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Register a new userA Systematic Search for Periodically Varying Quasars in Pan-STARRS1: An Extended Baseline Test in Medium Deep Survey Field MD09
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T. Liu
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We present a systematic search for periodically varying quasars and supermassive black hole binary (SMBHB) candidates in the Pan-STARRS1 (PS1) Medium Deep Surveys MD09 field. From a color-selected sample of 670 quasars extracted from a multi-band deep-stack catalog of point sources, we locally select variable quasars and look for coherent periods with the Lomb-Scargle periodogram. Three candidates from our sample demonstrate strong variability for more than ~3 cycles, and their PS1 light curves are well fitted to sinusoidal functions. We test the persistence of the candidates apparent periodic variations detected during the 4.2 years of the PS1 survey with archival photometric data from the SDSS Stripe 82 survey or new monitoring with the Large Monolithic Imager at the Discovery Channel Telescope. None of the three periodic candidates (including PSO J334.2028+1.4075) remain persistent over the extended baseline of 7 - 14 years, corresponding to a detection rate of < 1 in 670 quasars in a search area of 5 deg^2. Even though SMBHBs should be a common product of the hierarchal growth of galaxies, and periodic variability in SMBHBs has been theoretically predicted, a systematic search for such signatures in a large optical survey is strongly limited by its temporal baseline and the red noise associated with normal quasar variability. We show that follow-up long-term monitoring (>5 cycles) is crucial to our search for these systems.
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Supermassive black hole binaries (SMBHBs) should be an inevitable consequence of the hierarchical growth of massive galaxies through mergers, and the strongest sirens of gravitational waves (GWs) in the cosmos. And yet, their direct detection has remained elusive due to the compact (sub-parsec) orbital separations of gravitationally bound SMBHBs. Here we exploit a theoretically predicted signature of a SMBHB in the time domain: periodic variability caused by a mass accretion rate that is modulated by the binarys orbital motion. We report our first significant periodically varying quasar detection from the systematic search in the Pan-STARRS1 (PS1) Medium Deep Survey. Our SMBHB candidate, PSO J334.2028+01.4075, is a luminous radio-loud quasar at $z=2.060$, with extended baseline photometry from the Catalina Real-Time Transient Survey, as well as archival spectroscopy from the FIRST Bright Quasar Survey. The observed period ($542 pm 15$ days) and estimated black hole mass ($log (M_{rm BH}/M_odot) = 9.97 pm 0.50$), correspond to an orbital separation of $7^{+8}_{-4}$ Schwarzschild radii ($sim 0.006^{+0.007}_{-0.003}$ pc), assuming the rest-frame period of the quasar variability traces the orbital period of the binary. This SMBHB candidate, discovered at the peak redshift for SMBH mergers, is in a physically stable configuration for a circumbinary accretion disk, and within the regime of GW-driven orbital decay. Our search with PS1 is a benchmark study for the exciting capabilities of LSST, which will have orders of magnitude larger survey power, and will potentially pinpoint the locations of thousands of SMBHBs in the variable night sky.
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.
[Abridged] We present a search for fast optical transients (~0.5 hr-1 day) using repeated observations of the Pan-STARRS1 Medium-Deep Survey (PS1/MDS) fields. Our search takes advantage of the consecutive g/r-band observations (16.5 min in each filter), by requiring detections in both bands, with non-detections on preceding and subsequent nights. We identify 19 transients brighter than 22.5 AB mag (S/N>10). Of these, 11 events exhibit quiescent counterparts in the deep PS1/MDS templates that we identify as M4-M9 dwarfs. The remaining 8 transients exhibit a range of properties indicative of main-belt asteroids near the stationary point of their orbits. With identifications for all 19 transients, we place an upper limit of R_FOT(0.5hr)<0.12 deg^-2 d^-1 (95% confidence level) on the sky-projected rate of extragalactic fast transients at <22.5 mag, a factor of 30-50 times lower than previous limits; the limit for a timescale of ~day is R_FOT<2.4e-3 deg^-2 d^-1. To convert these sky-projected rates to volumetric rates, we explore the expected peak luminosities of fast optical transients powered by various mechanisms, and find that non-relativistic events are limited to M~-10 mag (M~-14 mag) for a timescale of ~0.5 hr (~day), while relativistic sources (e.g., GRBs, magnetar-powered transients) can reach much larger luminosities. The resulting volumetric rates are <13 (M~-10 mag), <0.05 (M~-14 mag) and <1e-6 Mpc^-3 yr^-1 (M~-24 mag), significantly above the nova, supernova, and GRB rates, respectively, indicating that much larger surveys are required to provide meaningful constraints. Motivated by the results of our search we discuss strategies for identifying fast optical transients in the LSST main survey, and reach the optimistic conclusion that the veil of foreground contaminants can be lifted with the survey data, without the need for expensive follow-up observations.
Automated classification of supernovae (SNe) based on optical photometric light curve information is essential in the upcoming era of wide-field time domain surveys, such as the Legacy Survey of Space and Time (LSST) conducted by the Rubin Observatory. Photometric classification can enable real-time identification of interesting events for extended multi-wavelength follow-up, as well as archival population studies. Here we present the complete sample of 5,243 SN-like light curves (in griz) from the Pan-STARRS1 Medium-Deep Survey (PS1-MDS). The PS1-MDS is similar to the planned LSST Wide-Fast-Deep survey in terms of cadence, filters and depth, making this a useful training set for the community. Using this dataset, we train a novel semi-supervised machine learning algorithm to photometrically classify 2,315 new SN-like light curves with host galaxy spectroscopic redshifts. Our algorithm consists of a random forest supervised classification step and a novel unsupervised step in which we introduce a recurrent autoencoder neural network (RAENN). Our final pipeline, dubbed SuperRAENN, has an accuracy of 87% across five SN classes (Type Ia, Ibc, II, IIn, SLSN-I). We find the highest accuracy rates for Type Ia SNe and SLSNe and the lowest for Type Ibc SNe. Our complete spectroscopically- and photometrically-classified samples break down into: 62.0% Type Ia (1839 objects), 19.8% Type II (553 objects), 4.8% Type IIn (136 objects), 11.7% Type Ibc (291 objects), and 1.6% Type I SLSNe (54 objects). Finally, we discuss how this algorithm can be modified for online LSST data streams.
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.
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