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Abstract With the advent of the Vera C. Rubin Observatory, the discovery rate of supernovae (SNe) will surpass the rate of SNe with real time spectroscopic follow-up by 3 orders of magnitude. Accurate photometric classifiers are essential to both select interesting events for follow-up in real time and for archival population-level studies. In this work, we investigate the impact of observable host-galaxy information on the classification of SNe, both with and without additional light-curve and redshift information. We find that host-galaxy information alone can successfully isolate relatively pure (>90%) samples of Type Ia SNe with or without redshift information. With redshift information, we can additionally produce somewhat pure (>70%) samples of Type II SNe and superluminous SNe. Additionally with redshift information, host-galaxy properties do not significantly improve the accuracy of SN classification when paired with complete light curves. In the absence of redshift information, however, galaxy properties significantly increase the accuracy of photometric classification. As a part of this analysis, we present the first formal application of a new objective function, the weighted hierarchical cross entropy, to the problem of SN classification. This objective function more naturally accounts for the hierarchical nature of SN classes and, more broadly, transients. Finally, we present a new set of SN classifications for the Pan-STARRS Medium Deep Survey of SNe that lack spectroscopic redshift, increasing the full photometric sample to >4400 events.
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A Systematic Exploration of Kilonova Candidates from Neutron Star Mergers during the Third Gravitational-wave Observing Run
Abstract We present a comprehensive analysis of 653 optical candidate counterparts reported during the third gravitational-wave (GW) observing run. Our sample concentrates on candidates from the 15 events (published in GWTC-2, GWTC-3, or not retracted on GraceDB) that had a >1% chance of including a neutron star in order to assess their viability as true kilonovae. In particular, we leverage tools available in real time, including pre-merger detections and cross-matching with catalogs (i.e., point-source, variable-star, quasar and host-galaxy redshift data sets), to eliminate 65% of candidates in our sample. We further employ spectroscopic classifications, late-time detections, and light-curve behavior analyses and conclude that 66 candidates remain viable kilonovae. These candidates lack sufficient information to determine their classifications, and the majority would require luminosities greater than that of AT 2017gfo. Pre-merger detections in public photometric survey data and comparison of cataloged host-galaxy redshifts with the GW event distances are critical to incorporate into vetting procedures, as these tools eliminated >20% and >30% of candidates, respectively. We expect that such tools that leverage archival information will significantly reduce the strain on spectroscopic and photometric follow-up resources in future observing runs. Finally, we discuss the critical role prompt updates from GW astronomers to the EM community play in reducing the number of candidates requiring vetting.
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- PAR ID:
- 10363509
- Publisher / Repository:
- DOI PREFIX: 10.3847
- Date Published:
- Journal Name:
- The Astrophysical Journal
- Volume:
- 927
- Issue:
- 1
- ISSN:
- 0004-637X
- Format(s):
- Medium: X Size: Article No. 50
- Size(s):
- Article No. 50
- Sponsoring Org:
- National Science Foundation
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