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量子计算:现状、挑战与未来展望
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文章探讨了量子计算的现状、基本原理及其面临的挑战。量子计算利用叠加、纠缠和干涉等量子特性,有望在特定领域实现指数级加速。然而,维持量子态的稳定性、构建大规模纠错系统以及开发相关软件仍是重大工程难题。尽管如此,量子计算在模拟物理过程、药物发现、材料科学和金融建模等领域展现出巨大潜力,未来将与经典计算机协同工作,而非完全取代。同时,量子计算也对现有网络安全构成潜在威胁,促使人们关注后量子密码学的发展。

⚛️ 量子计算的基本原理:文章介绍了量子计算的核心概念,包括量子比特(qubit)利用叠加态同时代表0和1,以及量子纠缠使多个量子比特共享信息,从而实现大规模并行处理。此外,量子干涉通过放大正确答案的概率来加速计算。

🚧 量子计算面临的技术挑战:尽管潜力巨大,但量子计算机的实现面临严峻挑战。量子比特极易受环境干扰而失去量子态(退相干),导致计算错误。因此,需要专门的、通常是低温控制的环境来维持量子态。构建稳定、大规模的量子系统,以及开发容错量子硬件和鲁棒的纠错技术是关键难题。

🚀 量子计算的潜在应用与未来:文章指出,量子计算机不会完全取代经典计算机,而是会协同工作。它们将专注于经典计算机无法胜任的特定任务,如药物研发、材料科学、金融建模、复杂优化问题以及大型人工智能模型。初期应用可能类似于早期的经典超级计算机,服务于大型机构。

🔒 量子计算对网络安全的影响:文章强调,量子计算对现有加密方法构成重大威胁,特别是可能破解广泛使用的公钥密码学。这引发了对数据安全和未来加密技术发展的担忧,可能需要提前做好准备以应对量子破解的风险。

Unless you’ve been living under a stone, you can’t have failed to notice that 2025 marks the first 100 years of quantum mechanics. A massive milestone, to say the least, about which much has been written in Physics World and elsewhere in what is the International Year of Quantum Science and Technology (IYQ). However, I’d like to focus on a specific piece of quantum technology, namely quantum computing.

I keep hearing about quantum computers, so people must be using them to do cool things, and surely they will soon be as commonplace as classical computers. But as a physicist-turned-engineer working in the aerospace sector, I struggle to get a clear picture of where things are really at. If I ask friends and colleagues when they expect to see quantum computers routinely used in everyday life, I get answers ranging from “in the next two years” to “maybe in my lifetime” or even “never”.

Before we go any further, it’s worth reminding ourselves that quantum computing relies on several key quantum properties, including superposition, which gives rise to the quantum bit, or qubit. The basic building block of a quantum computer – the qubit – exists as a combination of 0 and 1 states at the same time and is represented by a probabilistic wave function. Classical computers, in contrast, use binary digital bits that are either 0 or 1.

Also vital for quantum computers is the notion of entanglement, which is when two or more qubits are co-ordinated, allowing them to share their quantum information. In a highly correlated system, a quantum computer can explore many paths simultaneously. This “massive scale” parallel processing is how quantum may solve certain problems exponentially faster than a classical computer.

The other key phenomenon for quantum computers is quantum interference. The wave-like nature of qubits means that when different probability amplitudes are in phase, they combine constructively to increase the likelihood of the right solution. Conversely, destructive interference occurs when amplitudes are out of phase, making it more likely to get the wrong answer.

Quantum interference is important in quantum computing because it allows quantum algorithms to amplify the probability of correct answers and suppress incorrect ones, making calculations much faster. Along with superposition and entanglement, it means that quantum computers could process and store vast numbers of probabilities at once, outstripping even the best classical supercomputers.

Towards real devices

To me, it all sounds exciting, but what have quantum computers ever done for us so far? It’s clear that quantum computers are not ready to be deployed in the real world. Significant technological challenges need to be overcome before they become fully realisable. In any case, no-one is expecting quantum computers to displace classical computers “like for like”: they’ll both be used for different things.

Yet it seems that the very essence of quantum computing is also its Achilles heel. Superposition, entanglement and interference – the quantum properties that will make it so powerful – are also incredibly difficult to create and maintain. Qubits are also extremely sensitive to their surroundings. They easily lose their quantum state due to interactions with the environment, whether via stray particles, electromagnetic fields, or thermal fluctuations. Known as decoherence, it makes quantum computers prone to error.

That’s why quantum computers need specialized – and often cryogenically controlled – environments to maintain the quantum states necessary for accurate computation. Building a quantum system with lots of interconnected qubits is therefore a major, expensive engineering challenge, with complex hardware and extreme operating conditions. Developing “fault-tolerant” quantum hardware and robust error-correction techniques will be essential if we want reliable quantum computation.

As for the development of software and algorithms for quantum systems, there’s a long way to go, with a lack of mature tools and frameworks. Quantum algorithms require fundamentally different programming paradigms to those used for classical computers. Put simply, that’s why building reliable, real-world deployable quantum computers remains a grand challenge.

What does the future hold?

Despite the huge amount of work that still lies in store, quantum computers have already demonstrated some amazing potential. The Canadian firm D-Wave, for example, claimed earlier this year to have carried out simulations of quantum magnetic phase transitions that wouldn’t be possible with the most powerful classical devices. If true, this was the first time a quantum computer had achieved “quantum advantage” for a practical physics problem (whether the problem was worth solving is another question).

There is also a lot of research and development going on around the world into solving the qubit stability problem. At some stage, there will likely be a breakthrough design for robust and reliable quantum computer architecture. There is probably a lot of technical advancement happening right now behind closed doors.

The first real-world applications of quantum computers will be akin to the giant classical supercomputers of the past. If you were around in the 1980s, you’ll remember Cray supercomputers: huge, inaccessible beasts owned by large corporations, government agencies and academic institutions to enable vast amounts of calculations to be performed (provided you had the money).

And, if I believe what I read, quantum computers will not replace classical computers, at least not initially, but work alongside them, as each has its own relative strengths. Quantum computers will be suited for specific and highly demanding computational tasks, such as drug discovery, materials science, financial modelling, complex optimization problems and increasingly large artificial intelligence and machine-learning models.

These are all things beyond the limits of classical computer resource. Classical computers will remain relevant for everyday tasks like web browsing, word processing and managing databases, and they will be essential for handling the data preparation, visualization and error correction required by quantum systems.

And there is one final point to mention, which is cyber security. Quantum computing poses a major threat to existing encryption methods, with potential to undermine widely used public-key cryptography. There are concerns that hackers nowadays are storing their stolen data in anticipation of future quantum decryption.

Having looked into the topic, I can now see why the timeline for quantum computing is so fuzzy and why I got so many different answers when I asked people when the technology would be mainstream. Quite simply, I still can’t predict how or when the tech stack will pan out. But as IYQ draws to a close, the future for quantum computers is bright.

The post Quantum computing: hype or hope? appeared first on Physics World.

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量子计算 Quantum Computing AI 人工智能 技术挑战 未来应用 网络安全 Cybersecurity 叠加 纠缠 干涉
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