The News: On March 28, 2024, D-Wave Quantum Inc., a public quantum annealing computing company founded in 1999 and based in Burnaby, B.C., Canada, and Palo Alto, California, announced its financial results for the 2023 fourth quarter and full year. The company highlighted “computational supremacy,” recent executive moves, product improvements, and customer use case collaborations. See the press release on the D-Wave website.
By the numbers:
- Revenue: $2.906 million in 4Q23 versus $2.394 million in 4Q22, $8.758 million in 2023 versus $7.173 million in 2022
- Operating expenses: $18.509 million in 4Q23 versus $22.301 million in 4Q22, $85.158 million in 2023 versus $63.708 million in 2022
- Net loss: $82.715 million in 2023 versus $53.702 million in 2022
- Total current assets: $59.356 million on December 31, 2023, versus $26.847 on December 31, 2022
Quantum in Context: D-Wave Q4 2023 Earnings and Other Numbers
Analyst Take: Although D-Wave posted modest revenue increases in the fourth quarter and full year 2023, we must balance those with net losses increasing by approximately $29 million from 2022 to 2023. The company continues to sign or renew customers, but the revenue numbers may indicate that large increases in the volume and size of significant deals may take some time. This delay gives D-Wave’s competitors developing universal digital “gate-and-circuit” quantum computers some time to scale their systems and implement error correction. Those competitors, especially those with superconducting approaches, should note that D-Wave has a strong patent portfolio. D-Wave itself is developing a digital system, giving the company two potential product lines in the quantum hardware space.
Annealing for Quantum Computing
Traditional annealing takes a metal like iron or steel, heats it to a specific temperature below its melting point, holds it at that temperature, and then cools it. The controlled cooling optimizes the metallic structure, allowing easier reshaping and reducing brittleness.
Simulated annealing is a classical computer science optimization heuristic designed to find approximate minimum or maximal values of some function for which exact computations may be too expensive. For example, one might want to minimize a cost function in a neural network. The heuristic replaces the cooling of metal in actual annealing with a numeric notion of “temperature” reduction that allows the heuristic to look around probabilistically for a value that may be close to optimal. Researchers have employed this heuristic to predict chemical structures and to find close solutions for the so-called traveling salesperson problem, an analog for the difficult task of finding the shortest possible ways to visit several cities each once, with returns to the home city.
Quantum annealing is simulated annealing in which the heuristic replaces the probabilistic aspect with quantum techniques involving superposition and moving to a ground state representing the solution. D-Wave implements this type of annealing in its quantum systems, applying the general annealing technique to various use cases.
Whether one is using simulated or quantum annealing, it can be challenging to translate the problem into the physics-based representation used by the system. D-Wave makes this easier with its Ocean quantum software development kit, which is analogous to IBM’s Qiskit or Google’s Cirq for digital quantum computing.
Curiously, there is also simulated quantum annealing, which uses classical techniques to allow a pretend quantum computer to perform a quantum-annealing-like process. People sometimes include these techniques within the “quantum-inspired” category. I’m not too fond of that term, but I can live with it as long as you remember it is not real quantum computing.
Vendors providing simulated quantum annealers include AWS and Fujitsu. You can consider both to be competitors of D-Wave.
Quantum “Computational Supremacy”
I have no use for the word “supremacy” in any form with any adjective when it comes to quantum computing.
Instead, I prefer to use the phrase Practical Quantum Advantage, meaning the point at which quantum and classical systems work together and perform significantly better than classical systems alone. I use “practical” to clarify that these quantum systems must show the advantage for the currently intractable problems most important to society, including business.
Although having a quantum computer perform better than a classical computer on a useless problem may have an academic interest, this matters much less to the general public once they cut through the quantum hype and hoopla. Therefore, any claim of a significant improvement must come with a good explanation of its ultimate value to people.
During the earnings call, D-Wave CEO Alan Baratz reminded listeners of D-Wave’s March 1 paper “Computational supremacy in quantum simulation.” This paper, posted on arXiv and listing more than 50 authors, is not yet peer-reviewed. It claims that “approximate classical methods cannot match the solution quality of the QPU in a reasonable amount of time.” The problem is highly technical, one of “simulation of nonequilibrium dynamics of a magnetic spin system quenched through a quantum phase transition,” but one that could potentially demonstrate an important computation regarding matter changing state. Before commenting on the result’s potential utility, I’ll await the paper’s peer-reviewed publication in Nature or a top physics journal.
Moving to a Universal Gate Model for Quantum Computing
Though D-Wave announced in October 2022 that it planned to develop a universal, non-annealing quantum computer, there is no mention of such a system in the press release; however it did provide an update to the market during analyst briefing day in January.
2023 Full Year Financial Comparison with IonQ and Rigetti
D-Wave, IonQ, and Rigetti Computing are the three primary pure-play quantum computing companies. Each went public via a special purpose acquisition company (SPAC): IonQ in October 2021, Rigetti in March 2022, and D-Wave in August 2022. The following table compares the three companies on four full-year financial metrics for 2022 and 2023. All currency figures are in millions.
It’s important to remember that these three companies compete with many private quantum computing startups and giant public international corporations such as IBM and NEC. The large corporations can subsidize their investments in quantum using profits from other areas.
With only two years for data points, it is hard to make predictions, though it is clear that IonQ is in the best position to spend on R&D and customer acquisition.
Key Takeaway: D-Wave has a high burn rate, given its revenue and current assets. Can annealing pay the bills while the company works on a universal quantum computer?
D-Wave is one of the few companies taking the annealing approach to quantum computing, and so it has been up to D-Wave to demonstrate its commercial utility. The qubit-based digital and analog quantum computing models are making rapid progress on scaling and reducing errors, which will lead to fault tolerance. Getting to Practical Quantum Advantage first may be a race but it is not a winner-take-all competition. D-Wave is still in the race, but it must keep the money flowing in while it hooks more customers on the annealing approach, ramps up on the digital quantum model, and then goes head-to-head with IBM, Google, and others.
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 is a former IBM employee and holds an equity position in the company. He holds small equity positions in Amazon and Google. The author does not hold any equity positions with any other 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.
Other Insights from The Futurum Group:
Quantum in Context: Rigetti Q4 2023 Earnings and Other Numbers
Quantum in Context: Pasqal Is the Latest to Publish a Roadmap
Quantinuum Announces Breakthroughs for Quantum Computing Scale-Up
Image Credit: D-Wave
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 released in March 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.
