The "Nine Chapters" Prototype Successfully Solves Graph Theory Problems
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Science and Technology Daily, Hefei, June 8 (reporter Wu Changfeng) On the 8th, the reporter learned from the University of Science and Technology of China that the research team composed of Pan Jianwei, Lu Chaoyang, Liu Naile, etc., based on the "nine chapter" optical quantum computing prototype, completed the solution of two types of graph theory problems, "dense subgraph" and "Max Haf"
Science and Technology Daily, Hefei, June 8 (reporter Wu Changfeng) On the 8th, the reporter learned from the University of Science and Technology of China that the research team composed of Pan Jianwei, Lu Chaoyang, Liu Naile, etc., based on the "nine chapter" optical quantum computing prototype, completed the solution of two types of graph theory problems, "dense subgraph" and "Max Haf". Through experiments and theoretical research, the acceleration brought by the "nine chapter" processing of these two types of graph theory problems to the search algorithm was studied, And the dependence of this acceleration on the scale of the problem and experimental noise. This research achievement is the first experimental research on problems with application value on a photon computing prototype with Quantum supremacy. The relevant papers have recently been published in the international academic journal "Physics Review Letters" in the form of "editorial recommendations" and have been featured on physics websites.
Recently, while Pan Jianwei's team continues to develop a higher quality and more expandable optical quantum computing prototype, they have carried out the research and exploration of applying the Gaussian Bose sampling task carried out in the "Nine Chapters" to graph theory problems.
In this research, researchers first used the Gaussian Bose sampling implemented in the "Nine Chapters" to accelerate the solution of graph theory problems by the random search algorithm and Simulated annealing algorithm. Researchers used over 200000 80 photon coincidence counting samples in the experiment, which is about 180 million times faster than the world's fastest supercomputer using the current optimal classical algorithm to accurately simulate the experiment.
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