Expanding commercial reach! Riedberg atomic array enables quantum optimized programming for arbitrary connectivity
Recently, the QuEra Computing team reported a broader approach to optimization computation than is known to be possible using neutral atomic machines. The latest problems that can be solved include maximum weighted independent set problems, quadratic unconstrained binary optimization problems, integer decomposition, and more; this provides a blueprint for solving a wider range of combinatorial optimization problems using Riedberg atomic arrays, with promising applications in transportation retail, robotics, logistics, and many more high-tech fields.
Limitations exist in programmable quantum systems
The experimental team's paper was published in the journal PRX QUANTUM under the title "Quantum optimization of arbitrary connectivity using Reedeburg atomic arrays" [1]. It is worth noting that in addition to the QuEra research team, the collaborators include Jin-Guo Liu, a Chinese scholar at Harvard University.
"There is no doubt that today's news helps QuEra deliver value to more partners faster." Alex Keesling, CEO of QuEra Computing, said [2], "This helps us get closer to our goals and also marks an important milestone for this industry. Opening the door for us to work with more enterprise partners who may have logistics needs, from transportation and retail to robotics and other high-tech areas, we are very excited about fostering these opportunities."
Steps to solve various optimization problems using programmable Riedberg atomic arrays.
Programmable quantum systems, such as the kind offered by QuEra, offer unique possibilities for testing the performance of various quantum optimization algorithms. However, there are some limitations to this: these are often set by specific hardware constraints. Specifically, the native connectivity of quantum bits for a particular platform (native connectivity) often limits the class of problems that can be solved. For example, the Riedberg atomic array allows solving the maximum independent set (MIS) problem, but the native encoding is restricted to unit-disk graphs.
The architecture of the unit-disk graph-maximum-weight independent set (UDG-MWIS) mapping in the three example problems.
Extended problem categories solved: logistics, pharmaceutical ......
The results of this study overcome the above geometric limitations and greatly expand the class of problems that can be solved with the Riedberg atomic array.
New classes of optimization problems can now be solved by neutral-atom quantum computers. These include problems such as maximum independent sets on graphs with arbitrary connectivity, and quadratic unconstrained binary optimization (QUBO) problems with arbitrary or restricted connectivity.
This additional functionality allows for applications in areas such as logistics scheduling and pharmaceuticals. For example, identifying the most promising candidate ingredients for new drugs at an early stage has long been a daunting task. With QuEra's new coding method, optimizing protein design will become a possibility. In this way, similar machines like QuEra's neutral-atom quantum computer Aquila will also be able to support researchers in more efficiently identifying the best samples to move forward in trials. This reduces the resources required for the development process of novel drugs and increases the likelihood of approval. As a result, drug manufacturers may see increased revenues and reduced costs [3].
Not only that, but this breakthrough provides a blueprint for solving various combinatorial optimization problems using Riedberg arrays.
Reference links
[1]https://arxiv.org/pdf/2209.03965.pdf
[2]https://thequantuminsider.com/2023/02/14/encoding-technique-can-help-neutral-atom-quantum-computers-solve-wider-set-of-applications/[3]https://phys.org/news/2023-02-encoding-breakthrough-wider-applications-neutral-atom.html
