On October 23, 2019 the journal Nature published Quantum Supremacy using a Programmable Superconducting Processor, which describes the breakthrough by Google’s AI Quantum team in building the first quantum processing system capable of clearly demonstrating an advantage over “classical” supercomputers on a particular class of difficult computational problems. But what does this mean, really, and what is its significance? To answer this question, let us first review just what a quantum computer is, and how Google has built theirs.

2019年10月23日，《自然》(Nature)杂志发表了《使用可编程超导处理器的量子至上论 》( Quantum Supremacy) ，该书描述了Google AI量子团队在构建首个量子处理系统方面所取得的突破，该系统能够明显证明在特定类别的困难计算机上优于``经典''超级计算机的优势计算问题。 但是，这实际上意味着什么，它的意义是什么？ 为了回答这个问题，让我们首先回顾一下量子计算机是什么，以及谷歌如何制造它们。

为什么要打扰量子计算？ (Why Bother with Quantum Computing?)

Quantum computing algorithms have existed since before the first prototype of a quantum processor was built in 1998, but even so, quantum algorithms are in their infancy as a field. One of the earliest quantum algorithms, Shor’s algorithm, from 1994, allows an integer N to be factored on a quantum computer in polynomial time, O((log N)²(log log N)(log log log N)), which is exponentially faster than the best known classical algorithm, the general number field sieve. It is the very “hardness” of factoring integers that underlies RSA and a number of other cryptographic systems. So solving what was once thought of as a theoretical problem in pure mathematics takes on considerable importance.

自1998年建立量子处理器的第一个原型之前，就已经存在量子计算算法，但即便如此，量子算法仍处于起步阶段。 最早的量子算法之一，Shor算法，始于1994年，它允许在整数计算机上以多项式时间O((log N )²(log log N )(log log log N ))分解整数N。指数比最著名的经典算法(通用数字场筛)快得多。 RSA和许多其他密码系统的基础是分解整数的非常“困难”。 因此，解决曾经被认为是纯数学中的理论问题的事物具有相当重要的意义。

Other established quantum algorithms offer fundamental advantages over the best known classical solutions. Some are quite theoretical. Others are more practical. Grover’s search algorithm from 1996 can find an element in an unsorted list of N elements in √N steps, compared to N/2 for a classical scheme. Proposed quantum optimization algorithms offer quadratic to exponential speedups over the best of known classical techniques. Quantum computations are the most natural way to simulate molecules and chemical reactions. But the field is in its infancy. We are only now learning how to build machines to run these algorithms.

其他已建立的量子算法与最著名的经典解决方案相比，具有根本的优势。 有些是很理论的。 其他更实用。 从1996年Grover的搜索算法可以在√N个步骤的N个元素的一个未排序的列表中找到的元素，相比于N / 2为一个传统的方案。 提出的量子优化算法在已知的经典技术中提供了从二次到指数的加速。 量子计算是模拟分子和化学React的最自然方法。 但是这个领域还处于起步阶段。 我们现在仅在学习如何构建运行这些算法的机器。

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量子计算基础 (Quantum Computing Basics)

经典二进制数据和量子态 (Classical Binary Data and Quantum States)

Conventional binary digital computers,“classical” computers in the quantum computing idiom, operate on the basis of bits, binary elements of information that are either 0 or 1. That’s only two possible values, but they can be concatenated to represent arbitrarily large value ranges, with each additional bit doubling the range of distinct values. Arithmetic, logical, and other operations can be performed on classical bit values by combining sequences of elements of boolean logic — AND, OR, NOT, etc — to operate on binary values and create new binary values.

传统的二进制数字计算机，即量子计算习语中的“经典”计算机，是基于比特或信息的二进制元素(为0或1)运行的。这只是两个可能的值，但可以将它们组合起来以表示任意大的值范围，每个额外的位使不同值的范围加倍。 通过组合布尔逻辑的元素序列(AND，OR，NOT等)以对二进制值进行运算并创建新的二进制值，可以对经典位值执行算术，逻辑和其他运算。

Quantum computers exploit the fact that quantum particles, such as electrons, photons, or ions, have properties like spin and polarization that can be manipulated to encode and process binary information. These processors operate on quantum bits, or qubits. This quantum information has unusual and counter-intuitive properties that make quantum computing both more powerful and more difficult than classical.

量子计算机利用了这样一个事实，即诸如电子，光子或离子之类的量子粒子具有诸如自旋和极化之类的特性，可以操纵这些特性来编码和处理二进制信息。 这些处理器在量子位或量子位上运行 。 这种量子信息具有非同寻常和违反直觉的特性，这使得量子计算比经典计算更强大，更困难。

A qubit will be represented by the state of a quantum system that can be usefully visualized as a “Bloch sphere”:

量子位将由量子系统的状态表示，该状态可以可视化为“布洛赫球”：