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@ARTICLE{Fiorelli:906298,
author = {Fiorelli, Eliana and Lesanovsky, Igor and Müller, Markus},
title = {{P}hase diagram of quantum generalized {P}otts-{H}opfield
neural networks},
journal = {New journal of physics},
volume = {24},
issn = {1367-2630},
address = {[London]},
publisher = {IOP},
reportid = {FZJ-2022-01352},
pages = {033012},
year = {2022},
abstract = {We introduce and analyze an open quantum generalization of
the q-state Potts-Hopfield neural network, which is an
associative memory model based on multi-level classical
spins. The dynamics of this many-body system is formulated
in terms of a Markovian master equation of Lindblad type,
which allows to incorporate both probabilistic classical and
coherent quantum processes on an equal footing. By employing
a mean field description we investigate how classical
fluctuations due to temperature and quantum fluctuations
effectuated by coherent spin rotations affect the ability of
the network to retrieve stored memory patterns. We construct
the corresponding phase diagram, which in the low
temperature regime displays pattern retrieval in analogy to
the classical Potts-Hopfield neural network. When increasing
quantum fluctuations, however, a limit cycle phase emerges,
which has no classical counterpart. This shows that quantum
effects can qualitatively alter the structure of the
stationary state manifold with respect to the classical
model, and potentially allow one to encode and retrieve
novel types of patterns.},
cin = {PGI-2},
ddc = {530},
cid = {I:(DE-Juel1)PGI-2-20110106},
pnm = {5224 - Quantum Networking (POF4-522)},
pid = {G:(DE-HGF)POF4-5224},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000766853300001},
doi = {10.1088/1367-2630/ac5490},
url = {https://juser.fz-juelich.de/record/906298},
}