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researcher

P. O’Brien

4 papers hereh-index 244 citations10 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2

Across the 2 of 4 papers where every author was matched, so the position is known.

fields
  • astro-ph.HE2
  • astro-ph.IM1
  • astro-ph.SR1
same name
  • P. O’Brien — 11 papers, h 8
  • P. O’Brien — 9 papers, h 6
  • P. O’Brien — 8 papers, h 2
  • P. O’Brien — 7 papers, h 8
  • P. O’Brien — 5 papers, h 19
  • P. O’Brien — 3 papers, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

collaborators

4 papers

astro-ph.HE2025

SN 2024cld: unveiling the complex mass-loss histories of evolved supergiant progenitors to core collapse supernovae

T. L. Killestein, M. Pursiainen, R. Kotak +52

Pre-explosion mass loss in supernova (SN) progenitors is a crucial unknown factor in stellar evolution, yet has been illuminated recently by the diverse zoo of interacting transien…

astro-ph.SR2025

GOTO065054+593624: a 8.5 mag amplitude dwarf nova identified in real time via Kilonova Seekers

T. L. Killestein, G. Ramsay, M. Kennedy +62

Dwarf novae are astrophysical laboratories for probing the nature of accretion, binary mass transfer, and binary evolution -- yet their diverse observational characteristics contin…

astro-ph.HE2024

SN 2023tsz: A helium-interaction driven supernova in a very low-mass galaxy

B. Warwick, J. Lyman, M. Pursiainen +49

SN 2023tsz is a Type Ibn supernova (SNe Ibn) discovered in an extremely low-mass host. SNe Ibn are an uncommon subtype of stripped-envelope core-collapse SNe. They are characterise…

astro-ph.IM2024

Kilonova Seekers: the GOTO project for real-time citizen science in time-domain astrophysics

T. L. Killestein, L. Kelsey, E. Wickens +51

Time-domain astrophysics continues to grow rapidly, with the inception of new surveys drastically increasing data volumes. Democratised, distributed approaches to training sets for…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.