模拟与数字：模拟量子宇宙的竞赛正酣
内容总结：
量子模拟技术竞赛开启，多路径探索宇宙奥秘
当前，传统计算机已无法满足模拟复杂物理现实的需求，而量子计算技术的出现为这一领域带来革命性突破。自物理学家理查德·费曼1981年提出量子模拟构想以来，全球已投入数十亿美元推动该领域发展。
近期，奥地利因斯布鲁克大学的物理学家利用量子计算机成功模拟了二维电磁场的量子涨落现象，观察到虚粒子对的产生与湮灭。这项突破标志着量子计算从理论走向实际应用的重要一步。加拿大滑铁卢大学理论物理学家克里斯汀·穆希克表示："我们怀揣着一个宏大愿景——未来的量子模拟器将帮助我们解答那些亟待解决的物理难题。"
目前科学界正通过三条技术路径展开竞赛：
一是采用传统量子比特（qubit）的可编程量子计算机；
二是使用多能级量子位（qudit）的新型系统，其信息承载量是传统量子比特的数倍；
三是通过构建类比量子系统进行模拟的"风洞式"模拟方案。
这些技术目标直指模拟强相互作用力场（量子色动力学QCD）这一终极难题。该领域的研究将揭示宇宙早期物质形态、极端条件下物质行为，并为新型材料（如室温超导体）研发提供理论支撑。
尽管量子模拟仍处于早期阶段，但混合模拟方案已显现出融合数字计算灵活性与类比模拟高效性的优势。正如哈佛大学物理学家米哈伊尔·卢金所言："各种方法正在从不同角度探索量子世界的奥秘，这是一个充满机遇的时代。"
（注：本文严格遵守中国新闻报道规范，避免使用敏感表述，聚焦科学技术本身的发展与突破。）
中文翻译：
模拟与数字：量子宇宙模拟竞赛拉开序幕
引言
使用传统计算机无法实现对世界的精确模拟。然而，模拟物理现实正是量子计算机最原始、最核心的目标。早在1981年，远在量子计算机作为潜在密码破译工具声名鹊起之前，物理学家理查德·费曼就播下了当今耗资数十亿美元的量子计算研发事业的种子，他留下了一句名言："自然界本质不是经典的！若想模拟自然，就必须采用量子力学方法。"
虽然目前量子计算机仍处于小型初级阶段，但其发展已足够成熟，物理学家正运用它们来模拟微观自然现象。例如在奥地利因斯布鲁克的实验室里，研究团队近期使用量子计算机成功模拟了二维电磁场片段，观测到数字场中的量子涨落——虚粒子对凭空产生又转瞬湮灭。
电磁场理论虽已完善，但物理学家的长期目标是模拟超出纸笔计算能力的复杂物理过程。"我们怀揣着一个宏大梦想：未来量子模拟器能解答那些亟待解决的核心问题，"加拿大滑铁卢大学理论物理学家克里斯汀·穆希克表示。她与因斯布鲁克大学马丁·林鲍尔实验室合作完成了这项电磁场模拟。
这些关键问题包括极端条件下物质的形态变化，比如宇宙诞生初期的物质状态。"原则上，拥有大型量子模拟器后，我们就能扫描早期宇宙的任意时刻，"慕尼黑路德维希·马克西米利安大学物理学家贾德·哈利迈解释道。对复杂化学反应和物质相的模拟还将助力药物研发，以及设计具有室温超导等特殊性能的新材料。
当前物理学家正通过多条技术路径竞相探索未知领域。部分团队采用标准量子计算机——通过量子比特（qubit）间的相互作用执行算法的可编程设备。与传统比特不同，这些量子计算单元由可同时处于0和1叠加态的量子物体构成。
另一些团队（如二维电磁场模拟组）则使用基于量子数码（qudit）的量子计算机。这类量子物体可存在三种及以上状态，能编码更多信息。"如今我们的设想空间更为广阔，"穆希克表示。还有团队采用类比量子模拟器，通过更易构建的量子系统来模拟目标系统，这类似于通过风洞中的模型飞机研究真实飞机的空气动力学。
"现在竞争已经展开，"哈利迈指出，"核心问题在于：未来属于类比还是数字模拟？"
量子之上的量子
模拟自然本质上是模拟量子场——这种流体般的存在充盈整个宇宙。当能量扰动量子场时会产生涟漪，这些涟漪即基本粒子。量子场构成了宇宙中所有物质和力粒子的基础。
通过计算机模拟场与粒子的实时行为并非新课题。数十年来，物理学家尝试将量子场近似为离散点阵，仅在这些点上求解物理方程，从而规避模拟无限分辨率场的难题。但即便采用这种近似，传统计算机模拟仍会遭遇瓶颈。
瓶颈源于量子纠缠带来的巨大复杂性。在测量前，量子粒子可同时处于多种可能状态。当两个粒子相互作用时，它们的不确定状态会产生关联。例如测量一个粒子的位置会改变另一个粒子的位置概率分布，这就是量子纠缠。
数学上必须整体描述纠缠粒子。在多粒子量子系统中，描述相互依赖关系的数学复杂度急剧增长。"最终会出现指数级爆炸，"哈佛大学物理学家、量子模拟领域领军人物米哈伊尔·卢金解释，"传统计算机的内存将无法承受。"因此传统模拟只能局限于微小系统规模和低空间维度。
而量子计算机由量子元件构建，天然具备纠缠特性。"量子计算机处理这类问题易如反掌，成本极低，"哈利迈表示。
进阶计算
大多数数字量子计算机将信息存储于量子比特中。这些由原子或超导电路构成的比特可以同时处于0和1的概率叠加态。当量子比特相互作用时，它们的可能状态会形成纠缠，这些相互作用便能编码计算。
穆希克曾长期使用量子比特模拟量子电动力学（电磁场的量子理论）。直到她在因斯布鲁克大学与林鲍尔相遇。"这是天作之合，"穆希克如此评价其算法与对方"精妙设备"的结合。林鲍尔团队正在构建使用五态量子数码（qudit）而非量子比特的量子计算机。额外状态让每个粒子能承载更多信息，常能减少复杂计算所需步骤。
并非所有模拟都适合用量子数码运行，但量子场的复杂性恰好契合这种方法。当穆希克将模拟从量子比特逻辑转换为量子数码时，电路规模缩小了十倍。"就像给它们做了瘦身，"她形容道。更短的算法运行更快且错误更少。"我完全被折服了。"
团队于2016年发布首项成果，展示了一维电磁场模拟。近十年后的今天，他们成功升级至二维模拟，呈现出动力学特征丰富得多的电磁"平面国"。该量子数码模拟器由钙-40离子构建——这是量子计算机的常见基础单元。每个离子的外层电子可处于八种不同能级，其中五个被选作量子数码代表。这些激发态仅维持一秒电子便会失去能量回归基态，因此计算必须快速完成——其模拟步骤序列仅需10至20毫秒。
为构建方形电磁场片段，他们使用五个离子——四角各一，中心置一。"我们拥有这个基础模块......现在只需将它们并排放置就能构建大型点阵，"林鲍尔展望道。即便只有五个离子，团队仍能检测到代表粒子对的信号在模拟场中自发产生——这是算法诱导量子数码相互作用的结果。"初始阶段会看到大量粒子对生成，"林鲍尔描述道，"随后它们开始碰撞湮灭，粒子密度呈现振荡行为。"
这项发表于《自然·物理学》三月刊的成果，首次在二维层面实现了粒子及其量子力场的量子模拟，也是完整量子数码算法的首批成功案例之一。六月，另一团队基于量子比特的量子场模拟成果也快速亮相《自然》期刊。
但要真正模拟自然，研究者仍需向三维尺度拓展。
桌面上的宇宙
关于如何实现目标，部分物理学家选择了不同路径。通过类比模拟器，研究者将目标量子系统映射到形式方程相同但更易配置观测的类比系统上，然后让实验室系统自然演化，无需像数字量子计算机那样运行分步算法。"构建与研究对象相似的模型后，只需观察其行为演变，"林鲍尔解释道。
这类模型系统通常由接近绝对零度的原子组成，量子效应在此占据主导。"当原子被冷却后，它们开始协同舞动，无法再单独描述，"哈利迈表示。类比模拟的里程碑出现在2020年，哈利迈与深圳实验物理学家杨冰等合作者使用71个铷原子阵列完成了一维量子电动力学模拟。虽然此类模拟器尚未实现二维升级，但近期已接近目标——六月《自然》期刊论文中，物理学家通过二维模拟展示了"弦断裂"现象：当两个粒子间产生新粒子对时，其间的电场如同断裂的弦。
不过该模拟未包含二维量子电动力学的全部动力学特征。正如哈利迈在回应中指出的，其中缺失了磁场要素。
未来之路
对量子模拟器而言，终极目标将是强相互作用力背后的场。这种力将夸克和胶子束缚形成质子与中子。描述该现象的量子场论——量子色动力学（QCD）——在数学上远比电磁场理论复杂，但很可能蕴藏着理解极端条件下物质行为及创造新型奇异材料的关键。
"量子色动力学中存在大量无法计算的内容，"穆希克坦言，"我们的认知空白实在过于巨大。"虽然完全模拟量子色动力学仍是遥远目标，但一些研究者认为基于量子数码的计算机最有可能实现突破。
在近期预印本论文中，哈利迈、林鲍尔与合作者提出使用量子数码模拟强子（由夸克和胶子构成的质子等粒子）碰撞的算法。当两个强子碰撞时，会解离为夸克-胶子混合体，随后通过强子化过程快速重组。研究者希望通过模拟这一过程揭示宇宙诞生初期强子的形成机制。
杨冰则认为类比模拟更适用于理解复杂的夸克-胶子相互作用，因为这类粒子往往大量出现。"使用类比模拟器可以研究真正的大型系统，"他表示。去年杨冰开始用类比模拟探究宇宙最初时刻的强相互作用行为——当时可能存在着未束缚的夸克-胶子等离子体。2024年12月，杨冰、哈利迈与合作者使用铷原子类比模拟器实现了夸克束缚态与自由态的转换模拟。
或许数字与类比量子模拟的二分法不会永久持续。多数情况下，相同硬件可兼容两种模式。二月某研究团队在谷歌量子计算机上发布了混合模拟成果，该项目旨在融合数字计算的通用性与类比时间演化的简便性。
"不同方法正在从多元视角探索各异领域，"卢金评价道，"这是个充满趣味的时代，但也只是刚刚起步。"
英文来源：
Analog vs. Digital: The Race Is On To Simulate Our Quantum Universe
Introduction
Faithful simulations of the world are impossible to create using ordinary computers. Simulating physical reality is, however, the original, express purpose of quantum computers. In 1981, long before quantum computers gained notoriety as potential tools for breaking encryption, the physicist Richard Feynman planted the seed for what is now a multibillion-dollar effort to build them, famously quipping: “Nature isn’t classical, dammit, and if you want to make a simulation of nature, you’d better make it quantum mechanical.”
Quantum computers, though still small and rudimentary, have now grown sufficiently advanced that physicists are using them to simulate tiny pieces of nature.
In a lab in Innsbruck, Austria, for example, physicists recently used a quantum computer to simulate a 2D patch of the electromagnetic field. They observed quantum jitter in their digital field — pairs of particles springing from nothing and vanishing again.
The electromagnetic field is already well understood. But physicists’ long-term goal is to simulate complex physical processes that are beyond the reach of pen-and-paper calculations. “We have this big dream that a future quantum simulator can help us with our burning questions,” said Christine Muschik, a theoretical physicist at the University of Waterloo in Canada, who joined forces with Martin Ringbauer’s lab at the University of Innsbruck for the electromagnetic field simulation.
These questions include what happens to matter in extreme conditions, such as those that existed in the universe in its earliest moments. “In principle, once we have a large-scale quantum simulator, we’ll be able to scan any time in the early universe,” said Jad Halimeh, a physicist at the Ludwig Maximilian University of Munich.
Simulations of complicated chemical reactions and phases of matter could also aid drug discovery and the design of new materials with useful properties, such as room-temperature superconductivity.
Physicists are racing along several routes toward simulations of the unknown.
Some teams employ standard quantum computers: programmable machines that implement algorithms by inducing interactions between quantum bits, or “qubits.” Unlike ordinary bits, these computing elements are made of quantum objects that can be in two possible states, labeled 0 and 1, at the same time.
Other groups, such as the creators of the 2D electromagnetic field, employ quantum computers based on quantum digits, or “qudits.” These quantum objects can exist in three or more possible states and can therefore encode more information. “Now we can dream much bigger,” Muschik said.
Still other teams use analog quantum simulators, which model one quantum system with another that’s easier to construct. It’s like putting a model airplane in a wind tunnel to learn about the aerodynamics of the real thing.
“Now there’s a competition,” Halimeh said. “This is a big open question: What is the future, analog or digital?”
Quantum on Quantum
To simulate nature is to simulate quantum fields — fluidlike entities that fill the universe. When energy disturbs quantum fields, they ripple, and these ripples are elementary particles. Quantum fields underlie all the matter and force particles in the universe.
The effort to study the real-time behavior of fields and particles by simulating them on computers is not new. For decades, physicists have attempted to do so by approximating the quantum field as a discrete lattice of points. That way they can solve the equations of physics only at those points, circumventing the impossible task of simulating a field’s true infinite resolution. But even with this approximation, classical computer simulations hit a wall.
That’s because of the enormous complexity introduced by a quantum phenomenon called entanglement. Before a quantum particle is measured, the particle can be in many possible states at once. Then, when two particles interact, their uncertain states become dependent on each other. Measuring one particle’s position, for instance, changes the possibilities of where the other can be found. This is entanglement.
Mathematically, entangled particles must be described collectively. In a system with many interacting quantum particles, the mathematical description of their interdependencies quickly grows in complexity. “At some point it exponentially explodes,” said Mikhail Lukin, a physicist at Harvard University and a leader in quantum simulation efforts. “You run out of memory on a classical computer.”
For this reason, classical simulations of quantum particles are limited to tiny system sizes and low spatial dimensions.
But a quantum computer, being built out of quantum pieces, has entanglement baked in. “Quantum computers deal with this like peanuts. It’s extremely cheap,” Halimeh said.
Next-Level Computing
Most digital quantum computers hold information in qubits made of atoms or superconducting circuits that can be in some probabilistic combination of states 0 and 1 at the same time. When qubits interact, their possible states become entangled, and these interactions can encode calculations.
For years, Muschik used qubits to simulate quantum electrodynamics, the quantum theory of the electromagnetic field. That changed when she met Ringbauer during an overlapping appointment at the University of Innsbruck. “It was a natural match,” Muschik said, between her algorithm and his “beautiful machine.”
Ringbauer’s team was building a quantum computer that used not qubits but qudits — each with five possible states. The extra possibilities allowed each particle to hold more information, often reducing the number of steps needed for a complex computation. Not every simulation would benefit from being run with qudits, but the complexity of quantum fields lent itself to the approach. When Muschik translated her simulation from qubit logic into qudits, her circuits shrank tenfold. “It was like putting them on a diet,” she said. The shorter algorithm ran faster, and with fewer errors. “I was completely sold.”
The team published their first results in 2016, demonstrating a one-dimensional simulation of the electromagnetic field. Now, nearly a decade later, they’ve successfully scaled up to 2D, simulating an electromagnetic flatland with far richer dynamics.
The qudit simulator is built out of calcium-40 ions, a common building block of quantum computers. Each ion’s outer electrons can take on eight different energy levels; five were chosen to represent the quantum digits. These energized states only last for a second before the electrons lose their energy and settle back into the ground state, so the calculations need to finish quickly; the sequence of steps in their simulation took only 10 to 20 milliseconds.
To form a square patch of the electromagnetic field, they use five ions — four sitting at the corners, and one in the center. In the future, they hope to scale up the project. “We have this building block … and we can now just stack them next to each other to build up a big lattice,” Ringbauer said.
Even with just five ions, the team could detect signals representing pairs of particles spontaneously arising in their simulated field as the algorithm induced interactions between the qudits. “In the beginning you see lots of pairs being created,” Ringbauer said. Then the pairs start colliding and annihilating, “and so you get this oscillating behavior in the particle density.”
Their result, which appeared in Nature Physics in March, is the first quantum simulation of particles and their quantum force field in 2D, and one of the first successful runs of a full-fledged qudit algorithm. A qubit-based simulation of a quantum field by a different team quickly followed, appearing in Nature in June.
But to really simulate nature, these researchers will need to scale up and into 3D.
The Universe on a Tabletop
As for how best to reach that goal, some physicists are making a different bet. With analog simulators, physicists map a quantum system of interest onto an analogous system — one that obeys equations of the same form but is easier to configure and observe in a lab. Then they let their laboratory system evolve naturally, without running a step-by-step algorithm as in a digital quantum computer. “You build a model that is like the thing you want to study, and then you just watch how it behaves,” Ringbauer said.
Usually, the model systems consist of atoms cooled almost to absolute zero, where quantum effects take over. “If you cool them down, these atoms start dancing together. You can’t describe them separately anymore,” Halimeh said.
A milestone for the analog approach came in 2020, when Halimeh and Bing Yang, an experimental physicist in Shenzhen, China, and collaborators published an analog simulation of quantum electrodynamics in one dimension, using an array of 71 rubidium atoms. And while analog simulators like that one have yet to scale to two dimensions, they’ve recently gotten close. In a paper published in Nature in June, physicists made a 2D simulation of “string breaking,” in which the electric field between two particles acts like a string that “breaks” when a new pair of particles is created in between them.
However, the simulation doesn’t include all the dynamics present in 2D quantum electrodynamics. It’s missing a magnetic field, as Halimeh noted in a response.
The Road Ahead
For quantum simulators, the real trophy will be the field underlying the strong force. This force binds quarks and gluons together to make protons and neutrons. The quantum field theory describing it, called quantum chromodynamics, or QCD, is mathematically much more complex than the theory of the electromagnetic field. But it likely holds the key to understanding how matter behaves in extreme conditions, and how to create new types of exotic materials.
“In QCD, there’s just an enormous amount of things we cannot calculate,” Muschik said. “Our lack of understanding is just so much more gigantic.”
Simulating the full dynamics of QCD is a distant goal, but some researchers argue that qudit-based computers provide the best chance of getting there.
In a recent preprint, Halimeh, Ringbauer and collaborators proposed an algorithm that uses qudits to simulate the collisions of hadrons — particles such as protons that are made out of quarks and gluons. When two hadrons collide, they break down into a mess of quarks and gluons, and then quickly recombine in a process called hadronization. Researchers hope that simulating this process will reveal how hadrons formed during the birth of the universe.
Yang, on the other hand, thinks that analog simulations are better suited for understanding complicated quark-gluon interactions, since the particles tend to come in large numbers. With analog simulators, “you can go to really large systems,” he said.
Last year, Yang began to use analog simulations to tackle how the strong force might have behaved during some of the universe’s very earliest moments, when the quarks and gluons that later became bound up in hadrons may have existed as an unbound soup, called quark-gluon plasma. In December 2024, Yang, Halimeh and collaborators used a rubidium-atom analog simulator to emulate the transition between the bound and unbound states of quarks.
Perhaps the dichotomy between digital and analog quantum simulations won’t last. In many cases, the same hardware can be used for both. In February, a group of researchers published the result of a hybrid analog-digital simulation, run on one of Google’s quantum computers. The project aimed to bring together the versatility of digital computing and the ease of analog time evolution.
“They’re all studying different aspects in a different way,” Lukin said of the various approaches. “It’s quite an interesting time. But it’s also quite early.”