US-China in a defining race for quantum supremacy
The stakes go beyond computational speed: at issue is who will build the technological infrastructure of the future, from intelligent supply chains and personalized medicine to quantum-secure communication and AI-enhanced robotics.
Quantum computing is not only a hardware battle; it is a battle for the infrastructure of the 21st century. Fig. 1. Quantum computing combines analog and digital paradigms.
Quantum computing combines the principles of computing with those of quantum mechanics. In 1981, American quantum physicist Richard Feynman noted that classical computers, whether analog or digital, struggle to simulate quantum phenomena efficiently.
He argued that only a quantum system could simulate another quantum system by using the peculiar behaviors of subatomic particles as computational resources. Feynman asked: 'Could we build a computer that works like the universe itself?'
That vision began to take concrete form in 1985, when British physicist David Deutsch published a landmark paper titled 'Quantum Theory, the Church-Turing Principle, and the Universal Quantum Computer .'
Deutsch proposed a theoretical framework for a universal quantum computer, introducing the concept of quantum gates and circuits, the building blocks of quantum algorithms. Deutsch laid the foundational architecture for the entire field of quantum computing.
At the core of quantum computers is the qubit, or quantum bit. Unlike regular bits in digital (binary) computers, which are either 0 or 1, a qubit can be both 0 and 1 at the same time, thanks to a special quantum mechanical property called superposition.
This enables quantum computers to solve specific problems, such as modeling molecules, optimizing systems, or securing data, significantly faster than conventional computers. Qubits can be created in various ways, such as utilizing the spin of tiny particles like electrons or the properties of light, depending on the specific task.
A qubit is typically visualized as a sphere, known as the Bloch sphere, which can be thought of as a 3D compass. The discrete structure (the polarities 0 and 1) provides the computational scaffolding: gates, circuits, and algorithms.
Whether they are 0 or 1 may depend on context. Computational processes within the Bloch sphere are analog. Quantum algorithms rely on this interplay to achieve exponential speedups in solving specific problems. Fig. 2. The 'fixed' classical binary bit and the 'quantum' bits of the qubit. Analog calculations are executed within the so-called Bloch sphere.
The first experimental quantum computers arrived in the late 1990s. In 1998, researchers at Oxford and MIT constructed a basic two-qubit quantum computer utilizing nuclear magnetic resonance (NMR) techniques.
Though limited in function, it served as a proof of concept. From the 2000s onward, quantum computing became a global technological race, involving academia, governments, tech giants, and startups.
In 2006, China entered the quantum computing race when the government announced its 2020 Science and Technology Roadmap, identifying 'quantum control' as a key area of basic research .
In 2021, its 14th Five-Year Plan, quantum information ranked second among cutting-edge science and technology fields, just behind artificial intelligence (AI). In March of this year, China launched a 1 trillion yuan (~US$138 billion) national venture fund, explicitly targeting quantum computing and related technologies.
China's advances in quantum computing have been spectacular. In 2020, scientists at the University of Science and Technology of China (USTC) unveiled Jiuzhang, a photonic quantum computer that performed a task in 200 seconds that would have taken a classical supercomputer over 2.5 billion years. Later versions, such as Jiuzhang 2.0, further improved performance.
In 2021, researchers at the University of Science and Technology of China (USTC) unveiled Zuchongzhi 2.1, a 66-qubit superconducting quantum processor that demonstrated a significant quantum advantage over classical supercomputers.
In 2023, the same team announced Zuchongzhi 3.0, a 105-qubit processor that further advanced performance benchmarks, reportedly outperforming previous benchmarks, including Google's 2019 Sycamore experiment, by a factor of up to a million in specific sampling tasks.
These achievements underscore China's rapid progress in hardware scaling and system optimization. Fig. 3. Quantum computing developments in the U.S. and China.
China has also taken a major leap forward in building a global quantum communication network by successfully establishing an ultra-secure quantum key distribution (QKD) link between Beijing and South Africa.
The breakthrough marks the latest milestone in China's ambitious Quantum Experiments at Space Scale (QUESS) program, which is centered around the satellite Micius (also known as Mozi), launched in 2016.
Micius has enabled several landmark achievements in quantum communication, including a 2017 quantum-encrypted video call between China and Austria, covering 7,600 kilometers, and secure communication experiments with Russia.
Quantum Key Distribution (QKD) is a method of transmitting encryption keys using quantum particles, such as photons. If intercepted, these quantum keys collapse, alerting users to a breach, thus ensuring a level of security unachievable by classical methods.
The latest demonstration used China's low-cost quantum micro- and nano-satellites in tandem with mobile ground stations, signaling a shift from experimental setups to deployable systems.
According to Yin Juan, a leading scientist behind Micius, this demonstration is part of China's plan to launch a global quantum communication service by 2027, targeting BRICS countries and other strategic partners.
While China's quantum computing efforts are centrally coordinated and state-led, the United States thrives on a model of decentralized, grassroots innovation driven by its world-leading tech industry, academic institutions and venture capital ecosystem.
Major players, including Google, IBM, Microsoft and Rigetti, are advancing diverse quantum hardware architectures, such as superconducting qubits, and hybrid platforms that integrate quantum processors with classical computing backends.
One of the most notable milestones occurred in 2019, when Google's Sycamore processor achieved quantum supremacy, completing a computational task in 200 seconds that would have taken a classical supercomputer an estimated 10,000 years. (Quantum supremacy is defined as demonstrating a quantum computer's superiority over classical systems in a specific task.)
Building on this success, Google unveiled its Willow processor in 2024, demonstrating progress toward fault-tolerant quantum computing through the implementation of error-corrected logical qubits—a critical step toward scalable quantum applications.
Although the US has some national coordination (the National Quantum Initiative Act (2018) and government funding), its strength lies in a vibrant ecosystem characterized by diversity of approaches, interdisciplinary collaboration and a culture of high-risk, high-reward experimentation.
Silicon Valley's innovation model encourages rapid prototyping, iterative design and aggressive commercialization timelines. Quantum startups receive significant backing from both public and private investors, enabling parallel experimentation across different technologies and use cases.
Moreover, the United States continues to lead in foundational theoretical research. It remains at the forefront of quantum error correction, quantum algorithm development and hybrid quantum–classical integration strategies, all of which are essential for transforming quantum computing from a lab-bound curiosity into a transformative industrial technology.
The link between academic research, corporate R&D and entrepreneurial dynamism positions the US as a formidable and resilient force in the quantum era.
Quantum computing will transform how humans interact with machines.
By fusing the strengths of both analog and digital computation, it promises to reshape human-machine interfaces (HMIs) and accelerate the convergence of AI, robotics, and advanced sensing technologies. This hybrid capability opens the door to more intuitive, responsive and adaptive machines that can engage with the world in ways closer to how humans think and feel.
Traditional binary computing relies on discrete bits, symbolic logic and rule-based processing. In contrast, human experience is inherently analog: we sense the world in smooth, continuous flows of perception, motion, emotion and intention. This fundamental mismatch limits current machines' ability to interpret complex human states such as mood, focus, or intention.
Quantum computing bridges this gap. As a hybrid system, it combines the fluidity of analog systems with the structure of digital logic, offering a powerful new platform for building machines that can both process continuous sensory input and make discrete, context-sensitive decisions. Fig. 4. Key features of the analog and digital principles.
In the field of robotics, the tension between analog and digital systems is particularly pronounced. Human-like movement involves solving continuous motion trajectories while simultaneously making discrete decisions, such as when to stop, turn or grasp an object. This blend of fluid dynamics and symbolic logic is difficult for classical computers to manage efficiently.
A similar challenge arises in brain-computer interfaces (BCIs). Brain activity is inherently analog, expressed through continuous waves and subtle fluctuations in electrical patterns. Translating these signals into discrete commands for digital systems demands enormous computational power and precision.
Quantum computing opens the possibility of real-time mental control of external devices, and even the emergence of shared cognitive environments where information flows seamlessly between human and machine. In such systems, intention, attention and emotion could be sensed, decoded and responded to with unprecedented speed and sensitivity.
Beyond hardware rivalry, long-term leadership in quantum computing will center on the integration of various technologies. China is still lagging behind the US in basic research, including the development of fault-tolerant systems.
However, China is well-positioned to play a leading role in integrating quantum computing, AI and robotics, thanks to its unique combination of industrial capacity, policy coordination, and state-of-the-art public infrastructure.
At the hardware level, China is unparalleled in its ability to produce quantum and AI components at scale. It has made breakthroughs in key technologies like superconducting quantum processors, photonic computing and scalable control systems.
At the same time, China leads the world in robotics manufacturing, and its domestic companies produce competitive AI accelerator chips such as Huawei's Ascend. The vertically integrated supply chain gives China a distinct advantage in building tightly coupled quantum, AI and robotic systems.
China is also expanding its geopolitical influence through technology exports, such as quantum key distribution links with Austria, Russia and South Africa, as well as robotics and AI systems across the Global South.
Its ambition is not only to master these technologies but to shape global standards and infrastructure, especially among BRICS and Belt and Road countries. Fig. 5. Expected milestone in quantum computing development. (HPC refers to High Performance Computing.)
Quantum computing will gradually increase its capabilities and expand into more domains. The primary users will be pharmaceutical and chemical companies, financial institutions, tech giants, governments and research institutions involved in climate modeling.
Smaller users and perhaps consumers may be able to rent 'quantum computing time' in the quantum cloud. (There won't be a quantum computer on every desk, but perhaps a quantum terminal.)
The jury is still out on who will win the quantum computing race. But the country that can fuse quantum computing with real-world systems, from intelligent supply chains to brain-computer interfaces, will play a leading role in the future of computation.
The winner may not be the one with the first universal quantum computer, but the one that builds the first quantum-powered infrastructure of the 21st century.
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Quantum computing is becoming the defining battleground of the 21st-century technological rivalry between the United States and China. The stakes go beyond computational speed: at issue is who will build the technological infrastructure of the future, from intelligent supply chains and personalized medicine to quantum-secure communication and AI-enhanced robotics. Quantum computing is not only a hardware battle; it is a battle for the infrastructure of the 21st century. Fig. 1. Quantum computing combines analog and digital paradigms. Quantum computing combines the principles of computing with those of quantum mechanics. In 1981, American quantum physicist Richard Feynman noted that classical computers, whether analog or digital, struggle to simulate quantum phenomena efficiently. He argued that only a quantum system could simulate another quantum system by using the peculiar behaviors of subatomic particles as computational resources. 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Qubits can be created in various ways, such as utilizing the spin of tiny particles like electrons or the properties of light, depending on the specific task. A qubit is typically visualized as a sphere, known as the Bloch sphere, which can be thought of as a 3D compass. The discrete structure (the polarities 0 and 1) provides the computational scaffolding: gates, circuits, and algorithms. Whether they are 0 or 1 may depend on context. Computational processes within the Bloch sphere are analog. Quantum algorithms rely on this interplay to achieve exponential speedups in solving specific problems. Fig. 2. The 'fixed' classical binary bit and the 'quantum' bits of the qubit. Analog calculations are executed within the so-called Bloch sphere. The first experimental quantum computers arrived in the late 1990s. In 1998, researchers at Oxford and MIT constructed a basic two-qubit quantum computer utilizing nuclear magnetic resonance (NMR) techniques. Though limited in function, it served as a proof of concept. From the 2000s onward, quantum computing became a global technological race, involving academia, governments, tech giants, and startups. In 2006, China entered the quantum computing race when the government announced its 2020 Science and Technology Roadmap, identifying 'quantum control' as a key area of basic research . In 2021, its 14th Five-Year Plan, quantum information ranked second among cutting-edge science and technology fields, just behind artificial intelligence (AI). In March of this year, China launched a 1 trillion yuan (~US$138 billion) national venture fund, explicitly targeting quantum computing and related technologies. China's advances in quantum computing have been spectacular. In 2020, scientists at the University of Science and Technology of China (USTC) unveiled Jiuzhang, a photonic quantum computer that performed a task in 200 seconds that would have taken a classical supercomputer over 2.5 billion years. Later versions, such as Jiuzhang 2.0, further improved performance. In 2021, researchers at the University of Science and Technology of China (USTC) unveiled Zuchongzhi 2.1, a 66-qubit superconducting quantum processor that demonstrated a significant quantum advantage over classical supercomputers. In 2023, the same team announced Zuchongzhi 3.0, a 105-qubit processor that further advanced performance benchmarks, reportedly outperforming previous benchmarks, including Google's 2019 Sycamore experiment, by a factor of up to a million in specific sampling tasks. These achievements underscore China's rapid progress in hardware scaling and system optimization. Fig. 3. Quantum computing developments in the U.S. and China. China has also taken a major leap forward in building a global quantum communication network by successfully establishing an ultra-secure quantum key distribution (QKD) link between Beijing and South Africa. The breakthrough marks the latest milestone in China's ambitious Quantum Experiments at Space Scale (QUESS) program, which is centered around the satellite Micius (also known as Mozi), launched in 2016. Micius has enabled several landmark achievements in quantum communication, including a 2017 quantum-encrypted video call between China and Austria, covering 7,600 kilometers, and secure communication experiments with Russia. Quantum Key Distribution (QKD) is a method of transmitting encryption keys using quantum particles, such as photons. If intercepted, these quantum keys collapse, alerting users to a breach, thus ensuring a level of security unachievable by classical methods. The latest demonstration used China's low-cost quantum micro- and nano-satellites in tandem with mobile ground stations, signaling a shift from experimental setups to deployable systems. According to Yin Juan, a leading scientist behind Micius, this demonstration is part of China's plan to launch a global quantum communication service by 2027, targeting BRICS countries and other strategic partners. While China's quantum computing efforts are centrally coordinated and state-led, the United States thrives on a model of decentralized, grassroots innovation driven by its world-leading tech industry, academic institutions and venture capital ecosystem. Major players, including Google, IBM, Microsoft and Rigetti, are advancing diverse quantum hardware architectures, such as superconducting qubits, and hybrid platforms that integrate quantum processors with classical computing backends. One of the most notable milestones occurred in 2019, when Google's Sycamore processor achieved quantum supremacy, completing a computational task in 200 seconds that would have taken a classical supercomputer an estimated 10,000 years. (Quantum supremacy is defined as demonstrating a quantum computer's superiority over classical systems in a specific task.) Building on this success, Google unveiled its Willow processor in 2024, demonstrating progress toward fault-tolerant quantum computing through the implementation of error-corrected logical qubits—a critical step toward scalable quantum applications. Although the US has some national coordination (the National Quantum Initiative Act (2018) and government funding), its strength lies in a vibrant ecosystem characterized by diversity of approaches, interdisciplinary collaboration and a culture of high-risk, high-reward experimentation. Silicon Valley's innovation model encourages rapid prototyping, iterative design and aggressive commercialization timelines. Quantum startups receive significant backing from both public and private investors, enabling parallel experimentation across different technologies and use cases. Moreover, the United States continues to lead in foundational theoretical research. It remains at the forefront of quantum error correction, quantum algorithm development and hybrid quantum–classical integration strategies, all of which are essential for transforming quantum computing from a lab-bound curiosity into a transformative industrial technology. The link between academic research, corporate R&D and entrepreneurial dynamism positions the US as a formidable and resilient force in the quantum era. Quantum computing will transform how humans interact with machines. By fusing the strengths of both analog and digital computation, it promises to reshape human-machine interfaces (HMIs) and accelerate the convergence of AI, robotics, and advanced sensing technologies. This hybrid capability opens the door to more intuitive, responsive and adaptive machines that can engage with the world in ways closer to how humans think and feel. Traditional binary computing relies on discrete bits, symbolic logic and rule-based processing. In contrast, human experience is inherently analog: we sense the world in smooth, continuous flows of perception, motion, emotion and intention. This fundamental mismatch limits current machines' ability to interpret complex human states such as mood, focus, or intention. Quantum computing bridges this gap. As a hybrid system, it combines the fluidity of analog systems with the structure of digital logic, offering a powerful new platform for building machines that can both process continuous sensory input and make discrete, context-sensitive decisions. Fig. 4. Key features of the analog and digital principles. In the field of robotics, the tension between analog and digital systems is particularly pronounced. Human-like movement involves solving continuous motion trajectories while simultaneously making discrete decisions, such as when to stop, turn or grasp an object. This blend of fluid dynamics and symbolic logic is difficult for classical computers to manage efficiently. A similar challenge arises in brain-computer interfaces (BCIs). Brain activity is inherently analog, expressed through continuous waves and subtle fluctuations in electrical patterns. Translating these signals into discrete commands for digital systems demands enormous computational power and precision. Quantum computing opens the possibility of real-time mental control of external devices, and even the emergence of shared cognitive environments where information flows seamlessly between human and machine. In such systems, intention, attention and emotion could be sensed, decoded and responded to with unprecedented speed and sensitivity. Beyond hardware rivalry, long-term leadership in quantum computing will center on the integration of various technologies. China is still lagging behind the US in basic research, including the development of fault-tolerant systems. However, China is well-positioned to play a leading role in integrating quantum computing, AI and robotics, thanks to its unique combination of industrial capacity, policy coordination, and state-of-the-art public infrastructure. At the hardware level, China is unparalleled in its ability to produce quantum and AI components at scale. It has made breakthroughs in key technologies like superconducting quantum processors, photonic computing and scalable control systems. At the same time, China leads the world in robotics manufacturing, and its domestic companies produce competitive AI accelerator chips such as Huawei's Ascend. The vertically integrated supply chain gives China a distinct advantage in building tightly coupled quantum, AI and robotic systems. China is also expanding its geopolitical influence through technology exports, such as quantum key distribution links with Austria, Russia and South Africa, as well as robotics and AI systems across the Global South. Its ambition is not only to master these technologies but to shape global standards and infrastructure, especially among BRICS and Belt and Road countries. Fig. 5. Expected milestone in quantum computing development. (HPC refers to High Performance Computing.) Quantum computing will gradually increase its capabilities and expand into more domains. The primary users will be pharmaceutical and chemical companies, financial institutions, tech giants, governments and research institutions involved in climate modeling. Smaller users and perhaps consumers may be able to rent 'quantum computing time' in the quantum cloud. (There won't be a quantum computer on every desk, but perhaps a quantum terminal.) The jury is still out on who will win the quantum computing race. But the country that can fuse quantum computing with real-world systems, from intelligent supply chains to brain-computer interfaces, will play a leading role in the future of computation. The winner may not be the one with the first universal quantum computer, but the one that builds the first quantum-powered infrastructure of the 21st century.
