Classification of BATSE, Swift, and Fermi Gamma-Ray Bursts from Prompt Emission Alone
Although it is generally assumed that there are two dominant classes of gamma-ray bursts (GRBs) with different typical durations, it has been difficult to classify GRBs unambiguously as short or long from summary properties such as duration, spectral hardness, and spectral lag. Recent work used t-di...
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| Format: | Article |
| Language: | English |
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IOP Publishing
2023-01-01
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| Series: | The Astrophysical Journal |
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| Online Access: | https://doi.org/10.3847/1538-4357/acb999 |
| _version_ | 1797701957366841344 |
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| author | Charles L. Steinhardt William J. Mann Vadim Rusakov Christian K. Jespersen |
| author_facet | Charles L. Steinhardt William J. Mann Vadim Rusakov Christian K. Jespersen |
| author_sort | Charles L. Steinhardt |
| collection | DOAJ |
| description | Although it is generally assumed that there are two dominant classes of gamma-ray bursts (GRBs) with different typical durations, it has been difficult to classify GRBs unambiguously as short or long from summary properties such as duration, spectral hardness, and spectral lag. Recent work used t-distributed stochastic neighborhood embedding (t-SNE), a machine-learning algorithm for dimensionality reduction, to classify all Swift GRBs as short or long. Here, the method is expanded, using two algorithms, t-SNE and UMAP, to produce embeddings that are used to provide a classification for 1911 BATSE bursts, 1321 Swift bursts, and 2294 Fermi bursts for which both spectra and metadata are available. Although the embeddings appear to produce a clear separation of each catalog into short and long bursts, a resampling-based approach is used to show that a small fraction of bursts cannot be robustly classified. Further, three of the 304 bursts observed by both Swift and Fermi have robust but conflicting classifications. A likely interpretation is that in addition to the two predominant classes of GRBs, there are additional, uncommon types of bursts which may require multiwavelength observations in order to separate them from more typical short and long GRBs. |
| first_indexed | 2024-03-12T04:43:11Z |
| format | Article |
| id | doaj.art-ac9e5346b2dc42e5ba9f6a975af878b7 |
| institution | Directory Open Access Journal |
| issn | 1538-4357 |
| language | English |
| last_indexed | 2024-03-12T04:43:11Z |
| publishDate | 2023-01-01 |
| publisher | IOP Publishing |
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| series | The Astrophysical Journal |
| spelling | doaj.art-ac9e5346b2dc42e5ba9f6a975af878b72023-09-03T09:30:45ZengIOP PublishingThe Astrophysical Journal1538-43572023-01-0194516710.3847/1538-4357/acb999Classification of BATSE, Swift, and Fermi Gamma-Ray Bursts from Prompt Emission AloneCharles L. Steinhardt0https://orcid.org/0000-0003-3780-6801William J. Mann1https://orcid.org/0000-0001-7691-0762Vadim Rusakov2https://orcid.org/0000-0001-7633-3985Christian K. Jespersen3https://orcid.org/0000-0002-8896-6496Cosmic Dawn Center (DAWN) , Denmark ; steinhardt@nbi.ku.dk; Niels Bohr Institute, University of Copenhagen , Lyngbyvej 2, DK-2100 Copenhagen Ø, DenmarkCosmic Dawn Center (DAWN) , Denmark ; steinhardt@nbi.ku.dk; Niels Bohr Institute, University of Copenhagen , Lyngbyvej 2, DK-2100 Copenhagen Ø, DenmarkCosmic Dawn Center (DAWN) , Denmark ; steinhardt@nbi.ku.dk; Niels Bohr Institute, University of Copenhagen , Lyngbyvej 2, DK-2100 Copenhagen Ø, DenmarkDepartment of Astrophysical Sciences, Princeton University , Princeton, NJ, 08544, USAAlthough it is generally assumed that there are two dominant classes of gamma-ray bursts (GRBs) with different typical durations, it has been difficult to classify GRBs unambiguously as short or long from summary properties such as duration, spectral hardness, and spectral lag. Recent work used t-distributed stochastic neighborhood embedding (t-SNE), a machine-learning algorithm for dimensionality reduction, to classify all Swift GRBs as short or long. Here, the method is expanded, using two algorithms, t-SNE and UMAP, to produce embeddings that are used to provide a classification for 1911 BATSE bursts, 1321 Swift bursts, and 2294 Fermi bursts for which both spectra and metadata are available. Although the embeddings appear to produce a clear separation of each catalog into short and long bursts, a resampling-based approach is used to show that a small fraction of bursts cannot be robustly classified. Further, three of the 304 bursts observed by both Swift and Fermi have robust but conflicting classifications. A likely interpretation is that in addition to the two predominant classes of GRBs, there are additional, uncommon types of bursts which may require multiwavelength observations in order to separate them from more typical short and long GRBs.https://doi.org/10.3847/1538-4357/acb999Gamma-ray burstersGamma-ray burstsDimensionality reductionClassification systems |
| spellingShingle | Charles L. Steinhardt William J. Mann Vadim Rusakov Christian K. Jespersen Classification of BATSE, Swift, and Fermi Gamma-Ray Bursts from Prompt Emission Alone The Astrophysical Journal Gamma-ray bursters Gamma-ray bursts Dimensionality reduction Classification systems |
| title | Classification of BATSE, Swift, and Fermi Gamma-Ray Bursts from Prompt Emission Alone |
| title_full | Classification of BATSE, Swift, and Fermi Gamma-Ray Bursts from Prompt Emission Alone |
| title_fullStr | Classification of BATSE, Swift, and Fermi Gamma-Ray Bursts from Prompt Emission Alone |
| title_full_unstemmed | Classification of BATSE, Swift, and Fermi Gamma-Ray Bursts from Prompt Emission Alone |
| title_short | Classification of BATSE, Swift, and Fermi Gamma-Ray Bursts from Prompt Emission Alone |
| title_sort | classification of batse swift and fermi gamma ray bursts from prompt emission alone |
| topic | Gamma-ray bursters Gamma-ray bursts Dimensionality reduction Classification systems |
| url | https://doi.org/10.3847/1538-4357/acb999 |
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