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. ...
Astrophysical journal/The Astrophysical journal,
11/2017, Letnik:
849, Številka:
2
Journal Article
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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.
ABSTRACT Luminous quasars at can be studied in detail with the current generation of telescopes and provide us with unique information on the first gigayear of the universe. Thus far, these studies ...have been statistically limited by the number of quasars known at these redshifts. Such quasars are rare, and therefore, wide-field surveys are required to identify them, and multiwavelength data are required to separate them efficiently from their main contaminants, the far more numerous cool dwarfs. In this paper, we update and extend the selection for the quasars presented in Bañados et al. (2014) using the Pan-STARRS1 (PS1) survey. We present the PS1 distant quasar sample, which currently consists of 124 quasars in the redshift range that satisfy our selection criteria. Of these quasars, 77 have been discovered with PS1, and 63 of them are newly identified in this paper. We present the composite spectra of the PS1 distant quasar sample. This sample spans a factor of ∼20 in luminosity and shows a variety of emission line properties. The number of quasars at presented in this work almost doubles the previously known quasars at these redshifts, marking a transition phase from studies of individual sources to statistical studies of the high-redshift quasar population, which was impossible with earlier, smaller samples.
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-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 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.
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.
ABSTRACT We present nebular-phase imaging and spectroscopy for the hydrogen-poor superluminous supernova (SLSN) SN 2015bn, at redshift z = 0.1136, spanning +250-400 days after maximum light. The ...light curve exhibits a steepening in the decline rate from 1.4 mag (100 days)−1 to 1.7 mag (100 days)−1, suggestive of a significant decrease in the opacity. This change is accompanied by a transition from a blue continuum superposed with photospheric absorption lines to a nebular spectrum dominated by emission lines of oxygen, calcium, and magnesium. There are no obvious signatures of circumstellar interaction or large 56Ni mass. We show that the spectrum at +400 days is virtually identical to a number of energetic SNe Ic such as SN 1997dq, SN 2012au, and SN 1998bw, indicating similar core conditions and strengthening the link between "hypernovae"/long gamma-ray bursts and SLSNe. A single explosion mechanism may unify these events that span absolute magnitudes of −22 < MB < −17. Both the light curve and spectrum of SN 2015bn are consistent with an engine-driven explosion ejecting 7-30 M of oxygen-dominated ejecta (for reasonable choices in temperature and opacity). A strong and relatively narrow O i λ7774 line, seen in a number of these energetic events but not in normal supernovae, may point to an inner shell that is the signature of a central engine.