II/381 PS1-PSC, Point Source Catalog (Miller+, 2021)
A morphological classification model to identify unresolved PanSTARRS1 sources:
I. Application in the ZTF real-time pipeline.
II. Update to the PS1 Point Source Catalog.
Miller A.A., Hall X.J., Tachibana Y.
<Publ. Astron. Soc. Pac. 133, 054502 (2021)>
=2024yCat.2381....0M 2024yCat.2381....0M
=2021PASP..133e4502M 2021PASP..133e4502M
+2018PASP..130l8001T 2018PASP..130l8001T
ADC_Keywords: Surveys ; Morphology ; Optical
Keywords: catalogs - computational methods - astrostatistics techniques
Abstract:
We present an update to the PanSTARRS-1 Point Source Catalog (PS1
PSC), which provides morphological classifications of PS1 sources. The
original PS1 PSC adopted stringent detection criteria that excluded
hundreds of millions of PS1 sources from the PSC. Here, we adapt the
supervised machine learning methods used to create the PS1 PSC and
apply them to different photometric measurements that are more widely
available, allowing us to add ∼144 million new classifications while
expanding the the total number of sources in PS1 PSC by ∼10%. We
find that the new methodology, which utilizes PS1 forced photometry,
performs ∼6%-8% worse than the original method. This slight
degradation in performance is offset by the overall increase in the
size of the catalog. The PS1 PSC is used by time-domain surveys to
filter transient alert streams by removing candidates coincident with
point sources that are likely to be Galactic in origin. The addition
of ∼144 million new classifications to the PS1 PSC will improve the
efficiency with which transients are discovered.
Description:
Using a machine learning model, the authors classified ∼1.5 billion
sources from the PanSTARRS1 (PS1) first data release (DR1) as either
resolved, extended objects or unresolved, point sources. This PS1
point source catalog (PS1-PSC) provides a probabilistic ranking of all
sources with a score of 0 corresponding to extended objects and 1
corresponding to point sources. The classifications are based on
morphological properties measured in the PS1 stack images, though not
every source in PS1 has a classification (see the paper for known
caveats). It has been demonstrated that this method does a far better
job of selecting stars and galaxies than a single hard cut on the
difference between the PSF and Kron magnitudes (see the figure to the
right). A full description of the catalog is described in Tachibana &
Miller (2018PASP..130l8001T 2018PASP..130l8001T). You can refer to the PS1-PSC data
products in papers or webpages using the DOI
http://doi.org/10.17909/t9-xjrf-7g34.
File Summary:
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FileName Lrecl Records Explanations
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ReadMe 80 . This file
hlspps1mh.sam 50 1000 Update to the Probabilistic Classifications of
Unresolved Point Sources in PanSTARRS1 from
Miller & Hall, 2021PASP..133e4502M 2021PASP..133e4502M
(144870754 sources)
hlspps1tm.sam 58 1000 Probabilistic Classifications of Unresolved
Point Sources in PanSTARRS1 from
Tachibana & Miller, 2018PASP..130l8001T 2018PASP..130l8001T
(1467097937 sources)
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See also:
II/349 : The Pan-STARRS release 1 (PS1) Survey - DR1 (Chambers+, 2016)
Byte-by-byte Description of file: hlspps1mh.sam
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Bytes Format Units Label Explanations
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1- 18 I18 --- objid PS1 ObjID
20- 31 F12.8 deg RAdeg Right ascension (J2000)
33- 44 F12.8 deg DEdeg Declination (J2000)
46- 50 F5.3 --- psScore [0/1] Point-source score (G1)
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Byte-by-byte Description of file: hlspps1tm.sam
--------------------------------------------------------------------------------
Bytes Format Units Label Explanations
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1- 18 I18 --- objid PS1 ObjID
20- 31 F12.8 deg RAdeg Right ascension (J2000)
33- 44 F12.8 deg DEdeg Declination (J2000)
46- 58 F13.11 --- psScore [0/1] Point-source score (G1)
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Global notes:
Note (G1): 0 corresponding to extended objects and 1 corresponding to
point sources.
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Acknowledgements:
Xander Hall, xjh(at)andrew.cmu.edu
(End) Francois-Xavier Pineau, Patricia Vannier [CDS] 26-Nov-2024