The Quantum Computing Arms Race
In a high-stakes technological battle, Amazon, Google, IBM, and Microsoft are locked in a race to create a practical quantum computer. Each tech giant has unveiled prototype quantum chips, each employing distinct strategies and promising diverse applications. While the field is evolving rapidly, significant obstacles remain before these innovations can be commercially deployed. Despite these challenges, the pace of development is quickening, with each company making substantial announcements of advancements in their respective prototype chips.
Quantum computing, a rapidly evolving and highly technical field, holds the promise to revolutionize problem-solving. Its potential applications range from drug discovery and the creation of new chemical compounds to breaking encryption methods, according to researchers. The prospect of such transformative power has ignited a race among the major players in the tech world. The goal is to lead the way in making quantum computing mainstream.
“You’re hearing a lot about it because this is a real tipping point,” said Oskar Painter, the director of quantum hardware at Amazon Web Services, in late February, following the company’s announcement of its Ocelot chip.
Classical vs. Quantum Computing
Understanding the fundamental difference between classical and quantum computing is essential. Classical computers use bits, which are binary digits (0s and 1s), to represent information. Quantum computing, on the other hand, utilizes qubits, which are the quantum equivalent of bits. When qubits behave predictably on a large scale, quantum computers can calculate equations with multiple solutions rapidly and conduct advanced computations that are impossible for classical computers. This makes them potentially capable of solving extremely complex problems far more quickly than conventional computers.
However, qubits are inherently unstable and prone to unpredictable behavior. They require specific, often extreme, operating conditions, such as low light exposure and extremely cold temperatures, to mitigate errors. Increasing the number of qubits generally leads to a higher error rate, which has slowed advancement in the field.
Small-scale quantum computers already exist, but the tech companies are striving to scale them up and make them useful to a wider audience beyond just scientists. Recently, Amazon, Google, and Microsoft have announced novel prototype chips, while IBM has advanced its existing quantum road map. Each company is pursuing unique approaches to reduce errors and increase scalability, which are longstanding challenges that have hindered the development of useful quantum computing.
Company-by-Company Approaches
Here’s a breakdown of the various approaches being taken by the major technology companies:
Microsoft
Microsoft’s Approach to quantum: Topological qubits Most powerful machine: Majorana 1
In February, Microsoft introduced its new quantum chip, Majorana 1. The company aims to accelerate the development of large-scale quantum computers from decades to just a few years.
Microsoft claims that the chip uses a new state of matter to produce “topological” qubits, claiming they are less susceptible to errors and more stable. Essentially, these qubits are based on a topological state of matter, which isn’t a liquid, gas, or solid. These quantum particles could retain a “memory” of their position and move around each other. This means information could be stored across the whole qubit. If parts of it fail, the topological qubit could still retain key information and become more fault-resistant.
“Microsoft’s progress is the hardest to get an idea about because it’s very niche,” said Tom Darras, founder of quantum computing startup Welinq. “Even experts in the industry find it difficult to assess the quality of these results.”
Although quantum experts agree that Microsoft still faces many challenges, and its peer-reviewed Nature paper only demonstrates aspects of what its researchers have claimed to achieve, some in the quantum ecosystem view it as a promising development.
Google’s Approach to quantum: Superconducting qubits Most powerful machine: Willow
In December, Google announced Willow, its newest quantum chip. They claim it can solve a problem in five minutes that the world’s fastest supercomputer would take 10 septillion years to solve.
Perhaps even more impressive is Google’s breakthrough in how quantum computers scale. Historically, the more qubits added and the more powerful the computer becomes, the more it is prone to errors. With Willow, Google’s researchers claim that adding more physical qubits to a quantum processor actually made it less error-prone, reversing the typical phenomenon. Referred to as “below threshold,” this accomplishment marks a significant milestone by cracking a problem that has been a challenge since the 1990s. In a study published in Nature, Google’s researchers posit this breakthrough could finally offer a way to build a useful large-scale quantum computer. While Google still must prove the theory in practice, a major milestone has been achieved.
Amazon
Amazon Web Services Approach to quantum: Superconducting qubits Most powerful machine: Ocelot
In late February, Amazon Web Services unveiled its Ocelot chip, a prototype designed to advance the company’s focus on cloud-based quantum computing.
An Amazon spokesperson stated the Ocelot prototype demonstrated the potential to increase efficiency in quantum error correction by up to 90% compared to conventional approaches. The chip makes use of a unique architecture that integrates cat qubit technology — named after Schrödinger’s famous cat thought experiment — and additional quantum error correction components that can be manufactured using processes borrowed from the electronics industry.
Troy Nelson, a computer scientist and the chief technology officer at Lastwall, a cybersecurity provider of quantum resilient technology, told Business Insider that Amazon’s Ocelot chip is another building block that the industry will use to build a functioning quantum computer. However, its error rate needs to be substantially lowered, and its chips would require more qubit density before they’re useful.
“There’s lots of challenges ahead. What Amazon gained in error correction was a trade-off for the complexity and the sophistication of the control systems and the readouts from the chip,” Nelson said. “We’re still in prototype days, and we still have multiple years to go, but they’ve made a great leap forward.”
IBM
IBM’s Approach to quantum: Superconducting qubits Most powerful machine: Condor
IBM has been a quantum frontrunner for some time, with several different prototype chips and its development of Q System One, the first circuit-based commercial quantum computer, unveiled in January 2019.
IBM’s Condor chip is the company’s most powerful in terms of its number of qubits. IBM has focused its approach on the quality of its gate operations and making its newer quantum chips modular so multiple smaller, less error-prone chips can be combined to make more powerful quantum computing machines.
Condor, the second-largest quantum processor ever made, was unveiled at the IBM Quantum Summit 2023 on December 4, 2023. At the same time, IBM debuted its Heron chip, a 133-qubit processor with a lower error rate. Rob Schoelkopf, cofounder and chief scientist of Quantum Circuits, told Business Insider that IBM has prioritized “error mitigation” over traditional error correction approaches. While IBM has so far been successful in what Schoelkopf calls “brute force scaling” with this approach, he said the methodology will need to be modified in the long run for efficiency.
Who Leads the Quantum Race?
Sankar Das Sarma, a theoretical condensed matter physicist at the University of Maryland, told Business Insider that Amazon Web Services Ocelot chip, Google’s Willow, and IBM’s Condor use a “more conventional” superconducting approach to quantum development compared to other competitors.
By contrast, Microsoft’s approach is based on topological Majorana zero modes, which also have a superconductor, but in “a radically different manner,” he said. If the Majorana 1 chip works correctly, Das Sarma added, it is protected topologically with minimal need for error correction, compared to claims from other tech companies that they have improved conventional error correction methods. Still, each company’s approach is “very different,” Das Sarma said. “It is premature to comment on who is ahead since the whole subject is basically in the initial development phase.”
Georges-Olivier Reymond, CEO of quantum computing startup Pasqal, cautions that Big Tech companies should be cautious about “raising expectations when promoting results.” This caution is shared by Scott Crowder, IBM’s VP of quantum adoption and business development, who expressed concerns that “over-hype” could lead people to discount quantum technology before its promise can be realized.
“We think we are on the cusp of demonstrating quantum advantage,” said Crowder, referring to when a quantum computer outperforms classical machines. “But the industry is still a few years from a fully fault-tolerant quantum computer.”
