Quantum Computation and Quantum Information
Quantum Computation and Quantum Information
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DOI：
10.1214/11-sts378
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发表时间：
2012-08-01
影响因子：
5.7
通讯作者：
Wang, Yazhen
中科院分区：
文献类型：
--
作者：
Wang, Yazhen
量子计算和量子信息是当前计算机科学、数学、物理科学和工程领域的研究热点。它们可能会导致通信、计算和密码学领域的新一轮技术创新。由于量子物理理论从根本上讲是随机的，随机性和不确定性深深植根于量子计算、量子模拟和量子信息。因此，量子算法本质上是随机的，量子模拟广泛使用蒙特卡罗技术。因此，统计学可以在量子计算和量子模拟中发挥重要作用，这反过来又为计算统计学提供了巨大的变革潜力。虽然经典计算机只能产生伪随机数，但量子计算机能够产生真正的随机数；量子计算机可以指数或平方地加速中值评估、蒙特卡罗积分和马尔可夫链模拟。本文对量子计算、量子模拟和量子信息作了简要的回顾。我们介绍了量子计算和量子模拟的基本概念，并提出了比现有经典算法快得多的量子算法。我们为量子算法的分析和量子模拟提供了一个统计框架。
Quantum computation and quantum information are of great current interest in computer science, mathematics, physical sciences and engineering. They will likely lead to a new wave of technological innovations in communication, computation and cryptography. As the theory of quantum physics is fundamentally stochastic, randomness and uncertainty are deeply rooted in quantum computation, quantum simulation and quantum information. Consequently quantum algorithms are random in nature, and quantum simulation utilizes Monte Carlo techniques extensively. Thus statistics can play an important role in quantum computation and quantum simulation, which in turn offer great potential to revolutionize computational statistics. While only pseudo-random numbers can be generated by classical computers, quantum computers are able to produce genuine random numbers; quantum computers can exponentially or quadratically speed up median evaluation, Monte Carlo integration and Markov chain simulation. This paper gives a brief review on quantum computation, quantum simulation and quantum information. We introduce the basic concepts of quantum computation and quantum simulation and present quantum algorithms that are known to be much faster than the available classic algorithms. We provide a statistical framework for the analysis of quantum algorithms and quantum simulation.