内容来源：https://www.quantamagazine.org/building-a-quantum-computer-one-fragile-qubit-at-a-time-20260819/

内容总结：

全球量子计算竞赛白热化：多技术路线并进，大规模商业化仍面临挑战

随着经典计算机逐渐逼近物理极限，被视为下一代计算革命核心的量子计算技术正迎来全球研发热潮。与依赖硅基晶体管存储“0”和“1”的传统计算机不同，量子计算机利用量子比特（qubit）的叠加与纠缠效应，具备在特定复杂问题（如药物研发、材料科学、密码破译）上实现指数级算力突破的潜力。然而，如何构建足够强大且稳定的量子计算机，仍是人类面临的前沿科学挑战。

当前，全球科研机构与科技巨头正沿着截然不同的技术路径“赛跑”。首先，在物理实现方式上，主要分为两大流派：一是利用天然量子系统，例如通过电磁场捕获单个离子，或使用高度聚焦的激光束（光镊）捕获中性原子；二是人造量子比特路线，即借鉴传统芯片的微纳加工工艺，构建由铝或铌等金属制成的超导电路，并在稀释制冷机中冷却至极低温度下运行，以IBM、谷歌等企业为代表。

尽管技术路线百花齐放，但量子比特的“脆弱性”是共性难题。量子态极易受到环境干扰而退相干，因此必须在完美隔离与可控操纵之间取得平衡。此外，从小规模原型机向大规模系统扩展，是摆在所有团队面前的最大“拦路虎”。据乐观估计，实现实用化量子计算至少需要数万乃至数百万个量子比特，同时还需配套日益复杂的调控和测量系统。

目前，尚无任何单一技术路线展现出绝对优势。业内普遍认为，量子计算尚未迎来属于它的“晶体管时刻”，距离大规模商业化应用仍有相当距离。但各方科研投入与工程尝试的提速，正让这一未来科技加速走进现实。

中文翻译：

引言
几乎所有现代计算机——从你洗碗机里廉价的微控制器，到为人工智能系统 crunch 数字的高科技硬件——都依赖同一种技术的不同版本：印有称为晶体管的微观结构的硅片。含有晶体管的电子电路可以在两种状态之间快速而可靠地切换，这两种状态通常标记为“0”和“1”。这使它们能够存储和操作比特，即信息的基本单位。
量子计算机有潜力以新的、更强大的方式处理信息，超越单纯的 1 和 0，并解决某些对其普通“经典”同类来说过于困难的问题。但要制造一台足够强大、能实现这一承诺的机器，仍然是一个巨大的挑战。量子计算还没有迎来它的“晶体管时刻”，研究人员仍在探索许多不同的方法来开发量子硬件。
当前的各种方法首先在它们用作量子比特的物理系统上有所不同，量子比特是量子计算机的基本构建块。与存储经典比特的电路不同，量子比特可以表现出叠加和纠缠等奇异现象，这赋予了它们额外的计算能力。但这些量子效应也非常脆弱，容易被量子比特与周围环境之间的杂散相互作用所破坏。每种提出的量子比特技术都试图调和两个难以同时实现的性质：量子比特必须与外部干扰隔离，但又必须易于研究人员操纵。
一些研究人员押注于自然量子系统，如原子。要将单个原子用作量子比特，你首先必须将其隔离并困在真空室中，研究人员为此探索了两种不同的方法。在离子阱量子计算中，研究人员从每个原子上敲掉一个电子，得到带正电的离子，这些离子可以被电场固定在适当位置。另一种方法使用称为光镊的紧密聚焦激光束阵列来困住中性原子。
其他研究人员正在追求一种替代方法，称为超导量子计算，涉及人造量子比特的设计。研究人员使用为经典计算开发的微加工工艺的改良版本，组装由铝和铌等金属制成的微小电路，这些金属在冷却到极低温度时会变成超导体。这些超导电路安置在称为稀释制冷机的特殊低温系统中，可以像量子比特一样工作。许多其他量子比特候选方案也已被探索，从电子自旋到光子，再到更奇特的量子系统。
从小型原型扩展到更大的系统是所有方法面临的最大挑战之一。仅仅制造几个好的量子比特是不够的：研究人员最终至少需要数万个——即使按照最乐观的估计——甚至可能数百万个。更多的量子比特也意味着更大、更复杂的控制和测量系统。虽然现在说哪种技术（如果有的话）会胜出还为时过早，但以下图片让我们一窥构建可靠量子计算机所需的雄心勃勃的努力。
D. Slichter/NIST
Ken Richardson
QuEra Computing
Thierry Lahaye/CNRS
Caltech/Endres Lab
IBM
Erik Lucero

英文来源：

Introduction
Practically all modern computers, from the cheap microcontroller in your dishwasher to high-tech hardware crunching numbers for artificial intelligence systems, rely on versions of the same technology: slabs of silicon patterned with microscopic structures called transistors. Electronic circuits containing transistors can rapidly and reliably toggle between two states, usually labeled “0” and “1.” That enables them to store and manipulate bits, the basic units of information.
Quantum computers have the potential to process information in new and more powerful ways beyond mere 1s and 0s, and to solve certain problems that are too hard for their ordinary “classical” cousins. But building a machine powerful enough to fulfill that promise remains a formidable challenge. Quantum computing hasn’t yet had its transistor moment, and researchers are still exploring many different approaches to developing quantum hardware.
Current approaches differ first and foremost in which physical systems they use as qubits, the elementary building blocks of quantum computers. Unlike circuits that store classical bits, qubits can exhibit strange phenomena like superposition and entanglement that give them extra computational power. But these quantum effects are also very fragile, easily disrupted by stray interactions between qubits and the surrounding environment. Each proposed qubit technology tries to reconcile two properties that are hard to achieve simultaneously: Qubits must be isolated from outside disturbances, but easy for researchers to manipulate.
Some researchers have placed their bets on natural quantum systems such as atoms. To use a single atom as a qubit, you must first isolate and trap it in a vacuum chamber, and researchers have pursued two distinct approaches to doing so. In trapped-ion quantum computing, researchers knock one electron off each atom to get positively charged ions that can be held in place by electric fields. The other approach uses arrays of tightly focused laser beams, called optical tweezers, to trap neutral atoms.
Other researchers are pursuing an alternative approach, called superconducting quantum computing, which involves the design of artificial qubits. Using modified versions of microfabrication processes developed for classical computing, researchers assemble tiny circuits made of metals like aluminum and niobium that become superconductors when cooled to very low temperatures. Housed in special cryogenic systems called dilution refrigerators, these superconducting circuits can act like qubits. Many other qubit candidates have been explored, from electron spins to photons to more exotic quantum systems.
Scaling up from small prototypes to much larger systems is one of the biggest challenges facing all these approaches. It’s not enough to make a few good qubits: Researchers will ultimately need at least tens of thousands, by even the most optimistic estimates, and perhaps even millions. More qubits also mean larger and more complex control and measurement systems. While it’s too early to say which technology, if any, will win out, the following images offer a glimpse inside the ambitious efforts required to build reliable quantum computers.
D. Slichter/NIST
Ken Richardson
QuEra Computing
Thierry Lahaye/CNRS
Caltech/Endres Lab
IBM
Erik Lucero