Highly Variable Quasar Candidates Selected from 4XMM-DR13 with Machine Learning
We present a sample of 12 quasar candidates with highly variable soft X-ray emission, selected from the fourth XMM-Newton Serendipitous Source Catalog (4XMM-DR13), using random forest (RF). Optical to mid-IR photometric data for the 4XMM-DR13 sources were obtained by correlating the sample with the...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IOP Publishing
2025-01-01
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| Series: | The Astrophysical Journal |
| Subjects: | |
| Online Access: | https://doi.org/10.3847/1538-4357/adc7b8 |
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