Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Efficient Use of Quantum Linear System Algorithms in Interior Point
  Methods for Linear Optimization   Quantum computing has attracted significant interest in the optimization
community because it potentially can solve classes of optimization problems
faster than conventional supercomputers. Several researchers proposed quantum
computing methods, especially Quantum Interior Point Methods (QIPMs), to solve
convex optimization problems, such as Linear Optimization, Semidefinite
Optimization, and Second-order Cone Optimization problems. Most of them have
applied a Quantum Linear System Algorithm at each iteration to compute a Newton
step. However, using quantum linear solvers in QIPMs comes with many
challenges, such as having ill-conditioned systems and the considerable error
of quantum solvers. This paper investigates how one can efficiently use quantum
linear solvers in QIPMs. Accordingly, an Inexact Infeasible Quantum Interior
Point Method is developed to solve linear optimization problems. We also
discuss how can we get an exact solution by Iterative Refinement without
excessive time of quantum solvers. Finally, computational results with QISKIT
implementation of our QIPM using quantum simulators are analyzed.

36
The categories of this paper are: cmp-lg
8
The categories of this paper are: hep-ex
24
The categories of this paper are: dg-ga
1
The categories of this paper are: cs
10
The categories of this paper are: q-bio
11
The categories of this paper are: hep-lat
32
The categories of this paper are: atom-ph
29
The categories of this paper are: funct-an
14
The categories of this paper are: math-ph
27
The categories of this paper are: comp-gas
34
The categories of this paper are: chem-ph
30
The categories of this paper are: q-alg
31
The categories of this paper are: ao-sci
22
The categories of this paper are: chao-dyn
17
The categories of this paper are: q-fin
25
The categories of this paper are: patt-sol