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Perspective on the Quantum Computing Industry#

2021 was a remarkable year for the quantum computing community. While the number of qubits saw significant growth, various quantum computing hardware technologies also advanced; more institutions began developing upper-layer software and algorithms, with an increasing number of algorithms being experimentally validated on small-scale practical problems. The scale at which quantum computers can solve problems largely depends on the number of qubits. Since 2021, major research teams have achieved breakthroughs, with neutral atom companies ColdQuanta and AtomComputing launching quantum computers with over 100 qubits, and Harvard-MIT developing a 256-qubit quantum simulator based on neutral atoms.

In the superconducting domain, the 66-qubit "Zuchongzhi" from the University of Science and Technology of China achieved quantum computational superiority, with computational complexity improved by six orders of magnitude compared to Google's "Sycamore"; Rigetti proposed a modular quantum processor architecture, expecting to release an 80-qubit processor within months; IBM launched the 127-qubit processor Eagle. In the ion trap domain, IonQ proposed a reconfigurable multi-core quantum architecture, which has expanded to 64 qubits. In the photonic quantum domain, traditional challenges of programming photonic quantum computing are being addressed, with increasing research showing that photonic quantum computing can also be programmed. For example, Xanadu and the National University of Defense Technology have demonstrated programmable photonic quantum computing chips, and researchers revealed that "Jiuzhang" will also be programmable in the future.

1. Overview of Quantum Computing Development
   From the technology roadmaps of mainstream quantum computing companies, breakthroughs in qubit numbers are expected around 2021-2022, with a target of exceeding 100 qubits and breaking through 1000 qubits within three years, aiming for one million qubits by the end of this decade (2030).
   Table 1 Mainstream Quantum Computing Company Roadmap
   
   Another dimension of whether quantum computers are useful is the quality of qubits, with key indicators including coherence time (determining how long a quantum state can be maintained), the degree of connectivity between qubits, and gate fidelity.

Regarding coherence time: In 2021, the research group led by Jin Qihuan at Tsinghua University set a new record for single-qubit coherence time (5500 seconds) in ion trap systems.

In terms of connectivity between qubits: Ion trap systems can achieve full connectivity, but with fewer qubits. Superconducting quantum computers, such as Zuchongzhi and Sycamore, connect each qubit to only four surrounding qubits. If connectivity can be improved, the scale of solvable problems will grow exponentially. Japan's RIKEN achieved entanglement of three semiconductor (silicon spin) qubits for the first time.

In terms of gate fidelity: Currently, the fidelity of two-qubit gates (entanglement gates) in the most advanced quantum computing systems is over 99%, with the highest record being 99.99% achieved by an Australian silicon quantum computing company using semiconductor technology, although they have only developed two qubits.

No current technology route can lead in all indicators simultaneously, and different technology routes have their own advantages and disadvantages. Research teams are continuously working on creating new qubits. In measurement and control: 2021 also saw breakthroughs. Some manufacturers, represented by Zurich Instruments, released measurement and control systems capable of measuring and controlling over 100 qubits. The biggest breakthrough was achieved by the University of New South Wales in Australia, proposing a technique to control millions of silicon spin qubits, laying a solid foundation for the future emergence of million-qubit processors. While quantum computing is rapidly developing, the progress of classical computing cannot be overlooked. In 2019, Google claimed that a supercomputer would take 10,000 years to complete a computation, but recent research indicates that classical simulation has reached speeds comparable to Google's quantum computer.

The theme of the field in 2021 can be defined as the competition between classical simulation and quantum computing, and this competition will continue, as the significant advancements in classical computing have forced quantum computing to accelerate its development pace.

2. Quantum Computing Industry Chain
   The quantum computing industry is currently in the early exploration stage, with few core participants and a relatively clear upstream and downstream industry chain. Currently, foreign tech giants such as IBM, Google, Amazon, Microsoft, Intel, and Honeywell are leading the industry, while new quantum computing companies like IonQ, Rigetti, and PsiQuantum have also secured hundreds of millions in venture capital and are equally strong. Domestic tech giants like Alibaba, Baidu, Tencent, and Huawei are also following suit, but the leading domestic quantum computing companies are primarily represented by companies like Origin Quantum and GuoDun Quantum that rely on universities. Overall, the domestic and international quantum computing industry chain has begun to take shape.

In terms of the industry chain, quantum computing device suppliers are mainly international companies, especially dilution refrigerators and low-temperature coaxial cables. However, in other areas, Chinese companies have already secured a place, particularly in measurement and control systems, where companies like Microda and GuoDun Quantum are on par with foreign manufacturers, and even achieving higher levels. Additionally, Origin Quantum has made certain breakthroughs in low-temperature components like attenuators and filters.

In chip manufacturing, the current manufacturing process for quantum chips is mainly completed in laboratories, but some leading quantum computing teams have begun manufacturing quantum chips in factories. For example, Google's "Sycamore" quantum chip was manufactured in a factory at the University of California, Santa Barbara (UCSB).

In January 2022, Origin Quantum's two self-built laboratories—the quantum chip manufacturing and packaging laboratory and the quantum computing assembly and testing laboratory—were officially put into operation, marking the second engineering quantum chip laboratory established in China after the Origin-Jinghe Quantum Chip Joint Laboratory in 2021.

Quantum computing companies in the industry chain mainly focus on hardware and software R&D. Currently, leading hardware teams are primarily tech giants and strong research institutions (such as the University of Science and Technology of China), but China's tech giants have entered the quantum computing field relatively late. Startups like Origin Quantum, GuoDun Quantum, Qike Quantum, and Turing Quantum are the backbone of the industry. In terms of software, there are already over 100 quantum software companies internationally, but there are relatively few quantum software companies in China.

3. Quantum Computing Application Scenarios#

The large size, extremely stringent operating environment, and multimillion-dollar price tag of quantum computers mean that current quantum computing applications mainly rely on cloud platforms for quantum hardware. Quantum computing and classical computing do not have a relationship of replacement and being replaced; instead, they play unique roles in specific scenarios that require extremely high computing power.

There is currently no consensus on all the problems that quantum computers will be able to solve, but research mainly focuses on the following types of computational problems:

• Simulation: Simulating processes occurring in nature that are difficult or impossible to describe and understand using today's classical computers. This has enormous potential in drug discovery, battery design, fluid dynamics, and pricing derivatives and options.

• Optimization: Using quantum algorithms to determine the optimal solution among a set of feasible options. This may apply to trunk logistics and portfolio risk management.

• Machine Learning: Identifying patterns in data to train machine learning algorithms. This can accelerate the development of artificial intelligence (for example, for autonomous vehicles) and help prevent fraud and money laundering.

• Cryptography: Breaking traditional encryption and supporting stronger encryption standards.

From an industry perspective, the potential applications of quantum computing mainly include supply chain, finance, transportation, logistics, pharmaceuticals, chemicals, automotive, aerospace, energy, and meteorology.

Pharmaceuticals, chemicals, and new materials: Quantum computing can simulate molecular properties, potentially helping researchers obtain large molecular characteristics in digital form, shortening theoretical verification time, and greatly advancing drug development in the pharmaceutical industry and the development of new materials.

Finance: Quantum computing is very suitable for complex financial modeling, with potential advantages in portfolio pricing, derivative pricing, etc. According to incomplete statistics, over 25 international banks and financial institutions have already collaborated with quantum computing companies.

Transportation, logistics, and supply chain: All three areas involve quantum computing optimization, utilizing quantum computing to optimize supply chains, transportation (including planes, trains, cars, etc.) routes, and logistics, thereby reducing costs.

Aerospace: Quantum computing helps address some of the most severe challenges facing the aerospace industry, from fundamental materials science research and machine learning optimization to complex systems optimization, and has the potential to change the way planes are manufactured and flown.

Energy: Quantum computing could be applied to simulate the chemical composition and accumulation of various types of clay in hydrocarbon wells—key factors for efficient hydrocarbon production; analyze and manage the fluid dynamics of wind farms; optimize autonomous robot facility inspections; and help create unprecedented opportunities to provide the clean energy the world wants and needs.

In February 2021, BP in the UK collaborated with IBM Quantum to explore ways to improve energy efficiency and reduce carbon emissions.

• Automotive: In recent years, major automotive manufacturers have accelerated the promotion of electrification strategies. During the electrification strategy process, quantum computing will leverage its advantages in chemical simulation, with several automotive manufacturers committed to using quantum computing technology to develop better-performing batteries.

• Meteorology: Quantum computing can effectively and quickly process large amounts of data with multiple variables, and parallel computing and continuously optimized algorithms can facilitate tracking and predicting meteorological conditions, helping to improve the accuracy of weather forecasts. Additionally, quantum computers can also identify and understand different weather patterns through machine learning.

Quantum Computers—Advancing Together
The physical platforms for current quantum computing require physical carriers for encoding qubits, allowing controllable coupling between different qubits, and having a certain resistance to noise environmental impacts.

In 2021, superconducting systems developed rapidly, with the scale of qubits continuously being refreshed, while ion traps, photonic quantum, silicon spin, and neutral atom technology routes also developed strongly. Other technology routes, such as diamond NV centers, have also made certain progress.

• Topological schemes faced setbacks when the paper on the "discovery of Majorana particles" (the cornerstone for achieving topological quantum computing) was retracted, but researchers remain confident that this error-correcting-free scheme can be realized. In summary, the development of physical implementation schemes for quantum computing is far from converging. In addition to gate-based quantum computers, the recently emerging coherent Ising machine (CIM) scheme has also performed well. In 2021, Japan's NTT achieved 100,000 qubits through the CIM scheme. Although it cannot be directly compared to gate-based quantum computers, this is still a significant milestone. Notably, in 2021, quantum annealing pioneer D-Wave announced plans to develop gate-based quantum computers, which somewhat indicates that the prospects for quantum annealers may be limited.

Note: The scoring uses a 5-point scale, with 1 being the worst and 5 being the best. ○ represents 1 point, ● represents 5 points. The green arrow indicates that the commercialization development is better than other routes, with yellow and red following in order.

1. Superconducting—Most Attention#

• Superconducting quantum computing is currently one of the fastest-developing solid-state quantum computing implementation methods internationally.

• The superconducting effect, as a macroscopic quantum effect, provides a lossless environment for coherent manipulation of quantum states. The energy levels of superconducting quantum circuits can be interfered with by external electromagnetic fields, making it easier to achieve customized development of circuits.

• Due to the maturity of integrated circuit technology, the scalability advantage of superconducting quantum circuits will become more apparent. Currently, quantum computing technology based on superconducting quantum circuits has achieved numerous breakthroughs in key technologies such as decoherence time, quantum state manipulation and reading, controllable coupling between qubits, and medium-to-large scale expansion, making it one of the most promising candidate technology routes for constructing universal quantum computers and quantum simulators.

• In 2021, China made significant progress in superconducting quantum research.

• In January 2021, Southern University of Science and Technology achieved a high-fidelity, highly scalable two-qubit quantum gate scheme using tunable couplers in a superconducting quantum circuit system. The experiment achieved fast (30 ns) high-fidelity (0.995) two-qubit gate operations. Compared to previous two-qubit gates, this scheme has higher robustness, requires fewer control lines, has less crosstalk impact, and simplifies the system calibration process. In February, Origin Quantum launched the domestically engineered superconducting quantum computer Origin Wuyuan No. 2.

• In May, a research team led by Pan Jianwei and Zhu Xiaobo from the University of Science and Technology of China successfully developed a 62-qubit programmable superconducting quantum computing prototype "Zuchongzhi," and based on this, achieved programmable two-dimensional quantum walks.

• In June, Pan Jianwei's team upgraded the programmable superconducting quantum computing prototype "Zuchongzhi" again, constructing a 66-qubit programmable superconducting quantum computing prototype "Zuchongzhi No. 2," achieving rapid resolution of a 20-layer cyclic "quantum random circuit sampling" task involving 56 qubits. In terms of computational complexity, it surpassed Google's "Sycamore" quantum computer by three orders of magnitude.

• In September, the team of Academician Guo Guangcan from the University of Science and Technology of China collaborated with Origin Quantum to study the impact of crosstalk on qubit state reading on the Origin "KuaFu" 6-qubit superconducting quantum chip, and innovatively proposed using shallow neural networks to identify and read qubit state information, thereby significantly suppressing the impact of crosstalk and further improving multi-qubit reading fidelity.

• In August, the research group of Duan Luming from Tsinghua University's Institute for Interdisciplinary Information Research conducted the first experimental study on the impact of environmental qubits on cross-resonance logic gates (CR) using a tunable coupler multi-qubit system, proposing solutions to effectively improve the fidelity of two-qubit gate operations under two conditions: with and without environmental qubits in large-scale superconducting quantum systems.

• In October, Pan Jianwei's team achieved 60-qubit 24-layer cyclic quantum random circuit sampling, with computational complexity exceeding that of "Sycamore" by six orders of magnitude.

• In October, Pan Jianwei's team used a variational quantum eigensolver (VQE) to simulate a Josephson junction array quantum circuit, discovering a new type of high-performance qubit called plasonium.

• In October, Tencent Quantum Laboratory achieved a fast, high-fidelity, easily scalable superconducting qubit initialization scheme, which, compared to existing work in the industry, has advantages of speed, high fidelity, minimal impact on surrounding qubits, and strong scalability.

• On September 12, Zhejiang University released two superconducting quantum chips. "Mogan No. 1" is a dedicated quantum chip that adopts a fully connected architecture, suitable for achieving quantum simulation for specific problems and precise control of quantum states. The other chip, "Tianmu No. 1," is aimed at universal quantum computing, adopting a more easily scalable nearest-neighbor connected architecture, integrating 36 superconducting qubits with longer qubit lifetimes (decoherence time of about 50 microseconds), achieving high-fidelity universal quantum gates (controlled phase gates, with accuracy better than 98%).

• Internationally, in April 2021, physicists at the National Institute of Standards and Technology (NIST) in the United States used fiber optics instead of metal wires to measure and control superconducting qubits, facilitating the scalability of quantum computers. In September 2021, Japan's National Institute of Information and Communications Technology (NICT) developed a fully nitride superconducting qubit with a superconducting transition temperature of 16K (-257°C), which is 15 degrees higher than the temperature required for other superconducting qubit structures.

• In November 2021, Professor James Hone's laboratory at Columbia University's School of Engineering demonstrated a superconducting qubit capacitor made from 2D materials, which is 1000 times smaller than chips produced by traditional methods.

• In December 2021, IBM released the superconducting quantum computing chip with the highest number of qubits to date—the 127-qubit processor Eagle.

• In December 2021, Rigetti Computing launched its next-generation 80-qubit Aspen-M quantum processor, utilizing its multi-chip patented technology, assembled from two 40-qubit chips. A new Aspen system based on a single-chip 40-qubit processor was also released simultaneously.

• In December 2021, the Finnish National Technical Research Center (VTT) and IQM launched the country's first 5-qubit superconducting quantum computer, Micronova. While progress was made in 2021, several studies indicated that superconducting quantum computers face some previously undiscovered obstacles.

• In June 2021, researchers at the University of Wisconsin-Madison proposed that cosmic rays might be one of the reasons for errors in superconducting qubits.

• In December 2021, Google demonstrated that cosmic rays indeed cause errors in superconducting qubits on its quantum processor. In August 2021, the Fermi National Accelerator Laboratory discovered that nanohydrides could shorten the coherence time of superconducting qubits. Researchers indicated they are working to overcome these obstacles.

2. Ion Trap—Quantum Volume#

Ion traps, also known as ion confinement, utilize the interaction force between charges and electromagnetic fields to restrain the motion of charged particles, using two energy levels composed of the ground state and excited state of confined ions as qubits. Quantum states are manipulated using microwave lasers, and qubit initialization and detection are achieved through continuous pumping light and state-related fluorescence.

Ion trap quantum computers have three main characteristics: high qubit quality, long coherence time, and high efficiency in qubit preparation and readout. Currently, ion trap quantum computers lead other technology routes in terms of qubit connectivity and coherence time. However, the issue of poor scalability is a major problem that needs to be addressed in ion trap systems.

In recent years, research teams around the world have been attempting to create ion trap quantum computers, with captured ions serving as entangled qubits to perform advanced computations. These computers have proven to be one of the most promising systems for practical quantum computing applications.

In 2021, ion trap quantum computers achieved new milestones. In January 2021, the research group led by Jin Qihuan at Tsinghua University first improved the coherence time of single qubits in ion trap systems to over one hour, reaching 5500 seconds.

• In June 2021, researchers at the University of Innsbruck successfully demonstrated a compact ion trap quantum computer.
• In August 2021, IonQ introduced the first reconfigurable multi-core quantum architecture (RMQA), claiming that this architecture can expand the number of qubits per chip to hundreds without compromising the stability and performance of the qubits as their numbers increase.
• In September 2021, a research team led by Professor Luo Le from Sun Yat-sen University achieved automated processing of qubit micromotion suppression in ion traps using artificial neural network technology and radio frequency microwave-spontaneous emission photon correlation technology, marking the first application of neural network technology in controlling micromotion of trapped ion qubits internationally.
• In September 2021, a research team led by the National Institute of Standards and Technology (NIST) in the United States set a world record for two-qubit gate fidelity without laser schemes, achieving [0.9964, 0.9987]. This scheme may allow simultaneous entanglement operations on multiple pairs of ions in large-scale ion trap quantum processors without increasing control signal power or complexity.
• In October 2021, the research group led by Duan Luming at Tsinghua University made significant progress in ion trap quantum information processing by achieving efficient cooperative cooling of long ion chains through laser cooling of a small number of optimally selected ions for the first time, reaching temperatures close to the limit of global laser cooling and preparing the technical foundation for multi-ion qubit quantum computing.
• In October 2021, researchers at the Joint Quantum Institute (JQI) at the University of Maryland achieved a lower error rate logic qubit by implementing a logical qubit through multiple physical qubits with higher error rates for the first time in experiments.
• In December 2021, the Honeywell team (now Quantinuum) achieved real-time detection and correction of quantum errors for the first time. Researchers used [[7, 1, 3]] color codes to encode, control, and repeatedly correct a single logical qubit using 10 physical qubits in the Honeywell ion trap quantum computer.
• On the last day of 2021, Quantinuum surprised again, announcing that their Honeywell H1-2 quantum computing system measured a quantum volume of 2048, the highest value among all technology routes.

3. Photonic Quantum—The Year of Commercialization Begins#

Quantum computing based on photons has several unique properties. First, the quantum states of photons can be maintained without a vacuum or cooling system, as their interaction with the external environment is extremely weak. Photonic quantum computers can operate in atmospheric environments at room temperature. Second, photons are the best information carriers for quantum communication because they propagate at the speed of light and provide large bandwidth for high data transmission capacity. Therefore, photonic quantum computers are fully compatible with quantum communication. The large bandwidth of photons also enables high-speed (high clock frequency) operations in photonic quantum computers. However, these characteristics also present inherent difficulties for quantum computing. Since photons do not interact with each other, it is challenging to implement two-qubit entanglement gates that require interaction between photons. Additionally, since photons propagate at the speed of light and do not stay in one place, many optical components must be arranged along the path of the photons, leading to inefficiencies. Currently, research on photonic quantum computers mainly focuses on overcoming these difficulties.

The year 2021 saw fruitful research results related to photonic quantum, marking the beginning of the commercialization of photonic quantum computers.

• In January 2021, scientists at the University of Tartu in Estonia found a method to develop a new type of optical quantum computer, showing that certain rare earth ions with specific characteristics can act as qubits, potentially bringing ultra-fast computing speeds and better reliability compared to earlier solutions.
• In February 2021, the National University of Defense Technology and other teams collaborated to develop a new type of programmable photonic quantum computing chip, which achieved complete programmable control over factors such as quantum walk evolution time, Hamiltonian, particle indistinguishability, and particle exchange characteristics for the first time, supporting various quantum algorithm applications based on quantum walk models.
• In March 2021, Canadian photonic quantum computing company Xanadu launched the X8 photonic quantum processor. This is a programmable, scalable photonic quantum chip capable of executing multiple algorithms. It can be integrated into existing fiber-optic telecommunications infrastructure, making it easier to scale and effectively reduce operational costs.
• In May 2021, the Extreme Optics Innovation Research Team at Peking University, along with collaborators, developed a multi-path Mach-Zehnder interferometer for Wheeler's delayed choice measurement device. This chip integrates over 350 photon components and nearly 100 adjustable phase shifters, making it one of the largest photonic quantum chips to date.
• In July 2021, researchers at the Technical University of Denmark achieved a complete platform for photonic quantum computing. This platform is versatile and scalable, with all operations conducted at room temperature and directly compatible with standard fiber-optic networks.
• In July 2021, the team led by Jin Xianmin at Shanghai Jiao Tong University proposed the first scalable dedicated photonic quantum computing scheme based on a photonic integrated chip, achieving a quantum acceleration algorithm for the "fast arrival" problem in experiments for the first time. In August 2021, a research team led by Xu Yi, an assistant professor at the University of Virginia, successfully achieved 40 quantum modes (qumodes) on a coin-sized chip using a frequency comb based on optical micro-resonators, marking the largest number of modes achieved on an integrated optical platform to date.
• In October 2021, the team led by Pan Jianwei and Lu Chaoyang at the University of Science and Technology of China successfully developed "Jiuzhang No. 2" based on the quantum computing prototype "Jiuzhang," increasing the number of photons from 76 to 113, achieving speeds for specific problems that are billions of times faster than supercomputers.
• In December 2021, photonic quantum computing company ORCA Computing achieved a photonic quantum computing platform known as the "Variational Bosonic Solver," which can be used to solve unconstrained quadratic binary optimization (QUBO) problems.

4. Neutral Atoms—Leading in the U.S.#

Quantum computing with neutral atoms typically captures and confines ultra-cold atoms from magneto-optical traps or Bose-Einstein condensates (BEC) using far-detuned optical dipole trap arrays or optical lattices in ultra-high vacuum cavities. The two magnetic energy levels of the hyperfine energy levels of the atomic ground state are encoded as the 0 and 1 states of a qubit. High numerical aperture lenses focus the Raman light, Rydberg excitation light, and state preparation light needed for manipulating atomic qubits onto individual atoms, allowing control over the qubits in the array. Simultaneously, the lenses collect the fluorescence of the atoms and transmit it to an electron-multiplying charge-coupled device (EMCCD) for quantum state detection.

Ion trap quantum computers have three main characteristics: high qubit quality, long coherence time, and high efficiency in qubit preparation and readout. Currently, ion trap quantum computers lead other technology routes in terms of qubit connectivity and coherence time. However, the issue of poor scalability is a major problem that needs to be addressed in ion trap systems.

In recent years, research teams around the world have been attempting to create ion trap quantum computers, with captured ions serving as entangled qubits to perform advanced computations. These computers have proven to be one of the most promising systems for practical quantum computing applications.

In 2021, ion trap quantum computers achieved new milestones. In January 2021, the research group led by Jin Qihuan at Tsinghua University first improved the coherence time of single qubits in ion trap systems to over one hour, reaching 5500 seconds.

• In June 2021, researchers at the University of Innsbruck successfully demonstrated a compact ion trap quantum computer.
• In August 2021, IonQ introduced the first reconfigurable multi-core quantum architecture (RMQA), claiming that this architecture can expand the number of qubits per chip to hundreds without compromising the stability and performance of the qubits as their numbers increase.
• In September 2021, a research team led by Professor Luo Le from Sun Yat-sen University achieved automated processing of qubit micromotion suppression in ion traps using artificial neural network technology and radio frequency microwave-spontaneous emission photon correlation technology, marking the first application of neural network technology in controlling micromotion of trapped ion qubits internationally.
• In September 2021, a research team led by the National Institute of Standards and Technology (NIST) in the United States set a world record for two-qubit gate fidelity without laser schemes, achieving [0.9964, 0.9987]. This scheme may allow simultaneous entanglement operations on multiple pairs of ions in large-scale ion trap quantum processors without increasing control signal power or complexity.
• In October 2021, the research group led by Duan Luming at Tsinghua University made significant progress in ion trap quantum information processing by achieving efficient cooperative cooling of long ion chains through laser cooling of a small number of optimally selected ions for the first time, reaching temperatures close to the limit of global laser cooling and preparing the technical foundation for multi-ion qubit quantum computing.
• In October 2021, researchers at the Joint Quantum Institute (JQI) at the University of Maryland achieved a lower error rate logic qubit by implementing a logical qubit through multiple physical qubits with higher error rates for the first time in experiments.
• In December 2021, the Honeywell team (now Quantinuum) achieved real-time detection and correction of quantum errors for the first time. Researchers used [[7, 1, 3]] color codes to encode, control, and repeatedly correct a single logical qubit using 10 physical qubits in the Honeywell ion trap quantum computer.
• On the last day of 2021, Quantinuum surprised again, announcing that their Honeywell H1-2 quantum computing system measured a quantum volume of 2048, the highest value among all technology routes.

5. Semiconductor Quantum Dots/Silicon Spins—Promising Quantum Dots#

Quantum dots are semiconductor nanostructures that confine excitons in three spatial dimensions. They are an important type of low-dimensional semiconductor material, with sizes in all three dimensions not exceeding twice the corresponding exciton Bohr radius of the semiconductor material. Silicon quantum dots are a part of the quantum dot examples. By adding electrons to pure silicon, scientists have created silicon quantum dots, which are artificial atoms that use microwaves to control the quantum states of electrons.

The advantage of silicon lies in its ability to leverage decades of accumulated experience in large-scale integrated circuit manufacturing from traditional microelectronics. Silicon qubits are more stable than superconducting qubits and have longer coherence times, but they require low temperatures and have fewer entangled states. Semiconductor quantum computing is currently a hot and mainstream research direction internationally.

• In April 2021, Origin Quantum, in collaboration with Academician Guo Guangcan's team from the University of Science and Technology of China, discovered the anisotropy of spin qubit control: by changing the relative direction of the applied magnetic field to the silicon crystal orientation, they could simultaneously optimize the control speed, decoherence rate, and addressability of spin qubits.
• In May 2021, Origin Quantum, in collaboration with Academician Guo Guangcan's team, achieved high-sensitivity measurement of the excitation energy spectrum of semiconductor double quantum dots using microwave superconducting resonators, providing an effective method for achieving high-fidelity readout of semiconductor qubits in the future.
• In May 2021, the silicon-based quantum computing company Equal1 Laboratories in the U.S./Ireland integrated qubits with all supporting control and readout electronic devices on the same integrated circuit using commercial silicon technology. In June 2021, a research group from RIKEN in Japan increased the number of entangled silicon-based spin qubits from 2 to 3, achieving a fidelity of 88% for the generated three-qubit state, which is in an entangled state suitable for error correction.

In October 2021, a research team from the University of Copenhagen achieved simultaneous operation of multiple spin qubits on a single quantum chip. In January 2022, the team led by Academician Guo Guangcan from the University of Science and Technology of China, along with researchers from the U.S. and Australia, achieved ultra-fast control of silicon-based spin qubits, which is currently the highest reported value internationally.

6. Topological Quantum Computing—Still Uncertain#

Quantum computing is a research scheme that utilizes quasi-particles with non-Abelian statistics in topological materials to construct qubits and perform quantum computations. Due to the topological stability of materials, topological quantum computing uses topological quantum states in many-body systems to store and manipulate quantum information, possessing inherent fault tolerance, and is expected to address key issues of qubit decoherence and fault-tolerant quantum computing. Although Microsoft retracted its paper on the discovery of Majorana fermions, 2021 still saw certain achievements in topological quantum computing.

At the beginning of 2021, Professor Li Qiang from the State University of New York discovered the key to achieving topological quantum computing, finding a new light-induced switch that can distort the lattice of Weyl semimetals, enabling a nearly dissipation-free massive electron flow. The discovery of these properties has advanced the realization of applications such as topological quantum computing. In 2021, China also made a series of breakthrough advancements in the exploration and implementation of this scheme. In material growth and preparation, the research group led by Zhao Jianhua at the Institute of Semiconductor Research of the Chinese Academy of Sciences used molecular beam epitaxy technology to prepare high-quality pure-phase InAs, InSb, and InAsSb semiconductor nanowires, achieving low-temperature in-situ epitaxial growth of superconductors on nanowires, with the heterojunction interface reaching atomic-level flatness. The research group led by He Ke and Xue Qikun at Tsinghua University prepared a new semiconductor nanowire system using selective area epitaxy, effectively reducing the impact of impurities on topological quantum devices and substrate lattice mismatch, laying the foundation for further realization of multiple Majorana quantum devices. In the preparation and transport measurement of topological quantum devices, Shen Jie from the Institute of Physics of the Chinese Academy of Sciences and Kouwenhoven from Delft University of Technology mapped out the complete electronic parity (parity) phase diagram in the quantum device "Majorana Island," providing clear information on the correlation between Coulomb oscillation amplitude and peak value, laying the groundwork for future construction of topological qubits. The theoretical group led by Liu Dong at Tsinghua University proposed an experimental detection method that utilizes the renormalization effect of the interaction between electrons introduced by dissipative electrodes and environmental bosons, allowing Majorana transport signals and other trivial transport signals to exhibit completely different scaling behaviors and temperature-voltage dependencies, thus potentially resolving the competition and debate over "Majorana states—Andreev states" in nanowire systems.

Table 8 Important Progress in Topological Quantum Computing in 2021

7. Diamond NV Centers—Great Expansion Difficulty#

Diamond NV centers exhibit excellent optical characteristics, such as observable zero-phonon lines at room temperature, stable luminescence, and long coherence times, especially with a very special fine energy level structure that allows for high-precision physical quantity detection and quantum control. Among them, ultra-low concentration NV centers, especially single NV centers, have received widespread attention in fields such as photon entanglement and quantum control. In addition, NV centers have been applied in precision measurement fields, such as temperature measurement, magnetic field measurement, ultra-high-resolution imaging, and high-performance gyroscopes. However, there are significant challenges in scaling up for use in quantum computers. In April 2021, the quantum computing startup Quantum Brilliance developed a compact quantum computer based on diamond NV centers, containing 5 qubits, and plans to launch a 50-qubit quantum computer within five years.

8. Quantum Annealers—Limited Progress Currently#

Quantum computers can be divided into quantum logic gate computers and quantum annealers. The major technology routes mentioned earlier are all proposed for building quantum logic gate computers, which are referred to as universal quantum computers. The first seven systems in this report are all gate-based quantum computing schemes. Quantum annealers do not require quantum logic gates but instead search for optimal solutions through the Ising model, making them a specialized quantum computer with unique advantages in optimization problems. Overall, there has been limited progress in quantum annealing technology in 2021. Notably, in 2021, quantum annealing pioneer D-Wave announced plans to develop gate-based quantum computers, indicating that the prospects for quantum annealers may be limited.

9. Coherent Ising Machines—Continue to Observe#

Coherent Ising machines (CIM) and quantum annealers share similar principles, both based on the Ising model, resembling a programmable network composed of artificial magnets, akin to a real magnetic system where each magnet can only be "up" or "down," tending to operate in low-energy states. The working principle is that if the connections between the magnet networks can be reprogrammed to represent real problems, once they set the optimization and low-energy direction they need to face, solutions can be inferred from their final states.

In quantum annealers, these artificial magnets are replaced by superconducting circuits as qubits. CIM replaces superconducting circuits with a special laser system called degenerate optical parametric oscillators (DOPO). CIM performs calculations using coupled DOPO pulses, attempting to find the best solution by measuring the final phase of the pulses. The optical pulses used in CIM can travel back and forth, allowing any two pulses to interact directly. Meanwhile, the underlying devices designed with optical components do not require low-temperature environments, offering high stability and good controllability.

Currently, research institutions and universities, including NTT, NII, NASA, Stanford, Caltech, Maryland, and the University of Tokyo, along with China's Boson Quantum Technology Company, are engaged in CIM research and development.

• In September 2021, Japan's NTT Basic Research Laboratory achieved a CIM computing experiment with 100,512 spin qubits, breaking the 100,000 barrier, leading all quantum computing technology schemes. Although the spin qubits of CIM cannot be directly compared to the number of qubits in universal quantum computing, this breakthrough can still be considered a milestone event. Domestic CIM research is still in its infancy, with Boson Quantum established at the end of 2020, and the company has revealed that it has completed the construction of a photonic quantum laboratory and is developing a 1000+ qubit-level CIM quantum AI co-processor engineering prototype, along with corresponding acceleration algorithms.

Core Components—Discovery and Breakthrough Report#

Key research focuses on low-temperature devices (primarily mK-level dilution refrigerators) that are essential for superconducting or semiconductor quantum computers, as well as quantum measurement and control systems (referred to as "measurement and control systems") that are crucial for controlling, processing, and computing quantum chips; coaxial cables serve as the bridge connecting low-temperature quantum chips and room-temperature measurement and control systems; additionally, superconducting quantum computers require extra low-temperature devices to prevent environmental noise interference; ultra-high vacuum equipment is essential for ion trap and neutral atom systems; the application of lasers is widespread, as systems like photonic, ion traps, and neutral atoms all require laser cooling or manipulation of qubits; other core components include single-photon sources and single-photon detectors, with single-photon sources mainly used in photonic quantum computers, while single-photon detectors are used in both photonic and ion trap systems.

Dilution refrigeration technology was first proposed in the 1950s and was concretely realized in the 1960s. The currently popular liquid-helium-free dilution refrigerators combine dilution refrigeration technology with liquid-helium-free cold head technology. From a theoretical standpoint, dilution refrigerators utilize the phase separation phenomenon occurring in a mixture of two isotopes of helium, helium-3 and helium-4, at around 0.8K. After phase separation, the mixture of helium-3 and helium-4 stratifies, with the upper layer being a lower-density helium-3-rich phase and the lower layer being a higher-density helium-3 dilution phase. By designing a gas circulation loop to allow helium-3 to circulate, the process of helium-3 atoms crossing the phase separation interface from the helium-3 concentrated phase to the helium-3 diluted phase at low temperatures is an endothermic cooling process, forming the lowest temperature in the mK range at this phase separation interface. Since it utilizes the physical processes of concentrated and diluted helium-3, this refrigerator is named a dilution refrigerator.

Technically, dilution refrigerators need to be placed in a vacuum chamber to achieve thermal insulation between low-temperature components and the external environment. To achieve the lowest temperature in the mK range, multi-stage cooling is required. First, the liquid-helium-free cold head of the refrigerator can provide a 4K basic low-temperature environment. On this basis, when the helium-3 and helium-4 mixture flows through the 4K cold plate, helium-4 can be initially liquefied. Then, evaporation cooling and the Joule-Thomson effect are used to completely liquefy helium-3 and helium-4, reaching a low temperature of around 1K. On this basis, the evaporation cooling of helium-3 can further lower the mixture temperature to achieve phase separation. Finally, the dilution refrigeration principle is used to achieve extremely low temperatures in the mK range.

The explosion of quantum computing both domestically and internationally has made companies like Bluefors, representing dilution refrigerators, leap into the ranks of "new stars" in the high-tech field. Currently, the main suppliers of dilution refrigerators internationally include Finland's Bluefors, the UK's Oxford Instruments, the US's JanisULT, and the Netherlands' Leiden Cryogenics. Bluefors has long held the largest market share due to its early entry into the quantum computing field, followed by Oxford Instruments. For instance, according to the bidding announcement from the Beijing Quantum Information Science Research Institute, the unit purchased 8 Bluefors and 5 Oxford Instruments dilution refrigerators in 2021. Currently, Bluefors offers four series of dilution refrigerators: SD, LD, XLD, and LH. Among them, the LD series is the best-selling dilution refrigerator from Bluefors, including LD250 and LD400.

In November 2021, Bluefors announced the launch of a new low-temperature platform, KIDE. This platform provides stronger cooling capabilities for larger chips. It can connect three hexagonal units to create a three-way quantum computing cluster. This low-temperature platform is still under development, but IBM has already announced its use in the upcoming IBM Quantum System 2 series machines.

In 2021, in addition to continuing deep cooperation with IBM, Bluefors joined Finland's quantum computing industry alliance BusinessQ to support enterprises in adopting and developing quantum technologies and solutions. Compared to Bluefors, Oxford Instruments entered the quantum computing market later, but in recent years, its dilution refrigerators have increasingly gained favor among quantum computing R&D teams, especially after launching the latest generation of liquid-helium-free dilution refrigerators, Proteox, in 2020. To date, Oxford Instruments has launched a series of dilution refrigerators with different models and application orientations, including the modular dilution refrigerator ProteoxMX (<10mK), the multi-qubit quantum computing dedicated liquid-helium-free dilution refrigerator ProteoxLX (<7mK), and the extreme low-temperature refrigerator Proteox5mK with a base temperature of 5mK.

The Proteox dilution refrigerator has further upgraded the bottom rapid sample exchange function, which can greatly improve the efficiency of quantum bit chip screening for users conducting rapid screening of small qubit samples and exploring process parameters. The bottom rapid sample exchange function can replace quantum bit chips individually without raising the entire refrigerator's temperature. Traditional dilution refrigerators typically take about 2-3 days to cool down overall, while the Proteox's design with bottom sample loading reduces the entire chip replacement and re-cooling time to just 3.5 hours. This will significantly enhance the efficiency of quantum bit chip screening.

2. Measurement and Control Systems#

Systems like ion traps, neutral atoms, and photons use natural particles as qubits, mainly manipulated through lasers. However, for superconducting and semiconductor quantum computers, quantum measurement and control systems (referred to as "measurement and control systems") play a crucial role in controlling, processing, and computing quantum chips. Early quantum measurement and control systems were built by quantum computing R&D teams using a series of scientific instruments. The biggest challenge of measurement and control systems is the need to manipulate multiple qubits simultaneously, as at least three or more DAC output channels are required for a single qubit, and at least two DAC output channels are needed while reading with ADC. When the number of qubits reaches dozens, synchronizing multiple channels and issuing a large number of experimental commands to hardware simultaneously within milliseconds becomes one of the most pressing challenges to solve. In recent years, a few domestic and foreign companies have developed dedicated measurement and control systems for quantum computers.

Table 9 Development History of Quantum Measurement and Control Systems

In 2016, Zurich Instruments began researching quantum measurement and control technology, subsequently launching quantum measurement and control software—LabOne. In 2018, Zurich Instruments introduced the first commercial quantum computing control system (QCCS) for controlling superconducting and spin qubits. Google developed an automated calibration system for quantum chips named Optimus in 2019 for its "quantum computational superiority" experiment. Additionally, the American measurement instrument company Tektronix was one of the earliest developers of quantum measurement and control systems.

In China, Chengdu Microda Technology, established in 2017, is one of the earliest teams to start developing measurement and control systems for superconducting quantum computers. After years of development, the company has collaborated with approximately 70% of domestic quantum computing companies and research institutions, providing quantum measurement and control system equipment and solutions to institutions such as the University of Science and Technology of China, Beijing Quantum Information Science Research Institute, and Southern University of Science and Technology. Microda launched the world's first system architecture based on secondary frequency conversion in 2018, featuring uV-level ultra-low noise, ultra-high stability DC voltage generation, and core indicators superior to advanced foreign products; it supports thousands of channels with scalable picosecond-level synchronization precision for low-noise arbitrary waveform generation; signal synchronization precision reaches 1ps with low-jitter triggering and timing control; and it generates ultra-wideband, low-phase noise, high-stability, and highly integrated microwave signals ranging from 200M to 20G.

Microda's quantum measurement and control technology layout covers all stages of quantum computer development, involving two major technology routes: room temperature measurement and control, and low temperature measurement and control. According to its roadmap, under room temperature measurement and control technology, the company has achieved scalable quantum computing measurement and control for 100 qubits, expecting to achieve full coverage for 1000 qubit-level room temperature quantum computing measurement and control by 2022. Under low temperature measurement and control technology, it is expected to develop a 1000 qubit-level low temperature quantum measurement and control chip within three years. According to the quantum computing roadmaps released by major domestic and foreign participants such as IBM and Origin Quantum, by around 2023, quantum measurement and control systems need to achieve control capabilities at the 1000 qubit level.

Origin Quantum launched the first commercial quantum measurement and control integrated machine, Origin Quantum AIO, in 2018, totaling 40 functional channels, with an output frequency range of 12-16 GHz, capable of measuring and controlling 8 qubits.

In 2020, the second-generation quantum measurement and control integrated machine was launched, supporting 216 channels, with 200 picoseconds synchronization stability, capable of measuring and controlling 32 qubits, providing a flexible Python interface library. Origin Quantum also developed supporting quantum measurement and control software PyQCat to improve testing speed while supporting more efficient quantum feedback functions.

In addition to the aforementioned companies, several new quantum measurement and control system suppliers have emerged in recent years, including GuoDun Quantum, one of China's earliest quantum technology companies.

GuoDun Quantum relies on the technical advantages accumulated over years of research and development and service in quantum information products. In April 2020, it proactively laid out quantum computing and officially established the Quantum Computing Control Technology Department. To meet the demand for multi-qubit superconducting quantum computing, GuoDun Quantum, in collaboration with the University of Science and Technology of China, launched the ez-Q™ Engine superconducting quantum computing control system in 2020. The overall price is only one-third to one-half of foreign commercial instruments. This product has been provided to teams such as the Institute of Physics of the Chinese Academy of Sciences and Southern University of Science and Technology. Based on this, an optimized version was launched in March 2021, improving product integration and convenience. The system can support over 100 qubits and is currently one of the largest quantum computing control systems in terms of the number of controlled qubits. The relevant technology has been applied to "Zuchongzhi" and completed the "quantum computational superiority" experiment.

In addition, the Dutch startup Qblox launched and demonstrated its next-generation quantum control stack at the American Physical Society (APS) annual meeting in 2021, providing all input and output signals from ultra-long DC to 18.5 GHz. It is packaged in a 19-inch rack called Cluster, capable of controlling and reading 20 qubits.

In addition to the currently widely used room temperature quantum measurement and control systems, Intel also launched the quantum bit low-temperature control chip Horse Ridge in 2019, followed by the second-generation chip in 2020. Horse Ridge simplifies the complex wiring of quantum system control by introducing key control functions of quantum computers into low-temperature refrigeration equipment—to get as close to the qubits themselves as possible. Research by Intel and QuTech in 2021 showed that their CMOS-based low-temperature controller devices achieved coherent control of a two-qubit processor at the same fidelity level (99.7%) as room temperature electronic devices. In 2021, there were other advancements in commercial quantum measurement and control systems. Tektronix achieved the integration of quantum measurement and control systems with dilution refrigerators, marking the first time in the industry.

• In March 2021, Zurich Instruments released the SHFQA quantum analyzer, with a single measurement and control system capable of reading up to 64 qubits.
• In July 2021, Australian company Archer Materials announced the development of a quantum bit control chip, marking the first time Archer recorded continuous wave electron spin resonance (cwESR) signals generated by specially designed superconducting devices on integrated micro quantum bits. They found that the on-chip cw-ESR signal characteristics were very consistent with signals obtained from room temperature measurements.
• Figure 7 shows the integrated measurement and control system. The left image is the Bluefors LD250 dilution refrigerator; the right image is the integration of the quantum measurement and control system with the dilution refrigerator.

In academia, significant breakthroughs have also been made in qubit control technology. In August 2021, researchers at the University of New South Wales in Australia proposed a new technology capable of simultaneously controlling millions of spin qubits. The team proposed a method of generating magnetic fields above the chip to manipulate all qubits simultaneously. Researchers found that the field generated by the resonator could control an area capable of accommodating 4 million qubits. Microsoft also proposed technology to control thousands of qubits. In November 2021, researchers from the University of Sydney and Microsoft invented a single chip that operates at a temperature 40 times lower than deep space temperature, demonstrating that "only two cables for transmitting information as input can generate control signals for thousands of qubits." In December 2021, researchers from Huazhong University of Science and Technology, in collaboration with researchers from Aalto University in Finland and VTT (Finnish National Technical Research Center), developed an on-chip device capable of generating high-quality microwave signals required for controlling quantum computers, which can operate at temperatures close to absolute zero. However, this device's microwave source cannot yet be directly used to control qubits, as the microwaves must be shaped into pulses. The team is currently developing methods to quickly turn the microwave source on and off.

3. Coaxial Cables#

Low-temperature coaxial cables are a type of superconducting cable specifically designed for transmitting, controlling, and reading microwave signals of qubits. Coaxial cables connect to the analog signal circuits in the rack/refrigerator, ensuring that the fragile quantum states of qubits are not destroyed, primarily used in superconducting quantum computers. Currently, Japan's Coax Company is the main manufacturer of coaxial cables, established in 1974, providing low-temperature semi-rigid cables. These cables are made of low-thermal-conductivity metal materials on the center and outer conductors, which can minimize the impact of external low temperatures. Another supplier is Delft Circuits, a Dutch startup founded in 2016, which mainly provides low-temperature coaxial cable Cri/oFlex® series products that can help monitor and control qubits, including some specialized cables for transmitting microwave signals. Currently, coaxial cables specifically for quantum computers are almost monopolized by these two companies. In August 2021, the U.S. DARPA released a tender for high-density connector low-temperature cable projects, requesting the industry to determine the feasibility of developing high-density connector low-temperature cables for future use in superconducting classical computing, superconducting quantum computing, and superconducting single-photon detector arrays. The goal is to create a new type of high-density data cable for superconducting electronic applications, featuring high density, low attenuation, low crosstalk, and low thermal load.

4. Low-Temperature Components#

The interaction between low-temperature quantum chips and room temperature measurement and control systems is a significant challenge faced by superconducting quantum computers. Coaxial cables serve as the bridge connecting them, but thermal processing must be performed at each temperature stage of the refrigerator during wiring to avoid overheating the mixing chamber. Additional components (including attenuators, filters, and amplifiers) need to be inserted at each stage.

Attenuators, filters, and amplifiers connect to the quantum processor for control and readout, corresponding to drive lines, flux lines, and output lines. In simple terms, attenuators are used to reduce in-band radiation, while filters (for signals not within the desired frequency range of the attenuator) are used to eliminate out-of-band radiation noise that does not fall within the frequency range of the signal intended for transmission to the device. After optimizing the signal through attenuators and filters, low-temperature amplifiers are used to enhance the signal. The main manufacturers of low-temperature amplifiers include American companies AmpliTech, B&Z Technology, L3Harris Narda-MITEQ, and QuinStar Technology Inc., as well as British Atlantic Microwave, Swedish Low Noise Factory, and Canadian Nanowave Technologies. China's Fudong Quantum Technology Company also has such products.

The main manufacturers of low-temperature attenuators include American API Technologies, XMA Corporation, and Quantum Microwave, as well as Japan's KEYCOM Corporation.

In February 2021, China's Origin Quantum announced the launch of ultra-low temperature series attenuators suitable for 10mK temperature environments.

Low-temperature high-pass filters are mainly produced by American Quantum Microwave. Origin Quantum also has related products. Origin Quantum established a long-term project team for low-temperature electronic devices in its quantum measurement and control department, focusing on the development of products such as circulators, power dividers, filters, Bias-Tee, and low-noise amplifiers.

5. Ultra-High Vacuum (UHV)#

Ultra-high vacuum is the necessary operating environment for ion trap qubits and neutral atom qubits, and even some semiconductor qubits require such environments. For example, Honeywell and IonQ's ion trap quantum chips are placed in a vacuum chamber the size of a basketball. Founded in 1961, the Canadian company Johnsen Ultravac Inc. (JUV) is a top supplier of ultra-high vacuum products globally. JUV's users span numerous research institutions and laboratories in North America, Europe, and Asia. Domestic suppliers of ultra-high vacuum chambers mainly include Beijing Weiyi Vacuum, Htc Riyan Vacuum, and Bart Vacuum Technology (Suzhou) Co., Ltd.

JUV's ultra-high vacuum chambers come in various standard configurations. They can be manufactured to meet specific technical and performance requirements based on customers' special needs, achieving vacuum performance in the range of 10^-11 torr. Current ultra-high vacuum chambers can basically meet the needs of quantum computers in ion trap systems.

In March 2021, the National Institute of Standards and Technology (NIST) in the United States planned to construct a cold atom vacuum sensor (CAVS) capable of measuring pressure under ultra-high vacuum (UHV) conditions, with corresponding pressures below 10^-7 Pa or 10^-9 torr. Currently, there are no reliable measurement tools at such pressures. The working principle of CAVS is to link the losses of ultra-cold 1μK lithium atoms caused by collisions with environmental room temperature atoms and molecules to the background pressure. This project theoretically determines the elastic rate coefficients of lithium atoms colliding with related background atoms and molecules and their temperature dependence.

6. Lasers#

The key difference between lasers and traditional light sources is the "coherence" of the light beam. Coherence determines the ability of a laser beam to perform various precision tasks, and high coherence makes lasers suitable for application in high-precision devices. For example, when controlling components of quantum computers, specific frequencies of highly coherent light beams are needed to control a large number of qubits for extended periods, and future quantum computers may require even more coherent light sources. Quantum computing systems such as ion traps, photons, and neutral atoms all require lasers.

Currently, the mainstream lasers are fiber lasers, with the American company IPG, founded in 1990, being the largest manufacturer of fiber lasers globally. Their product line covers high, medium, and low-power fiber lasers. The leading domestic laser company is the publicly listed company Raycus Laser, whose high-power laser technology has reached an internationally leading level and is gradually replacing products from major overseas laser manufacturers in the domestic market.

On December 10, 2021, the first 100kW ultra-high-power industrial fiber laser and supporting equipment jointly developed by Raycus Laser and Nanhua University were officially put into operation. From project initiation to successful development and delivery, it took only six months. As the largest industrial fiber laser in China and the second-largest in the world, it will play a significant role in advanced manufacturing, aerospace, and medical equipment.

7. Single-Photon Sources#

Deterministic high-quality single-photon sources are key components for developing photonic quantum information technology, including quantum communication and photonic quantum computing. Spontaneous parametric down-conversion (SPDC) is a traditional device for generating single photons, but it is an uncertain single-photon source with a low generation probability. In recent years, the application of quantum dot-based photon sources has become increasingly widespread. In 2013, the team led by Pan Jianwei and Lu Chaoyang at the University of Science and Technology of China pioneered the quantum dot pulse resonance excitation technology internationally. In 2016, this team achieved the best overall performance of single-photon sources reported internationally at that time. In 2019, they proposed coherent two-color excitation and elliptical microcavity coupling theoretical schemes, experimentally solving the two last challenges faced by single-photon sources: mixed polarization and laser background scattering, successfully developing deterministic polarization, high purity, high indistinguishability, and high-efficiency single-photon sources. Based on this, the photonic quantum computing prototype "Jiuzhang" successfully achieved "quantum computational superiority."

In addition to single photons, photonic quantum computers can also use continuous variables, such as squeezed light. In the "Jiuzhang" photonic quantum computer, squeezed states are produced through optical parametric down-conversion (OPDC). The Canadian quantum computing company Xanadu produces squeezed states of light by replacing large nonlinear crystals in optical parametric amplifiers with nanophotonic waveguide resonators. In December 2021, Japan's NTT, the University of Tokyo, and RIKEN collaborated to develop a fiber-coupled squeezed light source that can operate at optical communication wavelengths. By combining it with fiber-optic components, they successfully generated continuous-wave squeezed light in a fiber-closed system for the first time, with quantum noise squeezed by over 75% and sideband frequencies exceeding 6 THz.

8. Single-Photon Detectors#

In quantum experiments, the life of a photon begins with its generation and ends with its detection, both of which require high efficiency. Currently, the main single-photon detectors used in quantum information technology include single-photon avalanche diodes (SPADs), superconducting nanowire single-photon detectors (SNSPDs), and electron-multiplying charge-coupled devices (EMCCDs). The first two types are mainly applied in photonic quantum information technology, while EMCCDs are widely used in ion trap and neutral atom quantum computers.

Single-photon avalanche diodes (SPADs) (also known as Geiger-mode APDs, photon counters, SPADs, or single-photon detectors) are traditional single-photon detectors. Based on this technology, in September 2021, GuoDun Quantum launched the first compact, high-performance near-infrared free-running single-photon detector series product—QCD600, featuring high detection efficiency, low dark counts, and compact stability. This type of single-photon detector is widely used in the quantum communication field, with strong quantum communication companies launching SPAD-based single-photon detectors, such as IDQ, Qike Quantum, and Wentian Quantum. Additionally, they can be used in quantum lidar, fluorescence lifetime detection, and single-photon ranging in extremely weak light detection scenarios. The first batch of QCD600 trial production samples delivered by GuoDun Quantum has been applied in an atmospheric detection radar product.

Compared to SPADs, the rapidly developing superconducting nanowire single-photon detectors (SNSPDs) have higher detection efficiency but require operation at low temperatures of 0.8k–3k. In May 2021, the team led by Liang Jingtao at the Institute of Physics of the Chinese Academy of Sciences, in collaboration with the team led by You Lixing at the Shanghai Institute of Microsystem and Information Technology, made progress in the field of SNSPD technology for space applications, achieving a new record of 93% detection efficiency in the communication band. The high-efficiency single-photon detector used in "Jiuzhang" comes from You Lixing's team. Currently, the team founded by You Lixing, Fudong Quantum Technology (Zhejiang) Co., Ltd., has commercialized SNSPD products. According to their website, their superconducting nanowire single-photon detection system has a detection efficiency of 95%, a maximum counting rate of >50MHz, and a dark count rate of <1cps, with over 80 global users. Their products include single-mode fiber-coupled SNSPDs, large sensitive area SNSPDs, and multi-pixel SNSPD arrays, achieving international first-class technical capabilities.

Another type of single-photon detector is the electron-multiplying charge-coupled device (EMCCD) detector, mainly used in ion trap quantum computers. In ion traps, lasers manipulate the quantum states of ions: spin up (representing qubit state "0") or spin down (representing qubit state "1"). Illuminating ions in the spin-down state with lasers causes them to emit light, which can be measured by single-photon detectors, allowing differentiation between spin-up and spin-down states. Additionally, in neutral atom quantum computers, EMCCDs can also be used to collect the fluorescence of atoms, with applications not significantly different from those in ion traps.

Taking calcium ion trap quantum computers as an example, since all ions are always subjected to Doppler laser (397 nm) cooling illumination, ions in different states will respond differently to the 397 nm light. Ions in the ground state will emit fluorescence, while those in the excited state will not. If it is a multi-qubit system, it can be interpreted as a binary string where emitting ions represent 1 and dark ions represent 0. By collecting and measuring this light with a highly sensitive camera, the computational results can be obtained.

The ion trap is encapsulated within a high vacuum chamber, and the fluorescence of the ions can be observed through a high-sensitivity CCD camera outside the chamber. Charge-coupled devices (CCDs) are semiconductor photoelectric devices developed in the early 1970s based on the photoelectric effect, featuring high quantum efficiency, large dynamic range, and good linearity. However, CCDs do not meet the requirements for single-photon detection, so in 2000, the Oxford Instruments Group launched the world's first EMCCD camera. Compared to ordinary CCDs, EMCCDs introduce on-chip gain, allowing signals and dark noise to be amplified by G times without affecting readout noise (which only relates to readout speed). Due to short exposure times and high frame rates, readout noise is the main source of noise. By amplifying signals to suppress readout noise, EMCCDs can achieve high-speed single-photon detection capabilities.

The Quantum Information Center Laboratory at Tsinghua University's Institute for Interdisciplinary Information Research is conducting research on the key special project of ion trap quantum computing funded by the Ministry of Science and Technology, aiming to construct a prototype quantum computer with 5 to 10 qubits. This research work has significant scientific value and far-reaching application prospects. During the project implementation, a series of advanced ion trap experiments will be conducted to build a large ion system based on ytterbium ions, using Oxford Instruments ANDOR's iXon series EMCCD as the main detector for the ion trap computer. Currently, many research teams in China conducting ion trap quantum computing research extensively use this series of EMCCDs, such as the research groups of Zhang Xiang from Renmin University of China, Jin Qihuan from Tsinghua University, and Shen Heng from Shanxi University.

Cloud Platforms, Software, Algorithms—Application First#

Development is the foundation for quantum computing applications, but solving practical problems relies on the development of cloud platforms, software, and algorithms.

As of 2021, approximately 20 research institutions worldwide have launched quantum computing cloud platforms. Strangeworks, the Institute of Physics of the Chinese Academy of Sciences, and the Beijing Quantum Institute launched their cloud platforms for the first time in 2021. Currently, there are cloud platforms based on superconducting, ion trap, annealing, photonic, nuclear magnetic resonance, and silicon spin hardware. Overall, companies that launched cloud platforms in earlier years, such as IBM, Microsoft, and Google, primarily focused on upgrading the types of quantum hardware supported by their cloud platforms, the number of physical and logical qubits, and integrating and developing more features in 2021.

In terms of software, current program design mainly revolves around hardware development. As quantum computer hardware has achieved phased results and the hardware environment is relatively stable, software will be a key area needing significant development at this stage. Currently, the focus is on programs serving R&D, such as those available for chip circuit design and verification, experimental result analysis, etc., to improve R&D efficiency and reduce trial-and-error costs.

In terms of algorithms, since quantum computing has been proven to have significant advantages over classical computing in computational power, it will first benefit industries with clear computational needs. Currently, industries such as chemical pharmaceuticals, finance, transportation logistics, and artificial intelligence have begun related collaborative research. In finance, international banks such as CCB, KPMG, and Goldman Sachs have collaborated with quantum computing companies. In the chemical and pharmaceutical sector, companies like Nippon Steel, Roche, and Janssen Pharmaceuticals have conducted simulation experiments on new materials and new molecules in collaboration with quantum companies.

1. Progress of Cloud Platforms
   Cloud computing has matured after nearly two decades of development. With the rapid development of quantum computing, the organic combination of quantum computing and cloud computing has produced "quantum computing cloud platforms," greatly overcoming the current challenges of expensive manufacturing costs, high maintenance difficulties, and large space occupation of quantum computers. Quantum computing cloud platforms not only promote the development of quantum software and algorithms but also play a significant role in cultivating the entire quantum ecosystem and increasing public awareness of quantum computing. Quantum computing cloud platforms will assist the commercialization process of quantum computing for a long time to come, meeting users' needs with lower costs and higher quality services.

Since IBM launched its commercial quantum computing cloud platform in 2016, there have been over 325,000 registered users, with the open-source Qiskit software development kit downloaded over 650,000 times, running 2 billion quantum circuits daily on the IBM Quantum system, and over 700 papers published using IBM Quantum. As of now, over 20 companies/research institutions worldwide have developed quantum computing cloud platforms. Quantum computing cloud platforms will assist the commercialization process of quantum computing for a long time to come, meeting users' needs with lower costs and higher quality services.

1. Progress of Cloud Platforms
   Cloud computing has matured after nearly two decades of development. With the rapid development of quantum computing, the organic combination of quantum computing and cloud computing has produced "quantum computing cloud platforms," greatly overcoming the current challenges of expensive manufacturing costs, high maintenance difficulties, and large space occupation of quantum computers. Quantum computing cloud platforms not only promote the development of quantum software and algorithms but also play a significant role in cultivating the entire quantum ecosystem and increasing public awareness of quantum computing. Quantum computing cloud platforms will assist the commercialization process of quantum computing for a long time to come, meeting users' needs with lower costs and higher quality services.

Note 1: Among the 24 quantum systems launched on the IBM cloud platform, only 7 systems are available to Chinese users, with the highest qubit count being 5; IBM's 127-qubit chip has not yet been launched.
Note 2: Rigetti's 40 and 80-qubit processors are still in internal testing and have not yet been launched.
Note 3: The number of qubits in quantum annealers cannot be compared to those in gate-based quantum computers.
Note 4: Azure Quantum and Rigetti have reached a partnership to connect the latter's quantum computers in the first quarter of this year.
Note 5: Strangeworks QC is a quantum development environment compatible across hardware and software, allowing users to register directly for IBM Quantum through the platform.
Source: ICV

In 2021, the latest developments in quantum computing cloud platforms both domestically and internationally are as follows.

(A) Foreign Quantum Computing Cloud Platforms

1. IBM
   In March 2021, IBM announced that its quantum cloud platform consists of IBM Quantum Composer and IBM Quantum Lab, replacing the previous IBM Quantum Experience. IBM Quantum Composer is a graphical quantum programming tool that allows users to build quantum circuits and run them on real quantum hardware or simulators. In Quantum Lab, users can write scripts combining Qiskit code, equations, visualizations, and narrative text in a Jupyter Notebook environment, running code on real quantum hardware or simulators, and storing, accessing, and managing files from anywhere.

Currently, the IBM quantum computing cloud platform implements three levels of access. The most basic access is Open Access, where users can simply register to access multiple quantum computing systems provided by the public cloud; the intermediate access is Advance Access, which has more open and additional systems with higher qubit counts and capacities for specific users; the advanced access is Premium Access, which allows users to use IBM's most advanced quantum computing systems through subscription priority time allocation. Advance Access and Premium Access require special user permission applications.

2. Microsoft
   In February 2021, Azure Quantum services were upgraded to a public preview version, allowing users to access IonQ, Honeywell, and Quantum Circuits Inc.'s quantum computers, as well as optimization algorithms developed by Microsoft, 1QBit, and Toshiba.

In June 2021, Azure Quantum further expanded its solver products, adding two new algorithms: Subrandom Monte Carlo (SSMC) and Population Annealing (PA) to the existing solvers of Parallel Tempering (PT) and Quantum Monte Carlo (QMC). In July 2021, Microsoft announced that Azure Quantum would add four new features:

1. Quantum Python developers can send circuits directly to Azure Quantum, allowing them to experience and interact with the Azure Quantum ecosystem using familiar tools through integration with major quantum Python SDKs.
2. Developers can access Azure Quantum for free from Jupyter Notebooks.
3. A cloud-based full-state simulator has been added, allowing developers to simulate larger quantum programs.
4. A new open simulator (preview version) has been launched, enabling developers to simulate how programs will run on today's available hardware systems.

In December 2021, Rigetti Computing announced a partnership with Microsoft to provide Rigetti quantum computers to users of the Microsoft Azure Quantum service through the cloud. The integration is expected to be completed in the first quarter of 2022 and opened to users, making Rigetti systems the largest quantum computers on Azure Quantum.

3. Google
   In