Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Quantum State Discrimination Using Noisy Quantum Neural Networks   Near-term quantum computers are noisy, and therefore must run algorithms with
a low circuit depth and qubit count. Here we investigate how noise affects a
quantum neural network (QNN) for state discrimination, applicable on near-term
quantum devices as it fulfils the above criteria. We find that when simulating
gradient calculation on a noisy device, a large number of parameters is
disadvantageous. By introducing a new smaller circuit ansatz we overcome this
limitation, and find that the QNN performs well at noise levels of current
quantum hardware. We also show that networks trained at higher noise levels can
still converge to useful parameters. Our findings show that noisy quantum
computers can be used in applications for state discrimination and for
classifiers of the output of quantum generative adversarial networks.

22
The categories of this paper are: chao-dyn
6
The categories of this paper are: astro-ph
26
The categories of this paper are: bayes-an
11
The categories of this paper are: hep-lat
2
The categories of this paper are: math
36
The categories of this paper are: cmp-lg
10
The categories of this paper are: q-bio
25
The categories of this paper are: patt-sol
17
The categories of this paper are: q-fin
18
The categories of this paper are: econ
14
The categories of this paper are: math-ph
19
The categories of this paper are: eess
0
The categories of this paper are: hep-ph
1
The categories of this paper are: cs
15
The categories of this paper are: nucl-ex
16
The categories of this paper are: stat