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  • 1. Bellm, Eric C.
    et al.
    Kulkarni, Shrinivas R.
    Graham, Matthew J.
    Dekany, Richard
    Smith, Roger M.
    Riddle, Reed
    Masci, Frank J.
    Helou, George
    Prince, Thomas A.
    Adams, Scott M.
    Barbarino, Cristina
    Stockholm University, Faculty of Science, Department of Astronomy. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Barlow, Tom
    Bauer, James
    Beck, Ron
    Belicki, Justin
    Biswas, Rahul
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Blagorodnova, Nadejda
    Bodewits, Dennis
    Bolin, Bryce
    Brinnel, Valery
    Brooke, Tim
    Bue, Brian
    Bulla, Mattia
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Burruss, Rick
    Cenko, S. Bradley
    Chang, Chan-Kao
    Connolly, Andrew
    Coughlin, Michael
    Cromer, John
    Cunningham, Virginia
    De, Kishalay
    Delacroix, Alex
    Desai, Vandana
    Duev, Dmitry A.
    Eadie, Gwendolyn
    Farnham, Tony L.
    Feeney, Michael
    Feindt, Ulrich
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Flynn, David
    Franckowiak, Anna
    Frederick, S.
    Fremling, C.
    Gal-Yam, Avishay
    Gezari, Suvi
    Giomi, Matteo
    Goldstein, Daniel A.
    Golkhou, V. Zach
    Goobar, Ariel
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Groom, Steven
    Hacopians, Eugean
    Hale, David
    Henning, John
    Ho, Anna Y. Q.
    Hover, David
    Howell, Justin
    Hung, Tiara
    Huppenkothen, Daniela
    Imel, David
    Ip, Wing-Huen
    Ivezic, Zeljko
    Jackson, Edward
    Jones, Lynne
    Juric, Mario
    Kasliwal, Mansi M.
    Kaspi, S.
    Kaye, Stephen
    Kelley, Michael S. P.
    Kowalski, Marek
    Kramer, Emily
    Kupfer, Thomas
    Landry, Walter
    Laher, Russ R.
    Lee, Chien-De
    Lin, Hsing Wen
    Lin, Zhong-Yi
    Lunnan, Ragnhild
    Stockholm University, Faculty of Science, Department of Astronomy. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Giomi, Matteo
    Mahabal, Ashish
    Mao, Peter
    Miller, Adam A.
    Monkewitz, Serge
    Murphy, Patrick
    Ngeow, Chow-Choong
    Nordin, Jakob
    Nugent, Peter
    Ofek, Eran
    Patterson, Maria T.
    Penprase, Bryan
    Porter, Michael
    Rauch, Ludwig
    Rebbapragada, Umaa
    Reiley, Dan
    Rigault, Mickael
    Rodriguez, Hector
    van Roestel, Jan
    Rusholme, Ben
    van Santen, Jakob
    Schulze, S.
    Shupe, David L.
    Singer, Leo P.
    Soumagnac, Maayane T.
    Stein, Robert
    Surace, Jason
    Sollerman, Jesper
    Stockholm University, Faculty of Science, Department of Astronomy. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Szkody, Paula
    Taddia, Francesco
    Stockholm University, Faculty of Science, Department of Astronomy. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Terek, Scott
    Van Sistine, Angela
    van Velzen, Sjoert
    Vestrand, W. Thomas
    Walters, Richard
    Ward, Charlotte
    Ye, Quan-Zhi
    Yu, Po-Chieh
    Yan, Lin
    Zolkower, Jeffry
    The Zwicky Transient Facility: System Overview, Performance, and First Results2019In: Publications of the Astronomical Society of the Pacific, ISSN 0004-6280, E-ISSN 1538-3873, Vol. 131, no 995, article id 018002Article in journal (Refereed)
    Abstract [en]

    The Zwicky Transient Facility (ZTF) is a new optical time-domain survey that uses the Palomar 48 inch Schmidt telescope. A custom-built wide-field camera provides a 47 deg(2) field of view and 8 s readout time, yielding more than an order of magnitude improvement in survey speed relative to its predecessor survey, the Palomar Transient Factory. We describe the design and implementation of the camera and observing system. The ZTF data system at the Infrared Processing and Analysis Center provides near-real-time reduction to identify moving and varying objects. We outline the analysis pipelines, data products, and associated archive. Finally, we present on-sky performance analysis and first scientific results from commissioning and the early survey. ZTF's public alert stream will serve as a useful precursor for that of the Large Synoptic Survey Telescope.

  • 2. Bianco, Federica B.
    et al.
    Drout, Maria R.
    Graham, Melissa L.
    Pritchard, Tyler A.
    Biswas, Rahul
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Narayan, Gautham
    Andreoni, Igor
    Cowperthwaite, Philip S.
    Ribeiro, Tiago
    Presto-Color: A Photometric Survey Cadence for Explosive Physics and Fast Transients2019In: Publications of the Astronomical Society of the Pacific, ISSN 0004-6280, E-ISSN 1538-3873, Vol. 131, no 1000, article id 068002Article in journal (Refereed)
    Abstract [en]

    We identify minimal observing cadence requirements that enable photometric astronomical surveys to detect and recognize fast and explosive transients and fast transient features. Observations in two different filters within a short time window (e.g., g-and-i, or r-and-z, within <0.5 hr) and a repeat of one of those filters with a longer time window (e.g., >1.5 hr) are desirable for this purpose. Such an observing strategy delivers both the color and light curve evolution of transients on the same night. This allows the identification and initial characterization of fast transient-or fast features of longer timescale transients-such as rapidly declining supernovae, kilonovae, and the signatures of SN ejecta interacting with binary companion stars or circumstellar material. Some of these extragalactic transients are intrinsically rare and generally all hard to find, thus upcoming surveys like the Large Synoptic Survey Telescope (LSST) could dramatically improve our understanding of their origin and properties. We colloquially refer to such a strategy implementation for the LSST as the Presto-Color strategy (rapid-color). This cadence's minimal requirements allow for overall optimization of a survey for other science goals.

  • 3.
    Biswas, Rahul
    et al.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University of Washington, USA.
    Daniel, Scott F.
    Hložek, R.
    Kim, A. G.
    Yoachim, Peter
    Enabling Catalog Simulations of Transient and Variable Sources Based on LSST Cadence Strategies2020In: Astrophysical Journal Supplement Series, ISSN 0067-0049, E-ISSN 1538-4365, Vol. 247, no 2, article id 60Article in journal (Refereed)
    Abstract [en]

    The Large Synoptic Survey Telescope (LSST) project will conduct a 10 year multi-band survey starting in 2022. Observing strategies for this survey are being actively investigated, and the science capabilities can be best forecasted on the basis of simulated strategies from the LSST Operations Simulator (OpSim). OpSim simulates a stochastic realization of the sequence of LSST pointings over the survey duration, and is based on a model of the observatory (including telescope) and historical data of observational conditions. OpSim outputs contain a record of each simulated pointing of the survey along with a complete characterization of the pointing in terms of observing conditions, and some useful quantities derived from the characteristics of the pointing. Thus, each record can be efficiently used to derive the properties of observations of all astrophysical sources found in that pointing. However, in order to obtain the time series of observations (light curves) of a set of sources, it is often more convenient to compute all observations of an astrophysical source, and iterate over sources. In this document, we describe the open source python package OpSimSummary, which allows for a convenient reordering. The objectives of this package are to provide users with an Application Programming Interface for accessing all such observations and summarizing this information in the form of intermediate data products usable by third party software such as SNANA, thereby also bridging the gap between official LSST products and preexisting simulation codes.

  • 4. Coughlin, Michael W.
    et al.
    Ahumada, Tomas
    Anand, Shreya
    De, Kishalay
    Hankins, Matthew J.
    Kasliwal, Mansi M.
    Singer, Leo P.
    Bellm, Eric C.
    Andreoni, Igor
    Cenko, S. Bradley
    Cooke, Jeff
    Copperwheat, Christopher M.
    Dugas, Alison M.
    Jencson, Jacob E.
    Perley, Daniel A.
    Yu, Po-Chieh
    Bhalerao, Varun
    Kumar, Harsh
    Bloom, Joshua S.
    Anupama, G. C.
    Ashley, Michael C. B.
    Bagdasaryan, Ashot
    Biswas, Rahul
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Buckley, David A. H.
    Burdge, Kevin B.
    Cook, David O.
    Cromer, John
    Cunningham, Virginia
    D'Ai, Antonino
    Dekany, Richard G.
    Delacroix, Alexandre
    Dichiara, Simone
    Duev, Dmitry A.
    Dutta, Anirban
    Feeney, Michael
    Frederick, Sara
    Gatkine, Pradip
    Ghosh, Shaon
    Goldstein, Daniel A.
    Golkhou, V. Zach
    Goobar, Ariel
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Graham, Matthew J.
    Hanayama, Hidekazu
    Horiuchi, Takashi
    Hung, Tiara
    Jha, Saurabh W.
    Kong, Albert K. H.
    Giomi, Matteo
    Kaplan, David L.
    Karambelkar, V. R.
    Kowalski, Marek
    Kulkarni, Shrinivas R.
    Kupfer, Thomas
    Masci, Frank J.
    Mazzali, Paolo
    Moore, Anna M.
    Mogotsi, Moses
    Neill, James D.
    Ngeow, Chow-Choong
    Martinez-Palomera, Jorge
    La Parola, Valentina
    Pavana, M.
    Ofek, Eran O.
    Patil, Atharva Sunil
    Riddle, Reed
    Rigault, Mickael
    Rusholme, Ben
    Serabyn, Eugene
    Shupe, David L.
    Sharma, Yashvi
    Singh, Avinash
    Sollerman, Jesper
    Stockholm University, Faculty of Science, Department of Astronomy. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Soon, Jamie
    Staats, Kai
    Taggart, Kirsty
    Tan, Hanjie
    Travouillon, Tony
    Troja, Eleonora
    Waratkar, Gaurav
    Yatsu, Yoichi
    GROWTH on S190425z: Searching Thousands of Square Degrees to Identify an Optical or Infrared Counterpart to a Binary Neutron Star Merger with the Zwicky Transient Facility and Palomar Gattini-IR2019In: Astrophysical Journal Letters, ISSN 2041-8205, E-ISSN 2041-8213, Vol. 885, no 1, article id L19Article in journal (Refereed)
    Abstract [en]

    The third observing run by LVC has brought the discovery of many compact binary coalescences. Following the detection of the first binary neutron star merger in this run (LIGO/Virgo S190425z), we performed a dedicated follow-up campaign with the Zwicky Transient Facility (ZTF) and Palomar Gattini-IR telescopes. The initial skymap of this single-detector gravitational wave (GW) trigger spanned most of the sky observable from Palomar Observatory. Covering 8000 deg(2) of the initial skymap over the next two nights, corresponding to 46% integrated probability, ZTF system achieved a depth of 21 m(AB) in g- and r-bands. Palomar Gattini-IR covered 2200 square degrees in J-band to a depth of 15.5 mag, including 32% integrated probability based on the initial skymap. The revised skymap issued the following day reduced these numbers to 21% for the ZTF and 19% for Palomar Gattini-IR. We narrowed 338,646 ZTF transient ?alerts? over the first two nights of observations to 15 candidate counterparts. Two candidates, ZTF19aarykkb and ZTF19aarzaod, were particularly compelling given that their location, distance, and age were consistent with the GW event, and their early optical light curves were photometrically consistent with that of kilonovae. These two candidates were spectroscopically classified as young core-collapse supernovae. The remaining candidates were ruled out as supernovae. Palomar Gattini-IR did not identify any viable candidates with multiple detections only after merger time. We demonstrate that even with single-detector GW events localized to thousands of square degrees, systematic kilonova discovery is feasible.

  • 5. Graham, Matthew J.
    et al.
    Barbarino, Cristina
    Stockholm University, Faculty of Science, Department of Astronomy. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Feindt, Ulrich
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Goobar, Ariel
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Lunnan, Ragnhild
    Stockholm University, Faculty of Science, Department of Astronomy. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Sollerman, Jesper
    Stockholm University, Faculty of Science, Department of Astronomy. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Taddia, Francesco
    Stockholm University, Faculty of Science, Department of Astronomy. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Biswas, Rahul
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Bulla, Mattia
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Zolkower, Jeffry
    The Zwicky Transient Facility: Science Objectives2019In: Publications of the Astronomical Society of the Pacific, ISSN 0004-6280, E-ISSN 1538-3873, Vol. 131, no 1001, article id 078001Article in journal (Refereed)
    Abstract [en]

    The Zwicky Transient Facility (ZTF), a public-private enterprise, is a new time-domain survey employing a dedicated camera on the Palomar 48-inch Schmidt telescope with a 47 deg(2) field of view and an 8 second readout time. It is well positioned in the development of time-domain astronomy, offering operations at 10% of the scale and style of the Large Synoptic Survey Telescope (LSST) with a single 1-m class survey telescope. The public surveys will cover the observable northern sky every three nights in g and r filters and the visible Galactic plane every night in g and r. Alerts generated by these surveys are sent in real time to brokers. A consortium of universities that provided funding (partnership) are undertaking several boutique surveys. The combination of these surveys producing one million alerts per night allows for exploration of transient and variable astrophysical phenomena brighter than r similar to 20.5 on timescales of minutes to years. We describe the primary science objectives driving ZTF, including the physics of supernovae and relativistic explosions, multi-messenger astrophysics, supernova cosmology, active galactic nuclei, and tidal disruption events, stellar variability, and solar system objects.

  • 6. Ivezić, Željko
    et al.
    Biswas, Rahul
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Zhan, Hu
    LSST: From Science Drivers to Reference Design and Anticipated Data Products2019In: Astrophysical Journal, ISSN 0004-637X, E-ISSN 1538-4357, Vol. 873, no 2, article id 111Article in journal (Refereed)
    Abstract [en]

    We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the solar system, exploring the transient optical sky, and mapping the Milky Way. LSST will be a large, wide-field ground-based system designed to obtain repeated images covering the sky visible from Cerro Pachon in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg(2) field of view, a 3.2-gigapixel camera, and six filters (ugrizy) covering the wavelength range 320-1050 nm. The project is in the construction phase and will begin regular survey operations by 2022. About 90% of the observing time will be devoted to a deep-wide-fast survey mode that will uniformly observe a 18,000 deg(2) region about 800 times (summed over all six bands) during the anticipated 10 yr of operations and will yield a co-added map to r similar to 27.5. These data will result in databases including about 32 trillion observations of 20 billion galaxies and a similar number of stars, and they will serve the majority of the primary science programs. The remaining 10% of the observing time will be allocated to special projects such as Very Deep and Very Fast time domain surveys, whose details are currently under discussion. We illustrate how the LSST science drivers led to these choices of system parameters, and we describe the expected data products and their characteristics.

  • 7. Kessler, R.
    et al.
    Narayan, G.
    Avelino, A.
    Bachelet, E.
    Biswas, Rahul
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Brown, P. J.
    Chernoff, D. F.
    Connolly, A. J.
    Dail, M.
    Daniel, S.
    Di Stefano, R.
    Drout, M. R.
    Galbany, L.
    González-Gaitán, S.
    Graham, M. L.
    Hložek, R.
    Ishida, E. E. O.
    Guillochon, J.
    Jha, S. W.
    Jones, D. O.
    Mandel, K. S.
    Muthukrishna, D.
    O'Grady, A.
    Peters, C. M.
    Pierel, J. R.
    Ponder, K. A.
    Prša, A.
    Rodney, S.
    Villar, V. A.
    Models and Simulations for the Photometric LSST Astronomical Time Series Classification Challenge (PLAsTiCC)2019In: Publications of the Astronomical Society of the Pacific, ISSN 0004-6280, E-ISSN 1538-3873, Vol. 131, no 1003, article id 094501Article in journal (Refereed)
    Abstract [en]

    We describe the simulated data sample for the Photometric Large Synoptic Survey Telescope (LSST) Astronomical Time Series Classification Challenge (PLAsTiCC), a publicly available challenge to classify transient and variable events that will be observed by the LSST, a new facility expected to start in the early 2020s. The challenge was hosted by Kaggle, ran from 2018 September 28 to December 17, and included 1094 teams competing for prizes. Here we provide details of the 18 transient and variable source models, which were not revealed until after the challenge, and release the model libraries at https://doi.org/10.5281/zenodo.2612896. We describe the LSST Operations Simulator used to predict realistic observing conditions, and we describe the publicly available SNANA simulation code used to transform the models into observed fluxes and uncertainties in the LSST passbands (ugrizy). Although PLAsTiCC has finished, the publicly available models and simulation tools are being used within the astronomy community to further improve classification, and to study contamination in photometrically identified samples of SN Ia used to measure properties of dark energy. Our simulation framework will continue serving as a platform to improve the PLAsTiCC models, and to develop new models.

  • 8. Lochner, Michelle
    et al.
    Scolnic, Daniel M.
    Awan, Humna
    Regnault, Nicolas
    Gris, Philippe
    Mandelbaum, Rachel
    Gawiser, Eric
    Almoubayyed, Husni
    Setzer, Christian N.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Huber, Simon
    Graham, Melissa L.
    Hlozek, Renee
    Biswas, Rahul
    Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Eifler, Tim
    Rothchild, Daniel
    Allam Jr., Tarek
    Blazek, Jonathan
    Chang, Chihway
    Collett, Thomas
    Goobar, Ariel
    Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). Stockholm University, Faculty of Science, Department of Physics.
    Hook, Isobel M.
    Jarvis, Mike
    Jha, Saurabh W.
    Kim, Alex G.
    Marshall, Phil
    McEwen, Jason D.
    Moniez, Marc
    Newman, Jeffrey A.
    Peiris, Hiranya V.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, UK.
    Petrushevska, Tanja
    Rhodes, Jason
    Sevilla-Noarbe, Ignacio
    Slosar, Anze
    Suyu, Sherry H.
    Tyson, J. Anthony
    Yoachim, Peter
    Optimizing the LSST Observing Strategy for Dark Energy Science: DESC Recommendations for the Wide-Fast-Deep Survey2018Manuscript (preprint) (Other academic)
    Abstract [en]

    Cosmology is one of the four science pillars of LSST, which promises to be transformative for our understanding of dark energy and dark matter. The LSST Dark Energy Science Collaboration (DESC) has been tasked with deriving constraints on cosmological parameters from LSST data. Each of the cosmological probes for LSST is heavily impacted by the choice of observing strategy. This white paper is written by the LSST DESC Observing Strategy Task Force (OSTF), which represents the entire collaboration, and aims to make recommendations on observing strategy that will benefit all cosmological analyses with LSST. It is accompanied by the DESC DDF (Deep Drilling Fields) white paper (Scolnic et al.). We use a variety of metrics to understand the effects of the observing strategy on measurements of weak lensing, large-scale structure, clusters, photometric redshifts, supernovae, strong lensing and kilonovae. In order to reduce systematic uncertainties, we conclude that the current baseline observing strategy needs to be significantly modified to result in the best possible cosmological constraints. We provide some key recommendations: moving the WFD (Wide-Fast-Deep) footprint to avoid regions of high extinction, taking visit pairs in different filters, changing the 2x15s snaps to a single exposure to improve efficiency, focusing on strategies that reduce long gaps (>15 days) between observations, and prioritizing spatial uniformity at several intervals during the 10-year survey.

  • 9. Mahabal, Ashish
    et al.
    Rebbapragada, Umaa
    Walters, Richard
    Masci, Frank J.
    Blagorodnova, Nadejda
    van Roestel, Jan
    Ye, Quan-Zhi
    Biswas, Rahul
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Burdge, Kevin
    Chang, Chan-Kao
    Duev, Dmitry A.
    Golkhou, V. Zach
    Miller, Adam A.
    Nordin, Jakob
    Ward, Charlotte
    Adams, Scott
    Bellm, Eric C.
    Branton, Doug
    Bue, Brian
    Cannella, Chris
    Connolly, Andrew
    Dekany, Richard
    Feindt, Ulrich
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Hung, Tiara
    Fortson, Lucy
    Frederick, Sara
    Fremling, C.
    Gezari, Suvi
    Graham, Matthew
    Groom, Steven
    Kasliwal, Mansi M.
    Kulkarni, Shrinivas
    Kupfer, Thomas
    Lin, Hsing Wen
    Lintott, Chris
    Lunnan, Ragnhild
    Stockholm University, Faculty of Science, Department of Astronomy. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Parejko, John
    Prince, Thomas A.
    Riddle, Reed
    Rusholme, Ben
    Saunders, Nicholas
    Sedaghat, Nima
    Shupe, David L.
    Singer, Leo P.
    Soumagnac, Maayane T.
    Szkody, Paula
    Tachibana, Yutaro
    Tirumala, Kushal
    van Velzen, Sjoert
    Wright, Darryl
    Machine Learning for the Zwicky Transient Facility2019In: Publications of the Astronomical Society of the Pacific, ISSN 0004-6280, E-ISSN 1538-3873, Vol. 131, no 997, article id 038002Article in journal (Refereed)
    Abstract [en]

    The Zwicky Transient Facility is a large optical survey in multiple filters producing hundreds of thousands of transient alerts per night. We describe here various machine learning (ML) implementations and plans to make the maximal use of the large data set by taking advantage of the temporal nature of the data, and further combining it with other data sets. We start with the initial steps of separating bogus candidates from real ones, separating stars and galaxies, and go on to the classification of real objects into various classes. Besides the usual methods (e.g., based on features extracted from light curves) we also describe early plans for alternate methods including the use of domain adaptation, and deep learning. In a similar fashion we describe efforts to detect fast moving asteroids. We also describe the use of the Zooniverse platform for helping with classifications through the creation of training samples, and active learning. Finally we mention the synergistic aspects of ZTF and LSST from the ML perspective.

  • 10. Malz, A.
    et al.
    Hložek, R.
    Allam, T.
    Bahmanyar, A.
    Biswas, Rahul
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Dai, M.
    Galbany, L.
    Ishida, E. E. O.
    Jha, S. W.
    Jones, D. O.
    Kessler, R.
    Lochner, M.
    Mahabal, A. A.
    Mandel, K. S.
    Martínez-Galarza, J. R.
    McEwen, J. D.
    Muthukrishna, D.
    Narayan, G.
    Peiris, Hiranya
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, UK.
    Peters, C. M.
    Ponder, K.
    Setzer, Christian N.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    The Photometric LSST Astronomical Time-series Classification Challenge PLAsTiCC: Selection of a Performance Metric for Classification Probabilities Balancing Diverse Science Goals2019In: Astronomical Journal, ISSN 0004-6256, E-ISSN 1538-3881, Vol. 158, no 5, article id 171Article in journal (Refereed)
    Abstract [en]

    Classification of transient and variable light curves is an essential step in using astronomical observations to develop an understanding of the underlying physical processes from which they arise. However, upcoming deep photometric surveys, including the Large Synoptic Survey Telescope (LSST), will produce a deluge of low signal-to-noise data for which traditional type estimation procedures are inappropriate. Probabilistic classification is more appropriate for such data but is incompatible with the traditional metrics used on deterministic classifications. Furthermore, large survey collaborations like LSST intend to use the resulting classification probabilities for diverse science objectives, indicating a need for a metric that balances a variety of goals. We describe the process used to develop an optimal performance metric for an open classification challenge that seeks to identify probabilistic classifiers that can serve many scientific interests. The Photometric LSST Astronomical Time-series Classification Challenge (PLASTICC) aims to identify promising techniques for obtaining classification probabilities of transient and variable objects by engaging a broader community beyond astronomy. Using mock classification probability submissions emulating realistically complex archetypes of those anticipated of PLASTICC, we compare the sensitivity of two metrics of classification probabilities under various weighting schemes, finding that both yield results that are qualitatively consistent with intuitive notions of classification performance. We thus choose as a metric for PLASTICC a weighted modification of the cross-entropy because it can be meaningfully interpreted in terms of information content. Finally, we propose extensions of our methodology to ever more complex challenge goals and suggest some guiding principles for approaching the choice of a metric of probabilistic data products.

  • 11. Muthukrishna, Daniel
    et al.
    Narayan, Gautham
    Mandel, Kaisey S.
    Biswas, Rahul
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Hložek, Renée
    RAPID: Early Classification of Explosive Transients Using Deep Learning2019In: Publications of the Astronomical Society of the Pacific, ISSN 0004-6280, E-ISSN 1538-3873, Vol. 131, no 1005, article id 118002Article in journal (Refereed)
    Abstract [en]

    We present Real-time Automated Photometric IDentification (RAPID), a novel time series classification tool capable of automatically identifying transients from within a day of the initial alert, to the full lifetime of a light curve. Using a deep recurrent neural network with gated recurrent units (GRUs), we present the first method specifically designed to provide early classifications of astronomical timeseries data, typing 12 different transient classes. Our classifier can process light curves with any phase coverage, and it does not rely on deriving computationally expensive features from the data, making RAPID well suited for processing the millions of alerts that ongoing and upcoming wide-field surveys such as the Zwicky Transient Facility (ZTF), and the Large Synoptic Survey Telescope (LSST) will produce. The classification accuracy improves over the lifetime of the transient as more photometric data becomes available, and across the 12 transient classes, we obtain an average area under the receiver operating characteristic curve of 0.95 and 0.98 at early and late epochs, respectively. We demonstrate RAPID's ability to effectively provide early classifications of observed transients from the ZTF data stream. We have made RAPID available as an open-source software package(8) for machine-learning-based alert brokers to use for the autonomous and quick classification of several thousand light curves within a few seconds.

  • 12. Scolnic, D.
    et al.
    Kessler, R.
    Brout, D.
    Cowperthwaite, P. S.
    Soares-Santos, M.
    Annis, J.
    Herner, K.
    Chen, H. -Y.
    Sako, M.
    Doctor, Z.
    Butler, R. E.
    Palmese, A.
    Diehl, H. T.
    Frieman, J.
    Holz, D. E.
    Berger, E.
    Chornock, R.
    Villar, V. A.
    Nicholl, M.
    Biswas, Rahul
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University of Washington, USA.
    Hounsell, R.
    Foley, R. J.
    Metzger, J.
    Rest, A.
    Garcia-Bellido, J.
    Moller, A.
    Nugent, P.
    Abbott, T. M. C.
    Abdalla, F. B.
    Allam, S.
    Bechtol, K.
    Benoit-Levy, A.
    Bertin, E.
    Brooks, D.
    Buckley-Geer, E.
    Rosell, A. Carnero
    Kind, M. Carrasco
    Carretero, J.
    Castander, F. J.
    Cunha, C. E.
    D'Andrea, C. B.
    da Costa, L. N.
    Davis, C.
    Doel, P.
    Drlica-Wagner, A.
    Eifler, T. F.
    Flaugher, B.
    Fosalba, P.
    Gaztanaga, E.
    Gerdes, D. W.
    Gruen, D.
    Gruendl, R. A.
    Gschwend, J.
    Gutierrez, G.
    Hartley, W. G.
    Honscheid, K.
    James, D. J.
    Johnson, M. W. G.
    Johnson, M. D.
    Krause, E.
    Kuehn, K.
    Kuhlmann, S.
    Lahav, O.
    Li, T. S.
    Lima, M.
    Maia, M. A. G.
    March, M.
    Marshall, J. L.
    Menanteau, F.
    Miquel, R.
    Neilsen, E.
    Plazas, A. A.
    Sanchez, E.
    Scarpine, V.
    Schubnell, M.
    Sevilla-Noarbe, I.
    Smith, M.
    Smith, R. C.
    Sobreira, F.
    Suchyta, E.
    Swanson, M. E. C.
    Tarle, G.
    Thomas, R. C.
    Tucker, D. L.
    Walker, A. R.
    How Many Kilonovae Can Be Found in Past, Present, and Future Survey Data Sets?2018In: Astrophysical Journal Letters, ISSN 2041-8205, E-ISSN 2041-8213, Vol. 852, no 1, article id L3Article in journal (Refereed)
    Abstract [en]

    The discovery of a kilonova (KN) associated with the Advanced LIGO (aLIGO)/Virgo event GW170817 opens up new avenues of multi-messenger astrophysics. Here, using realistic simulations, we provide estimates of the number of KNe that could be found in data from past, present, and future surveys without a gravitational-wave trigger. For the simulation, we construct a spectral time-series model based on the DES-GW multi-band light curve from the single known KN event, and we use an average of BNS rates from past studies of 103Gpc(-3) yr(-1), consistent with the one event found so far. Examining past and current data sets from transient surveys, the number of KNe we expect to find for ASAS-SN, SDSS, PS1, SNLS, DES, and SMT is between 0 and 0.3. We predict the number of detections per future survey to be 8.3 from ATLAS, 10.6 from ZTF, 5.5/69 from LSST (the Deep Drilling/Wide Fast Deep), and 16.0 from WFIRST. The maximum redshift of KNe discovered for each survey is z = 0.8 for WFIRST, z = 0.25 for LSST, and z = 0.04 for ZTF and ATLAS. This maximum redshift for WFIRST is well beyond the sensitivity of aLIGO and some future GW missions. For the LSST survey, we also provide contamination estimates from Type Ia and core-collapse supernovae: after light curve and template-matching requirements, we estimate a background of just two events. More broadly, we stress that future transient surveys should consider how to optimize their search strategies to improve their detection efficiency and to consider similar analyses for GW follow-up programs.

  • 13.
    Setzer, Christian N.
    et al.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Biswas, Rahul
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Peiris, Hiranya V.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, UK.
    Rosswog, Stephan
    Stockholm University, Faculty of Science, Department of Astronomy. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Korobkin, Oleg
    Wollaeger, Ryan T.
    Serendipitous discoveries of kilonovae in the LSST main survey: maximizing detections of sub-threshold gravitational wave events2019In: Monthly notices of the Royal Astronomical Society, ISSN 0035-8711, E-ISSN 1365-2966, Vol. 485, no 3, p. 4260-4273Article in journal (Refereed)
    Abstract [en]

    We investigate the ability of the Large Synoptic Survey Telescope (LSST) to discover kilonovae (kNe) from binary neutron star (BNS) and neutron star-black hole (NSBH) mergers, focusing on serendipitous detections in the Wide-Fast-Deep (WFD) survey. We simulate observations of kNe with proposed LSST survey strategies, focusing on cadence choices that are compatible with the broader LSST cosmology programme. If all kNe are identical to GW170817, we find the baseline survey strategy will yield 58 kNe over the survey lifetime. If we instead assume a representative population model of BNS kNe, we expect to detect only 27 kNe. However, we find the choice of survey strategy significantly impacts these numbers and can increase them to 254 and 82 kNe over the survey lifetime, respectively. This improvement arises from an increased cadence of observations between different filters with respect to the baseline. We then consider the detectability of these BNS mergers by the Advanced LIGO/Virgo (ALV) detector network. If the optimal survey strategy is adopted, 202 of the GW170817-like kNe and 56 of the BNS population model kNe are detected with LSST but are below the threshold for detection by the ALV network. This represents, for both models, an increase by a factor greater than 4.5 in the number of detected sub-threshold events over the baseline strategy. These subthreshold events would provide an opportunity to conduct electromagnetic-triggered searches for signals in gravitational-wave data and assess selection effects in measurements of the Hubble constant from standard sirens, e.g. viewing angle effects.

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