The Pan-STARRS 3pi stack data (images and catalogs) were released to the world as DR1 on 2016 December 19. This provides a high-quality network of calibration sources over three quarters of the sky to a modest depth. Telescopes both large and small (depths overlapping i ~ 17 to 21 mag) observing fields north of Dec=-30 deg in the optical will have good PS1 calibration sources in the field, observed through the same column as the target sources, allowing simple relative calibration for astrometry, photometry and spectroscopy.
To allow us (and others) to take advantage of this, I have produced a point source catalog in the LSST reference catalog format and also in the astrometry.net format we have used in the past. Details on the contents, construction and use of the catalog are available from the README.txt file included in the catalog, which I will summarise here.
Overview
This reference catalog contains astrometry and grizy photometry for 2,990,470,528 point sources at Dec > -30 deg to i ~ 22.5 mag.
Users of this catalog should include the following acknowledgement in publications:
The Pan-STARRS1 Surveys (PS1) have been made possible through contributions of the Institute for Astronomy, the University of Hawaii, the Pan-STARRS Project Office, the Max-Planck Society and its participating institutes, the Max Planck Institute for Astronomy, Heidelberg and the Max Planck Institute for Extraterrestrial Physics, Garching, The Johns Hopkins University, Durham University, the University of Edinburgh, Queen’s University Belfast, the Harvard-Smithsonian Center for Astrophysics, the Las Cumbres Observatory Global Telescope Network Incorporated, the National Central University of Taiwan, the Space Telescope Science Institute, the National Aeronautics and Space Administration under Grant No. NNX08AR22G issued through the Planetary Science Division of the NASA Science Mission Directorate, the National Science Foundation under Grant No. AST-1238877, the University of Maryland, and Eotvos Lorand University (ELTE), the Los Alamos National Laboratory, and the Gordon and Betty Moore Foundation.
Relevant papers for information and citation include:
- Chambers et al., “The Pan-STARRS1 Surveys”, 2016arXiv161205560C
- Magnier et al., “The Pan-STARRS Data Processing System”, 2016arXiv161205240M
- Waters et al., “Pan-STARRS Pixel Processing: Detrending, Warping, Stacking”, 2016arXiv161205245W
- Magnier et al., “Pan-STARRS Pixel Analysis: Source Detection and Characterization”, 2016arXiv161205244M
- Magnier et al., “Pan-STARRS Photometric and Astrometric Calibration”, 2016arXiv161205242M
- Flewelling et al., “The Pan-STARRS1 Database and Data Products”, 2016arXiv161205243F
- Tonry et al., “The Pan-STARRS1 Photometric System”, 2012ApJ…750…99T
- Schlafly et al., “Photometric Calibration of the First 1.5 Years of the Pan-STARRS1 Survey”, 2012ApJ…756…158S
LSST-style format
The LSST-style format uses FITS files divided by HTM. You can download the LSST-style catalog here. Be warned that it’s rather large: 423 GB. You can download a subset of the catalog by grabbing the appropriate FITS files; see the section in the README.txt entitled “Field selections” for details.
You need to install it in your data repo:
ln -s /path/to/ps1_pv3_3pi_20170110/ /path/to/DATA_REPO/ref_cats
Then you need to adjust your configuration. Here’s a configuration for processCcd.py (either to put in your obs package as config/processCcd.py, or to specify on the command-line with --configfile). See also the section below on “Common configuration” for colorterms and filterMap.
from lsst.meas.algorithms import LoadIndexedReferenceObjectsTask
config.calibrate.astromRefObjLoader.retarget(LoadIndexedReferenceObjectsTask)
config.calibrate.astromRefObjLoader.ref_dataset_name = "ps1_pv3_3pi_20170110"
config.calibrate.photoRefObjLoader.retarget(LoadIndexedReferenceObjectsTask)
config.calibrate.photoRefObjLoader.ref_dataset_name = "ps1_pv3_3pi_20170110"
config.calibrate.photoCal.photoCatName = "ps1_pv3_3pi_20170110"
Astrometry.net-style format
The astrometry.net-style format uses custom FITS files divided by HEALPix and indexed using tools provided by astrometry.net. You can download the astrometry.net-style catalog here. This format is a bit smaller than the LSST-style format (it does not include as much detail, e.g., proper motions), but is still quite hefty at 396 GB. If you want a subset of the catalog, you will need to figure out the appropriate HEALPix using the get-healpix tool from astrometry.net (I’m not entirely sure whether it’s the “XY”, “RING” or “NESTED” scheme you want) and grab the *_and_<healpix>_[012].fits files. Or you can grab the appropriate files from the LSST-style format and generate your own astrometry.net-style catalog using the included scripts; see the README.txt under “Astrometry.net format” for details.
The downloaded catalog doesn’t need to be installed in the data repo, but it should be declared to eups:
eups declare astrometry_net_data ps1_pv3_3pi_20170110-and -r /path/to/ps1_pv3_3pi_20170110-and
Then, to use it, you need to:
setup -j astrometry_net_data ps1_pv3_3pi_20170110-and
No configuration changes are currently required, because astrometry.net-style catalogs are currently the default (this will likely change soon), but do see the section below on “Common configuration” for colorterms and filterMap.
Common configuration
Regardless of which style of catalog you use, you need to set the colorterms and filterMap appropriately for your camera. Here is an example configuration for processCcd.py:
# These colorterms are for HSC, included as an example
colorterms = config.calibrate.photoCal.colorterms
from lsst.pipe.tasks.colorterms import ColortermDict, Colorterm
colorterms.data["ps1*"] = ColortermDict(data={
'g': Colorterm(primary="g", secondary="r", c0=0.00730066, c1=0.06508481, c2=-0.01510570),
'r': Colorterm(primary="r", secondary="i", c0=0.00279757, c1=0.02093734, c2=-0.01877566),
'r2': Colorterm(primary="r", secondary="i", c0=0.00117690, c1=0.00003996, c2=-0.01667794),
'i': Colorterm(primary="i", secondary="z", c0=0.00166891, c1=-0.13944659, c2=-0.03034094),
'i2': Colorterm(primary="i", secondary="z", c0=0.00180361, c1=-0.18483562, c2=-0.02675511),
'z': Colorterm(primary="z", secondary="y", c0=-0.00907517, c1=-0.28840221, c2=-0.00316369),
'y': Colorterm(primary="y", secondary="z", c0=-0.00156858, c1=0.14747401, c2=0.02880125),
})
# For the HSC r2 and i2 filters, use the r and i values from the catalog
for refObjLoader in (config.calibrate.astromRefObjLoader,
config.calibrate.photoRefObjLoader,
config.charImage.refObjLoader,
):
refObjLoader.filterMap['r2'] = 'r'
refObjLoader.filterMap['i2'] = 'i'
EDIT Aug 2020: NCSA/LSST doesn’t seem to be running their web server at the moment. If you can’t access it, there’s a copy of the catalog available from http://tigress-web.princeton.edu/~pprice/ps1_pv3_3pi_20170110/ .
