Abstract
Exploiting quantum properties to outperform classical ways of information processing is an outstanding goal of modern physics. A promising route is quantum simulation, which aims at implementing relevant and computationally hard problems in controllable quantum systems. Here we demonstrate that in a trapped ion setup, with present day technology, it is possible to realize a spin model of the Mattis-type that exhibits spin glass phases. Our method produces the glassy behaviour without the need for any disorder potential, just by controlling the detuning of the spin-phonon coupling. Applying a transverse field, the system can be used to benchmark quantum annealing strategies which aim at reaching the ground state of the spin glass starting from the paramagnetic phase. In the vicinity of a phonon resonance, the problem maps onto number partitioning, and instances which are difficult to address classically can be implemented.
Highlights
Exploiting quantum properties to outperform classical ways of information processing is an outstanding goal of modern physics
Hopfield model describes brain functions such as associative memory by an interacting spin system[1]. This directly relates to computer and information sciences, where pattern recognition or error-free coding can be achieved using spin models[2]
Many optimization problems, like number partitioning or the travelling salesman problem, belonging to the class of NP-hard problems, can be mapped onto the problem of finding the ground state of a specific spin model[3,4]. This implies that solving spin models is a task for which no general efficient classical algorithm is known to exist
Summary
Exploiting quantum properties to outperform classical ways of information processing is an outstanding goal of modern physics. Hopfield model describes brain functions such as associative memory by an interacting spin system[1] This directly relates to computer and information sciences, where pattern recognition or error-free coding can be achieved using spin models[2]. Many optimization problems, like number partitioning or the travelling salesman problem, belonging to the class of NP-hard problems, can be mapped onto the problem of finding the ground state of a specific spin model[3,4]. This implies that solving spin models is a task for which no general efficient classical algorithm is known to exist. A controversial development, supposed to provide an exact numerical understanding of spin glasses, regards the
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