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Spin glass Physics with trapped ions simulation to solve complex problems

The spin glasses describe collections of small magnets interacting randomly among themselves. Image: ICFO

The spin glasses describe collections of small magnets interacting randomly among themselves. Image: ICFO

31/05/2016

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Researchers at the University of Barcelona and the Institute of Photonic Sciences (ICFO) have proved that quantum simulations with trapped ions could help solve complex computational problems.

One of the discoveries of the quantum information theory is that it allows solving problems in a more efficient way than using any other classic known algorithm. One of these problems is the number-partitioning, which divides several numbers of each set into two subgroups, leaving the total amount of numbers equal. Although it may seem a simple task, it is a rather difficult problem to solve with classical computers.

These mathematic problems can be usually linked to a physical model, which allows solving the original problem by finding the minimum energy state of the system. In this case, the used physical systems are spin glasses, which describe collections of tiny magnets randomly interacting with each other.

In a recent study published in Nature Communications, by Bruno Julià Díaz, researcher at the Department of Quantum Physics and Astrophysics of the Faculty of Physics, and the researchers of ICFO Tobias Grass, David Raventós and Christian Gogolin, led by ICREA Professor Maciej Lewenstein, it is shown how to simulate spin glasses with trapped ions.

The idea was proposed by the research team and it shows how to solve the number-partitioning problem by applying a technique called “quantum annealing”. The aim is to get to the lower energy state of the system using the quantum properties of the matter. The implementation of this method is possible thanks to the modern techniques of trapping, cooling and manipulation of ions.

 

Article reference:

T. Grass, D. Raventós, B. Julià Díaz, C. Gogolin, M. Lewenstein. “Quantum annealing for the number-partitioning problem using a tunable spin glass of ions”. Nature Communications, 7, May 2016. Doi:10.1038/ncomms11524

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