LEESBURG, Virginia, October 05, 2021 (GLOBE NEWSWIRE) – Quantum Computer Inc. (the âCompanyâ or âQCIâ) (QUBT), a leader in bridging the power of classical and quantum computing, today announced research showing that âDomain Wallâ coding – a method of representing Information in quantum computers – performs better than other methods for discrete optimization problems. This breakthrough has had a significant impact on a variety of real-world challenges, such as the traveling salesman problem, which requires choosing an optimal solution from an extremely large number of possibilities. QCI’s technical advisor, Dr. Nick Chancellor, who developed the method and was part of the research team that demonstrated its effectiveness, will present the paper on the D-Wave Qubits 21 conference on Oct 6 at 3:45 p.m. ET.
Coding of domain walls topological defects (if adjacent 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. The British team of Dr. Chancellor, who included other QCI experts, proved that the domain wall method is better than others on annealers like D-Wave and will likely work well on gate-model computers as well. For example, for a problem where discrete variables can take three values, domain wall coding uses two-thirds as many qubits to solve the problem as compared to other methods. It also found results that other coding techniques missed. Dr. Federal Chancellor will present their results and discuss the relevance for optimization problems, such as the distance compensation between cities for a traveling salesman.
Interestingly, they demonstrated how coding interacts with the physics of the quantum processor for better answers, an important and often overlooked consideration. This post, on the QCI blog provides a simple but detailed explanation in English.
“Getting as much out of the early quantum computers as possible is really important given how common discrete vs. binary problems are in the real world,” said Dr. Nick Chancellor, who is also a research fellow at Durham University, “This innovation is an important step in improving our skills, especially given the value we have found using this coding. It has improved in every way that we could think of for critical problems. “
“Today’s first innovation in domain wall coding increases the size of a problem a quantum computer can solve by 30 times,” said Rebel Brown, VP, Strategy & Marketing, QCI. “Since quantum computers scale the number of qubits they support, we expect these and other innovations at QCI to significantly accelerate the time to realizable solutions to production problems with Qatalyst and quantum systems.”
Most real-world optimization problems involve discrete variables vs. binary decisions. Consider the transportation route where a truck can take one of three roads; Microchip design that allows a component to be placed in four locations; Planning an event that can take place at seven times, or choosing the best of ten locations to build a facility. While the choices are often not binary, traditional computers tend to be. Discrete-to-binary encodings like the domain wall are very useful in solving real-world problems that require discrete answers with quantum computers.
A paper describing the study is on the ArXiv.org Preprint server and is also subjected to a peer review.
About Quantum Computing Inc.
Quantum Computing Inc. (QCI) (QUBT) is focused on adding value to quantum computing for real business solutions. The company’s flagship product, Qatalyst, is the first software that combines the power of classical and quantum computing, hides complexity and enables SMEs to solve complex computing problems today. QCI’s team of experts in finance, computing, security, math and physics has more than a century of experience with complex technologies; from leading supercomputing innovations to massively parallel programming to security that protects nations. Connect to QCI LinkedIn and @QciQuantum on twitter. For more information on QCI, see www.quantumcomputinginc.com.
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