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已有 1113 次阅读 2017-10-22 13:51 |个人分类:量子机器学习|系统分类:科研笔记|关键词:量子机器学习,量子计算,机器学习,D-Wave,希格斯玻色子| 量子计算, 量子机器学习, 机器学习, D-Wave, 希格斯玻色子 |文章来源:转载





DWave system shows quantum computers can learn to detect particle signatures in mountains of data, but doesn’t outpace conventional methods — yet.

Physicists have been working hard to develop machines that can use quantum mechanical tricks to speed up computation. But they also hope that such quantum computers can return the favour and help them to discover new laws of nature.

Now, a team has shown that a quantum circuit can learn to sift through reams of data from atom-smashing experiments in search of a new particle. Their proof-of-principle study — performed using a machine built by quantum-computing company D-Wave working on the now-familiar case of the Higgs boson — does not yet provide a clear advantage over conventional techniques. But the authors say that quantum machine learning could make a difference in future experiments, when the amounts data will grow even larger. Their research was published on 18 October in Nature.


Solving a Higgs optimization problem with quantum annealing for machine learning



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