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A primer on the quantum landscape

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A primer on the quantum landscape

Over the past decade, quantum computing and the broader quantum landscape have undergone transformative growth. No longer confined to the realm of science fiction or even academic research, quantum computers have taken the plunge into the world of commercialization. Systems have become more powerful, use cases have proliferated, and general interest has been piqued.

As quantum computers have moved out of the lab and into the market, an entire landscape has sprung up around them. From quantum networks building out an early quantum internet, to quantum-secure communication and even quantum sensors, quantum seems to be everywhere these days. Here, we provide a guide to the primary components of the developing quantum landscape, key vendors operating in the space, current and future use cases for the technology, and published road maps offering us a glimpse at where quantum is headed next.

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Quantum computing, while certainly still a cutting-edge technology, has passed from an era of conjecture into an era of utility. The broader quantum landscape and vendor ecosystem have developed in tandem, and over the past several years, quantum technology has morphed into a quickly evolving industry with immense potential. From post-quantum cryptographic protocols being rolled out for Apple Inc.'s iMessaging service to quantum computers, and artificial intelligence working in tandem to solve novel problems, quantum is steadily marching forward into new corners of industry, and our everyday lives. While there is more work to be done and more potential for quantum technologies to achieve, we are no longer waiting for the moment when quantum computers are considered useful rather than novel. With the recent upswing in generative AI and the strain it is expected to put on compute resources, quantum computing is better poised than ever to prove itself as the next frontier of computing and technological development.

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The quantum landscape

When the word "quantum" enters a conversation, it can refer to many things. Broadly, however, quantum technologies utilize principles of quantum mechanics (the physics of subatomic particles), harnessing the unique properties of these particles for novel applications. While quantum computers are one of the most well-known technology (IT) applications of quantum mechanics, the quantum landscape also includes networks and communication, security applications, and environmental sensors.

Quantum computing

This subset of computer science uses quantum mechanics to build more powerful computers to solve problems that are more difficult to solve using classical computation techniques. Quantum computers harness a unique property of subatomic particles known as superposition: the ability to exist not just in a single state, but multiple states at once. In computing, that correlates to a computer that, rather than using a bit (0 or 1) to represent data, uses a qubit, which can be both 0 and 1 at the same time. The field of quantum computing consists of hardware vendors physically building quantum computers, software vendors specializing in quantum-specific developer tools, and QCaaS (quantum computing as a service) providers selling leased access to quantum computers, usually via the cloud.

Quantum networks and communication

Quantum networks utilize quantum mechanical principles for faster and more secure information transfer. Providers are working on a very early iteration of a quantum internet using quantum repeaters, which allow qubit transportation at ultra-fast rates on existing telecom infrastructure. Quantumly entangled particles have the potential for instantaneous data transfer, a phenomenon known as quantum teleportation, allowing for instantaneous communication across vast distances without being bound by the "universal speed limit" of light.

One of the hot-topic issues at play in quantum communication is quantum key distribution, which uses the quantum mechanical properties of a system to help detect potential eavesdroppers, an ability not provided by standard cryptography. Also on the security side of things, as quantum computers become more powerful, there has been a big push to develop quantum-resistant (post-quantum) security algorithms, which will be able to withstand the additional computation power of larger quantum computers.

Quantum sensors

These represent a separate corner of the quantum landscape, with some vendors using quantum mechanical principles to create more accurate sensing technology. In some cases, quantum sensors have been used as a stepping-stone market for quantum computing vendors looking for an early revenue stream, with end products including atomic clocks (used in communication, geology and space navigation) as well as environmental sensors (used by the oil/gas industry and autonomous vehicles).

Vendor landscape

Most of today's quantum vendors operate primarily within the computing sphere in some way, either as quantum hardware or software providers, or a mix of the two.

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In addition, some companies focus their efforts on quantum networking or security, although the overlap with other areas of the quantum landscape is often significant. Many of the largest cloud providers also offer QCaaS, connecting users to quantum computers via the cloud.

Key use cases and early adopting industries

One of the biggest shifts over the past decade in the realm of quantum computing has been the emergence of early use cases for the technology. While quantum computers still have plenty of runway in their ultimate development, today's iterations are already seeing use in what has been termed the era of quantum utility. Today's early quantum computers are functional rather than simply theoretical and are well-suited to solve problems requiring ultra-high-powered compute resources in a variety of industries, including finance, chemistry and pharmaceuticals, sustainability, and communications.

Finance

Quantum computers are particularly well-suited to solve complex, mathematically based problems, so perhaps it is no surprise that finance has been one of the earliest adopters of this technology. Specific use cases include trading optimization, targeting and prediction, and risk profiling. Major financial institutions such as Citigroup Inc., Goldman Sachs Group Inc. and JPMorgan Chase & Co. have active collaborations with key quantum computing companies.

Chemistry and pharmaceuticals

Along with solving mathematical problems, quantum computers are ideal for simulating complex natural processes found in scientific fields such as chemistry. Numerous research papers have been published containing new quantum algorithms designed to tackle problems ranging from predicting the electronic structure of molecules to simulating chemical dynamics. By enhancing the computational power available to theoretical chemists, the implications are profound for drug manufacture. The pharmaceutical industry has already begun working with the quantum computing industry to help speed up drug discovery, with 1QBit, Accenture Labs and Biogen Inc. recently collaborating to produce a novel structural molecular comparison algorithm.

Sustainability

Sustainability is another area full of problems ideally suited to quantum computers. Climate modeling is notoriously compute-intensive, so access to a higher-powered system has the potential to open the door to more accurate and timely climate models for scientists. In addition, advancements currently being made in the chemistry space are already influencing sustainability efforts, with quantum computers being used to develop new, more efficient materials, with the aim of replacing carbon-intensive materials with low-carbon alternatives.

Communication and security

Perhaps one of the most publicized use cases of quantum technology involves its role in secure data storage and communication. Quantum computers are anticipated to become powerful enough to crack current security algorithms, leading to a global push to develop and identify quantum-resistant (post-quantum) algorithms that can withstand more powerful attacks. The National Institute of Standards and Technology (NIST) is in the middle of a selection process to identify ideal algorithms, while some companies have pushed ahead with new encryption models in the interim. In February, Apple announced a new quantum-secure encryption model for its iMessage service known as PQ3, protecting users from "harvest now, decrypt later" attacks wherein attackers could collect and store data now to decrypt when a sufficiently powerful quantum computer is developed.

Quantum computing, AI and other new technologies

Given the upswing in generative AI capabilities seen in 2023, new opportunities for collaboration between quantum computing and AI tools have already begun to proliferate. In June, Microsoft Corp. announced the release of Copilot in Azure Quantum, an AI assistant designed to help aid quantum users by generating underlying calculations, querying data, writing code and providing guided answers in a free, browser-based experience. In January 2024, Microsoft took its AI and quantum combo in a more machine-learning direction. In a partnership with the Department of Energy's Pacific Northwest National Laboratory, the Azure Quantum team used AI to identify a new, previously unknown material not present in nature that has the potential to be used in resource-efficient batteries.

While pairing generative and "traditional" AI with quantum computing clearly has exciting potential, quantum computing is poised to make a substantial impact of its own. In S&P Global Market Intelligence 451 Research's Digital Pulse, Emerging Technologies 2023 survey, respondents were asked about the impact of new or emerging technologies on their organizations within the next three years — 48.5% of survey respondents said they believe quantum computing will have a high impact on their business within that time frame, ranking quantum computing higher than other hyped emerging technologies, such as enterprise metaverse applications (40.4%) and even zero- or low-carbon computing (44.4%).

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In total, quantum computing ranked fourth on our list of impactful new tech, behind only AI for security operations (58.7%), private 5G networking (53.9%) and generative AI (52.6%). In all, 79% of survey respondents believe quantum computing will have a notable impact on their organization within the next three years.

Barriers, roadmaps and next steps

While quantum computing has come a long way in the past decade, the technology is still developing. Quantum computers are in a noisy, intermediate state that International Business Machines Corp. has dubbed the "era of quantum utility." This is in contrast with the long-anticipated "era of quantum advantage," in which quantum computers and their associated systems are powerful enough to consistently surpass classical computation techniques.

To reach this stage, quantum computers need to address two key barriers: scale and consistency. Because of the constraints of quantum computing, scaling up the size of a quantum computer can be incredibly difficult. Some only operate at super-cold temperatures, while other architectures rely on complex systems of lasers to hold individual atoms in place, making larger systems exponentially more difficult to build.

Although some architectures may be better suited to scaling up quantum computers in an efficient way, today's largest computers are currently operating at around 1,000 qubits — much smaller than will be needed for the computational powerhouses of the future. Many vendors have published timelines for the anticipated scale-up of their quantum systems, with IBM anticipating the rollout of a 100,000-qubit system in 2033. In the interim, there has been a substantial push to develop hybrid computation techniques, where early quantum computers collaborate with classical computing systems to solve certain algorithms.

Size is not the only issue that must be overcome. In quantum computing, atomic particles must be held in place long enough for calculations to be run. Coherence time, the length of time that a qubit can be manipulated, matters substantially in the overall effectiveness of a quantum system. Other considerations, including system noisiness and faulty gates or measurements, will necessitate quantum error correction — essentially the ability to account for and overcome errors while running an algorithm on a quantum computer. Error correction is included on most quantum computing roadmaps, with IBM planning to introduce an intermediary error mitigation technique in its 2024 system and aiming to solve error correction by 2029.

Beyond the improvements in hardware, there is also work to be done in the buildout of developer tools designed to democratize access to quantum computing. Interacting with a quantum computer requires working with quantum-specific programming languages (Q#, Cirq, Qiskit), and given the current shortage of quantum computing experts, there will likely need to be an upswing in software platforms built to make quantum computing accessible to a wider range of programmers.

As with any new technology, more growth is expected and more innovation is yet to come. The quantum landscape today looks markedly different from that seen 10, or even five, years ago. While it is impossible to predict the future, the next five years should see the quantum landscape continue to evolve out of early commercialization into a robust and powerful market.

This article was published by S&P Global Market Intelligence and not by S&P Global Ratings, which is a separately managed division of S&P Global.
451 Research is a technology research group within S&P Global Market Intelligence. For more about 451 Research, please contact.

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