Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Machine Learning Methods for Track Classification in the AT-TPC   We evaluate machine learning methods for event classification in the
Active-Target Time Projection Chamber detector at the National Superconducting
Cyclotron Laboratory (NSCL) at Michigan State University. An automated method
to single out the desired reaction product would result in more accurate
physics results as well as a faster analysis process. Binary and multi-class
classification methods were tested on data produced by the $^{46}$Ar(p,p)
experiment run at the NSCL in September 2015. We found a Convolutional Neural
Network to be the most successful classifier of proton scattering events for
transfer learning. Results from this investigation and recommendations for
event classification in future experiments are presented.

10
The categories of this paper are: q-bio
11
The categories of this paper are: hep-lat
37
The categories of this paper are: supr-con
36
The categories of this paper are: cmp-lg
19
The categories of this paper are: eess
21
The categories of this paper are: adap-org
24
The categories of this paper are: dg-ga
27
The categories of this paper are: comp-gas
32
The categories of this paper are: atom-ph
16
The categories of this paper are: stat
26
The categories of this paper are: bayes-an
4
The categories of this paper are: cond-mat
17
The categories of this paper are: q-fin
25
The categories of this paper are: patt-sol
7
The categories of this paper are: hep-th
29
The categories of this paper are: funct-an