Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Beating classical heuristics for the binary paint shop problem with the
  quantum approximate optimization algorithm   The binary paint shop problem (BPSP) is an APX-hard optimization problem of
the automotive industry. In this work, we show how to use the Quantum
Approximate Optimization Algorithm (QAOA) to find solutions of the BPSP and
demonstrate that QAOA with constant depth is able to beat classical heuristics
on average in the infinite size limit $n\rightarrow\infty$. For the BPSP, it is
known that no classical algorithm can exist which approximates the problem in
polynomial runtime. We introduce a BPSP instance which is hard to solve with
QAOA, and numerically investigate its performance and discuss QAOA's ability to
generate approximate solutions. We complete our studies by running first
experiments of small-sized instances on a trapped-ion quantum computer through
AWS Braket.

23
The categories of this paper are: solv-int
18
The categories of this paper are: econ
0
The categories of this paper are: hep-ph
37
The categories of this paper are: supr-con
21
The categories of this paper are: adap-org
19
The categories of this paper are: eess
34
The categories of this paper are: chem-ph
10
The categories of this paper are: q-bio
26
The categories of this paper are: bayes-an
24
The categories of this paper are: dg-ga
14
The categories of this paper are: math-ph
9
The categories of this paper are: nlin
35
The categories of this paper are: mtrl-th
25
The categories of this paper are: patt-sol
31
The categories of this paper are: ao-sci
28
The categories of this paper are: alg-geom