Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Localization of gravitational waves using machine learning   An observation of gravitational waves is a trigger of the multi-messenger
search of an astronomical event. A combination of the data from two or three
gravitational wave telescopes indicates the location of a source and
low-latency data analysis is key to transferring the information to other
telescopes sensitive at different wavelengths. In contrast to the current
method, which relies on the matched-filtering technique, we proposed the use of
machine learning that is much faster and possibly more accurate than matched
filtering. Our machine-learning method is a combination of the method proposed
by Chatterjee {\it et al.} and a method using the temporal convolutional
network. We demonstrate the sky localization of a gravitational-wave source
using four telescopes: LIGO H1, LIGO L1, Virgo, and KAGRA, and compare the
result in the case without KAGRA to examine the positive influence of having
the fourth telescope in the global gravitational-wave network.

32
The categories of this paper are: atom-ph
4
The categories of this paper are: cond-mat
18
The categories of this paper are: econ
11
The categories of this paper are: hep-lat
34
The categories of this paper are: chem-ph
6
The categories of this paper are: astro-ph
1
The categories of this paper are: cs
26
The categories of this paper are: bayes-an
17
The categories of this paper are: q-fin
25
The categories of this paper are: patt-sol
37
The categories of this paper are: supr-con
0
The categories of this paper are: hep-ph
33
The categories of this paper are: plasm-ph
9
The categories of this paper are: nlin
23
The categories of this paper are: solv-int
13
The categories of this paper are: quant-ph