The year 2024 was an interesting year for Quantum Technology and for the world at large. Among the themes we discuss, there are a couple of notable areas that are changing the investment landscape of quantum computers, such as retail investing in quantum computing and the technological push for logical qubits.
Rise of the Retail Quantum Investor
There is no doubt in our minds that there is now visibility among investors, especially retail investors, regarding quantum computing and allied quantum technologies. You may argue that we have been here before with several rounds of prior excitement. Still, we think it is different this time, as we’ve seen steady capital inflows into some of the popular pure-play quantum computing companies such as IonQ, Rigetti, and D-Wave.
Inevesting $1000 into an equal weighting of each of these stocks (IonQ, Rigetti, and D-Wave) that’s $333.33 for each company initially. You’d have approximately $552.32 return from RGTI, $1135.66 from D-Wave, and $857.66 from IonQ. That gives a total of $2545.64, a profit of $1545.64. Gains like this will have captured the minds of the investment community, and no doubt some will already be choosing the color of their “Lambo” in anticipation of continuing further gains.
We think 2024 marked the turning point for quantum computing to become mainstream. It’s no longer a strange and esoteric subject studied by boffins with only theoretical applications. The reality is that almost every major (mainly USA) technology company is exploring quantum computing in some fashion or another. Writing extensively for several years on the output of some of these labs, we can say that some of the offerings are becoming increasingly mature.
IBM has had public access to its cloud-based quantum computers since 2018. Other companies, such as D-Wave, have actually marked their 25th anniversary—that is 25 years in business. We think the wider community is accepting the idea that there is actually a market for quantum computers. Sure, it’s still very early, and use cases are somewhat limited, but companies are increasingly paying for access to explore and experiment with this fledgling technology.
For example, D-Wave Systems, founded in 1999 in Burnaby, Canada, pioneered commercial quantum computing with its 2011 quantum annealing system. Specializing in optimization problems, its systems differ from gate-based quantum computers by focusing on practical applications like logistics and machine learning. D-Wave’s latest Advantage series features over 5,000 qubits, advancing its applicability across industries. While D-Wave makes quantum annealers, it also aims at gate-based quantum computers. Numerous companies have explored the utility of quantum computers from D-Wave for typical optimization problems such as traffic routing.
IonQ, founded in 2015 by Christopher Monroe and Jungsang Kim, leverages trapped ion technology to build high-fidelity quantum computers. Its systems, known for long coherence times, are accessible via major cloud platforms like Amazon Braket, Microsoft Azure, and Google Cloud, democratizing quantum computing. By emphasizing hardware scalability and ease of access, IonQ has positioned itself as a leader in the quantum computing industry.
Today, IonQ is worth just shy of $7bln, still perhaps a minnow in the grand scheme of things. However, this is a pure-play quantum computing company that, unlike Google, doesn’t have recourse to other markets, such as through its advertising products like Adsense.
The broader purpose of gate-based computers, which allies itself to various problems, not just those that can be formulated in a certain way (such as QUBO), remains the focus for much of the quantum computing market. Still, of course, any slight improvement in efficiency that quantum computers can potentially bring can translate into massive savings or gains for those significant problems. Just a tiny fraction of percentage efficiency can take billions off the cost and show up in the bottom line of many large corporate financial statements.
Quantum FOMO
For many, the massive uptake in the use of LLMs was a surprise. Even those who work in AI were not expecting it. Many researchers and practitioners didn’t believe it was possible. They doubted that a model, essentially just predicting the next token in sequence, could drive a new technological revolution. We think there will be a fear of missing out on the FOMO of Quantum Computing.
For a long time, we have thought that the astute will realize this. They understand the importance of entering early in the LLMs-driven AI revolution. This early entry could have made them as rich as Croesus. The same goes for the GPU revolution, driven by the likes of NVIDIA. For many, quantum computing is a compelling offering. They want to invest now on the ground floor of this burgeoning technology.
Some will say there are no utility applications of quantum computing right now, and in some ways, they might be correct. Still, there are well-understood problems and algorithms. These will benefit from quantum computing when those computers reach a certain size. The science behind quantum computing is robust and rigorous. Many of the problems are understood. Many argue that the field faces a challenge. The key is scaling up the number of qubits, which are the fundamental unit of quantum computers. It is also important to improve their characteristics.
Logical Qubits. Going Beyond Fault Tolerance.
Fault-tolerant quantum computing refers to the ability of a quantum computer to perform accurate computations despite errors inherent to quantum systems. This is achieved by using quantum error correction codes that encode logical qubits into more physical qubits, protecting information against noise and imperfections in hardware. Fault tolerance is essential for scaling quantum computers to solve complex problems, as it enables reliable operation over extended periods and under varying conditions, paving the way for practical, large-scale quantum applications.
NISQ, or Noisy Intermediate-Scale Quantum, describes the current era of quantum computing characterized by devices with typically 50-100 qubits. These systems are powerful enough to perform some computations beyond classical capabilities but are limited by noise and error rates.
Unlike fault-tolerant systems, NISQ devices cannot perform long, error-corrected computations. However, they are useful for exploring quantum algorithms, optimization problems, and simulating quantum systems, serving as a stepping stone toward scalable, fault-tolerant quantum computers.
A logical qubit is an error-corrected unit of quantum information formed by combining multiple physical qubits. Through quantum error correction codes, logical qubits are protected from noise and imperfections that affect physical qubits, enabling stable and reliable computation. Logical qubits are a cornerstone of fault-tolerant quantum computing, as they allow quantum systems to perform complex computations over long durations while mitigating the impact of errors.
QuEra Computing, a developer of neutral-atom quantum technologies, has achieved significant progress in logical qubit research, advancing the pursuit of scalable and fault-tolerant quantum computing. By leveraging quantum error correction techniques, they focus on overcoming physical qubits’ fragility and error-prone nature. Combining multiple physical qubits into logical qubits enhances computational stability and reliability. A recent milestone by QuEra, in collaboration with Harvard, MIT, and NIST/UMD, demonstrated the use of 48 logical qubits for executing complex quantum algorithms, marking a significant leap in the field.
QuEra’s neutral-atom systems, such as their advanced Aquila platform, are pivotal in this research. These systems enable precise control over hundreds of qubits with high connectivity and programmability. The company has developed methods to implement and entangle large logical qubits, facilitating the execution of quantum algorithms with reduced error rates.
We liken the focus on logical qubits to the industry, taking for granted that its engineers can create quantum circuits without worrying about correcting errors. After all, on classical computers, we don’t assume that we need ten times as many bits to store a sequence. We don’t take this due to the error correction required. This perspective on quantum count as “logical” will yield a better metric overall. We believe it will help eradicate some wilder headlines and push quantum computers toward true utility-scale.
Quantum Eco System
Each qubit type has distinct advantages tailored to specific applications. For instance, superconducting qubits are well-suited for rapid quantum logic gates in near-term applications. Trapped ions excel in error correction and precision. Photonic systems offer communication potential, and neutral atoms shine in reprogrammable quantum simulations. Meanwhile, topological qubits promise long-term scalability and robustness but have not yet been realized. But whatever technology eventually turns up to power qubits, the rest of the quantum computer stack is getting increasingly more mature and advanced.
To many observers, it may look like a fight between competing technologies, perhaps akin to VHS vs. Beta Max. The VHS and Betamax formats were competing video cassette technologies in the 1970s and 1980s. VHS became the dominant standard due to its longer recording time and broader industry support, while Betamax offered superior picture quality.
The great thing about the quantum computer industry today is that there is a growing ecosystem. This ecosystem includes not only systems but also people and funding. Unlike the emergence of classical computers back in the 1950s, this growth is more comprehensive. So, while we have multiple technologies on offer, we can still work on the software, tooling, and problems. We don’t need to worry too much about the eventual technologies that may win out. It can even be that one technology doesn’t need to win out, and multiple qubit technologies can co-exist.
Governments Are Waking Up to Quantum
During Donald Trump’s tenure from 2016 to 2020, the U.S. government made vital strides in quantum computing and quantum technologies. This progress was driven mainly by increased funding, strategic initiatives, and the development of national policies.
One of the most significant actions was the passage of the National Quantum Initiative Act in December 2018. This law aimed to accelerate quantum research and development in the United States. The initiative provided substantial federal funding—$1.2 billion over five years—to support research, education, and development in quantum information science.
The Act created the National Quantum Coordination Office (NQCO) to oversee the federal government’s quantum efforts. It aims to foster collaboration between academia, industry, and government agencies. This initiative helped establish a national framework for quantum research.
Trump Era. A New Era for Quantum Computing?
The new term of Trump’s second presidency could accelerate technological progress in quantum. Entrepreneur Elon Musk’s appointment to DOGE () could drive some of the largest technological advancements in recent history and further accelerate the pace of quantum tech. While Musk doesn’t have a quantum computer company, he has almost everything else, from Cars to AI to Brain-Computer Interfaces.
Under Trump’s administration, federal agencies such as the Department of Energy (DOE), National Science Foundation (NSF), and Department of Defense (DoD) significantly increased funding for quantum computing research. The DOE, in particular, launched efforts to establish Quantum Information Science Research Centers across the U.S. to advance quantum computing, sensing, and networking.
The next four years, particularly in the US, could experience the “white heat” of technological progress. A president who has already shown his hand in progressing quantum technologies, coupled with one of the most successful entrepreneurs of all time, could lead to a renaissance in computing technologies, not just quantum.
The roaring 20’s or Depression Era?
The Roaring 1920s and the Great Depression Era were two starkly contrasting periods in U.S. history, each marked by distinct social, cultural, and economic conditions. We are now 100 years from this time frame, but could we repeat history a century later?
The 1920s, often called the Roaring Twenties, was a period of economic prosperity, cultural transformation, and social change in the U.S. Following the end of World War I, the country experienced rapid industrialization, technological advancements, and a booming stock market. Consumer goods like automobiles, radios, and household appliances became widely accessible, leading to a consumer-driven economy.
It was also a time of Jazz Age culture, with jazz music and new forms of entertainment becoming popular, while the flapper lifestyle symbolized a break from traditional norms. However, despite the prosperity, this period was also marked by speculation in the stock market, which eventually led to its dramatic crash in 1929.
In contrast, the Great Depression, which began with the stock market crash of 1929, plunged the U.S. into severe economic hardship. Unemployment soared, banks failed, and businesses collapsed, resulting in widespread poverty and hardship for millions. President Franklin D.
Roosevelt’s New Deal programs, launched in the 1930s, were aimed at economic recovery and reform, but the effects of the Depression were felt throughout the decade. The era also saw significant social and cultural struggles, including the Dust Bowl, further devastating farmers and rural communities in the central U.S.
It is hard not to see the rise of technology like AI and LLMs, NVIDIA’s rise, and wonder if we are not already in the midst of the roaring 20s—not the 1920s but the 2020s.
The Rise of Quantum Personalities
The rise of quantum computing has been significantly influenced by a number of key figures whose work spans theoretical foundations, hardware development, and industry applications. These figures include those who educate and inspire. This is not an exhaustive list.
John Preskill is a professor of theoretical physics at Caltech and is widely recognized for his pioneering work in quantum information theory. He coined the term “quantum supremacy,” which refers to the point where quantum computers can solve problems that classical computers cannot. Preskill has been instrumental in developing the framework for understanding quantum error correction and the potential of quantum computers to revolutionize various fields of science and technology.
Peter Shor, a professor at MIT, is best known for Shor’s algorithm, which demonstrated that quantum computers could factor large numbers exponentially faster than classical computers, posing a potential threat to traditional encryption methods. His work laid the foundation for the field of quantum algorithms, which has helped shape the trajectory of quantum computing research.
A key figure in the founding of quantum computing, David Deutsch is a physicist at the University of Oxford known for his work on the theory of quantum computation. In the 1980s, Deutsch proposed the concept of a universal quantum computer, which was a revolutionary idea at the time and inspired subsequent work on quantum algorithms and quantum complexity theory.
Alain Aspect, a French physicist, is known for his experimental work that helped confirm the validity of quantum entanglement—a fundamental concept in quantum mechanics that plays a crucial role in quantum computing. His work has been foundational in demonstrating the non-locality of quantum particles, a principle that has significant implications for developing quantum communication and cryptography.
Lov Grover is another influential figure. He is recognized for developing Grover’s algorithm, which offers a quantum speedup for searching unsorted databases. His contributions have expanded the understanding of quantum algorithms and their potential practical applications in optimization and machine learning.
Bob Sutor is perhaps best known for his work as IBM’s Vice President, where he led the development of the company’s quantum initiatives. Sutor was instrumental in the launch and expansion of the IBM Quantum Experience, a cloud-based quantum computing platform that allows researchers, students, and developers to access quantum computers remotely. Bob is also the Vice President and Practice Lead for Emerging Technologies at The Futurum Group.
He continues to write newer editions of his book “Dancing With Qubits”, which has to be the only quantum computing book that doesn’t include the world “Quantum”.
Stephanie Wehner is a leading researcher in quantum communication and quantum internet technologies. As the Director of the Quantum Internet Alliance (QIA), she plays a pivotal role in advancing the vision of a large-scale quantum internet by 2030, a goal that involves connecting quantum processors across Europe. Her research focuses on developing quantum networks, which will enable secure, ultra-fast communication channels leveraging the principles of quantum mechanics.
Wehner’s work is integral to the Quantum Internet initiative, which aims to revolutionize communication by utilizing quantum entanglement and superposition to create inherently secure networks that are immune to eavesdropping and capable of transmitting quantum data over long distances. The development of such a network is seen as a critical step towards realizing the full potential of quantum computing by enabling distributed quantum computing, quantum cryptography, and more.
Summary for 2025
Drawing some parallels between the technological progress of the past, we think 2025 is going to be an exciting time for quantum computing and quantum tech. We expect more consolidation of the same heady progress that we have seen, and we think that quantum computers will continue to generate interest among the wider public.
One aspect we are excitingly waiting for is the new Trump Era, which should see a renewed focus on technology. We know that the combined force of Trump and Elon will likely accelerate technological progress and increase the urgency of big projects like “Getting to Mars” and “AI,” and we also think Quantum Computing could find its way into being the over-spill from AI, as significant capital continues to flow into AI, it’s looking for the “next thing,” and that next thing is Quantum Computing. Granted, a lot of interest will be FOMO, but that interest will likely be well rewarded by growing progress in the future of computing.
