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| Hauptverfasser: | , , , , , , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| Online-Zugang: | https://arxiv.org/abs/2511.04966 |
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| _version_ | 1866911253425815552 |
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| author | Yuan, Mao Niu, Jiarui Feng, Yi Lv, Xu-ning Miao, Chenchen Meng, Lingqi Peng, Bo Deng, Li Yan, Jingye Zhu, Weiwei |
| author_facet | Yuan, Mao Niu, Jiarui Feng, Yi Lv, Xu-ning Miao, Chenchen Meng, Lingqi Peng, Bo Deng, Li Yan, Jingye Zhu, Weiwei |
| contents | Fast radio bursts (FRBs) are transient signals exhibiting diverse strengths and emission bandwidths. Traditional single-pulse search techniques are widely employed for FRB detection; yet weak, narrow-band bursts often remain undetectable due to low signal-to-noise ratios (SNR) in integrated profiles. We developed DANCE, a detection tool based on cluster analysis of the original spectrum. It is specifically designed to detect and isolate weak, narrow-band FRBs, providing direct visual identification of their emission properties. This method performs density clustering on reconstructed, RFI-cleaned observational data, enabling the extraction of targeted clusters in time-frequency domain that correspond to the genuine FRB emission range. Our simulations show that DANCE successfully extracts all true signals with SNR~>5 and achieves a detection precision exceeding 93%. Furthermore, through the practical detection of FRB 20201124A, DANCE has demonstrated a significant advantage in finding previously undetectable weak bursts, particularly those with distinct narrow-band features or occurring in proximity to stronger bursts. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_04966 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Detecting FRB by DANCE: a method based on DEnsity ANalysis and Cluster Extraction Yuan, Mao Niu, Jiarui Feng, Yi Lv, Xu-ning Miao, Chenchen Meng, Lingqi Peng, Bo Deng, Li Yan, Jingye Zhu, Weiwei High Energy Astrophysical Phenomena Instrumentation and Methods for Astrophysics Fast radio bursts (FRBs) are transient signals exhibiting diverse strengths and emission bandwidths. Traditional single-pulse search techniques are widely employed for FRB detection; yet weak, narrow-band bursts often remain undetectable due to low signal-to-noise ratios (SNR) in integrated profiles. We developed DANCE, a detection tool based on cluster analysis of the original spectrum. It is specifically designed to detect and isolate weak, narrow-band FRBs, providing direct visual identification of their emission properties. This method performs density clustering on reconstructed, RFI-cleaned observational data, enabling the extraction of targeted clusters in time-frequency domain that correspond to the genuine FRB emission range. Our simulations show that DANCE successfully extracts all true signals with SNR~>5 and achieves a detection precision exceeding 93%. Furthermore, through the practical detection of FRB 20201124A, DANCE has demonstrated a significant advantage in finding previously undetectable weak bursts, particularly those with distinct narrow-band features or occurring in proximity to stronger bursts. |
| title | Detecting FRB by DANCE: a method based on DEnsity ANalysis and Cluster Extraction |
| topic | High Energy Astrophysical Phenomena Instrumentation and Methods for Astrophysics |
| url | https://arxiv.org/abs/2511.04966 |