We present optical light curves, redshifts, and classifications for spectroscopically confirmed Type Ia supernovae (SNe Ia) discovered by the Pan-STARRS1 (PS1) Medium Deep Survey. We detail ...improvements to the PS1 SN photometry, astrometry, and calibration that reduce the systematic uncertainties in the PS1 SN Ia distances. We combine the subset of PS1 SNe Ia (0.03 < z < 0.68) with useful distance estimates of SNe Ia from the Sloan Digital Sky Survey (SDSS), SNLS, and various low-z and Hubble Space Telescope samples to form the largest combined sample of SNe Ia, consisting of a total of SNe Ia in the range of 0.01 < z < 2.3, which we call the "Pantheon Sample." When combining Planck 2015 cosmic microwave background (CMB) measurements with the Pantheon SN sample, we find and for the wCDM model. When the SN and CMB constraints are combined with constraints from BAO and local H0 measurements, the analysis yields the most precise measurement of dark energy to date: and for the CDM model. Tension with a cosmological constant previously seen in an analysis of PS1 and low-z SNe has diminished after an increase of 2× in the statistics of the PS1 sample, improved calibration and photometry, and stricter light-curve quality cuts. We find that the systematic uncertainties in our measurements of dark energy are almost as large as the statistical uncertainties, primarily due to limitations of modeling the low-redshift sample. This must be addressed for future progress in using SNe Ia to measure dark energy.
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
Recenzirano
Odprti dostop
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.
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
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.
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
Recenzirano
Odprti dostop
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
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.
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.
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
Recenzirano
Odprti dostop
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.
ABSTRACT
We obtained high-resolution infrared spectroscopy and short-cadence photometry of the 600–800 Myr Praesepe star K2-100 during transits of its 1.67-d planet. This Neptune-size object, ...discovered by the NASA K2 mission, is an interloper in the ‘desert’ of planets with similar radii on short-period orbits. Our observations can be used to understand its origin and evolution by constraining the orbital eccentricity by transit fitting, measuring the spin-orbit obliquity by the Rossiter–McLaughlin effect, and detecting any extended, escaping the hydrogen–helium envelope with the 10 830 -Å line of neutral helium in the 2s3S triplet state. Transit photometry with 1-min cadence was obtained by the K2 satellite during Campaign 18 and transit spectra were obtained with the IRD spectrograph on the Subaru telescope. While the elevated activity of K2-100 prevented us from detecting the Rossiter–McLaughlin effect, the new photometry combined with revised stellar parameters allowed us to constrain the eccentricity to e < 0.15/0.28 with 90/99 per cent confidence. We modelled atmospheric escape as an isothermal, spherically symmetric Parker wind, with photochemistry driven by ultraviolet radiation, which we estimate by combining the observed spectrum of the active Sun with calibrations from observations of K2-100 and similar young stars in the nearby Hyades cluster. Our non-detection (<5.7 m Å) of a transit-associated He i line limits mass-loss of a solar-composition atmosphere through a T ≤ 10000 K wind to <0.3 M⊕ Gyr−1. Either K2-100b is an exceptional desert-dwelling planet, or its mass-loss is occurring at a lower rate over a longer interval, consistent with a core accretion-powered scenario for escape.
We study the time lags between the continuum emission of quasars at different wavelengths, based on more than four years of multi-band (g, r, i, z) light curves in the Pan-STARRS Medium Deep Fields. ...As photons from different bands emerge from different radial ranges in the accretion disk, the lags constrain the sizes of the accretion disks. We select 240 quasars with redshifts of z 1 or z 0.3 that are relatively emission-line free. The light curves are sampled from day to month timescales, which makes it possible to detect lags on the scale of the light crossing time of the accretion disks. With the code JAVELIN, we detect typical lags of several days in the rest frame between the g band and the riz bands. The detected lags are ∼2-3 times larger than the light crossing time estimated from the standard thin disk model, consistent with the recently measured lag in NGC 5548 and microlensing measurements of quasars. The lags in our sample are found to increase with increasing luminosity. Furthermore, the increase in lags going from g − r to g − i and then to g − z is slower than predicted in the thin disk model, particularly for high-luminosity quasars. The radial temperature profile in the disk must be different from what is assumed. We also find evidence that the lags decrease with increasing line ratios between ultraviolet Fe ii lines and Mg ii, which may point to changes in the accretion disk structure at higher metallicity.