Oral Presentation Astronomical Society of Australia Annual Scientific Meeting including HWWS 2013

Locations of Peculiar Supernovae as a Diagnostic of Their Origins (#38)

Fang Yuan 1 2 , Chiaki Kobayashi 3 , Brian P Schimidt 1 2 , Philipp Podsiadlowski 4 , Stuart A Sim 2 5 , Richard A Scalzo 1 2
  1. Australian National University, Weston Creek, ACT, Australia
  2. ARC Centre of Excellence for All-sky Astrophysics (CAASTRO), Canberra, Australia
  3. University of Hertfordshire, Hatfield, UK
  4. Oxford University, Oxford, UK
  5. Queen's University Belfast, Belfast, UK
One of the key questions for understanding supernovae is the nature of their progenitors. For very nearby core-collapse supernovae, direct identifications of pre-explosion progenitor stars have led to the tightest constraints on their physical characteristics - but this is only possible in a handful of cases. Recently, an increasing number of unusual transients occurring far away from galaxies have been discovered by wide-field transient surveys. For these outlying events, direct observation of the local stellar population is impossible, due to low surface brightness. In this paper, we study a class of peculiar sub-luminous "calcium-rich" supernovae which exhibit locations consistently well outside their host galaxies' centres. We compare their distribution with globular clusters and stellar populations through the results of self-consistent cosmological simulations. A statistical analysis shows that their distribution is consistent with globular clusters or a very old metal-poor population. Because several of the objects have photometric limits which exclude an underlying globular cluster, we can conclude that this population represents an exotic explosion process involving the oldest most metal poor stars in the local universe.  Recent large transient experiments indicate that there are other classes of objects that occur at atypically large distances from their host galaxies. The methods developed in this paper can be used in the future to help identify the progenitors of these unusual classes of objects as sufficient numbers become available to undertake a statistical analysis.