How Many Kilonovae Can Be Found in Past, Present, and Future Survey Data Sets?
- Creators
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Scolnic, D.
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Eifler, T. F.
- DES Collaboration
Abstract
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 10^3 Gpc^(-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.
Additional Information
© 2017 The American Astronomical Society. Received 2017 October 13; Accepted 2017 November 25; Published 2017 December 22. Funding for the DES Projects has been provided by the DOE and NSF (USA), MEC/MICINN/MINECO (Spain), STFC (UK), HEFCE (UK). NCSA (UIUC), KICP (U. Chicago), CCAPP (Ohio State), MIFPA (Texas A&M), CNPQ, FAPERJ, FINEP (Brazil), DFG (Germany) and the Collaborating Institutions in the Dark Energy Survey. The Collaborating Institutions are Argonne Lab, UC Santa Cruz, University of Cambridge, CIEMAT-Madrid, University of Chicago, University College London, DES Brazil Consortium, University of Edinburgh, ETH Zurich, Fermilab, University of Illinois, ICE (IEEC-CSIC), IFAE Barcelona, Lawrence Berkeley Lab, LMU Mnchen and the associated Excellence Cluster Universe, University of Michigan, NOAO, University of Nottingham, Ohio State University, University of Pennsylvania, University of Portsmouth, SLAC National Lab, Stanford University, University of Sussex, Texas A&M University, and the OzDES Membership Consortium. Based in part on observations at Cerro Tololo Inter-American Observatory, National Optical Astronomy Observatory, which is operated by the Association of Universities for Research in Astronomy (AURA) under a cooperative agreement with the National Science Foundation. The DES Data Management System is supported by the NSF under grant numbers AST-1138766 and AST-1536171. This work was supported in part by the Kavli Institute for Cosmological Physics at the University of Chicago through grant NSF PHY-1125897 and an endowment from the Kavli Foundation and its founder Fred Kavli. We gratefully acknowledge support from NASA grant 14-WPS14-0048. D.S. is supported by NASA through Hubble Fellowship grant HST-HF2-51383.001 awarded by the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., for NASA, under contract NAS 5-26555. This analysis was done using the Midway-RCC computing cluster at University of Chicago. The Berger Time-Domain Group at Harvard is supported in part by the NSF through grants AST-1411763 and AST-1714498, and by NASA through grants NNX15AE50G and NNX16AC22G. The UCSC group is supported in part by NSF grant AST-1518052, the Gordon & Betty Moore Foundation, the Heising-Simons Foundation, generous donations from many individuals through a UCSC Giving Day grant, and from fellowships from the Alfred P. Sloan Foundation and the David and Lucile Packard Foundation to R.J.F. R.B. acknowledges partial support from the Washington Research Foundation Fund for Innovation in Data-Intensive Discovery and the Moore/Sloan Data Science Environments Project at the University of Washington.Attached Files
Published - Scolnic_2018_ApJL_852_L3.pdf
Submitted - 1710.05845.pdf
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Additional details
- Eprint ID
- 84022
- Resolver ID
- CaltechAUTHORS:20171222-104216917
- Department of Energy (DOE)
- NSF
- Ministry of Education and Science (MEC)
- Ministerio de Ciencia e Innovación (MCINN)
- Ministerio de Economía, Industria y Competitividad (MINECO)
- Science and Technology Facilities Council (STFC)
- Higher Education Funding Council for England
- National Center for Supercomputing Applications (NCSA)
- Kavli Institute for Cosmological Physics
- Center of Cosmology and Astro Particle Physics (CCAPP)
- Mitchell Institute for Fundamental Physics and Astronomy
- Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
- Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ)
- Financiadora de Estudos e Projetos (FINEP)
- Deutsche Forschungsgemeinschaft (DFG)
- AST-1138766
- NSF
- AST-1536171
- NSF
- PHY-1125897
- NSF
- Kavli Foundation
- 14-WPS14-0048
- NASA
- HST-HF2-51383.001
- NASA Hubble Fellowship
- NAS 5-26555
- NASA
- AST-1411763
- NSF
- AST-1714498
- NSF
- NNX15AE50G
- NASA
- NNX16AC22G
- NASA
- AST-1518052
- NSF
- Gordon and Betty Moore Foundation
- Heising-Simons Foundation
- University of California, Santa Cruz
- Alfred P. Sloan Foundation
- David and Lucile Packard Foundation
- Washington Research Foundation
- University of Washington
- Created
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2017-12-22Created from EPrint's datestamp field
- Updated
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2021-11-15Created from EPrint's last_modified field