Recently, Google and China have independently announced advancements in quantum computing. Google’s Willow chip demonstrates “below-threshold” error correction, achieving a benchmark calculation in minutes that would take supercomputers billions of years. China’s Zuchongzhi 3.0 processor, with 105 qubits, exhibits comparable performance and plans to implement similar error correction techniques.

Both achievements represent significant steps toward building practical, large-scale quantum computers, highlighting a global race for quantum advantage. The potential applications span numerous fields, including AI, medicine and energy.

Recetly unveiled by a research team led by physicist Jian-Wei Pan at the University of Science and Technology of China, the Zuchongzhi 3.0 has positioned the country as a notable competitor alongside the United States in the race to harness the potential of quantum computing.

Achieving quantum computational advantage

Zuchongzhi 3.0’s significance lies in its ability to achieve what is known as “quantum computational advantage,” a critical milestone in quantum computing. This term signifies the point where a quantum computer can execute calculations that would take classical computers, even the most powerful supercomputers, an impractically long time to complete.

At the core of Zuchongzhi 3.0’s achievement is its performance on a complex computational task known as random circuit sampling. This involves applying a series of random quantum gates to create quantum states, followed by measurements to sample the resulting probability distribution. The Zuchongzhi 3.0 processor, utilizing an 83-qubit, 32-cycle random circuit, accomplished this task, generating one million samples in just a few hundred seconds.

To put this into perspective, performing the same calculation using the Frontier supercomputer—considered one of the most powerful supercomputers at the time of Zuchongzhi 3.0’s development—would require an estimated 6.4 billion years. This stark contrast in processing time highlights the potential of quantum computers to accelerate certain types of computations dramatically compared to classical computers.

This achievement puts Zuchongzhi 3.0 in the same league as Google’s Willow in achieving a significant quantum computational advantage.

Zuchongzhi 3.0 and Willow

The unveiling of Zuchongzhi 3.0 came shortly after Google announced their Willow processor, underscoring the intense competition between the two nations in quantum computing. Both processors share a key characteristic: they house 105 qubits, the highest number achieved to date in superconducting quantum devices. This makes them the largest superconducting quantum processors, showcasing the rapid progress in scaling up quantum hardware.

While both processors represent significant advancements, they also exhibit distinct features. Zuchongzhi 3.0 stands out for its high operational fidelities—a critical metric indicating the accuracy of quantum operations—through various optimizations, including refining circuit parameters, enhancing the electric field distribution, upgrading the attenuator configuration and improving the chip fabrication process.

Zuchongzhi 3.0’s average Pauli error for single-qubit gates has been reduced to 0.10% and for iSwap-like gates to 0.38%.

The processor has also achieved improvements in readout performance, a crucial aspect for accurately measuring the states of qubits, through strategies like increasing the coupling strength between qubits and readout resonators, tuning the linewidths of the readout resonators, and optimizing the bandpass filter design to protect the qubit from the Purcell effect.

In contrast to Zuchongzhi 3.0’s emphasis on fidelity and readout performance, Google’s Willow processor has garnered attention for its advancements in quantum error correction—a major challenge in the field. Willow demonstrates what Google calls “below-threshold” error correction, where the error rate decreases as the number of qubits increases. This breakthrough is key to building more reliable and scalable quantum computers.

While the Chinese team behind Zuchongzhi 3.0 has not yet demonstrated similar error correction levels, they have acknowledged its importance and announced plans to incorporate comparable techniques in their processor. Their roadmap includes reaching distance-7 surface codes, a crucial benchmark in error correction, within a few months.

Role of classical simulation in assessing quantum advantage

To fully appreciate the significance of Zuchongzhi 3.0 and its comparison to other processors, it is essential to understand the role of classical simulation in evaluating quantum computational advantage.

Currently, the tensor network algorithm is regarded as the most advanced classical algorithm for simulating random quantum circuits, the type of experiment performed on Zuchongzhi 3.0. Using this algorithm, researchers can estimate the computational resources and time required to simulate a quantum experiment on a classical computer.

In the case of Zuchongzhi 3.0, simulating its 83-qubit, 32-cycle experiment using the tensor network algorithm is estimated to take an impractical amount of time, even on the most powerful supercomputers.

Is Europe falling behind?

Despite the Quantum Flagship initiative funded by the European Union at the 1€ billion level (about $1.043 billion) on a 10-year timescale, Europe cannot match the U.S. and China’s significant investment in quantum computing.

Over 5,000 researchers are working on quantum-related initiatives in the EU and other associated countries, according to the initiative.

As of October 2024, China has the largest investment with $15 billion spent on quantum computing research of the estimated $42 billion funding for quantum computing worldwide, according to QURECA. The United States comes second, with $4.98 billion from the National Quantum Initiative.

Additionally, companies like IBM, Google (Alphabet), Amazon, Microsoft, Intel and D-Wave are investing millions of dollars in research and development of quantum computing hardware and software.

The future landscape of quantum computing

While quantum computing is still in its early stages, its progress is remarkable. The rapid increase in qubit count, coupled with improvements in fidelity and the development of error correction techniques, points toward a future where quantum computers could revolutionize fields like drug discovery, materials science, AI and more.

The race for quantum leadership is intensifying, with the U.S. and China investing heavily in research and development. This competition drives innovation and accelerates progress in the field, pushing the boundaries of what is possible with quantum computers.

By: DocMemory
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