The Pan-STARRS1 Database and Data Products Flewelling, H. A.; Magnier, E. A.; Chambers, K. C. ...
The Astrophysical journal. Supplement series,
11/2020, Letnik:
251, Številka:
1
Journal Article
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Abstract
This paper describes the organization of the database and the catalog data products from the Pan-STARRS1 3
π
Steradian Survey. The catalog data products are available in the form of an ...SQL-based relational database from MAST, the Mikulski Archive for Space Telescopes at STScI. The database is described in detail, including the construction of the database, the provenance of the data, the schema, and how the database tables are related. Examples of queries for a range of science goals are included.
We present light curves and classification spectra of 17 hydrogen-poor superluminous supernovae (SLSNe) from the Pan-STARRS1 Medium Deep Survey (PS1 MDS). Our sample contains all objects from the PS1 ...MDS sample with spectroscopic classification that are similar to either of the prototypes SN 2005ap or SN 2007bi, without an explicit limit on luminosity. With a redshift range , PS1 MDS is the first SLSN sample primarily probing the high-redshift population; our multifilter PS1 light curves probe the rest-frame UV emission, and hence the peak of the spectral energy distribution. We measure the temperature evolution and construct bolometric light curves, and find peak luminosities of erg s−1 and lower limits on the total radiated energies of erg. The light curve shapes are diverse, with both rise and decline times spanning a factor of ∼5 and several examples of double-peaked light curves. When correcting for the flux-limited nature of our survey, we find a median peak luminosity at 4000 of and a spread of .
Physical Properties of 15 Quasars at z 6.5 Mazzucchelli, C.; Bañados, E.; Venemans, B. P. ...
The Astrophysical journal,
11/2017, Letnik:
849, Številka:
2
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Quasars are galaxies hosting accreting supermassive black holes; due to their brightness, they are unique probes of the early universe. To date, only a few quasars have been reported at (<800 Myr ...after the big bang). In this work, we present six additional quasars discovered using the Pan-STARRS1 survey. We use a sample of 15 quasars to perform a homogeneous and comprehensive analysis of this highest-redshift quasar population. We report four main results: (1) the majority of quasars show large blueshifts of the broad C iv λ1549 emission line compared to the systemic redshift of the quasars, with a median value ∼3× higher than a quasar sample at ; (2) we estimate the quasars' black hole masses ( (0.3-5) × 109 M ) via modeling of the Mg ii λ2798 emission line and rest-frame UV continuum and find that quasars at high redshift accrete their material (with ) at a rate comparable to a luminosity-matched sample at lower redshift, albeit with significant scatter (0.4 dex); (3) we recover no evolution of the Fe ii/Mg ii abundance ratio with cosmic time; and (4) we derive near-zone sizes and, together with measurements for quasars from recent work, confirm a shallow evolution of the decreasing quasar near-zone sizes with redshift. Finally, we present new millimeter observations of the C ii 158 m emission line and underlying dust continuum from NOEMA for four quasars and provide new accurate redshifts and C ii/infrared luminosity estimates. The analysis presented here shows the large range of properties of the most distant quasars.
Pan-STARRS Photometric and Astrometric Calibration Magnier, Eugene. A.; Schlafly, Edward. F.; Finkbeiner, Douglas P. ...
The Astrophysical journal. Supplement series,
11/2020, Letnik:
251, Številka:
1
Journal Article
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Abstract
We present the details of the photometric and astrometric calibration of the Pan-STARRS1 3
π
Survey. The photometric goals were to reduce the systematic effects introduced by the camera and ...detectors, and to place all of the observations onto a photometric system with consistent zero-points over the entire area surveyed, the ≈30,000 deg
2
north of
δ
= −30°. Using external comparisons, we demonstrate that the resulting photometric system is consistent across the sky to between 7 and 12.4 mmag depending on the filter. For bright stars, the systematic error floor for individual measurements is (
σ
g
,
σ
r
,
σ
i
,
σ
z
,
σ
y
) = (14, 14, 15, 15, 18) mmag. The astrometric calibration compensates for similar systematic effects so that positions, proper motions, and parallaxes are reliable as well. The bright-star systematic error floor for individual astrometric measurements is 16 mas. The Pan-STARRS Data Release 2 (DR2) astrometric system is tied to the Gaia DR1 coordinate frame with a systematic uncertainty of ∼5 mas.
Efficient identification and follow-up of astronomical transients is hindered by the need for humans to manually select promising candidates from data streams that contain many false positives. These ...artefacts arise in the difference images that are produced by most major ground-based time-domain surveys with large format CCD cameras. This dependence on humans to reject bogus detections is unsustainable for next generation all-sky surveys and significant effort is now being invested to solve the problem computationally. In this paper, we explore a simple machine learning approach to real–bogus classification by constructing a training set from the image data of ∼32 000 real astrophysical transients and bogus detections from the Pan-STARRS1 Medium Deep Survey. We derive our feature representation from the pixel intensity values of a 20 × 20 pixel stamp around the centre of the candidates. This differs from previous work in that it works directly on the pixels rather than catalogued domain knowledge for feature design or selection. Three machine learning algorithms are trained (artificial neural networks, support vector machines and random forests) and their performances are tested on a held-out subset of 25 per cent of the training data. We find the best results from the random forest classifier and demonstrate that by accepting a false positive rate of 1 per cent, the classifier initially suggests a missed detection rate of around 10 per cent. However, we also find that a combination of bright star variability, nuclear transients and uncertainty in human labelling means that our best estimate of the missed detection rate is approximately 6 per cent.
We use 1169 Pan-STARRS supernovae (SNe) and 195 low-z (z < 0.1) SNe Ia to measure cosmological parameters. Though most Pan-STARRS SNe lack spectroscopic classifications, in a previous paper we ...demonstrated that photometrically classified SNe can be used to infer unbiased cosmological parameters by using a Bayesian methodology that marginalizes over core-collapse (CC) SN contamination. Our sample contains nearly twice as many SNe as the largest previous SN Ia compilation. Combining SNe with cosmic microwave background (CMB) constraints from Planck, we measure the dark energy equation-of-state parameter w to be −0.989 0.057 (stat+sys). If w evolves with redshift as w(a) = w0 + wa(1 − a), we find w0 = −0.912 0.149 and wa = −0.513 0.826. These results are consistent with cosmological parameters from the Joint Light-curve Analysis and the Pantheon sample. We try four different photometric classification priors for Pan-STARRS SNe and two alternate ways of modeling CC SN contamination, finding that no variant gives a w differing by more than 2% from the baseline measurement. The systematic uncertainty on w due to marginalizing over CC SN contamination, , is the third-smallest source of systematic uncertainty in this work. We find limited (1.6 ) evidence for evolution of the SN color-luminosity relation with redshift, a possible systematic that could constitute a significant uncertainty in future high-z analyses. Our data provide one of the best current constraints on w, demonstrating that samples with ∼5% CC SN contamination can give competitive cosmological constraints when the contaminating distribution is marginalized over in a Bayesian framework.
The Pan-STARRS Data-processing System Magnier, Eugene A.; Chambers, K. C.; Flewelling, H. A. ...
The Astrophysical journal. Supplement series,
11/2020, Letnik:
251, Številka:
1
Journal Article
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Abstract
The Pan-STARRS data-processing system is responsible for the steps needed to downloaded, archive, and process all images obtained by the Pan-STARRS telescopes, including real-time detection ...of transient sources such as supernovae and moving objects including potentially hazardous asteroids. With a nightly data volume of up to 4 TB and an archive of over 4 PB of raw imagery, Pan-STARRS is solidly in the realm of Big Data astronomy. The full data-processing system consists of several subsystems covering the wide range of necessary capabilities. This article describes the Image Processing Pipeline and its connections to both the summit data systems and the outward-facing systems downstream. The latter include the Moving Object Processing System (MOPS) and the public database: the Published Science Products Subsystem.
Abstract
The Pan-STARRS1 (PS1) Science Consortium has carried out a set of imaging surveys using the 1.4 gigapixel GPC1 camera on the PS1 telescope. As this camera is composed of many individual ...electronic readouts and covers a very large field of view, great care was taken to ensure that the many instrumental effects were corrected to produce the most uniform detector response possible. We present the image-detrending steps used as part of the processing of the data contained within the public release of Pan-STARRS1 Data Release 1 (DR1). In addition to the single image processing, the methods used to transform the 375,573 individual exposures into a common sky-oriented grid are discussed, as well as those used to produce both the image stack and difference combination products.
ABSTRACT The dust extinction curve is a critical component of many observational programs and an important diagnostic of the physics of the interstellar medium. Here we present new measurements of ...the dust extinction curve and its variation toward tens of thousands of stars, a hundred-fold larger sample than in existing detailed studies. We use data from the APOGEE spectroscopic survey in combination with ten-band photometry from Pan-STARRS1, the Two Micron All-Sky Survey, and Wide-field Infrared Survey Explorer. We find that the extinction curve in the optical through infrared is well characterized by a one-parameter family of curves described by R(V). The extinction curve is more uniform than suggested in past works, with ( R ( V ) ) = 0.18 , and with less than one percent of sight lines having R ( V ) > 4 . Our data and analysis have revealed two new aspects of Galactic extinction: first, we find significant, wide-area variations in R(V) throughout the Galactic plane. These variations are on scales much larger than individual molecular clouds, indicating that R(V) variations must trace much more than just grain growth in dense molecular environments. Indeed, we find no correlation between R(V) and dust column density up to E ( B − V ) 2 . Second, we discover a strong relationship between R(V) and the far-infrared dust emissivity.
Abstract
Over 3 billion astronomical sources have been detected in the more than 22 million orthogonal transfer CCD images obtained as part of the Pan-STARRS1 3
π
survey. Over 85 billion instances of ...those sources have been automatically detected and characterized by the Pan-STARRS Image Processing Pipeline photometry software,
psphot
. This fast, automatic, and reliable software was developed for the Pan-STARRS project but is easily adaptable to images from other telescopes. We describe the analysis of the astronomical sources by
psphot
in general as well as for the specific case of the third processing version used for the first two public releases of the Pan-STARRS 3
π
Survey data.
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