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Quantum Computing Inc. Demonstrates that “Domain-Wall” Encoding Delivers the Best Performance for Solving Real-world Optimization Problems
Research to be Presented at D-Wave Qubits Conference Shows the Impact of Physics on Information LEESBURG, Va., Oct. 05, 2021 (GLOBE NEWSWIRE) -- Quantum
About this update from Quantum Computing Inc.
[{"type":"text","content":"Research to be Presented at D-Wave Qubits Conference Shows the Impact of Physics on Information\nLEESBURG, Va., Oct. 05, 2021 (GLOBE NEWSWIRE) -- Quantum Computing Inc. (the “company” or “QCI”) (Nasdaq: QUBT), a leader in bridging the power of classical and quantum computing, today announced research that provides evidence that “domain-wall” encoding— a method for representing information in quantum computers — delivers better performance for discrete optimization problems than other methods. This breakthrough has significant implications for a wide range of real-world challenges, such as the traveling salesperson problem, which requires choosing an optimal solution from an extremely large number of possibilities. QCI Technical Advisor Dr. Nick Chancellor, who developed the method, and was part of the research team that demonstrated its efficacy, will present the paper at the D-Wave Qubits 21 conference on October 6 at 3:45 PM ET. Domain-wall encoding leverages topological defects (when adjoining structures are out of phase) and Ising spin chains (discrete variables that represent magnetic dipole spin moments) to efficiently represent information in quantum computing systems. Dr. Chancellor’s UK team, which also included other QCI experts, proved that the domain-wall method is better than others on annealers, like D-Wave’s, and will also likely excel for gate model computers. For example, in a problem where discrete variables can take three values, domain wall-encoding uses two thirds as many qubits to solve the problem vs. other methods. It also found results that other encoding techniques missed. Dr. Chancellor will present their findings and discuss the relevance for optimization problems, such as reconciling the distance between cities for a traveling salesperson. Interestingly, they demonstrated how encoding interacts with the physics of the quantum processor to get better answers, an important and often overlooked consideration. This post, on the QCI blog provides a plain English but detailed explanation. \"It is really important to get as much as we can out of early quantum computers, given how common discrete vs. binary problems are in the real world,” said Dr. Nick Chancellor, who is also a research and teaching fellow at Durham University. “This innovation is an important step to advance our capabilities, especially gi...