Bibliographic Details
| Title: |
Classifying FRB spectrograms using nonlinear dimensionality reduction techniques |
| Authors: |
Yang, X., Zhang, S. -B., Wang, J. -S., Wu, X. -F. |
| Publication Year: |
2023 |
| Collection: |
Astrophysics |
| Subject Terms: |
Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Instrumentation and Methods for Astrophysics |
| More Details: |
Fast radio bursts (FRBs) are mysterious astronomical phenomena, and it is still uncertain whether they consist of multiple types. In this study we use two nonlinear dimensionality reduction algorithms - Uniform Manifold Approximation and Projection (UMAP) and t-distributed stochastic neighbour embedding (t-SNE) - to differentiate repeaters from apparently non-repeaters in FRBs. Based on the first Canadian Hydrogen Intensity Mapping Experiment (CHIME) FRB catalogue, these two methods are applied to standardized parameter data and image data from a sample of 594 sub-bursts and 535 FRBs, respectively. Both methods are able to differentiate repeaters from apparently non-repeaters. The UMAP algorithm using image data produces more accurate results and is a more model-independent method. Our result shows that in general repeater clusters tend to be narrowband, which implies a difference in burst morphology between repeaters and apparently non-repeaters. We also compared our UMAP predictions with the CHIME/FRB discovery of 6 new repeaters, the performance was generally good except for one outlier. Finally, we highlight the need for a larger and more complete sample of FRBs.
Comment: 10 pages, 9 figures, 4 tables, accepted by MNRAS |
| Document Type: |
Working Paper |
| DOI: |
10.1093/mnras/stad1304 |
| Access URL: |
http://arxiv.org/abs/2304.13912 |
| Accession Number: |
edsarx.2304.13912 |
| Database: |
arXiv |
