
AsianScientist (Apr. 24, 2019) – Scientists in Japan have developed an algorithm that allows a Canadian-designed quantum computer to more efficiently identify the best solution for complicated problems. Their findings are published in Scientific Reports.
Quantum computing takes advantage of the ability of subatomic particles to exist in more than one state at the same time. It is expected to take modern-day computing to the next level by enabling the processing of more information in less time.
The D-Wave quantum annealer, developed by a Canadian company, employs the concepts of quantum physics to solve ‘combinatorial optimization problems.’ A typical example of this sort of problem is: ‘Given a list of cities and the distances between each pair of cities, what is the shortest possible route that visits each city and returns to the origin city?’ Businesses and industries face a large range of similarly complex problems in which they want to find the optimal solution among many possible ones using the least amount of resources.
In the present study, scientists led by Assistant Professor Masayuki Ohzeki of Japan’s Tohoku University collaborated with global automotive components manufacturer Denso Corporation and other colleagues to develop an algorithm that improves the D-Wave quantum annealer’s ability to solve combinatorial optimization problems.
The algorithm works by partitioning an original large problem into a group of subproblems. The D-Wave annealer then iteratively optimizes each subproblem to eventually solve the original larger one. The Tohoku University algorithm improves on another algorithm using the same concept by allowing the use of larger subproblems, ultimately allowing it to find a greater number of optimal solutions more efficiently.
“The proposed algorithm is also applicable to the future version of the D-Wave quantum annealer, which contains many more quantum bits, or qubits,” said Ohzeki. “As the number of qubits mounted in the D-Wave quantum annealer increases, we will be able to obtain even better solutions,” he said.
The article can be found at: Okada et al. (2019) Improving Solutions by Embedding Larger Subproblems in a D-Wave Quantum Annealer.
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Source: Tohoku University; Photo: Pixabay.
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