The Solar System Notification Alert Processing System (SNAPS): Asteroid Population Outlier Detection
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arXiv
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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866914879152062464 |
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| author | Gowanlock, Michael Trilling, David E. Kramer, Daniel Chernyavskaya, Maria McNeill, Andrew |
| author_facet | Gowanlock, Michael Trilling, David E. Kramer, Daniel Chernyavskaya, Maria McNeill, Andrew |
| contents | The Solar System Notification Alert Processing System (SNAPS) is a ZTF and Rubin Observatory alert broker that will send alerts to the community regarding interesting events in the Solar System. SNAPS is actively monitoring Solar System objects and one of its functions is to compare objects (primarily main belt asteroids) to one another to find those that are outliers relative to the population. In this paper, we use the SNAPShot1 dataset which contains 31,693 objects from ZTF and derive outlier scores for each of these objects. SNAPS employs an unsupervised approach; consequently, to derive outlier rankings for each object, we propose four different outlier metrics such that we can explore variants of outlier scores and add confidence to outlier rankings. We also provide outlier scores for each object in each permutation of 15 feature spaces, between 2 and 15 features, which yields 32,752 total feature spaces. We show that we can derive population outlier rankings each month at Rubin Observatory scale using four Nvidia A100 GPUs, and present several avenues of scientific investigation that can be explored using population outlier detection. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_20176 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | The Solar System Notification Alert Processing System (SNAPS): Asteroid Population Outlier Detection Gowanlock, Michael Trilling, David E. Kramer, Daniel Chernyavskaya, Maria McNeill, Andrew Earth and Planetary Astrophysics Instrumentation and Methods for Astrophysics The Solar System Notification Alert Processing System (SNAPS) is a ZTF and Rubin Observatory alert broker that will send alerts to the community regarding interesting events in the Solar System. SNAPS is actively monitoring Solar System objects and one of its functions is to compare objects (primarily main belt asteroids) to one another to find those that are outliers relative to the population. In this paper, we use the SNAPShot1 dataset which contains 31,693 objects from ZTF and derive outlier scores for each of these objects. SNAPS employs an unsupervised approach; consequently, to derive outlier rankings for each object, we propose four different outlier metrics such that we can explore variants of outlier scores and add confidence to outlier rankings. We also provide outlier scores for each object in each permutation of 15 feature spaces, between 2 and 15 features, which yields 32,752 total feature spaces. We show that we can derive population outlier rankings each month at Rubin Observatory scale using four Nvidia A100 GPUs, and present several avenues of scientific investigation that can be explored using population outlier detection. |
| title | The Solar System Notification Alert Processing System (SNAPS): Asteroid Population Outlier Detection |
| topic | Earth and Planetary Astrophysics Instrumentation and Methods for Astrophysics |
| url | https://arxiv.org/abs/2405.20176 |