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Cambridge University Press, Publications of the Astronomical Society of Australia, (38), 2021

DOI: 10.1017/pasa.2021.19

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Processing GOTO survey data with the Rubin Observatory LSST Science Pipelines II: Forced Photometry and lightcurves

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Data provided by SHERPA/RoMEO

Abstract

AbstractWe have adapted the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) Science Pipelines to process data from the Gravitational-wave Optical Transient Observer (GOTO) prototype. In this paper, we describe how we used the LSST Science Pipelines to conduct forced photometry measurements on nightly GOTO data. By comparing the photometry measurements of sources taken on multiple nights, we find that the precision of our photometry is typically better than 20 mmag for sources brighter than 16 mag. We also compare our photometry measurements against colour-corrected Panoramic Survey Telescope and Rapid Response System photometry and find that the two agree to within 10 mmag (1$σ$) for bright (i.e.,$∼ 14{\rm th} \mathrm{mag}$) sources to 200 mmag for faint (i.e.,$∼ 18{\rm th} \mathrm{mag}$) sources. Additionally, we compare our results to those obtained by GOTO’s own in-house pipeline,gotophoto, and obtain similar results. Based on repeatability measurements, we measure a$5σ$L-band survey depth of between 19 and 20 magnitudes, depending on observing conditions. We assess, using repeated observations of non-varying standard Sloan Digital Sky Survey stars, the accuracy of our uncertainties, which we find are typically overestimated by roughly a factor of two for bright sources (i.e.,$< 15{\rm th} \mathrm{mag}$), but slightly underestimated (by roughly a factor of 1.25) for fainter sources ($> 17{\rm th} \mathrm{mag}$). Finally, we present lightcurves for a selection of variable sources and compare them to those obtained with the Zwicky Transient Factory and GAIA. Despite the LSST Software Pipelines still undergoing active development, our results show that they are already delivering robust forced photometry measurements from GOTO data.