Poster abstract details

Image subtraction is a fundamental method for transient detection in time domain astronomy. Since point spread function (PSF) of images from ground-based telescopes is generally varying, mainly due to non-constant seeing condition, thus image subtraction is non-trivial for effective transient detection, for example in SN survey. Some convolution-based algorithm (like Alard & Lupton (1998) and Miller (2008)) has long been applied to solve such problems, and also new statistics-based optimal subtraction algorithm (Zackay, Ofek (2016)) was suggested to do it with better transient candidates identification.

Here we developed an algorithm of image subtraction in Fourier Space, where GPUs would be naturally able to speed up the underlying FFTs processes and make it to be a robust method for BIG astronomical time-domain data. It shows excellent performance especially for crowded field like LMC center images, and we have applied the algorithm for latest DECam SN-survey data.