| Name: | Kumar Pranshu |
| Affiliation: | Aryabhatta Research Institute of Observational Sciences, Nainital |
| Conference ID : | ASI2023_289 |
| Title : | Automated transient detection in the context of International Liquid Mirror Telescope |
| Authors : | Kumar Pranshu, Kuntal Misra, Bhavya Ailawadhi, Naveen Dukiya, Paul Hickson, Brajesh Kumar, Vibhor Negi, Bikram Pradhan, Jean Surdej |
| Mode of Presentation: | Poster |
| Abstract Category : | Instrumentation and Techniques |
| Abstract : | In the era of sky surveys like the Palomar Transient Factory (PTF), the Zwicky Transient Facility (ZTF), and the upcoming Vera Rubin Observatory (VRO) and the International Liquid Mirror Telescope (ILMT), a plethora of astronomical data is expected. The ZTF scans the sky with a FoV of 48 deg2 and the upcoming VRO will have a FoV of 9.6 deg2 but with much larger aperture. The FoV of the 4 m ILMT covers a 22’ wide strip. Detection of transient sources require the images to be processed through a Difference Imaging Algorithm (DIA) and subsequent identification and classification. With its limiting magnitude of 22 in g’ filter, the ILMT is expected to discover several known and unknown stellar sources including transients. We propose an image subtraction algorithm and a Convolutional Neural Network (CNN) based automated transient discovery system in order to detect and identify these sources. This system will be integrated in the ILMT transient detection pipeline in future. |
