PS1-12bqf , the SIMBAD biblio

PS1-12bqf , the SIMBAD biblio (18 results) C.D.S. - SIMBAD4 rel 1.8 - 2026.10.15CEST15:11:30


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Title First 3 Authors
2014ApJ...787..138L 521       D     X C       13 32 225 Hydrogen-poor superluminous supernovae and long-duration gamma-ray bursts have similar host galaxies. LUNNAN R., CHORNOCK R., BERGER E., et al.
2015ApJ...804...90L 173       D     X         5 19 56 Zooming in on the progenitors of superluminous supernovae with the HST. LUNNAN R., CHORNOCK R., BERGER E., et al.
2016A&A...593A.115J 55       D     X         2 31 11 Taking stock of superluminous supernovae and long gamma-ray burst host galaxy comparison using a complete sample of LGRBs. JAPELJ J., VERGANI S.D., SALVATERRA R., et al.
2017MNRAS.470.3566C 41           X         1 22 54 Superluminous supernova progenitors have a half-solar metallicity threshold. CHEN T.-W., SMARTT S.J., YATES R.M., et al.
2017ApJ...849L...4C 40           X         1 10 19 Spatially resolved MaNGA observations of the host galaxy of superluminous supernova 2017egm. CHEN T.-W., SCHADY P., XIAO L., et al.
2018ApJ...852...81L viz 1182       D S   X C       28 32 93 Hydrogen-poor superluminous supernovae from the Pan-STARRS1 Medium Deep Survey. LUNNAN R., CHORNOCK R., BERGER E., et al.
2018MNRAS.473.1258S 97       D     X         3 75 131 Cosmic evolution and metal aversion in superluminous supernova host galaxies. SCHULZE S., KRUHLER T., LELOUDAS G., et al.
2018ApJ...869..166V 16       D               2 58 6 Superluminous supernovae in LSST: rates, detection metrics, and light-curve modeling. VILLAR V.A., NICHOLL M. and BERGER E.
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...901...61L viz 124           X C       2 27 32 Four (super)luminous supernovae from the first months of the ZTF survey. LUNNAN R., YAN L., PERLEY D.A., 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.
2020A&A...643A..47O 16       D               1 93 ~ The interacting nature of dwarf galaxies hosting superluminous supernovae. ORUM S.V., IVENS D.L., STRANDBERG P., et al.
2021MNRAS.504.2535I 84               F     2 31 24 The first Hubble diagram and cosmological constraints using superluminous supernovae. INSERRA C., SULLIVAN M., ANGUS C.R., et al.
2022ApJ...931..153S 17       D               1 84 5 Constraints on the Explosion Timescale of Core-collapse Supernovae Based on Systematic Analysis of Light Curves. SAITO S., TANAKA M., SAWADA R., 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.
2022ApJ...941..107G 43           X         1 238 16 Luminous Supernovae: Unveiling a Population between Superluminous and Normal Core-collapse Supernovae. GOMEZ S., BERGER E., NICHOLL M., et al.
2024ApJ...961..169H 18       D               2 110 ~ An Extensive Hubble Space Telescope Study of the Offset and Host Light Distributions of Type I Superluminous Supernovae. HSU B., BLANCHARD P.K., BERGER E., et al.
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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