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Quantum Computing
Quantum computers use quantum physics to store information and solve problems. There are different technologies that can create the basic building blocks (qubits) of these computers. But it might take more than 10 years for companies to develop the complex systems of accurate qubits required for the quantum age. The challenging engineering issues, exaggerated expectations, and lack of profits for many quantum companies suggest that a long period of slow progress is likely.
The competition is narrowing between the US and China
China has been catching up with the US and is now very close in terms of progress. However, their approaches are different. In the US, private companies are leading the way, while in China, state institutions are gaining more expertise. Some companies, like Alibaba and Baidu, have even decided to focus on providing advanced technology to China's national institutions instead of the market.
Early quantum edge will come from optimization algorithms
In the coming years, we will have more and better quantum computers called NISQ devices. These devices will be stronger and less likely to break. They will help with optimization tasks, like VQA, and will work together with regular computers. At the same time, regular computers will also improve and do things that were thought to only be possible with quantum computers.
Leading companies in quantum computing include IBM, Google, Microsoft, and Amazon. Smaller companies and start-ups like Quantinuum, IonQ, Rigetti, PsiQuantum, Zapata AI, Riverlane, and Q-CTRL are also involved. These companies are investing in the development and use of quantum computers. However, some companies like Alibaba and Baidu have left the quantum computing market.
Technology Briefing
The idea of quantum computing was introduced in the 1980s. It is a field of science that uses quantum mechanics to study and develop new technologies. This field is still being actively researched, and there are many difficult engineering challenges that need to be overcome.
What are quantum computers?
Quantum computers apply the principles of quantum mechanics to store information and carry out calculations.
Quantum computing is a technology that uses the unusual behavior of subatomic particles to create incredibly powerful computers. Unlike the classical computers found in our smartphones and laptops, quantum computers operate differently in terms of their applications.
Quantum computers are not general-purpose systems. Instead, they are powerful parallel processing systems designed for specific tasks. In theory, they can simulate complex and uncertain systems such as the weather, financial markets, chemical reactions, molecules, and neurons in the human brain in a matter of seconds.
What is the difference between classical computers and quantum computers?
The power of quantum versus classical computing can be illustrated by looking at how each would tackle the problem of finding the way out of a complex maze involving millions of possible escape routes. The classical binary computer would check each escape route one after the other until it found the correct solution. In contrast, the quantum computer would test all possible escape routes simultaneously.
The term ‘classical computer’ is used throughout this report. It refers to computers that use bits (ones or zeros) to compute tasks. All the computers in phones, laptops, and even the world’s fastest supercomputers are classical in this context.
What is the difference between universal quantum computers and annealers?
Universal quantum computers are capable of solving a wide range of computing problems, while quantum annealers are better suited for optimization problems, such as finding the shortest route from point A to point B. Although quantum annealers have a higher number of qubits, they can only be programmed for optimization problems and cannot handle other types of problems. This limitation means that many quantum algorithms, such as Shor's and Grover's, cannot be executed on quantum annealers. Unlike universal quantum computers, quantum annealers do not utilize logic gates, which are used in classical computers in the form of transistors.
What is a qubit?
Classical computers use bits, or binary digits, to transmit data, but quantum computers utilize qubits, or quantum bits. Unlike bits, which can only represent either a one or a zero, qubits have the unique ability to represent both at the same time. This is because qubits have a probability distribution, meaning they can have a 70% chance of being a one and a 30% chance of being a zero, for example.
Quantum computers take advantage of two essential properties in quantum mechanics: superposition and Entanglement.
When a qubit is both a one and a zero at the same time, it is said to be in a superposition. Superposition is the general name for the condition when a system is in multiple states at once and only assumes a single state when measured.
Assuming a coin is a quantum entity, flipping it would result in a superposition, where the chance of it landing on either heads or tails is uncertain. When the coin lands, a measurement is taken, determining the outcome as either heads or tails.
Think about an electron, which has a quality called "spin." This spin can be up or down. Up means one and down means zero. When we put the electron into superposition, it has a chance of having either an up or down spin. This means we can't be sure if the electron is a one or a zero at that time. It could be both or somewhere in the middle. We only find out if the spin is up or down (like a coin landing) when we measure it. Then we know if the electron is a one or a zero.
Quantum particles in superposition are useful when we have more than one. This brings us to the second fundamental principle of quantum mechanics: entanglement. Two (or more) particles that are entangled cannot be individually described, and their properties depend entirely on one another. So, entangled qubits can affect each other. The probability distribution of a qubit (being a one or zero) depends on the probability distribution of all other qubits in the system.
When we add more qubits to a system, entanglement becomes very strong. A 2-qubit system can be in four different states: 00, 01, 10, and 11. But if we add another qubit, there are eight possible states: 000, 001, 010, 100, 011, 101, 110, and 111. Each new qubit doubles the number of states that the computer can look at. This is much more powerful than classical computing, where the power only increases a little with each new bit.
When qubits are tangled, they can do many things at the same time. One thing they could do is simulate complicated protein molecules, which would take regular computers millions of years to do. But keeping the qubits stable is challenging.
What is coherence?
Coherence is an essential aspect of quantum computing, referring to a qubit's ability to exist in a superposition state between one and zero. If a quantum system is perfectly isolated from its environment, it can maintain coherence indefinitely. However, its surrounding environment greatly affects the coherence of a subatomic particle.
For instance, fluctuations in temperature can disrupt the particle's energy levels, which are crucial for coherence. As time passes, the quantum system will eventually lose coherence, causing the superposition to collapse and rendering calculations impossible.
A quantum system is useless in perfect isolation because it must be measured to provide results. The problem is that the act of measuring a qubit is also an interaction with the external environment and contributes to decoherence.
Other sources of interactions include sound, crosstalk between qubits, and electromagnetic interference. The more qubits involved in the system, the harder it is to maintain coherence long enough to complete any meaningful computation, even though coherence will often only need to last a few seconds to complete a task. This is why extreme measures are taken to control conditions. For example, keeping the system at very low temperatures reduces the chance of thermal interference.
What are the six key types of qubit architecture?
Quantum computing’s current technology stack relies on hardware that tries to maintain coherence by reducing interaction. There are a variety of qubit architectures, each requiring a different infrastructure. Hardware can involve cryogenic fridges within vacuum chambers, superconducting circuits, and ions or optical processing based on silicon photonics. Thus, qubits bear little or no resemblance to their classical counterparts.
There are six main qubit architectures:
Superconducting qubits1
Photonic qubits2
Trapped ion qubits3
Spin qubits4
Neutral atom qubits5
Topological qubits6
Do quantum computers outperform classical computers?
Quantum computers have shown potential that distinguishes them from classical computers, particularly in their ability to perform certain computations much faster than classical systems. However, whether quantum computers are superior to classical computers depends on the context of their application.
Google's announcement in October 2019 of achieving quantum supremacy with its 53-qubit Sycamore processor marked a significant milestone. The processor completed a specific task in 300 seconds that, according to Google, would take a classical supercomputer millions of years to perform. This claim sparked excitement as it seemed to demonstrate the potential of quantum computing to outperform classical computing in certain tasks. However, the claim was met with skepticism when IBM argued that their classical supercomputer could complete the same task in significantly less time (2.5 days), challenging the notion of quantum supremacy in this instance.
The University of Science and Technology of China (USTC) made a more widely accepted claim of quantum supremacy in December 2020 using a photonic approach, which, despite its programming challenges due to its specificity in solving certain types of problems (boson sampling), was indisputable. USTC furthered its achievements by building two additional quantum computers in October 2021, showcasing the advancement in quantum computing capabilities.
Xanadu, a Canadian startup, further contributed to the field in June 2022 by reporting improvements upon the results achieved by Google and USTC, indicating ongoing progress towards more practical applications of quantum computing.
Quantum computers have demonstrated the potential to surpass classical computers in specific tasks, marking significant milestones towards achieving quantum supremacy. However, the superiority of quantum computers over classical ones is not yet universally applicable across all types of computational problems. It will take years of development before quantum computers can be broadly applied to a wide range of applications beyond specialized tasks. Quantum computing is still in its early stages, and its full potential is yet to be realized.
What is quantum volume?
Quantum volume is an IBM metric that measures a quantum computer's performance and capabilities, taking into account factors such as qubit number, connectivity, and error rates. This metric is crucial due to the poor quality of qubits in current quantum computers, hindering progress towards commercially viable quantum computing.
Recent developments have improved quantum volume on a 32-qubit device, highlighting the need to reduce error rates for better quantum computer performance. However, complex algorithms like Shor's or Grover's still require more time to be solved on a scale that addresses real-world problems. Research is currently focused on developing algorithms for quantum simulators that can run on classical computers, NISQ devices, or a hybrid of both, showing that quantum computing technology is still in its early stages.
Industry Analysis
Industry Evolution:
Paul Benioff introduced quantum computing in 1980.
Billions invested in R&D over decades with modest outcomes.
Transitioned from proof of principle to beta testing in three decades.
By 2019, fewer than 30 quantum devices available for external exploration; none capable of running complex, industry-changing algorithms.
Recent years have seen a surge in the number of quantum devices, yet a significant quantum advantage remains elusive.
Market Size and Growth:
2022 market size estimated between $500 million and $1 billion.
Forecasted growth to $10 billion by 2026-2030, with a CAGR of 30% to 50%.
Market predictions are speculative due to the industry's infancy and potential for unexpected breakthroughs.
Current Market Dynamics:
Early sales mainly from quantum annealed computers and small prototypes by companies like D-Wave, IBM, IonQ, and Rigetti.
Significant growth in cloud-based quantum services offered by major tech companies, including IBM, Google, Microsoft, and recently Amazon.
Leading startups D-Wave, IonQ, and Rigetti have quarterly revenues under $10 million, with IonQ showing the most stable growth.
Commercial-scale quantum computing expected to start by 2027, as per industry executives.
Quantum encryption seen as essential once quantum computing becomes mainstream, with the current market for quantum encryption being negligible.
Cybersecurity market, potentially related to quantum encryption, valued at $172 billion in 2023, expected to rise to $290 billion by 2027.
Use Cases
Here are a few key points about industry use cases for quantum computing:
Molecular modeling: Simulating molecule behavior and interactions for drug discovery, battery design, etc. Key players include pharmaceutical, chemical, and automotive companies.
Cybersecurity: Quantum key distribution for secure communication, and post-quantum cryptography to protect against attacks from future quantum computers.
Financial modeling: Complex portfolio optimization, fraud detection, risk analysis. Banks like JP Morgan and Goldman Sachs are exploring applications.
Logistics: Route optimization, scheduling, supply chain management. Volkswagen, Deutsche Bahn, defense contractors working on use cases.
Manufacturing: Process optimization through simulation of chemical reactions. Siemens, EDF partnering with quantum startups.
AI/neural networks: Faster training and optimization of machine learning models. Important for the future development of artificial intelligence.
Military/defense: Navigation, sensing, imaging, communications, computing for command and control. Raytheon, Lockheed Martin, governments investing heavily.
Space: Precision navigation and timing through atomic clocks and sensors. Inflection working with U.S. Navy.
Key industry players across the board see potential in quantum but are still in exploratory research mode as the technology is still emerging. Practical applications are limited today but could expand rapidly with advances.
Signals
Foreign direct investment trends
FDI is crucial for acquiring technology and skilled workers from other countries, and is a key factor in developing quantum computers. It also promotes growth and investment in the field.
Although FDI related to quantum computing is still scarce, most investments are currently being made in Europe. This can be attributed to growing quantum ecosystems and favorable research conditions in several European countries.
The key FDI transactions associated with the quantum computing theme since the beginning of 2023 are listed in the table below.
M&A trends
Quantum computing M&As are rare, with investors preferring minority investments in start-ups and tech companies opting for partnerships instead of full acquisitions.
In 2024, Alphabet spinout SandboxAQ merged with computational chemistry start-up Good Chemistry, which specializes in quantum computing and AI simulations. This is SandboxAQ's second acquisition, following the purchase of cybersecurity and encryption software start-up Cryptosense in September 2022. This acquisition will help SandboxAQ create post-quantum cryptography solutions.
The key M&A transactions associated with quantum computing since January 2021 are listed in the table below.
Venture financing trends
Quantum computing is still in its early stages, so companies are hesitant to invest in unproven technology, resulting in a lack of M&A activity.
If technology maturity is the main reason for market consolidation, it could take 10 years for Big Tech companies to acquire promising start-ups. However, funding may also be a challenge for many start-ups. Quantum computing is at risk of facing a "winter" similar to the development of AI. Challenges in the industry, slow progress, and long timelines for commercialization will dampen excitement for its potential. This is happening during a time when companies are in need of cash due to macroeconomic conditions.
Investors’ patience will be tested, and many may choose to exit. Larger tech companies are the most likely acquirers of quantum start-ups, with purchases made primarily for talent rather than intellectual property (IP). The partnerships ’s merger in November 2021.
Despite this, several companies, including Origin Quantum, IQM, Xanadu, Silicon Quantum Computing, Sandbox AQ, Oxford Quantum Circuits, and Photonic, saw significant increases in capital in 2022 and 2023.
The key venture financing deals associated with the quantum computing theme since 2021 are shown below.
Value Chain
Quantum infrastructure: This includes the basic components needed to build a quantum computer like superconducting cables, cryogenic refrigeration, lasers, microwave equipment, and quantum sensors. Key players are Coax, Bluefors, Hamamatsu Photonics, Rohde & Schwarz, and AOSense.
Quantum hardware platforms: This covers the core technologies for engineering qubits, including superconducting, trapped ions, spin, photonic, neutral atoms, and topological. Leaders include IBM, Honeywell, Intel, IonQ, PsiQuantum, and Microsoft.
Quantum software: This involves programming languages, algorithms, simulations, and resource management for quantum computers. Major companies are Microsoft, IBM, Alphabet, D-Wave, Rigetti, and startups like Q-CTRL and Zapata AI.
Quantum applications: Current focus areas are optimization, differential equations, linear algebra, and factorization. Users span logistics, finance, chemicals, aerospace, and cybersecurity.
Quantum services: Consulting, cloud access, and education to help businesses adopt quantum. Dominated by IBM, Microsoft, D-Wave, and consultancies like Accenture and McKinsey.
Players
Public Companies
D-Wave: A pioneer in quantum annealing computing for over 20 years, D-Wave has brought several generations of specialized quantum computers to market and provides quantum services through its Leap cloud platform.
Fujitsu: Fujitsu is spearheading Japan's drive for self-sufficiency in quantum computing through extensive R&D and partnerships, with plans to develop quantum computers with over 1,000 qubits.
IBM: With deep expertise across the quantum stack from hardware to software, IBM aims to lead the quantum computing industry and provides cloud quantum services through IBM Q.
Intel: Leveraging its semiconductor expertise, Intel is advancing silicon spin qubits and offering chip manufacturing capability to bolster quantum research and development.
IonQ: This trapped ion qubit specialist went public in late 2021 and is focused on building modular and networked quantum architectures with dozens of high-quality qubits.
Microsoft: Through Azure Quantum, Microsoft provides quantum development tools and cloud access to quantum hardware, while pursuing topological qubits as a long-term differentiator.
Rigetti: Developing superconducting qubits since 2013, Rigetti offers cloud quantum services and built a 40+ qubit system in 2021 before going public via SPAC in early 2022.
Private Companies
Pasqal : A leader in neutral atom qubits, Pasqal is advancing techniques to control atomic qubits and has partnered with Microsoft to provide quantum technology.
PsiQuantum : With substantial funding, PsiQuantum aims to achieve fault tolerant quantum computing using silicon photonics to manufacture qubits at scale.
Q-CTRL : This Australian firm is a pioneer in quantum infrastructure control software to stabilize qubits and suppress errors that degrade quantum calculations.
Quantinuum: Formed by combining Honeywell's hardware expertise with Cambridge Quantum's software capabilities, Quantinuum is integrating key pieces of the quantum stack.
Sandbox AQ: Spun out from Google, Sandbox focuses on software for quantum algorithms, cybersecurity and cloud integration, offering strategic consulting services.
Universal Quantum: This company has bold aims to build a 1 million qubit fault tolerant quantum computer using trapped ion qubits and advanced control systems.
Conclusion
The road to viable quantum computing has been long, with billions invested over decades yielding modest revenues so far. However, if the technology achieves the anticipated breakthroughs, the market could expand rapidly, especially in areas like cybersecurity, finance, and drug discovery. While significant hurdles remain, quantum computing continues to hold great promise to transform industries in the years ahead.
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Superconducting qubits: Superconducting circuits are cooled to near absolute zero in cryogenic containers. The superconducting method is a popular quantum engineering model known for its fast calculations and lack of moving parts. There are concerns that manufacturing identical circuits in large quantities may impede progress and that cryogenic systems may have a limit on the number of qubits they can handle.
Photonic qubits: Light beams, composed of photons, are produced and directed through mirrors and splitters. Light orientation encodes information, and silicon can detect photons. Heat has no effect on photons, creating a more coherent system. Techniques for programming a photonic device to run multiple quantum algorithms are still in early development.
Trapped ion qubits: Lasers provide energy to ions (charged atoms) that are confined using electromagnetic forces. The interactions between excited ions give rise to quantum computation. Trapped ion qubits have high fidelities, resulting in low error rates for more accurate calculations and a higher quantum volume. Currently, materials experts are working towards minimizing the impact of substances used in building ion traps.
Spin qubits: Particles with spin, like electrons, are controlled in semiconductors. Spin qubits need higher temperatures (1 Kelvin) compared to superconducting and trapped ion methods, which could make them more popular due to fewer engineering challenges. Silicon and diamond spin qubits are proposed, but material interference remains a concern.
Neutral atom qubits: Light traps neutral atoms, and their nuclear magnetic spin states set the qubit state. This method may enable smaller, field-deployable quantum computers without cryogenic refrigeration. Neutral atom qubits are less accurate than trapped ion and superconducting qubits, but they are useful for high-precision atomic clocks.
Topological qubits: Although theoretical, the topological qubit would bend, stretch, and twist braids of a quasiparticle—the anyon. Topological qubits may retain and stabilize information better than current alternatives. The two-dimensional anyon was first theorized in the early 1980s. Perdue and École Normale Supérieure teams only found experimental proof of the anyon in 2020. Physics experiments on anyons and the topological qubit are still in development.