A breakthrough in coding allows a wider set of programs to be decoded using quantum computers with neutral atoms. QuEra Computing and university researchers have developed a method to extend the optimization calculations possible with neutral atom quantum computers. This breakthrough, published in PRX Quantum, expands applications in industries such as logistics and pharmaceuticals, overcoming hardware limitations to solve more complex problems.

QuEra Computing, manufacturer of Aquila, the world’s first and only publicly available neutral-atom quantum computer, recently announced that its research team has discovered a method to perform a wider set of optimization calculations than previously known possible using neutral atomic machines. Atoms The findings in the paper “Quantum Optimization with Arbitrary Coupling Using Rydberg Atom Arrays” were published today. PRX Quantum and the work of QuEra researchers and collaborators at Harvard University and the University of Innsbruck: Minh-Thi Nguyen, Jin-Guo Liu, Jonathan Wurtz, Mykhailo D. Lukin, Sheng-Tao Wang, and Hannes Pichler.

“There is no doubt that today’s news is helping QuEra deliver value to more partners faster. “This helps us get closer to our goals and is an important milestone for the industry,” said Alex Kiesling, CEO of QuEra Computing. “This opens the door to working with more corporate partners who may have logistics needs, from shipping and retail to robotics and other high-tech industries, and we are excited to develop these opportunities.”

Programmable quantum systems such as QuEra offer unique opportunities to test the performance of various quantum optimization algorithms. However, there may be limitations usually imposed by certain hardware limitations. In particular, native qubit coupling for a given platform often limits the class of problems that can be solved. For example, Rydberg arrays of atoms naturally allow solving maximum independent set (MIS) problems, but the encoding itself is limited to pseudo-volume disk graphs.

The results of the paper significantly expand the class of problems that can be solved using Rydberg atomic arrays, overcoming the limitations of geometric graphs mentioned above. Now new class optimization problems can be solved using neutral atom machines. These include maximum independent sets on arbitrary connected graphs and quadratic unconstrained binary optimization (QUBO) problems with arbitrary or constrained connectivity.

This additional feature enables applications in fields such as logistics planning and pharmaceuticals. For example, identifying the most promising early-stage candidate compounds for new pharmaceuticals has long been a challenge. Thanks to the new QuEra coding method, an optimized protein design becomes possible. In this way, machines like the Aquila will be able to help researchers more efficiently identify the best samples for testing. This reduces the resources needed to develop new types of drugs and increases the likelihood of approval. Accordingly, drug manufacturers can achieve higher revenues and lower costs.

Thus, this breakthrough opens the scheme of using Rydberg atomic arrays to solve a wide variety of combinatorial optimization problems using modern quantum computers.