Automated Transient detection and classification in the context of ILMT

peer reviewedIn the era of sky surveys like PTF, ZTF and the upcoming Vera Rubin Observatory and ILMT, a plethora of imaging data will become available. ZTF scans the sky with a field of view of 48 deg2 and the upcoming Rubin Observatory will have a FoV of 9.6 deg2 but with much larger aperture. The 4m ILMT covers a 22’ wide strip. Transient detection requires all these imaging data to be processed through a Difference Imaging Algorithm and subsequent identification and classification. The ILMT is also expected to discover several known and unknown astrophysical objects including transients. Here, we propose an image subtraction algorithm and a convolutional neural network based automated transient discovery system which will be integrated in the ILMT transient detection and classification pipeline in the future