No Arabic abstract
Time domain astronomy was revolutionised with the discovery of the first kilonova, AT2017gfo, in August 2017 which was associated with the gravitational wave signal GW170817. Since this event, numerous wide-field surveys have been optimising search strategies to maximise their efficiency of detecting these fast and faint transients. With the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS), we have been conducting a volume limited survey for intrinsically faint and fast fading events to a distance of $Dsimeq200$ Mpc. Two promising candidates have been identified from this archival search, with sparse data - PS15cey and PS17cke. Here we present more detailed analysis and discussion of their nature. We observe that PS15cey was a luminous, fast declining transient at 320 Mpc. Models of BH-NS mergers with a very stiff equation of state could possibly reproduce the luminosity and decline but the physical parameters are extreme. A more likely scenario is that this was a SN2018kzr-like merger event. PS17cke was a faint and fast declining event at 15 Mpc. We explore several explosion scenarios of this transient including models of it as a NS-NS and BH-NS merger, the outburst of a massive luminous star, and compare it against other known fast fading transients. Although there is uncertainty in the explosion scenario due to difficulty in measuring the explosion epoch, we find PS17cke to be a plausible kilonova candidate from the model comparisons.
We searched for an optical counterpart to the first gravitational wave source discovered by LIGO (GW150914), using a combination of the Pan-STARRS1 wide-field telescope and the PESSTO spectroscopic follow-up programme. As the final LIGO sky maps changed during analysis, the total probability of the source being spatially coincident with our fields was finally only 4.2 per cent. Therefore we discuss our results primarily as a demonstration of the survey capability of Pan-STARRS and spectroscopic capability of PESSTO. We mapped out 442 square degrees of the northern sky region of the initial map. We discovered 56 astrophysical transients over a period of 41 days from the discovery of the source. Of these, 19 were spectroscopically classified and a further 13 have host galaxy redshifts. All transients appear to be fairly normal supernovae and AGN variability and none is obviously linked with GW150914. We illustrate the sensitivity of our survey by defining parameterised lightcurves with timescales of 4, 20 and 40 days and use the sensitivity of the Pan-STARRS1 images to set limits on the luminosities of possible sources. The Pan-STARRS1 images reach limiting magnitudes of i = 19.2, 20.0 and 20.8 respectively for the three timescales. For long timescale parameterised lightcurves (with FWHM=~40d) we set upper limits of M_i <= -17.2 -0.9/+1.4 if the distance to GW150914 is D = 400 +/- 200Mpc. The number of type Ia SN we find in the survey is similar to that expected from the cosmic SN rate, indicating a reasonably complete efficiency in recovering supernova like transients out to D = 400 +/- 200 Mpc.
We present the discovery of the first high redshift (z > 5.7) quasar from the Panoramic Survey Telescope and Rapid Response System 1 (Pan-STARRS1 or PS1). This quasar was initially detected as an i dropoutout in PS1, confirmed photometrically with the SAO Widefield InfraRed Camera (SWIRC) at Arizonas Multiple Mirror Telescope (MMT) and the Gamma-Ray Burst Optical/Near-Infrared Detector (GROND) at the MPG 2.2 m telescope in La Silla. The quasar was verified spectroscopically with the the MMT Spectrograph, Red Channel and the Cassegrain Twin Spectrograph (TWIN) at the Calar Alto 3.5 m telescope. It has a redshift of 5.73, an AB z magnitude of 19.4, a luminosity of 3.8 x 10^47 erg/s and a black hole mass of 6.9 x 10^9 solar masses. It is a Broad Absorption Line quasar with a prominent Ly-beta peak and a very blue continuum spectrum. This quasar is the first result from the PS1 high redshift quasar search that is projected to discover more than a hundred i dropout quasars, and could potentially find more than 10 z dropout (z > 6.8) quasars.
Nova Delphini 2013 was identified on the 14th of August 2013 and eventually rose to be a naked eye object. We sought to study the behaviour of the object in the run-up to outburst and to compare it to the pre-outburst photometric characteristics of other novae. We searched the Pan-STARRS 1 datastore to identify pre-outburst photometry of Nova Del 2013 and identified twenty-four observations in the 1.2 years before outburst. The progenitor of Nova Delphini showed variability of a few tenths of a magnitude but did not brighten significantly in comparison with archival plate photometry. We also found that the object did not vary significantly on the approximately half hour timescale between pairs of Pan-STARRS 1 observations.
We present the details of the photometric and astrometric calibration of the Pan-STARRS1 $3pi$ 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 square degrees north of $delta$ = -30 degrees. The astrometric calibration compensates for similar systematic effects so that positions, proper motions, and parallaxes are reliable as well. The Pan-STARRS Data Release 2 (DR2) astrometry is tied to the Gaia DR1 release.
We present the implementation and use of algorithms for matching point-spread functions (PSFs) within the Pan-STARRS Image Processing Pipeline (IPP). PSF-matching is an essential part of the IPP for the detection of supernovae and asteroids, but it is also used to homogenize the PSF of inputs to stacks, resulting in improved photometric precision compared to regular coaddition, especially in data with a high masked fraction. We report our experience in constructing and operating the image subtraction pipeline, and make recommendations about particular basis functions for constructing the PSF-matching convolution kernel, determining a suitable kernel, parallelisation and quality metrics. We introduce a method for reliably tracking the noise in an image throughout the pipeline, using the combination of a variance map and a `covariance pseudo-matrix. We demonstrate these algorithms with examples from both simulations and actual data from the Pan-STARRS1 telescope.