Speaker
Takahiro S Yamamoto
(Nagoya University)
Description
Convolutional neural networks (CNN) have an advantage in computational cost for the search of continuous gravitational waves (CGWs). We are developing a deep learning method for CGW searches. In our previous work, we proposed a method in which the doubly Fourier transformed strain data are used as inputs of CNN and assessed the effects of non-Gaussian artifacts. In this talk, we will talk about the application of our work for the directed searches of CGWs.
Primary author
Takahiro S Yamamoto
(Nagoya University)
