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Title: How Many Kilonovae Can Be Found in Past, Present, and Future Survey Data Sets?

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 $${10}^{3}\,{\mathrm{Gpc}}^{-3}\,{\mathrm{yr}}^{-1}$$, 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. Finally, 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.

Authors:
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Publication Date:
Research Org.:
SLAC National Accelerator Lab., Menlo Park, CA (United States)
Sponsoring Org.:
USDOE; National Aeronautic and Space Administration (NASA)
OSTI Identifier:
1417636
Grant/Contract Number:
AC02-76SF00515; 14-WPS14-0048; HST-HF2-51383.001; NAS 5-26555; AST-1411763; AST- 1714498; NNX15AE50G; NNX16AC22G
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
The Astrophysical Journal. Letters
Additional Journal Information:
Journal Volume: 852; Journal Issue: 1; Journal ID: ISSN 2041-8213
Publisher:
Institute of Physics (IOP)
Country of Publication:
United States
Language:
English
Subject:
79 ASTRONOMY AND ASTROPHYSICS; Stars: Neutron

Citation Formats

Scolnic, D., 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, R., Hounsell, R., Foley, R. J., Metzger, J., Rest, A., García-Bellido, J., Möller, A., Nugent, P., Abbott, T. M. C., Abdalla, F. B., Allam, S., Bechtol, K., Benoit-Lévy, 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., Costa, L. N. da, 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., and Walker, A. R. How Many Kilonovae Can Be Found in Past, Present, and Future Survey Data Sets?. United States: N. p., 2017. Web. doi:10.3847/2041-8213/aa9d82.
Scolnic, D., 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, R., Hounsell, R., Foley, R. J., Metzger, J., Rest, A., García-Bellido, J., Möller, A., Nugent, P., Abbott, T. M. C., Abdalla, F. B., Allam, S., Bechtol, K., Benoit-Lévy, 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., Costa, L. N. da, 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?. United States. doi:10.3847/2041-8213/aa9d82.
Scolnic, D., 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, R., Hounsell, R., Foley, R. J., Metzger, J., Rest, A., García-Bellido, J., Möller, A., Nugent, P., Abbott, T. M. C., Abdalla, F. B., Allam, S., Bechtol, K., Benoit-Lévy, 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., Costa, L. N. da, 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., and Walker, A. R. 2017. "How Many Kilonovae Can Be Found in Past, Present, and Future Survey Data Sets?". United States. doi:10.3847/2041-8213/aa9d82.
@article{osti_1417636,
title = {How Many Kilonovae Can Be Found in Past, Present, and Future Survey Data Sets?},
author = {Scolnic, D. and Kessler, R. and Brout, D. and Cowperthwaite, P. S. and Soares-Santos, M. and Annis, J. and Herner, K. and Chen, H. -Y. and Sako, M. and Doctor, Z. and Butler, R. E. and Palmese, A. and Diehl, H. T. and Frieman, J. and Holz, D. E. and Berger, E. and Chornock, R. and Villar, V. A. and Nicholl, M. and Biswas, R. and Hounsell, R. and Foley, R. J. and Metzger, J. and Rest, A. and García-Bellido, J. and Möller, A. and Nugent, P. and Abbott, T. M. C. and Abdalla, F. B. and Allam, S. and Bechtol, K. and Benoit-Lévy, A. and Bertin, E. and Brooks, D. and Buckley-Geer, E. and Rosell, A. Carnero and Kind, M. Carrasco and Carretero, J. and Castander, F. J. and Cunha, C. E. and D’Andrea, C. B. and Costa, L. N. da and Davis, C. and Doel, P. and Drlica-Wagner, A. and Eifler, T. F. and Flaugher, B. and Fosalba, P. and Gaztanaga, E. and Gerdes, D. W. and Gruen, D. and Gruendl, R. A. and Gschwend, J. and Gutierrez, G. and Hartley, W. G. and Honscheid, K. and James, D. J. and Johnson, M. W. G. and Johnson, M. D. and Krause, E. and Kuehn, K. and Kuhlmann, S. and Lahav, O. and Li, T. S. and Lima, M. and Maia, M. A. G. and March, M. and Marshall, J. L. and Menanteau, F. and Miquel, R. and Neilsen, E. and Plazas, A. A. and Sanchez, E. and Scarpine, V. and Schubnell, M. and Sevilla-Noarbe, I. and Smith, M. and Smith, R. C. and Sobreira, F. and Suchyta, E. and Swanson, M. E. C. and Tarle, G. and Thomas, R. C. and Tucker, D. L. and Walker, A. R.},
abstractNote = {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 ${10}^{3}\,{\mathrm{Gpc}}^{-3}\,{\mathrm{yr}}^{-1}$, 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. Finally, 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.},
doi = {10.3847/2041-8213/aa9d82},
journal = {The Astrophysical Journal. Letters},
number = 1,
volume = 852,
place = {United States},
year = 2017,
month =
}

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  • An historical overview is provided of the mathematical foundations of uncertainty quantification and the roles played in the more recent past by nuclear data uncertainties in nuclear data evaluations and nuclear applications. Significant advances that have established the mathematical framework for contemporary nuclear data evaluation methods, as well as the use of uncertainty information in nuclear data evaluation and nuclear applications, are described. This is followed by a brief examination of the current status concerning nuclear data evaluation methodology, covariance data generation, and the application of evaluated nuclear data uncertainties in contemporary nuclear technology. A few possible areas for futuremore » investigation of this subject are also suggested.« less