to register and photometrically calibrate images based on catalogs that are available online; photometry is measured using Source Extractor aperture photometry. PP has been designed for asteroid observations, but can be used with any kind of imaging data.

Scope and Applicability

PP has been designed to provide automated photometry for the majority of data coming from small to medium-sized observatories. It is not intended to provide high-accuracy photometry, nor is it designed to work on extremely sparse or crowded fields. PP requires a field of view of a few arcminutes to ensure that sufficient background stars are available for registration and photometric calibration. For a field several arcminutes across, calibrated photometric uncertaintes are usually better than 0.05 mag, if sufficient non-saturated background stars with cataloged brightness are available. Feel free to try PP on your data, but please be aware that it has its limitations.

The following features are currently available as part of PP:

  • automated aperture photometry based on a curve-of-growth analysis
  • photometric calibration in ugriz, BVRI, JHK based on catalog coverage
  • full support of moving target photometry
  • target identification based on tabulated positions for fixed targets and moving targets, target identifier for moving targets
  • support of Gaia (DR1) astrometry for image registration
  • Python 2 and 3 compatibility (thanks to boada)

Future versions of the pipeline will support newly available catalogs for astrometry and photometry (e.g., GAIA DR2). If you are interesting in using PP for a specific task, let me know!

License and Contact

The Photometry Pipeline is distributed under the GNU GPLv3 license.

Copyright (C) 2016 Michael Mommert

Feel free to contact me in case of questions or suggestions: michael . mommert (at) nau . edu

Acknowledgments

If you are using PP for your research, please acknowledge PP by citing

  • Mommert, M. 2017, PHOTOMETRYPIPELINE: An Automated Pipeline for Calibrated Photometry, Astronomy & Computing, 18, 47.

PP is supported by NASA grants NNX15AE90G and NNX14AN82G and has been developed in the framework of the Mission Accessible Near-Earth Objects Survey (MANOS).

Indices and tables