Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Identifying the nature of the QCD transition in relativistic collision
  of heavy nuclei with deep learning   Using deep convolutional neural network (CNN), the nature of the QCD
transition can be identified from the final-state pion spectra from hybrid
model simulations of heavy-ion collisions that combines a viscous hydrodynamic
model with a hadronic cascade "after-burner". Two different types of equations
of state (EoS) of the medium are used in the hydrodynamic evolution. The
resulting spectra in transverse momentum and azimuthal angle are used as the
input data to train the neural network to distinguish different EoS. Different
scenarios for the input data are studied and compared in a systematic way. A
clear hierarchy is observed in the prediction accuracy when using the
event-by-event, cascade-coarse-grained and event-fine-averaged spectra as input
for the network, which are about 80%, 90% and 99%, respectively. A comparison
with the prediction performance by deep neural network (DNN) with only the
normalized pion transverse momentum spectra is also made. High-level features
of pion spectra captured by a carefully-trained neural network were found to be
able to distinguish the nature of the QCD transition even in a simulation
scenario which is close to the experiments.

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The categories of this paper are: math-ph
5
The categories of this paper are: gr-qc
1
The categories of this paper are: cs
32
The categories of this paper are: atom-ph
2
The categories of this paper are: math
30
The categories of this paper are: q-alg
7
The categories of this paper are: hep-th
26
The categories of this paper are: bayes-an
21
The categories of this paper are: adap-org
18
The categories of this paper are: econ
24
The categories of this paper are: dg-ga
20
The categories of this paper are: acc-phys
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The categories of this paper are: supr-con
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The categories of this paper are: q-fin
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The categories of this paper are: funct-an
33
The categories of this paper are: plasm-ph