期刊文献+

量子信息技术对银行的挑战和机遇 被引量:4

The Challenges and Opportunities of Quantum Information Technology to Banks
下载PDF
导出
摘要 随着量子信息技术快速发展,世界主要科技强国及企业纷纷加大量子信息技术研发力度,量子通信、量子计算等技术应用已走向实用化,量子定位、量子存储等技术已在实验基础上取得突破性成就。本文以银行为主体,阐述了量子信息技术部分领域发展现状,首先分析量子计算对银行的挑战及应对方法,继而分析量子通信、量子计算、量子存储、量子定位技术带给银行的机遇及应用困难,并据此提出银行的量子信息技术应用策略。 As quantum information technology developed fast in the past years, the power and technology companies pay much attention on it, quantum communication and quantum computation are coming into application, quantum position and quantum memory are making groundbreaking achievements. The article focuses on banks and introduces the development of branches of quantum information technology. Based on this, we firstly analysis the threats by quantum computation and solutions are also presented. Then, we analysis the application prospects of them. In the end, suggestions for banks are given.
出处 《浙江金融》 2018年第10期3-10,共8页 Zhejiang Finance
关键词 银行 量子信息 量子通信 量子计算 Bank Quantum Information Technology Quantum Communication Quantum Computation
  • 相关文献

参考文献4

二级参考文献18

  • 1郭光灿.量子信息科学——一个令人惊奇的新兴领域[J].中国科学院院刊,2007,22(1):57-60. 被引量:8
  • 2Kollar D, Friedman N. Probabilistic graphical models: principles and techniques. Cambridge: The MIT Press, 2009.
  • 3Balasubramanian M, Schwartz E L. The isomap algorithm and topological stability. Science, 2002, 295: 7.
  • 4Roweis S T, Saul L K. Nonlinear dimensionality reduction by locally linear embedding. Science, 2000, 290: 2323-2326.
  • 5Mayer-Schnberger V, Cukier K. 大数据时代. 盛杨燕, 周涛, 译. 杭州: 浙江人民出版社, 2013.
  • 6Wang F, Zhao B, Zhang C. Linear time maximum margin clustering. IEEE Trans Neural Netw, 2010, 21: 319-332.
  • 7Deng J, Dong W, Socher R, et al. ImageNet: a large-scale hierarchical image database. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. Piscataway: IEEE, 2009. 248-255.
  • 8Krizhevsky A, Sutskever I, Hinton G. Imagenet classification with deep convolutional neural networks. In: Proceedings of NIPS Conference, Lake Tahoe, 2012. 1106-1114.
  • 9Sheng V S, Provost F, Ipeirotis P G. Get another label? improving data quality and data mining using multiple, noisy labelers. In: Proceedings of 14th ACM International Conference on Knowledge Discovery and Data Mining. New York: ACM, 2008. 614-622.
  • 10Chen S, Zhang J, Chen G, et al. What if the irresponsible teachers are dominating? a method of training on samples and clustering on teachers. In: Proceedings of 24th AAAI Conference, Atlanta, 2010. 419-424.

共引文献65

同被引文献29

引证文献4

二级引证文献9

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部