Quantum computing
Quantum computing
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DOI：
10.1145/1274000.1274128
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发表时间：
2007-07
期刊：
影响因子：
--
通讯作者：
L. Spector
中科院分区：
文献类型：
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作者：
L. Spector
如果建造大规模量子计算机的努力最终取得成功，并且这些计算机的性能符合乐观的预期，那么计算机科学将发生根本性的变化。尽管如此，计算机科学家仍然缺乏对量子计算能力的透彻理解，并且并不总是清楚如何最好地利用所理解的能力。这种困境的存在是因为量子算法难以掌握，更难以编写。尽管国际上进行了大规模的努力，但只有少数重要的量子算法被记录在案，留下了许多关于量子算法潜力的基本问题没有得到解答。这些尚未解决的问题是自动编程技术应用的理想挑战。特别是遗传编程技术，已经产生了几种新的量子算法，预计未来会有进一步的发现。这些方法将帮助研究人员发现如何使用量子计算机解决其他实际问题，它们还将有助于指导量子计算的能力和限制的理论工作。本教程将介绍量子计算，并介绍使用进化计算进行自动量子计算机编程。没有物理学或进化计算的背景将被假定。虽然本教程的主要重点将放在一般概念上，但也将提出具体的结果，包括遗传编程产生的人类竞争结果。后续材料可从演讲者的书中获得，自动量子计算机编程：遗传编程方法，由Springer和Kluwer学术出版社出版。
Computer science will be radically transformed if ongoing efforts to build large-scale quantum computers eventually succeed and if the properties of these computers meet optimistic expectations. Nevertheless, computer scientists still lack a thorough understanding of the power of quantum computing, and it is not always clear how best to utilize the power that is understood. This dilemma exists because quantum algorithms are difficult to grasp and even more difficult to write. Despite large-scale international efforts, only a few important quantum algorithms are documented, leaving many essential questions about the potential of quantum algorithms unanswered. These unsolved problems are ideal challenges for the application of automatic programming technologies. Genetic programming techniques, in particular, have already produced several new quantum algorithms and it is reasonable to expect further discoveries in the future. These methods will help researchers to discover how additional practical problems can be solved using quantum computers, and they will also help to guide theoretical work on both the power and limits of quantum computing. This tutorial will provide an introduction to quantum computing and an introduction to the use of evolutionary computation for automatic quantum computer programming. No background in physics or in evolutionary computation will be assumed. While the primary focus of the tutorial will be on general concepts, specific results will also be presented, including human-competitive results produced by genetic programming. Follow-up material is available from the presenter's book, Automatic Quantum Computer Programming: A Genetic Programming Approach, published by Springer and Kluwer Academic Publishers.