首页> 外文期刊>Artificial Intelligence for Engineering Design, Analysis & Manufacturing >Evolving blackbox quantum algorithms using genetic programming
【24h】

Evolving blackbox quantum algorithms using genetic programming

机译:使用遗传编程的不断发展的黑匣子量子算法

获取原文
获取原文并翻译 | 示例
           

摘要

Although it is known that quantum computers can solve certain computational problems exponentially faster than classical computers, only a small number of quantum algorithms have been developed so far. Designing such algorithms is complicated by the rather nonintuitive character of quantum physics. In this paper we present a genetic programming system that uses some new techniques to develop and improve quantum algorithms. We have used this system to develop two formerly unknown quantum algorithms. We also address a potential deficiency of the quantum decision tree model used to prove lower bounds on the query complexity of the parity problem.
机译:尽管众所周知,量子计算机可以比传统计算机以指数方式更快地解决某些计算问题,但到目前为止,仅开发了少数量子算法。量子物理学的相当非直觉的特性使设计这样的算法变得复杂。在本文中,我们介绍了一种遗传编程系统,该系统使用一些新技术来开发和改进量子算法。我们已经使用该系统开发了两个以前未知的量子算法。我们还解决了量子决策树模型的潜在缺陷,该模型用于证明奇偶校验问题的查询复杂性的下限。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号