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[转载]自然杂志:通过量子机器学习寻找希格斯玻色子

已有 317 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|文章来源:转载

       D-Wave系统(量子计算机系统)显示量子计算机可以学会在堆积如山的海量数据中发现粒子的特征,但目前还没有超过常规方法。

       物理学家们一直在努力开发能够使用量子力学技巧加速计算的量子计算机。但他们也希望这样的量子计算机能够回报人们的青睐,帮助他们发现新的自然规律。

       现在,一个研究团队已经表明量子电路可以通过学习从原子碰撞实验的大量数据中筛选数据以搜寻一个新的粒子。他们的验证原理的研究使用D-Wave公司的量子计算机,在处理现在熟悉的希格斯玻色子时,并没有提供比传统技术明显的优势。但是研究者们认为,当数据量增长到更大时,量子机器学习将会在未来的实验中产生影响。他们的研究发表在10月18日的自然杂志上。


原文:

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.


来源:http://www.nature.com/news/quantum-machine-goes-in-search-of-the-higgs-boson-1.22860?WT.mc_id=Weibo_NatureNews_20171020_CONT

Solving a Higgs optimization problem with quantum annealing for machine learning

http://www.nature.com/nature/journal/v550/n7676/full/nature24047.html






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