Missing building block for quantum optimization

image: The Innsbruck Quantum Optimization Team: Kilian Ender, Clemens Dlaska, Wolfgang Lechner, Rick van Bijnen, Andreas Kruckenhauser, Glen Bigan Mbeng (left to right)
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Credit: Uni Innsbruck

The development of quantum computers continues all over the world and there are various concepts on how computing using the properties of the quantum world can be implemented. Many of them have already advanced experimentally in areas that can no longer be emulated on conventional computers. But the technologies have not yet reached the point where they can be used to solve larger computational problems. Therefore, researchers are currently looking for applications that can be implemented on existing platforms. “We are looking for tasks that we can compute on existing hardware,” says Rick van Bijnen of the Institute for Quantum Optics and Quantum Information at the Austrian Academy of Sciences in Innsbruck. A team around Van Bijnen and the Lechner research group now proposes a method for solving optimization problems using neutral atoms.

Software Solutions

To develop scientifically and industrially relevant applications for existing quantum hardware in the near future, researchers are looking for special algorithms that structurally match the strengths of a quantum platform. “This co-design of algorithms and experimental platforms allows these systems to operate without error correction, which is still difficult to achieve today,” explains Wolfgang Lechner from the Department of Theoretical Physics at the University of Innsbruck. The physicists plan to implement their optimization algorithm on neutral atoms trapped and arranged in optical tweezers. They can be programmed through the interaction of highly excited Rydberg states. To avoid the limitations of previous approaches, physicists do not implement the algorithm directly, but use the so-called parity architecture, a scalable, problem-independent hardware design for combinatorial optimization problems, which Wolfgang Lechner developed with Phillip Hauke ​​and Peter Zoller. in Innsbruck. In this way, the optimization algorithm requires only problem-dependent single-qubit operations and problem-independent four-qubit operations. Finding a straightforward and simple implementation for these four-qubit operations was the biggest challenge for the Innsbruck researchers. For this purpose, they designed a special quantum gate. “We implemented the algorithm directly in the language of the experiment,” explains first author Clemens Dlaska. “Thus, the algorithm can be performed on current quantum hardware by simply optimizing the duration of laser pulses in a feedback loop.”

Arbitrary scalability

With the proposed concept, the performance of existing quantum hardware in solving relevant optimization problems can be studied for sizeable problems currently impossible to simulate on classical supercomputers. The fact that the hardware platform and the software solution can be extended to a large extent without modifications is an important advantage of the new method.

The Innsbruck team has just presented its new concept in Physical examination letters. The research was funded by the Austrian Science Fund FWF, the European Union under the PASQuanS project and the Hauser-Raspe Foundation.

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About Mariel Baker

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