## Scientists have overcome the three major challenges of semiconductor quantum com

Since the concept of quantum computing was first introduced in 1980, the field has gone through more than four decades of development history.

Quantum bits, or qubits, are the basic information units in this field, similar to bits in classical computers.

However, while classical bits only have two states, 0 or 1, quantum bits also have other states, including superposition states that encompass both 0 and 1.

This property gives quantum computers an exponential acceleration capability over classical computers when executing complex algorithms and solving certain tasks.

Therefore, building a large number of quantum bits is crucial for the development of quantum computing technology.Initially, researchers in this field primarily utilized the quantum states of photons or atoms to encode quantum bits.

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This method has significant advantages in advancing fundamental physical research. However, due to the demanding experimental conditions required to manipulate photons or atoms in a vacuum environment, the construction of large-scale quantum computers still faces immense challenges.

In this context, silicon-based quantum computing technology, which integrates the cutting-edge quantum computing technology and semiconductor integrated circuit technology, has rapidly developed over the past decade and is expected to become the best solution for quantum computing.

The main reason is that, compared with photon and atom-based quantum computing, silicon-based quantum computing is more practical. It can use traditional integrated circuit processes to construct quantum bits in a semiconductor environment, thereby achieving a quantum processor.

As a result, in recent years, a large number of companies related to silicon-based quantum computing have emerged in Europe, America, Australia, and other places. Not only are technology companies such as Intel and IBM focusing on this field, but there are also many quantum computing startups, such as the UK's Quantum Motion and Australia's Diraq.At the same time, there are also some research teams engaged in this field globally, including the research group of Dr. Xue Xiao, a postdoctoral fellow at Delft University of Technology in the Netherlands.

Currently, Dr. Xue Xiao's research is committed to achieving distributed and integrable quantum computing. In terms of computing modules, he has achieved a silicon-based two-qubit logic fidelity of 99.65%, reaching the fidelity threshold required for quantum error correction for the first time; in terms of integration, he has collaborated with Intel to test and verify a low-temperature quantum control chip based on the 22-nanometer process, achieving control of quantum chips using low-temperature chips for the first time; in terms of inter-module communication, he has used superconducting microwave photons to achieve two-qubit logic between long-distance silicon-based quantum modules.

With the conquest of the three most important challenges in the field of quantum computing in silicon-based semiconductor systems, namely high fidelity, integrability, and modular architecture, Dr. Xue Xiao has promoted silicon-based quantum computing to become one of the most promising quantum computing systems in just a few years. He has become one of the Chinese selected for the "35 Innovators Under 35" by MIT Technology Review in 2023.

Conquering the three key challenges in the field of quantum computing in silicon-based semiconductor systems, promoting silicon-based quantum computing to become one of the best quantum computing systems.As mentioned above, silicon-based quantum computing has tremendous potential for development. However, compared to other systems that started earlier, such as ion traps and superconducting circuits, there are still many fundamental issues that need to be addressed.

Among them, the most important is the fidelity of qubits based on electron spin.

In quantum computing, fidelity is a very important concept, referring to the accuracy of quantum states or quantum operations, which will directly affect the quality of quantum information transmission, the accuracy of quantum computing, and the security of quantum communication.

"Fidelity is directly opposed to non-fidelity, the latter represents the probability of errors occurring in the calculation. Only by increasing the correct rate as much as possible can a large number of logical operations be performed on qubits," Xue Xiao explained.

In the early stages of the development of silicon-based quantum computing, the silicon materials used by laboratories around the world were all natural silicon, which contains 4.7% of the Si-29 isotope. Si-29 has a non-zero nuclear spin, and due to the hyperfine interaction, it will cause the electron spin to decohere very quickly.In 2019, during his Ph.D. studies at Delft University of Technology, Xue Xiao first verified a two-qubit logic fidelity of 92% in natural silicon[1]. However, this is still a distance away from the 99% fidelity required for fault-tolerant quantum computing.

"Quantum computing will always have an error rate, and it will grow exponentially as the number of quantum bits increases. Therefore, we need to use redundant quantum bits to perform error correction on the target quantum bits, and the fidelity threshold required for error correction is 99%," said Xue Xiao.

That is to say, only by reaching this threshold can error correction be likely to succeed.

Therefore, to achieve this goal, Xue Xiao and his collaborators purified the silicon material isotopically, removing the vast majority of Si-29 isotopes. At the same time, they improved the dielectric layer of the material and precisely controlled the exchange interaction of the two-qubit system with Hamiltonian.

For Xue Xiao, the unknown is the biggest challenge encountered in the process of this research."Although we had set a goal before the experiment to achieve a fidelity of over 99%, we were not sure whether we could succeed. This uncertainty can lead to severe self-doubt," he said, "To overcome this uncertainty, we can only continuously look for any possible space for optimization in the experimental system."

Ultimately, through relentless efforts, the research group achieved a silicon-based two-qubit logic fidelity of up to 99.65% in 2022, crossing the threshold of fault-tolerant quantum computing for the first time in the world[2]. This work was selected as the cover article of the Nature issue.

In addition to high fidelity, another major challenge of silicon-based quantum computing is to achieve the integration of quantum chips.

In Google's "quantum supremacy" experiment, more than 200 control and read lines need to enter the cryostat from room temperature. This not only brings a lot of noise but is also not conducive to integration and expansion.

To solve this problem, since 2020, the research group where Xue Xiao is located has cooperated with Intel to explore the miniaturization and chip-based quantum control and reading instruments, and to explore the feasibility of integrating with the quantum processor itself.On this basis, they have designed a low-temperature control chip based on the 22-nanometer process (codenamed "Horse Ridge") [3]. The size and power consumption of the chip are 4 square millimeters and 384 milliwatts, respectively, capable of replacing the bulky traditional high-frequency instruments and achieving the same fidelity.

In addition, current research on quantum computing also focuses on achieving distributed and integrable quantum computing, that is, constructing multiple small-scale computing modules and enabling quantum communication between modules.

In this regard, Xue Xiao and his collaborators used superconducting microwave photons to achieve two-bit logic between silicon-based quantum modules at a long distance in 2023. It is understood that the relevant paper is currently under peer review, and Xue Xiao is a co-first author [4].

Committed to achieving a truly fully integrated modular silicon-based quantum processor, promoting the development of China's quantum, semiconductor, and artificial intelligence in three major fields.

In fact, for the emerging field of quantum information, Xue Xiao had already understood it after the college entrance examination. Originating from the interest in this field, he decided to fill in the University of Science and Technology of China as the first choice and was successfully admitted.During his undergraduate studies, his main interest was multi-photon entanglement based on linear optics.

After going to Tsinghua University for graduate studies in 2014, he focused on the research of graphene quantum dots.

In 2017, he went to Delft University of Technology to pursue a Ph.D. in physics, and since then he has started researching spin qubits in semiconductors.

When talking about why he chose this direction, Xue Xiao said it was mainly based on the following three reasons.

Firstly, he has a strong interest in both quantum technology and condensed matter physics, and semiconductor computing is the only research direction that allows him to explore both aspects at the same time.Secondly, the qubits of silicon-based quantum computing are smaller than 100 nanometers, which naturally gives them an integration advantage. Moreover, the industry already has mature large-scale production processes, which can help integrate this system with existing traditional silicon-based circuits.

Thirdly, the international competition in the three major fields of quantum, semiconductor, and artificial intelligence in China is becoming increasingly fierce. Research on silicon-based quantum computing can not only promote the industrial development of both quantum and semiconductor fields but also is expected to be applied in the development of artificial intelligence.

It is worth mentioning that the development between quantum and artificial intelligence can promote each other.

Xue Xiao pointed out: "When quantum computing can truly bring about an increase in computing power, it will naturally promote the development of artificial intelligence; and existing artificial intelligence algorithms can also be used to serve the optimization and design of quantum chips."

Looking at the application of quantum computing, there is no doubt that it will be widely applied in the industry in the near future and play an important value in the encryption algorithms in banking systems and digital currency systems, optimization algorithms in unmanned driving and urban transportation, and quantum simulation algorithms in the design of new drugs and new functional materials.However, to realize such application prospects, it is necessary to highly integrate millions or even tens of millions of quantum bits. The silicon-based quantum computing platform we are researching is currently the system with the most hope to achieve this breakthrough, said Xue Xiao.

At present, he has achieved significant breakthroughs in the field of high fidelity, integrability, and modular architecture, which are recognized by the field. Therefore, in the next phase, he plans to create a truly fully integrated modular silicon-based quantum processor.

At the same time, he also plans to work with domestic peers in related fields to promote the industrialization of silicon-based quantum technology, thereby promoting the development of China's quantum, semiconductor, and artificial intelligence fields.

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