PS1-10ahf , the SIMBAD biblio

PS1-10ahf , the SIMBAD biblio (18 results) C.D.S. - SIMBAD4 rel 1.8 - 2026.10.15CEST12:33:28

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Bibcode/DOI Score in Title|Abstract|
Keywords 		in a table in teXt, Caption, ... Nb occurence Nb objects in ref Citations
(from ADS) 		Title First 3 Authors
2015MNRAS.448.1206M viz 2223   K A D S   X C       56 272 59 Selecting superluminous supernovae in faint galaxies from the first year of the Pan-STARRS1 Medium Deep Survey. McCRUM M., SMARTT S.J., REST A., et al.
2016ApJ...818...77O 16       D               2 10 7 Quark-novae occurring in massive binaries : a universal energy source in superluminous supernovae with double-peaked light curves. OUYED R., LEAHY D. and KONING N.
2016MNRAS.457L..79N 135       D     X   F     3 14 35 Seeing double: the frequency and detectability of double-peaked superluminous supernova light curves. NICHOLL M. and SMARTT S.J.
2017ApJ...850...55N 18       D               2 41 176 The magnetar model for Type I superluminous supernovae. I. Bayesian analysis of the full multicolor light-curve sample with MOSFiT. NICHOLL M., GUILLOCHON J. and BERGER E.
2017ApJ...851...95S 16       D               1 24 24 Magnetar-powered superluminous supernovae must first be exploded by jets. SOKER N. and GILKIS A.
2018ApJ...852...81L viz 299       D     X C       7 32 93 Hydrogen-poor superluminous supernovae from the Pan-STARRS1 Medium Deep Survey. LUNNAN R., CHORNOCK R., BERGER E., et al.
2018MNRAS.473.1258S 17       D               2 75 131 Cosmic evolution and metal aversion in superluminous supernova host galaxies. SCHULZE S., KRUHLER T., LELOUDAS G., et al.
2018A&A...611A..45R 80           X         2 47 13 Search for γ-ray emission from superluminous supernovae with the Fermi-LAT. RENAULT-TINACCI N., KOTERA K., NERONOV A., et al.
2018ApJ...867..113M 16       D               2 37 11 Systematic investigation of the fallback accretion-powered model for hydrogen-poor superluminous supernovae. MORIYA T.J., NICHOLL M. and GUILLOCHON J.
2018ApJ...869..166V 16       D               1 58 6 Superluminous supernovae in LSST: rates, detection metrics, and light-curve modeling. VILLAR V.A., NICHOLL M. and BERGER E.
2019ApJ...884...83V 93             C       1 3 37 Supernova photometric classification pipelines trained on spectroscopically classified supernovae from the Pan-STARRS1 Medium-Deep Survey. VILLAR V.A., BERGER E., MILLER G., et al.
2020ApJ...897..114B 16       D               1 67 ~ The pre-explosion mass distribution of hydrogen-poor superluminous supernova progenitors and new evidence for a mass-spin correlation. BLANCHARD P.K., BERGER E., NICHOLL M., et al.
2020ApJ...904...74G 16       D               1 145 ~ FLEET: a redshift-agnostic machine learning pipeline to rapidly identify hydrogen-poor superluminous supernovae. GOMEZ S., BERGER E., BLANCHARD P.K., et al.
2021ApJ...909...24K 17       D               1 93 ~ Photospheric velocity gradients and ejecta masses of hydrogen-poor superluminous supernovae: proxies for distinguishing between fast and slow events. KONYVES-TOTH R. and VINKO J.
2021MNRAS.502.1678K 84           X         2 51 12 SN 2020ank: a bright and fast-evolving H-deficient superluminous supernova. KUMAR A., KUMAR B., PANDEY S.B., et al.
2022MNRAS.514.2627C 17       D               1 63 5 A puzzle solved after two decades: SN 2002gh among the brightest of superluminous supernovae. CARTIER R., HAMUY M., CONTRERAS C., et al.
2023MNRAS.521.2814K 104       D         F     4 24 1 The rest-frame ultraviolet of superluminous supernovae - I. Potential as cosmological probes. KHETAN N., COOKE J. and BRANCHESI M.
2024MNRAS.535..471G 197       D S   X         4 274 ~ The Type I superluminous supernova catalogue I: light-curve properties, models, and catalogue description. GOMEZ S., NICHOLL M., BERGER E., et al.

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