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Register a new userSelection of Burst-like Transients and Stochastic Variables Using Multi-Band Image Differencing in the Pan-STARRS1 Medium-Deep Survey
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We present a novel method for the light-curve characterization of Pan-STARRS1 Medium Deep Survey (PS1 MDS) extragalactic sources into stochastic variables (SV) and burst-like (BL) transients, using multi-band image-differencing time-series data. We select detections in difference images associated with galaxy hosts using a star/galaxy catalog extracted from the deep PS1 MDS stacked images, and adopt a maximum a posteriori formulation to model their difference-flux time-series in four Pan-STARRS1 photometric bands g,r,i, and z. We use three deterministic light-curve models to fit burst-like transients and one stochastic light curve model, the Ornstein-Uhlenbeck process, in order to fit variability that is characteristic of active galactic nuclei (AGN). We assess the quality of fit of the models band-wise source-wise, using their estimated leave-out-one cross-validation likelihoods and corrected Akaike information criteria. We then apply a K-means clustering algorithm on these statistics, to determine the source classification in each band. The final source classification is derived as a combination of the individual filter classifications. We use our clustering method to characterize 4361 extragalactic image difference detected sources in the first 2.5 years of the PS1 MDS, into 1529 BL, and 2262 SV, with a purity of 95.00% for AGN, and 90.97% for SN based on our verification sets. We combine our light-curve classifications with their nuclear or off-nuclear host galaxy offsets, to define a robust photometric sample of 1233 active galactic nuclei and 812 supernovae. We use these samples to identify simple photometric priors that would enable their real-time identification in future wide-field synoptic surveys.
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We analyze the wavelength-dependent variability of a sample of spectroscopically confirmed active galactic nuclei (AGN) selected from near-UV ($NUV$) variable sources in the GALEX Time Domain Survey that have a large amplitude of optical variability (difference-flux S/N $>$ 3) in the Pan-STARRS1 Medium Deep Survey (PS1 MDS). By matching GALEX and PS1 epochs in 5 bands ($NUV$, $g_{P1}$, $r_{P1}$, $i_{P1}$, $z_{P1}$) in time, and taking their flux difference, we create co-temporal difference-flux spectral energy distributions ($Delta f$SEDs) using two chosen epochs for each of the 23 objects in our sample on timescales of about a year. We confirm the bluer-when-brighter trend reported in previous studies, and measure a median spectral index of the $Delta f$SEDs of $alpha_{lambda}$ = 2.1 that is consistent with an accretion disk spectrum. We further fit the $Delta f$SEDs of each source with a standard accretion disk model in which the accretion rate changes from one epoch to the other. In our sample, 17 out of 23 ($sim$74 %) sources are well described by this variable accretion-rate disk model, with a median average characteristic disk temperature $bar{T}^*$ of $1.2times 10^5$~K that is consistent with the temperatures expected given the distribution of accretion rates and black hole masses inferred for the sample. Our analysis also shows that the variable accretion rate model is a better fit to the $Delta f$SEDs than a simple power law.
We present a systematic search for periodically varying quasar and supermassive black hole binary (SMBHB) candidates in the Pan-STARRS1 Medium Deep Survey. From $sim9,000$ color-selected quasars in a $sim50$ deg$^{2}$ sky area, we initially identify $26$ candidates with more than $1.5$ cycles of variation. We extend the baseline of observations via our imaging campaign with the Discovery Channel Telescope and the Las Cumbres Observatory network and reevaluate the candidates using a more rigorous, maximum likelihood method. Using a range of statistical criteria and assuming the Damped Random Walk model for normal quasar variability, we identify one statistically significant periodic candidate. We also investigate the capabilities of detecting SMBHBs by the Large Synoptic Survey Telescope using our study with MDS as a benchmark and explore any complementary, multiwavelength evidence for SMBHBs in our sample.
The Pan-STARRS1 (PS1) survey has obtained imaging in 5 bands (grizy_P1) over 10 Medium Deep Survey (MDS) fields covering a total of 70 square degrees. This paper describes the search for apparently hostless supernovae (SNe) within the first year of PS1 MDS data with an aim of discovering new superluminous supernovae (SLSNe). A total of 249 hostless transients were discovered down to a limiting magnitude of M_AB ~ 23.5, of which 76 were classified as Type Ia SNe. There were 57 SNe with complete light curves that are likely core-collapse SNe (CCSNe) or SLSNe and 12 of these have had spectra taken. Of these 12 hostless, non-Type Ia SNe, 7 were SLSNe of Type Ic at redshifts between 0.5-1.4. This illustrates that the discovery rate of Type Ic SLSNe can be maximised by concentrating on hostless transients and removing normal SNe Ia. We present data for two new possible SLSNe; PS1-10pm (z = 1.206) and PS1-10ahf (z = 1.1), and estimate the rate of SLSNe-Ic to be between 3^{+3}_{-2} * 10^{-5} and 8^{+2}_{-1} * 10^{-5} of the CCSNe rate within 0.3 <= z <= 1.4 by applying a Monte-Carlo technique. The rate of slowly evolving, SN2007bi-like explosions is estimated as a factor of 10 lower than this range.
We study the properties of 975 active galactic nuclei (AGN) selected by variability in the Pan-STARRS1 Medium-Deep Survey. Using complementary multi wavelength data from the ultraviolet to the far-infrared, we use SED fitting to determine the AGN and host properties at $z<1$, and compare to a well-matched control sample. We confirm the trend previously observed that the variability amplitude decreases with AGN luminosity, but on the other hand, we observe that the slope of this relation steepens with wavelength resulting in a redder when brighter trend at low luminosities. Our results show that AGN are hosted by more massive hosts than control sample galaxies, while the restframe, dust-corrected $NUV-r$ color distribution of AGN hosts is similar to control galaxies. We find a positive correlation between the AGN luminosity and star formation rate (SFR), independent of redshift. AGN hosts populate the whole range of SFRs within and outside the Main Sequence of star forming galaxies. Comparing the distribution of AGN hosts and control galaxies, we show that AGN hosts are less likely to be hosted by quiescent galaxies, but more likely to be hosted by Main Sequence or starburst galaxies.
Pan-STARRS1 has carried out a set of distinct synoptic imaging sky surveys including the $3pi$ Steradian Survey and the Medium Deep Survey in 5 bands ($grizy_{P1}$). The mean 5$sigma$ point source limiting sensitivities in the stacked 3$pi$ Steradian Survey in $grizy_{P1}$ are (23.3, 23.2, 23.1, 22.3, 21.4) respectively. The upper bound on the systematic uncertainty in the photometric calibration across the sky is 7-12 millimag depending on the bandpass. The systematic uncertainty of the astrometric calibration using the Gaia frame comes from a comparison of the results with Gaia: the standard deviation of the mean and median residuals ($ Delta ra, Delta dec $) are (2.3, 1.7) milliarcsec, and (3.1, 4.8) milliarcsec respectively. The Pan-STARRS system and the design of the PS1 surveys are described and an overview of the resulting image and catalog data products and their basic characteristics are described together with a summary of important results. The images, reduced data products, and derived data products from the Pan-STARRS1 surveys are available to the community from the Mikulski Archive for Space Telescopes (MAST) at STScI.
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