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@ARTICLE{Headley:1010627,
author = {Headley, David and Müller, Thorge and Martin, Ana and
Solano, Enrique and Sanz, Mikel and Wilhelm-Mauch, Frank},
title = {{A}pproximating the quantum approximate optimization
algorithm with digital-analog interactions},
journal = {Physical review / A},
volume = {106},
number = {4},
issn = {2469-9926},
address = {Woodbury, NY},
publisher = {Inst.},
reportid = {FZJ-2023-03142},
pages = {042446},
year = {2022},
abstract = {The quantum approximate optimization algorithm was proposed
as a heuristic method for solving combinatorial optimization
problems on near-term quantum computers and may be among the
first algorithms to perform useful computations in the
postsupremacy, noisy, intermediate-scale era of quantum
computing. In this work we exploit the recently proposed
digital-analog quantum computation paradigm, in which the
versatility of programmable universal quantum computers and
the error resilience of quantum simulators are combined to
improve platforms for quantum computation. We show that the
digital-analog paradigm is suited to the quantum approximate
optimization algorithm due to the algorithm's variational
resilience against the coherent errors introduced by the
scheme. By performing large-scale simulations and providing
analytical bounds for its performance in devices with finite
single-qubit operation time we observe regimes of
single-qubit operation speed in which the considered
variational algorithm provides a significant improvement
over nonvariational counterparts in the digital-analog
scheme.},
cin = {PGI-12},
ddc = {530},
cid = {I:(DE-Juel1)PGI-12-20200716},
pnm = {5215 - Towards Quantum and Neuromorphic Computing
Functionalities (POF4-521)},
pid = {G:(DE-HGF)POF4-5215},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000883685200004},
doi = {10.1103/PhysRevA.106.042446},
url = {https://juser.fz-juelich.de/record/1010627},
}