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Insights into the Quantum Computing Industry#

2021 was a remarkable year for the quantum computing field. As the number of qubits grew significantly, 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 launch an 80-qubit processor within months; IBM introduced the 127-qubit Eagle processor. 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 more research indicating that photonic quantum computing can also be programmed. For instance, 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 1 million qubits by the end of this decade (2030).
   Table 1: Roadmap of Mainstream Quantum Computing Companies
   
   Another dimension to assess the usefulness of quantum computers is the quality of qubits, with key indicators including coherence time (determining how long quantum states 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 individual qubits only to four surrounding qubits. If connectivity can be improved, the scale of solvable problems could 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 the 2-qubit gates (entangling gates) in the most advanced quantum computing systems is over 99%. The highest record is 99.99%, achieved by an Australian silicon quantum computing company using semiconductor technology, although they have only developed 2 qubits.

No current technology route can lead in all indicators simultaneously, and different technology routes have their own advantages and disadvantages. Research teams continue to develop new qubits. Breakthroughs were also made in measurement and control in 2021. Some manufacturers, represented by Zurich Instruments, released measurement and control systems capable of measuring and controlling over 100 qubits. The most significant breakthrough was achieved by researchers at the University of New South Wales in Australia, who proposed a technology capable of controlling 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 could be defined as the competition between classical simulation and quantum computing, and this competition will continue, as significant advancements in classical computing have forced quantum computing to accelerate its development.

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

From the perspective 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. Companies like Microda and Guoshield Quantum have no gap with foreign manufacturers and can even reach higher levels. Additionally, breakthroughs have been made in low-temperature components such as attenuators and filters.

In terms of chip manufacturing, the current manufacturing process for quantum chips mainly takes place 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, the two laboratories independently built by Benyuan Quantum—the quantum chip manufacturing and packaging laboratory and the quantum computing assembly testing laboratory—were officially put into use. This is also the second engineering quantum chip laboratory established in China after the Benyuan-Jinghe Quantum Chip Joint Laboratory in 2021.

Quantum computing companies in the industry chain mainly focus on hardware and software research and development. Currently, leading hardware teams are mainly tech giants and strong research institutions (such as the University of Science and Technology of China), but China's tech giants entered the quantum computing field relatively late. Startups like Benyuan Quantum, Guoshield 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 demanding operating environment, and multimillion-dollar price tag of quantum computers mean that current quantum computing applications mainly occur through cloud platforms. Quantum computing and classical computing do not have a relationship of replacement; instead, they play unique advantages in specific scenarios that require extremely high computing power through high-speed parallel computing.

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 derivatives and options pricing.

• 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 (e.g., 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 validation time, and greatly advancing drug research and development in the pharmaceutical industry and the development of new materials.

Finance: Quantum computing is well-suited for complex financial modeling, with potential advantages in portfolio pricing, derivatives pricing, etc. According to incomplete statistics, over 25 major international banks and financial institutions have collaborated with quantum computing companies.

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

Aerospace: Quantum computing helps address some of the most severe challenges faced by the aerospace industry, from fundamental materials science research and machine learning optimization to complex systems optimization, and it has the potential to change how aircraft 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 their 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 containing 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 identify and understand different weather patterns through machine learning.

Quantum computers—advancing together—require a physical platform for quantum computing that can encode qubits, allowing for controllable coupling between different qubits and providing some resistance to environmental noise.

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

• Topological schemes, although they faced setbacks due to the retraction of a paper on the "discovery of Majorana particles" (the cornerstone of achieving topological quantum computing), researchers remain confident that this error-correction-free scheme can be realized. In summary, the development of physical realization 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 also a significant milestone. 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.

Note: The scoring uses a 5-point scale, with 1 being the worst and 5 being the best. ○ represents 1 point, ● represents 5 points. Green arrows indicate that commercialization 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.

• 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 significant 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 realized fast (30ns) 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, Benyuan Quantum launched the domestically engineered superconducting quantum computer "Benyuan 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 solutions for 56 qubits in a 20-layer cyclic "quantum random circuit sampling" task. 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 Benyuan Quantum to study the impact of crosstalk on qubit state reading on the Benyuan "Kua Fu" 6-qubit superconducting quantum chip, innovatively proposing the use of 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 first experimentally studied the effect of environmental qubits on cross-resonance logic gates using a tunable coupler multi-qubit system and proposed a solution to effectively improve the fidelity of two-qubit gate operations in large-scale superconducting quantum systems under two conditions: the presence and absence of environmental qubits.

• In October, Pan Jianwei's team achieved 60 qubits in a 24-layer cyclic quantum random circuit sampling, with computational complexity exceeding "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 in speed, 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 precision better than 98%).

• Internationally, in April 2021, physicists at the National Institute of Standards and Technology (NIST) used optical fibers 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 superconducting qubit made entirely of nitrogen, 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 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 Eagle processor.

• 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 introduced 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 causes of 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 nano-hydrides 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 movement 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 laser irradiation, 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 acting as entangled qubits to perform advanced computations. These computers have proven to be one of the most promising systems for practical applications of quantum computing.

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 1 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 number increases.
• In September 2021, Professor Luo Le's research team at Sun Yat-sen University's School of Physics and Astronomy achieved automated processing of qubit micromotion suppression in ion traps using artificial neural network technology and radio frequency microwave-spontaneous radiation photon correlation technology. This was the first time that neural network technology was applied to the micromotion control of trapped ion qubits internationally.
• In September 2021, a research team led by the National Institute of Standards and Technology (NIST) set a world record for the fidelity of a two-qubit gate without laser schemes, reaching [0.9964, 0.9987]. This scheme may allow for 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, achieving efficient cooperative cooling of long ion chains for the first time by laser cooling a small number of optimally selected ions, 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 logic qubit using multiple physical qubits with higher error rates. They used 9 data qubits encoded with Bacon-Shor-13 and 4 auxiliary qubits to achieve one logic qubit.
• In December 2021, the Honeywell team (now Quantinuum) first achieved real-time detection and correction of quantum errors. Researchers used [[7, 1, 3]] color codes to encode, control, and repeatedly correct a single logical qubit using 10 physical qubits in Honeywell's 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 room temperature atmospheric environments. Second, photons are the best information carriers for quantum communication, as 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 allows for 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 entangling 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 computing, 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 rare earth ions with certain characteristics can serve 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, the 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-based telecommunications infrastructure, making scaling easier and effectively reducing operating 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 computers. 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 and successfully implemented 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 frequency combs 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 problem processing that are 1 billion billion times faster than supercomputers.
• In December 2021, the photonic quantum computing company ORCA Computing achieved a platform known as the "Variational Boson Sampler," 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 ground state hyperfine energy levels of the atoms 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 qubit manipulation onto individual atoms, forming control over the qubits in the array. Simultaneously, the lenses collect the fluorescence from 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 acting as entangled qubits to perform advanced computations. These computers have proven to be one of the most promising systems for practical applications of quantum computing.

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 1 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 number increases.
• In September 2021, Professor Luo Le's research team at Sun Yat-sen University's School of Physics and Astronomy achieved automated processing of qubit micromotion suppression in ion traps using artificial neural network technology and radio frequency microwave-spontaneous radiation photon correlation technology. This was the first time that neural network technology was applied to the micromotion control of trapped ion qubits internationally.
• In September 2021, a research team led by the National Institute of Standards and Technology (NIST) set a world record for the fidelity of a two-qubit gate without laser schemes, reaching [0.9964, 0.9987]. This scheme may allow for 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, achieving efficient cooperative cooling of long ion chains for the first time by laser cooling a small number of optimally selected ions, 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 logic qubit using multiple physical qubits with higher error rates. They used 9 data qubits encoded with Bacon-Shor-13 and 4 auxiliary qubits to achieve one logic qubit.
• In December 2021, the Honeywell team (now Quantinuum) first achieved real-time detection and correction of quantum errors. Researchers created a single logical qubit and applied multiple rounds of quantum error correction. This logical qubit can prevent two main types of errors occurring in quantum computers: bit flips and phase flips.
• 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 subset of quantum dots. 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, Benyuan Quantum, in collaboration with Academician Guo Guangcan's team from the University of Science and Technology of China, discovered the anisotropy of spin qubit manipulation: by changing the relative direction of the applied magnetic field to the silicon crystal orientation, they could simultaneously optimize the manipulation rate, decoherence rate, and addressability of spin qubits.
• In May 2021, Benyuan Quantum, in collaboration with Academician Guo Guangcan's team, achieved highly sensitive measurements 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 processes.
• In June 2021, a research team 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 a usable entangled state for error correction.
• In October 2021, the research team at the University of Copenhagen achieved simultaneous operation of multiple spin qubits on a single quantum chip. In January of this year, 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 ultrafast manipulation of silicon-based spin qubits, which is currently the highest value reported internationally.

6. Topological Quantum Computing—Still Uncertain Topology#

Quantum computing utilizes quasi-particles with non-Abelian statistics in topological materials to construct qubits and execute 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. It is expected to solve key issues of qubit decoherence and fault-tolerant quantum computing, making it a frontier research area in quantum computing. Although Microsoft retracted a paper on the discovery of Majorana fermions, there were still certain achievements in topological quantum computing in 2021.

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 like topological quantum computing. In 2021, China also made a series of breakthrough advancements in exploring and implementing this scheme. In material growth and preparation, the Semiconductor Research Institute of the Chinese Academy of Sciences, led by Zhao Jianhua's research group, 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 heterojunction interfaces reaching atomic-level flatness. The research group of He Ke and Xue Qikun at Tsinghua University prepared a new semiconductor nanowire system using selective area epitaxy methods, 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, 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 values, 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 the Majorana transport signal and other trivial transport signals to exhibit completely different scaling behaviors and temperature-voltage dependencies, 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 have 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 like photon entanglement and quantum control. Additionally, 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 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 constructing quantum logic gate computers, which are known 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 find optimal solutions through the Ising model, making them specialized quantum computers with unique advantages in handling 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 magnets 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 are designed with optical components, which, compared to superconducting devices, do not require low-temperature environments and offer high stability and controllability.

Currently, research institutions and universities, including NTT, NII, NASA, Stanford, Caltech, Maryland, and the University of Tokyo, as well as 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 and 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 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 and corresponding acceleration algorithms.

Core Components—Discovery and Breakthrough Report#

Key research focuses on low-temperature devices (mainly dilution refrigerators at mK levels) 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 applied 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 helium-free dilution refrigerators combine dilution refrigeration technology with helium-free cold head technology. From a theoretical perspective, dilution refrigerators utilize the phase separation phenomenon occurring in the mixed liquid of two isotopes of helium, helium-3 and helium-4, at around 0.8K. After phase separation, the helium-3 and helium-4 mixed liquid stratifies, with the upper layer being a low-density helium-3-rich phase and the lower layer being a high-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 dilution phase at low temperatures is an endothermic cooling process, which can create the lowest temperatures at the mK level 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 temperatures at the mK level, multi-stage cooling is required. First, the helium-free cold head of the refrigerator can provide a basic low-temperature environment of 4K. On this basis, when the helium-3 and helium-4 mixed liquid flows through the 4K cold plate, it can initially liquefy helium-4. Subsequently, evaporation cooling and the Joule-Thomson effect are used to completely liquefy helium-3 and helium-4, reaching low temperatures around 1K. On this basis, the evaporation cooling of helium-3 can further lower the mixed liquid temperature to achieve phase separation. Finally, the dilution refrigeration principle is used to achieve mK-level ultra-low temperatures.

The explosion of quantum computing both domestically and internationally has propelled companies like Bluefors, representing dilution refrigerators, to become "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 example, according to the bidding announcement from the Beijing Quantum Information Science Research Institute, this 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 Bluefors's best-selling dilution refrigerator, 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 announced its use in the upcoming IBM Quantum System 2 series machines.

In 2021, in addition to continuing to achieve 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 research teams, especially after the launch of the latest generation of helium-free dilution refrigerators, Proteox, in 2020.

So far, 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 helium-free dilution refrigerator ProteoxLX (<7mK), and the extreme low-temperature refrigerator Proteox5mK with a base temperature of 5mK.

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

2. Measurement and Control Systems#

Ion traps, neutral atoms, and photonic systems 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 role in controlling, processing, and computing quantum chips. Early quantum measurement and control systems were built by quantum computing research 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 just one 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 challenging problems to solve. In recent years, a few domestic and foreign companies have announced the development of measurement and control systems specifically 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 launched the first commercial quantum computing control system (QCCS) for controlling superconducting and spin qubits. Google developed a quantum chip automation calibration system called 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 begin developing measurement and control systems for superconducting quantum computers. After years of development, the company has collaborated with about 70% of domestic quantum computing companies and research institutions, providing quantum computing 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 first launched a system architecture based on secondary frequency conversion internationally in 2018, featuring uV-level ultra-low noise, ultra-high stability DC voltage generation, and core indicators superior to foreign advanced 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 microwave signals with ultra-wide bandwidth from 200M to 20G, low phase noise, high stability, and high integration.

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

Benyuan 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 picosecond synchronization stability, capable of measuring and controlling 32 qubits, providing a flexible Python interface library. Benyuan 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 Guoshield Quantum, which is one of China's earliest quantum technology companies.

Guoshield Quantum relies on the technical advantages accumulated over years of research and development in quantum information products. In April 2020, it proactively laid out quantum computing and officially established the Quantum Computing Control Technology Department. In response to the demand for multi-qubit superconducting quantum computing, Guoshield 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, Chinese Academy of Sciences, and Southern University of Science and Technology. Based on this, an optimized version was launched in March 2021, improving integration and convenience. This system can support over 100 qubits and is one of the largest quantum computing control systems currently available. The relevant technology has been applied to "Zuchongzhi" and completed the "quantum computational superiority" experiment.

Investment and Financing#

Feature 1: Public Financing has Become a Trend for Quantum Technology Companies. In September 2021, ion trap quantum computing company IonQ went public on the New York Stock Exchange through a SPAC acquisition, raising $650 million and setting a record for the largest single financing for a quantum technology company, with a peak market value of $6.9 billion. In October 2021, Rigetti signed a final merger agreement with the special purpose acquisition company Supernova II. The merged company is expected to receive approximately $458 million in cash, including over $100 million in fully committed PIPE, direct investments, and $345 million in cash held in the Supernova II trust account. In December, it was announced that PIPE would increase by $45 million.

Feature 2: Record Single Financing Amount. Silicon Valley photonic quantum computing company Psi Quantum set a record for non-public quantum technology company financing, completing $450 million in Series D financing in July 2021. Many other quantum computing companies have also secured financing amounts exceeding tens of millions of dollars. For example, photonic quantum computing company Xanadu raised $100 million, non-stack quantum computing company Quantum Machines raised $50 million, and neutral atom quantum computing company Pasqal raised €25 million, while quantum control technology company Q-Ctrl raised $25 million.

Quantum communication and security are emerging fields based on the current information communication and network security industry, enriched by new technologies. At the same time, because quantum communication and security technologies are still frontier technologies, the research instruments and equipment that support the development of auxiliary industries, especially those providing precise measurements and state stability (such as low-temperature devices), actually provide equipment for this industry. For instance, in practical experiments, to pursue some extreme and special requirements, the quality or performance parameters of light sources are higher than those in actual QKD networking products; low-temperature thermostats may also be used as environmental aids for experimental samples in some experiments. It should be noted that some precision instruments and equipment are indispensable hardware for quantum communication research and development (such as oscilloscopes, arbitrary waveform generators), which are mostly mature research equipment and thus not included in this industrial supplier map.

The upstream of the quantum communication and security industry chain consists of suppliers providing core devices and components. Currently, the commercial form of PQC is expected to be similar to that of the cryptographic algorithm industry, with its upstream possibly consisting of some software development tools and hardware testing devices. A complete industrial chain specifically for PQC has not yet formed, so it is not included in this upstream research scope. The construction of QKD networks is currently mainly based on fiber optic networks and satellite-based systems, with fiber optic QKD network infrastructure construction accounting for the majority. Therefore, classic optical communication products are also used in the QKD industry chain, but these products are relatively mature (such as power supplies, optical fibers, broadcast modulators, polarizing beam splitters, PFGA, analog-to-digital converters, etc.) and widely applied, so they are not included in this industrial supplier map. This research mainly focuses on core, new quantum communication products. These companies provide light sources (such as lasers, entanglement sources), photon detectors, QRNG, and other components (such as quantum memory, which plays an important role in long-distance quantum communication and quantum internet). These products collectively constitute QKD device products (such as quantum key distribution machines, quantum key receivers, or integrated quantum key receivers).

Upstream QRNG Photon Detector Photon Source Other Note: Some companies' logos appear multiple times to show that the company is involved in different sectors.

| Version Feb 2023 quantum memory optical components single-photon counter Table 2-1 Quantum Communication and Security Upstream – Core Equipment and Devices

The midstream of the industry chain consists of suppliers providing overall solutions in the field of quantum communication and security. For example, some of them integrate upstream products and provide supporting software or platform systems, offering core support for the implementation of QKD networks. Midstream companies are mainly divided into those developing products and solutions based on quantum physics principles (such as QKD device providers Toshiba and Guoshield Quantum), those developing products and solutions based on mathematical algorithms (such as UK PQ Shield and China's Quantum Safety Technology), and those researching key management and quantum secure communication SaaS companies.

Midstream
PQC QKD Encryption Platform/Key Management/Quantum SaaS Guoshield Quantum | Version Feb 2023 Table 2-2 Quantum Communication and Security Midstream

This time, the participants in the quantum communication and security industry mainly focus on profit-oriented organizations, especially startups. However, universities and research institutions also significantly contribute to the development of the quantum communication and security industry, providing important technologies. Many startups in this field have incubated from universities or research institutions. For example, IDQ is a spin-off from the University of Geneva, Guoshield Quantum is a spin-off from the University of Science and Technology of China, Q-bird is a spin-off from Delft University of Technology, and Quantum Dice is a spin-off from the University of Oxford. Additionally, traditional companies in the fields of cybersecurity and semiconductors are increasingly implementing quantum security technologies, such as NXP, Thales, and Fortinet. Furthermore, IBM and Google are also involved in quantum information security while deploying research in the quantum computing field.

Note: This diagram mainly considers companies whose core business is based on quantum technology, and traditional companies entering the quantum field are not included.

From the perspective of the countries where the companies are headquartered, the United States, Canada, the European Union (such as Germany, France, Spain, Italy, Finland), the UK, and China are the countries with a dense presence of participants in the quantum communication and security field. Additionally, Russia, Israel, Japan, South Korea, India, Singapore, and Australia also have many startups in the quantum communication and security field.

From the perspective of the segmentation of companies' businesses in quantum security and communication, the U.S. has few QKD hardware companies, while there are many PQC algorithm software and security platform companies; Canadian companies also mainly focus on algorithm software and security platform companies; Chinese companies are primarily hardware companies, with only one company in the PQC field; companies in the UK and Switzerland lean towards hardware; and EU member states also have a majority of hardware companies. Core quantum security companies in Russia, Israel, India, Japan, South Korea, and Australia are also primarily hardware-focused.

Participants in the Quantum Communication and Security Industry#

The downstream of the quantum security industry consists of demand and user organizations for quantum security products. Currently, the downstream applications of quantum security technology are still in the exploratory stage of promoting the possibilities of industry applications. The organizations displayed in this quantum security industry downstream consist of two categories: one category is organizations that directly procure quantum security products or services. For example, some national departments related to defense are among the earliest organizations to procure quantum security devices; the other category includes organizations that have a demand for quantum security products but also collaborate with quantum startups to develop products or services. For instance, since the deployment of QKD is mostly based on existing fiber optic communication networks, there is cooperation between QKD suppliers and telecommunications companies that have fiber optic communication infrastructure. For example, Huawei has conducted field trials of quantum encryption using SDN on commercial optical networks. Therefore, telecommunications-related companies will always be a significant downstream application party.

Although it is still challenging to predict the full range of uses for all infrastructure in the future, the main applications have basically been determined. The downstream companies/organizations are mainly defense, finance, energy networks, data centers, smart driving, mobile operators, and personal consumption units that have high demands for information security. Currently, the downstream procurers/suppliers are mainly party and government military units, large enterprises, and institutions.

Currently, QKD is the most mature technology product in the quantum communication and security field, already applied in many countries and industries. Since the PQC algorithm is still in the standardization phase, although many technology suppliers have emerged, feedback from the market on actual products will still be needed after the standards are published. This evaluation mainly targets suppliers that have the capability to provide a complete QKD system solution.

Based on the CTF model's definitions of the four levels of sectors, the evaluation of QKD field suppliers is as follows:

Currently, QKD is the most mature technology product in the quantum communication and security field, already applied in many countries and industries. Since the PQC algorithm is still in the standardization phase, although many technology suppliers have emerged, feedback from the market on actual products will still be needed after the standards are published. This evaluation mainly targets suppliers that have the capability to provide a complete QKD system solution.

In 2022, the construction of quantum communication network infrastructure in the United States, Canada, the UK, France, South Korea, China, Poland, India, and other countries further developed. The relevant developments are as follows:

In May, the U.S. Department of Energy's Brookhaven National Laboratory (BNL) launched a new quantum network facility providing researchers with the tools and capabilities needed to make large-scale quantum entanglement distribution networks a reality. The new facility already has one of the most advanced regional quantum networks in the U.S., with the longest quantum network in the U.S. being completed by BNL and Stony Brook University, spanning 98 miles and connecting the campuses of both institutions.

In June, the Chicago Quantum Exchange (CQE) at the University of Chicago connected laboratories in the city and suburbs to a quantum network for the first time, establishing a 200-kilometer QKD network that distributes quantum keys at a speed of over 80,000 quantum bits per second. This network, which will soon be open to academia and industry, will become one of the first publicly available quantum security technology testing platforms in the U.S. The entire network currently consists of six nodes, transmitting particles carrying quantum encoded information between Argonne National Laboratory and two buildings in Chicago (the University of Chicago campus and CQE headquarters near Hyde Park).

In June, the U.S. Illinois Quantum Network (IEQNET) research team deployed a quantum network between two DOE laboratories 50 kilometers apart, simultaneously transmitting a traditional clock signal and a quantum signal, with the two signals remaining synchronized within a time window of less than 5 picoseconds, marking an important step toward building practical multi-node quantum networks.

In the U.S.: Despite the lack of large-scale national infrastructure planning, research work on QKD applications continues to advance.

In August, the Hefei Quantum Metropolitan Area Network was launched, currently the largest, most user-rich, and most comprehensive quantum secure communication metropolitan area network. This network was constructed by China Telecom Quantum, with core equipment provided by Guoshield Quantum, including 8 core sites and 159 access sites, with a total fiber length of 1147 kilometers, providing quantum secure access services to nearly 500 party and government agencies at the city and district levels. This network is expected to serve industries such as finance, energy, healthcare, and technology, and is anticipated to expand to four counties and one city, connecting to the national quantum backbone network.

In September, the intercity QKD link between Warsaw and Poznań was established, spanning 380 kilometers. This link is part of the national quantum communication infrastructure project developed by the Polish National Laboratory for Photonics and Quantum Technologies (NLPQT), constructed in collaboration with the Poznań Supercomputing and Networking Center (PSNC) and Swiss company IDQ, providing services for various applications such as telemedicine, medical data transmission, data storage, and public services. PSNC aims to further integrate the metro QKD infrastructure developed in Poznań in 2021 with this new long-distance QKD link between Poznań and Warsaw, with the ultimate goal of interconnecting all high-performance computing centers in Poland and establishing a universal access layer for QKD services.

In 2023, Chinese research teams first broke the 1000-kilometer distance for TF-QKD (Twin-Field Quantum Key Distribution) lines based on fiber transmission, reaching 1002 kilometers. This achievement is a key step toward the future construction of large-scale quantum networks. The experiment demonstrated the feasibility of using the send-or-not-send (SNS) protocol for TF-QKD over long-distance fiber.

The quantum key distribution open new architecture developed by the research team at Beijing Quantum Institute successfully achieved quantum key distribution communication experiments over 615 kilometers of fiber. This experiment is based on coherent sideband stabilization and remote laser source frequency calibration technology, and the newly developed open architecture does not require service fibers, achieving secure encoding at the 400-kilometer level, 500-kilometer level, 600-kilometer level, and breaking the encoding rate limit of non-relay QKD, successfully demonstrating quantum key distribution experiments with arm lengths differing by hundreds of kilometers.

The distance for QKD lines based on fiber transmission is gradually increasing, laying the foundation for the construction of large-scale quantum networks. By developing key technologies such as high-fidelity integrated photonic quantum state control and high-count-rate superconducting single-photon detection, real-time quantum key distribution at a rate of 115.8 Mbps can be achieved. The experimental results will enhance the previous encoding rate record by an order of magnitude.

The new transmission record is based on a new theory of QKD encryption, which removes the previous limitations on distance and data transmission rates in quantum secure communication. Using traditional fiber and optical amplifier methods, quantum secure communication has been achieved over more than 1032 kilometers of fiber optic cable, with data transmission rates (key rates) significantly exceeding previous records (previously: 0.0034 bits/second; now: 34 bits/second).

The latest demonstration of a hybrid link QKD technology with all-weather operation and resistance to strong background noise successfully showcased the combination of space and fiber links to achieve Hong-Ou-Mandel (HOM) interference. Under conditions where the traditional BB84 protocol cannot function properly, this technology can still effectively perform multi-dimensional interference quantum key distribution (MDI-QKD). Additionally, researchers have explored the feasibility of satellite-based HOM interference, laying an important foundation for constructing a hybrid communication network that integrates terrestrial and space components.

The hybrid matching quantum key distribution (MP-QKD) protocol utilizes the data post-processing method of maximum likelihood estimation to accurately estimate the frequency difference of two independent lasers for parameter estimation, achieving secure encoding at the 100-kilometer, 200-kilometer, and 300-kilometer levels, with significant improvements in encoding rates compared to previous original MDI experiments, and encoding rates at 300 kilometers and 400 kilometers improved by three orders of magnitude compared to previous experiments.

The application of "asynchronous matching" technology in quantum communication can greatly enhance the key rate and combines the advantages of the "dual-field" protocol and the "measurement-device-independent" protocol to achieve the longest possible quantum communication distance with a simpler quantum communication architecture. By improving the measurement-device-independent (MDI) quantum key distribution scheme using the strategy of asynchronous pairing, it retains the characteristics of the dual-field protocol that breaks the relationship between encoding rate and transmission loss while simplifying the structure. In terms of encoding rates, it has successfully achieved 57 kbps at 201 km, 5 kbps at 306 km, 590 bps at 413 km, and 42.64 bps at 50 km.

Using quantum vacuum states to generate random numbers typically has speed limitations. Therefore, researchers have created a quantum random number generator by utilizing the behavior of particle-antiparticle pairs, finding that its speed is 200 times faster than traditional systems, achieving a generation rate of 100 Gbit per second in experiments, raising the speed record for quantum random number generation based on vacuum by an order of magnitude.

Using the avalanche photodiode's electron tunneling effect, a discrete QRNG can output raw random sequences at a rate of 100 Mbps under normal temperature and pressure, with a minimum entropy of 0.9944 bits/bit for 8,000,000 bits and a minimum entropy of 0.9872 bits/bit certified by NIST SP 800-90B. This makes it possible to achieve a quantum random number generator that continuously outputs high randomness without any post-processing for extended periods.

Additionally, the raw data output by this QRNG has also made progress in maintaining high randomness over long periods of continuous stable output, with the system continuously outputting 1,174 Gbits of raw data over 11,744 seconds, achieving a statistical minimum entropy distribution with an average value of 0.9892 bits/bit.

The combination of quantum non-locality, quantum secure algorithms, and zero-knowledge proofs has led to the first realization of a public service random number beacon using a device-independent quantum random number generator as an entropy source, with quantum cryptography as identity authentication. This has been applied in the field of zero-knowledge proofs (ZKP), eliminating the security risks associated with achieving true randomness in non-interactive zero-knowledge proofs (NIZKP), thereby enhancing the security of NIZKP.

Major Progress in PQC#

03 New neural network training methods "Recursive Learning" can achieve side-channel attacks on the highest 5th-order mask of the Crystals-Kyber algorithm among the four PQC algorithms published by NIST, recovering information bits (message bits) with a probability exceeding 99%. This finding indicates that neural networks can be used to crack NIST's PQC algorithms, highlighting the need for security assessments of PQC algorithms.

The development of quantum key distribution (QKD) and post-quantum cryptography (PQC) is showing a trend of collaborative development. In recent years, although QKD initially received more attention, the focus on PQC has rapidly increased in 2022 and 2023, leading to a parallel development trend in investment and financing, policy support, research enthusiasm, and commercial potential. The global layout of QKD technology is expanding, with over 30 countries constructing related infrastructure. At the same time, the foundational research of technologies like QKD continues to be a focus for future development, aiming to improve system security and efficiency while addressing practical application challenges such as photon loss and noise interference.

PQC technology is entering a growth phase, benefiting from standardization and policy support, with its commercialization and application exploration imminent. PQC technology is iterating and upgrading to meet the needs of different application scenarios. At the same time, plans for the commercialization and migration of PQC are being initiated, with enterprises and organizations actively exploring the migration of existing encryption algorithms to the PQC framework to assess their commercial potential and cost-effectiveness. The involvement of government agencies and NIST's standardization documents provide guidance for the migration of PQC, promoting the development of related solutions to enhance communication and data security and mitigate the risks of algorithm cracking.

The continuous improvement of the industrial ecosystem is driven by global quantum policies, which will continue to promote the positive development of the quantum communication and security field. At the national policy level, 2023 witnessed the first or updated release of national quantum strategies by multiple countries, injecting momentum into the long-term development of quantum communication. Additionally, many governments provide funding support at the research level.

Despite certain obstacles, cross-national cooperation in the quantum communication and security field is increasing. Multiple countries have signed memorandums of cooperation in quantum science and technology, and some countries are collaborating to strengthen breakthroughs in the migration of PQC.

Companies in the quantum communication field often collaborate with those in quantum computing and quantum precision measurement, discovering new opportunities. In 2023, this trend of cross-field collaboration has become increasingly evident, manifested in the close integration of quantum computing and quantum communication. It is expected that interdisciplinary collaboration will become more common in the future, driving the improvement of the quantum ecosystem and enhancing the security of quantum communication.

The downstream application scenarios are gradually increasing, with the demand for quantum security driving the application of QRNG technology in multiple fields, particularly in enhancing the security performance of automobiles, mobile devices, and the Internet of Things. At the same time, the application of QKD technology in industries such as finance, government, and defense is continuously expanding, demonstrating the broad potential of quantum communication infrastructure. Furthermore, telecommunications companies are developing encryption solutions utilizing PQC technology, and government and military agencies worldwide are increasingly emphasizing collaboration with the private sector to accelerate the acquisition of advanced quantum security technologies, ensuring the security of communication and data transmission.

Microsoft has broken its own world record set two months ago. On November 19, at the Microsoft Ignite 2024 conference, Microsoft and neutral atom quantum computing company Atom Computing launched a commercial quantum machine with 24 logical qubits, breaking the record for the highest number of entangled logical qubits—two months after Microsoft set the record on Quantinuum's hardware, with the new number being double that. Additionally, they demonstrated the ability to detect and correct errors and perform computations on 28 logical qubits. It is reported that a comprehensive quantum computing suite will be delivered in 2025, which will be available for local installation and accessible on Azure quantum cloud services.

https://quantumcomputer.ac.cn/index.html

Introduction to Quantum Programming

https://quantum-book-by-originq.readthedocs.io/en/latest/index.html

For the implementation of quantum algorithms, they can also be found on GitHub under quantum computing.
https://github.com/HuntFeng/Quantum-Computing
Welcome to follow Finquantum, an organization focused on learning and sharing knowledge related to quantum computing.
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Variational Quantum Eigensolver (VQE)
Reference:
https://doi.org/10.1038/ncomms5213

Quantum Computer Q Language Learning

Qiskit Learning Resources: https://qiskit.org/learn

The first attempt to implement the no-cloning principle in quantum functional programming. GitHub address:
https://github.com/Quantumzhao/Quantum-Abstract-Language

Architecture Overview: Entering the World of Quantum Computers!#

[doge][doge] Quantum computers are computers based on quantum machines, with the core being the Hermitian transformation of qubits, achieving computation through transformations of vector spaces. [doge][doge] Current quantum computers have strong parallelism and can primarily achieve large-scale integer factorization. [doge][doge] This course will help you build a solid foundation in quantum computing, covering everything from basic knowledge to understanding how quantum computing works. Quantum computing processes information at astonishing speeds using principles of quantum mechanics.

YouTube video link: https://www.youtube.com/watch?v=tsbCSkvHhMo Author: quantum-soar

Question set: https://drive.google.com/drive/folders/1A-RHTQFRY_pipVfItQBxMU-xEexRESQj

Free programming courses: https://www.freecodecamp.org/chinese/learn
Read technical articles in the column: https://www.freecodecamp.org/chinese/news
Get help in the forum: https://forum.freecodecamp.org/c/chinese/533

【Reference Materials】
IBM Quantum Decade
https://www.ibm.com/thought-leadership/institute-business-value/en-us/report/quantum-decade
120 Unsolved Scientific Frontier Issues
https://www.edu.cn/rd/kexuetansuo/zui_xin_dong_tai/202104/t20210412_2095259.shtml
Rigetti 2023 Q2 Report
https://investors.rigetti.com/node/8756/pdf
IonQ 2023 Q2 Report
https://ionq.com/news/ionq-announces-second-quarter-2023-financial-results
D-Wave 2023 Q2 Report
https://www.dwavesys.com/company/newsroom/press-release/d-wave-reports-second-quarter-results/
The IBM Quantum Development Roadmap
https://www.ibm.com/quantum/roadmap
Research publications
https://quantumai.google/research/publications