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Quantinuum Announces Breakthroughs for Quantum Computing Scale-Up

The News: Quantinuum, a quantum computing company based in Broomfield, Colorado, announced breakthroughs in reducing the complexity of the wiring necessary to control and move the company’s trapped ion qubits. This development is a crucial component in allowing Quantinuum to scale-up its systems. See the blog post on the Quantinuum website.

Quantinuum Announces Breakthroughs for Quantum Computing Scale-Up

Analyst Take: Since the early 1980s, scientists and technologists have discussed the promise of quantum computing to solve computationally expensive and challenging use-case problems in areas such as financial services, optimization, AI, chemistry, material science, and healthcare.

Moving from the relatively small quantum computers we have today, with dozens to slightly more than one thousand qubits (quantum bits), to the hundreds of thousands to millions of qubits we will need for future use cases requires innovation on many technological fronts. Quantum system providers must control all these qubits individually and in pairs to fully enable the quantum programming model. Quantinuum’s breakthroughs simplify how the company manipulates its trapped ion qubits, allowing Quantinuum to increase the size and scale of its systems with much less hardware overhead.

I define Practical Quantum Advantage as the point where quantum computing hardware and software, working together with their classical counterparts, provide a significant advantage over classical techniques alone in solving problems critical to society. Quantinuum’s progress is an essential step and milestone for the company and the industry to achieve Practical Quantum Advantage.

Classical Buses and Quantum Multiplexing

In a classical, non-quantum computer, the CPU and its cores are connected to and control other system parts via the address, control, and data buses. The semiconductor circuits in the buses and chips multiplex signals, so each device or memory location does not need its own dedicated wiring. Decades ago, bus technology was much simpler because CPUs were smaller and had limited memory. With billions of transistors today, fast and efficient multiplexing is standard.

Classical computers use the bits 0 and 1 at their lowest levels to perform basic logic operations such as “not” and “and.” From there, we build up more complicated circuits that perform arithmetic and, ultimately, everything you do and experience on devices like your phone or laptop. Quantum computers, in contrast, use qubits and have much more complicated operations enabled by superposition and implementing entanglement.

Depending on how you build your system, you may use microwaves, lasers, or electrical fields to manipulate the qubits and implement the operations, called gates. You may have many “wires” to transmit the control signals for these actions. When you only have a few qubits, this is not a problem because the number of wires is also small. This value can grow to an unwieldy size as the number of qubits increases unless you implement multiplexing.

Quantinuum Announces Breakthroughs for Quantum Computing Scale-Up
An ENIAC computer circa 1950 with its wiring. (Image Source: Wikimedia Commons)

Moving Qubits Efficiently

Quantinuum’s breakthrough is using multiplexing to reduce the growth of the number of control wires and signals required to “sort” their qubits into proper positions to perform one- and two-qubit gates. Some quantum computing modalities, the different physical implementations of qubits, require moving ions or neutral atoms to execute operations, including those that create entanglement. This technique enables shorter circuits, though possibly at the cost of higher execution times and errors due to atom movement. Quantinuum believes it can counter each of these potential downsides.

Other modalities, such as the superconducting varieties, have physically fixed qubits. Software compilers for these devices extend quantum circuits with gates that swap quantum values in intermediate qubits to perform two-qubit operations for non-adjacent qubits. These extra “swaps” can decrease the essential algorithmic operation time available before the qubits become unstable and inaccurate. Engineering involves tradeoffs, and each quantum computing provider must tackle and balance those based on their choice of core qubit technology.

In their research pre-print paper, “Scalable Multispecies Ion Transport in a Grid Based Surface-Electrode Trap,” posted to the arXiv, the Quantinuum authors state that their sorting wiring reduction technique “could be extended to implement other conditional operations involving control fields such as gates, initialization, and measurement.” That is, while they have tackled the sorting problem, they believe their new work generally applies to simplifying the wiring for the other critical ion trap qubit control functions.

Key Takeaway: Quantinuum Continues to Make Strong Engineering Progress Building Quantum Computers

Given this and recent announcements, I expect Quantinuum to continue building ion trap quantum computing systems with state-of-the-art electronics and high-quality, low-error qubits. I look forward to future results that double or triple the qubits in Quantinuum’s ion traps and connect those ion traps with high-fidelity quantum networking.

Disclosure: The Futurum Group is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.

Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of The Futurum Group as a whole.

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Author Information

Dr. Bob Sutor has been a technical leader and executive in the IT industry for over 40 years.Bob’s industry role is to advance quantum and AI technologies by building strong business, partner, technical, and educational ecosystems. The singular goal is to evolve quantum and AI to help solve some of the critical computational problems facing society today. Bob is widely quoted in the press, delivers conference keynotes, and works with industry analysts and investors to accelerate understanding and adoption of quantum technologies.Bob is the Vice President and Practice Lead for Emerging Technologies at The Futurum Group. He helps clients understand sophisticated technologies in order to make the best use of them for success in their organizations and industries. He is also an Adjunct Professor in the Department of Computer Science and Engineering at the University at Buffalo, New York, USA.More than two decades of Bob’s career were spent in IBM Research in New York. During his time there, he worked on or led efforts in symbolic mathematical computation, optimization, AI, blockchain, and quantum computing. He was also an executive on the software side of the IBM business in areas including middleware, software on Linux, mobile, open source, and emerging industry standards. He was the Vice President of Corporate Development and, later, Chief Quantum Advocate, at Infleqtion, a quantum computing and quantum sensing company based in Boulder, Colorado USA.Bob is a theoretical mathematician by training, has a Ph.D. from Princeton University, and an undergraduate degree from Harvard College.

He’s the author of a book about quantum computing called Dancing with Qubits which was published in 2019, with the Second Edition scheduled for release in April, 2024. He is also the author of the 2021 book Dancing with Python, an introduction to Python coding for classical and quantum computing.Areas in which he’s worked: quantum computing, AI, blockchain, mathematics and mathematical software, Linux, open source, standards management, product management and marketing, computer algebra, and web standards.

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