After Google’s Willow comes Microsoft’s Majorana 1, promising more fantastical quantum computing ahead. But does the reality live up to the hype? Satyen K. Bordoloi investigates.
So far, we could only say that about AI, but since last year, even quantum computing has been moving at a pace that’s hard for anyone to keep up with. Google’s announcement about its Willow chip was barely a few months ago, and hot on its heels comes Microsoft with Majorana 1, promising even more fantastical features. While the tech industry is naturally excited about this new chip—so much so that Satya Nadella is allowing people to touch and feel its compactness—it’s important to approach it critically, just as we did with Google’s announcement.
Microsoft claims that what makes its chip a breakthrough is its use of a whole new state of matter for the architecture of its quantum chip. Instead of using electrons, as chips from Google, Intel, IBM, and others do, Microsoft’s Majorana 1 uses something called Majorana particles.
The Birth of Majorana 1: The Majorana 1 chip is named after the Majorana fermion—an elusive quasiparticle theorized by Ettore Majorana in 1937. It is this particle that sets the chip apart from what Google or IBM have achieved. By using Majorana fermions, the chip employs topological qubits instead of the superconducting or trapped-ion qubits commonly used by competitors like Google and IBM. This is a unique approach, the world’s first topoconductor, which Microsoft promises will tackle problems that are currently too complex for today’s classical computers and “realize quantum computers capable of solving meaningful, industrial-scale problems in years, not decades.”
What’s a Topological Qubit?: At the heart of Majorana 1 is the concept of topological qubits. Unlike conventional qubits used by its competitors, which are notoriously fragile and prone to environmental interference, topological qubits encode information in the system’s ‘shape,’ making them resistant to disturbances. Imagine twisting a string; the knots encode information that is resistant to small changes. This protection promises a far more fault-tolerant quantum computing system, reducing the need for complex error correction, which has been the bane of quantum computing so far.
This is achieved by the topoconductor, created by carefully combining indium arsenide and aluminum, demanding atomic-level precision during fabrication to avoid disrupting delicate quantum states. The topological state is achieved by cooling the topoconductor to near absolute zero. At these cryogenic temperatures, aluminum transitions into a superconducting state, allowing electrons to flow without resistance.
The Majorana 1 Chip: In videos released since the announcement of Majorana 1, Satya Nadella is seen holding the chip, which is about the size of a human palm. In the world of quantum computing, this is remarkably small, considering that traditional quantum systems require vast, intricate infrastructures to house far fewer qubits. This compact design is made possible by integrating error correction directly into the chip through the use of topological qubits. By combining scalability with reliability, the Majorana 1 chip seems to be setting a new benchmark for quantum computing hardware.
Superconducting Qubits: The Established Players: The 1,125-qubit machine by the company Atom and IBM’s 1,121-qubit Condor chip, are the current state-of-the-art in superconducting qubit technology. Both IBM and Google have made significant strides in quantum computing, with IBM focusing on superconducting qubits and Google on both superconducting and photonic qubits. While some of these systems boast higher qubit counts, they face significant challenges in error rates and scalability. Google’s Willow, released in December 2024, has 105 qubits but achieved below-threshold quantum error correction.
Microsoft’s Majorana 1 processor, on the other hand, promises a different approach. By using topological qubits, Majorana 1 aims to reduce error rates significantly. The use of Majorana zero modes (MZMs) in a topological superconductor allows for qubits that are inherently more stable and resistant to environmental interference, achieving intrinsic error rates below 0.1% due to their topological protection. This could potentially reduce the overhead for error correction by orders of magnitude compared to superconducting systems. This stability means that the need for complex error correction mechanisms is reduced, making the system more reliable and scalable.
The Quantum Computing Landscape: The field of quantum computing is already producing diverse approaches. In addition to Google, IBM, and Microsoft, companies like Xanadu (with their photonic qubits) and IonQ (with trapped ions) are pursuing unique strategies for quantum computing. Each approach has its strengths and weaknesses, and while not all will survive, the current thriving competition bodes well for the future of quantum computing.
Skepticism and Realism: While Microsoft’s claims are promising, we must always take company press releases with a grain of salt, as we did with Google’s Willow. Take, for instance, the peer-reviewed Nature paper they released alongside the chip. The issue here is that it only shows part of what the researchers have claimed, with the roadmap still including many hurdles to be overcome. While the Microsoft press release showcases what is supposed to be quantum computing hardware, we don’t yet have any independent confirmation of its capabilities.
For example, the paper published in Nature demonstrates a single-shot interferometric measurement of fermion parity in InAs–Al hybrid devices, which is a crucial step toward topological quantum computation. However, it does not yet demonstrate the full capabilities of a quantum processor. The roadmap outlines a path to fault-tolerant quantum computation, but it is still a theoretical framework that needs to be validated experimentally.
While Microsoft’s roadmap projects a path to 1 million qubits per chip, significant hurdles remain in improving topoconductor yield rates and cryogenic control systems.
Current Capabilities and Future Potential: Majorana 1 is still in the research phase. The first generation of devices focuses on single-qubit operations and measurement-based qubit benchmarking. The roadmap outlines a path to more complex devices, including two-qubit operations and quantum error detection, but these have yet to be fully realized.
What could give Microsoft an edge in quantum computing is the potential for Majorana 1 to scale up to a million qubits on a single chip. This is still theoretical, but if achieved, it would represent a significant leap forward for quantum computing. This scalability, combined with the inherent stability of topological qubits, could enable practical quantum computing applications in almost every field—from artificial intelligence and drug discovery to materials science.
The timeline for commercial availability is uncertain, but Microsoft has stated that it expects to “realize quantum computers capable of solving meaningful, industrial-scale problems in years, not decades.”
The hype around Majorana 1 is justified by its innovative use of topological qubits and the potential for scalable, error-resistant quantum computing. However, it is important to maintain a realistic perspective, considering the current state of the technology and the challenges that remain. The true impact of Majorana 1 will become clearer as more independent research and validation are conducted.
What is clear, however, is that the race for quantum computing has picked up speed. Whether it is superconducting, photonic, or topological qubits, it is now inevitable that one of these—or perhaps each—will unlock quantum computing’s true potential, transforming it from a laboratory curiosity into an industrial powerhouse that reshapes our technological landscape.
In case you missed:
- Google’s Willow Quantum Chip: Separating Reality from Hype
- Why a Quantum Internet Test Under New York Threatens to Change the World
- Kodak Moment: How Apple, Amazon, Meta, Microsoft Missed the AI Boat, Playing Catch-Up
- You’ll Never Guess What’s Inside NVIDIA’s Latest AI Breakthrough
- AI Taken for Granted: Has the World Reached the Point of AI Fatigue?
- The Rise of Personal AI Assistants: Jarvis to ‘Agent Smith’
- The Great Data Famine: How AI Ate the Internet (And What’s Next)
- Nuclear Power: Tech Giants’ Desperate Gamble for AI
- Is Cloud Computing Headed for Rough Weather
- ChatGPT’s Total Recall: AI’s Leap from 404 Errors to Sentimental Reminders
