Microsoft today introduced Majorana 1, the world’s first quantum chip powered by a new Topological Core architecture that it expects will realize quantum computers capable of solving meaningful, industrial-scale problems in years, not decades.

It leverages the world’s first topoconductor, a breakthrough type of material which can observe and control Majorana particles to produce more reliable and scalable qubits, which are the building blocks for quantum computers.

In the same way that the invention of semiconductors made today’s smartphones, computers and electronics possible, topoconductors and the new type of chip they enable offer a path to developing quantum systems that can scale to a million qubits and are capable of tackling the most complex industrial and societal problems, Microsoft said.

“We took a step back and said ‘OK, let’s invent the transistor for the quantum age. What properties does it need to have?’” said Chetan Nayak, Microsoft technical fellow. “And that’s really how we got here – it’s the particular combination, the quality and the important details in our new materials stack that have enabled a new kind of qubit and ultimately our entire architecture.”

This new architecture used to develop the Majorana 1 processor offers a clear path to fit a million qubits on a single chip that can fit in the palm of one’s hand, Microsoft said. This is a needed threshold for quantum computers to deliver transformative, real-world solutions – such as breaking down microplastics into harmless byproducts or inventing self-healing materials for construction, manufacturing or healthcare. All the world’s current computers operating together can’t do what a one-million-qubit quantum computer will be able to do. 

“Whatever you’re doing in the quantum space needs to have a path to a million qubits. If it doesn’t, you’re going to hit a wall before you get to the scale at which you can solve the really important problems that motivate us,” Nayak said.  “We have actually worked out a path to a million.”

The topoconductor, or topological superconductor, is a special category of material that can create an entirely new state of matter – not a solid, liquid or gas but a topological state. This is harnessed to produce a more stable qubit that is fast, small and can be digitally controlled, without the tradeoffs required by current alternatives. A new paper published Wednesday in Nature outlines how Microsoft researchers were able to create the topological qubit’s exotic quantum properties and also accurately measure them, an essential step for practical computing.

This breakthrough required developing an entirely new materials stack made of indium arsenide and aluminum, much of which Microsoft designed and fabricated atom by atom. The goal was to coax new quantum particles called Majoranas into existence and take advantage of their unique properties to reach the next horizon of quantum computing, Microsoft said.  

The world’s first Topological Core powering the Majorana 1 is reliable by design, incorporating error resistance at the hardware level making it more stable.

Commercially important applications will also require trillions of operations on a million qubits, which would be prohibitive with current approaches that rely on fine-tuned analog control of each qubit. The Microsoft team’s new measurement approach enables qubits to be controlled digitally, redefining and vastly simplifying how quantum computing works.

This progress validates Microsoft’s choice years ago to pursue a topological qubit design – a high risk, high reward scientific and engineering challenge that is now paying off. Today, the company has placed eight topological qubits on a chip designed to scale to one million.

“From the start we wanted to make a quantum computer for commercial impact, not just thought leadership,” said Matthias Troyer, Microsoft technical fellow. “We knew we needed a new qubit. We knew we had to scale.”

That approach led the Defense Advanced Research Projects Agency (DARPA), a federal agency that invests in breakthrough technologies that are important to national security, to include Microsoft in a rigorous program to evaluate whether innovative quantum computing technologies could build commercially relevant quantum systems faster than conventionally believed possible.  

Microsoft is now one of two companies to be invited to move to the final phase of DARPA’s Underexplored Systems for Utility-Scale Quantum Computing (US2QC) program – one of the programs that makes up DARPA’s larger Quantum Benchmarking Initiative – which aims to deliver the industry’s first utility-scale fault-tolerant quantum computer, or one whose computational value exceeds its costs. 

‘It just gives you the answer’

In addition to making its own quantum hardware, Microsoft has partnered with Quantinuum and Atom Computing to reach scientific and engineering breakthroughs with today’s qubits, including the announcement last year of the industry’s first reliable quantum computer.

These types of machines offer important opportunities to develop quantum skills, build hybrid applications and drive new discovery, particularly as AI is combined with new quantum systems that will be powered by larger numbers of reliable qubits. Today, Azure Quantum offers a suite of integrated solutions allowing customers to leverage these leading AI, high performance computing and quantum platforms in Azure to advance scientific discovery.

But reaching the next horizon of quantum computing will require a quantum architecture that can provide a million qubits or more and reach trillions of fast and reliable operations. Today’s announcement puts that horizon within years, not decades, Microsoft said.

Because they can use quantum mechanics to mathematically map how nature behaves with incredible precision – from chemical reactions to molecular interactions and enzyme energies – million-qubit machines should be able to solve certain types of problems in chemistry, materials science and other industries that are impossible for today’s classical computers to accurately calculate.

• For instance, they could help solve the difficult chemistry question of why materials suffer corrosion or cracks. This could lead to self-healing materials that repair cracks in bridges or airplane parts, shattered phone screens or scratched car doors.

• Because there are so many types of plastics, it isn’t currently possible to find a one-size-fits-all catalyst that can break them down – especially important for cleaning up microplastics or tackling carbon pollution. Quantum computing could calculate the properties of such catalysts to break down pollutants into valuable byproducts or develop non-toxic alternatives in the first place.

• Enzymes, a kind of biological catalyst, could be harnessed more effectively in healthcare and agriculture, thanks to accurate calculations about their behavior that only quantum computing can provide. This could lead to breakthroughs helping to eradicate global hunger: boosting soil fertility to increase yields or promoting sustainable growth of foods in harsh climates.

Most of all, quantum computing could allow engineers, scientists, companies and others to simply design things right the first time – which would be transformative for everything from healthcare to product development. The power of quantum computing, combined with AI tools, would allow someone to describe what kind of new material or molecule they want to create in plain language and get an answer that works straightaway – no guesswork or years of trial and error.  

“Any company that makes anything could just design it perfectly the first time out. It would just give you the answer,” Troyer said. “The quantum computer teaches the AI the language of nature so the AI can just tell you the recipe for what you want to make.”

Rethinking quantum computing at scale

The quantum world operates according to the laws of quantum mechanics, which are not the same laws of physics that govern the world we see. The particles are called qubits, or quantum bits, analogous to the bits, or ones and zeros, that computers now use.

Qubits are finicky and highly susceptible to perturbations and errors that come from their environment, which cause them to fall apart and information to be lost. Their state can also be affected by measurement – a problem because measuring is essential for computing. An inherent challenge is developing a qubit that can be measured and controlled, while offering protection from environmental noise that corrupts them.

Qubits can be created in different ways, each with advantages and disadvantages. Nearly 20 years ago, Microsoft decided to pursue a unique approach: developing topological qubits, which it believed would offer more stable qubits requiring less error correction, thereby unlocking speed, size and controllability advantages. The approach posed a steep learning curve, requiring uncharted scientific and engineering breakthroughs, but also the most promising path to creating scalable and controllable qubits capable of doing commercially valuable work.

The disadvantage is – or was – that until recently the exotic particles Microsoft sought to use, called Majoranas, had never been seen or made. They don’t exist in nature and can only be coaxed into existence with magnetic fields and superconductors. The difficulty of developing the right materials to create the exotic particles and their associated topological state of matter is why most quantum efforts have focused on other kinds of qubits.

The Nature paper marks peer-reviewed confirmation that Microsoft has not only been able to create Majorana particles, which help protect quantum information from random disturbance, but can also reliably measure that information from them using microwaves.

Majoranas hide quantum information, making it more robust, but also harder to measure. The Microsoft team’s new measurement approach is so precise it can detect the difference between one billion and one billion and one electrons in a superconducting wire – which tells the computer what state the qubit is in and forms the basis for quantum computation.

The measurements can be turned on and off with voltage pulses, like flicking a light switch, rather than finetuning dials for each individual qubit. This simpler measurement approach that enables digital control simplifies the quantum computing process and the physical requirements to build a scalable machine.

Microsoft’s topological qubit also has an advantage over other qubits because of its size. Even for something that tiny, there’s a “Goldilocks” zone, where a too-small qubit is hard to run control lines to, but a too-big qubit requires a huge machine, Troyer said. Adding the individualized control technology for those types of qubits would require building an impractical computer the size of an airplane hangar or football field.

Majorana 1, Microsoft’s quantum chip that contains both qubits as well as surrounding control electronics, can be held in the palm of one’s hand and fits neatly into a quantum computer that can be easily deployed inside Azure datacenters.

“It’s one thing to discover a new state of matter,” Nayak said. “It’s another to take advantage of it to rethink quantum computing at scale.”

Designing quantum materials atom by atom

Microsoft’s topological qubit architecture has aluminum nanowires joined together to form an H. Each H has four controllable Majoranas and makes one qubit. These Hs can be connected, too, and laid out across the chip like so many tiles.

“It’s complex in that we had to show a new state of matter to get there, but after that, it’s fairly simple. It tiles out. You have this much simpler architecture that promises a much faster path to scale,” said Krysta Svore, Microsoft technical fellow.

The quantum chip doesn’t work alone. It exists in an ecosystem with control logic, a dilution refrigerator that keeps qubits at temperatures much colder than outer space and a software stack that can integrate with AI and classical computers. All those pieces exist, built or modified entirely in-house, she said.

To be clear, continuing to refine those processes and getting all the elements to work together at accelerated scale will require more years of engineering work. But many difficult scientific and engineering challenges have now been met, Microsoft said.

Getting the materials stack right to produce a topological state of matter was one of the hardest parts, Svore added. Instead of silicon, Microsoft’s topoconductor is made of indium arsenide, a material currently used in such applications as infrared detectors and which has special properties. The semiconductor is married with superconductivity, thanks to extreme cold, to make a hybrid.

“We are literally spraying atom by atom. Those materials have to line up perfectly. If there are too many defects in the material stack, it just kills your qubit,” Svore said.

“Ironically, it’s also why we need a quantum computer – because understanding these materials is incredibly hard. With a scaled quantum computer, we will be able to predict materials with even better properties for building the next generation of quantum computers beyond scale,” she said.

Related links:

Learn more: Introducing Microsoft Majorana 1

Read more: Microsoft unveils Majorana 1, the world’s first quantum processor powered by topological qubits

Learn more: Microsoft’s Quantum Ready program

Learn more: Azure Quantum Solutions  

Read more: In a historic milestone, Azure Quantum demonstrates formerly elusive physics needed to build scalable topological qubits

Read more: Nature: Interferometric Single-Shot Parity Measurement in InAs-Al Hybrid Devices

Read more: arXiv: Roadmap to fault tolerant quantum computation using topological qubit arrays

Top image: Majorana 1, the first quantum chip powered by a Topological Core based on a revolutionary new class of materials developed by Microsoft. Photo by John Brecher for Microsoft. 

While training for the Paralympics, self-proclaimed data nerd Samantha Bosco wore a sleep tracker, logged her macronutrients and meticulously analyzed her performance data. Already a champion cyclist with years of experience, she used AI to find even more ways to improve her performance, from researching mobility exercises to reading tips for better sleep. 

Her embrace of digital technology became part of the routine that helped her win a gold medal at the 2024 Paris Paralympic Games.  

“The analytics helped with really fine-tuning those little things that add up,” Bosco says. “It kept my motivation up and reminded me of why I’m tracking the data in the first place.” 

Analyzing data is just one part of a technology project that Bosco and other elite women athletes are doing to help improve their well-being, performance and careers. They learned how to use Microsoft tools for research, data analysis and more with expertise from Parity, a sports marketing and sponsorship organization focused on closing the gender income gap in professional sports. The company connects women athletes with high-profile brands, including Microsoft. 
 

“Generative AI has the ability to democratize access to a lot of capabilities like data analytics that have been fairly expensive to access, and things that are expensive to access are typically not available to women athletes,” says Phillippa Thomson, chief data scientist at Parity. “Microsoft is an amazing partner, in that we’re very aligned in how we think about equity in sports.” 

In training for the Paralympics and Olympics, the four athletes involved in the project were already tracking performance data with their coaches, so Thomson helped them analyze things outside the gym: sleep, nutrition, mood and self-care. She analyzed their data with Microsoft Excel, while they made their busy lives easier with Microsoft Copilot, an AI tool they’re still using today.  

“The benefit of this particular project is that the barrier to start using data with Microsoft products is very low, because they’re designed to be accessible to a lot of people,” she says. 
 

In addition to tracking data, Bosco used Copilot to get the most out of the Paris Games, asking it for restaurant recommendations and tattoo ideas to honor the moment — a huge comeback after she qualified for the 2020 Tokyo Games but couldn’t go due to a serious cycling accident. 

Now enjoying a season off the bike, she’s looking ahead to the 2028 Paralympics and excited to do more with data and AI. She wants to measure her sweat and blood sugar, and try Copilot in Excel, despite already being a spreadsheet expert with a master’s degree in accounting. 

“It was like having my own personal assistant, which can take off the stress of having to figure things out yourself,” she says. “I think there are a lot more opportunities to explore, and I’m looking forward to using Copilot to help track new data and see if it can find trends faster for me.”  

Her goals as a Paralympian aren’t just about being an athlete but also an advocate for people with disabilities. Born with a bowed tibia, she had several surgeries to address the condition that left her with a shorter, atrophied leg. She spent three years on crutches as a child and developed her love of cycling and competing through bike rides with her dad. 

“I feel the most at home and capable when I’m on my bike. It makes me feel the strongest,” says Bosco. “My parents were really big on not letting my disability define me, so I feel like I’m an advocate by showing people that they’re capable of so many things.” 

For weightlifter Jourdan Delacruz’s second trip to the Olympics, she tracked sleep and well-being as part of a holistic way to improve performance, which included working on mindfulness and nutrition. She used Copilot to find recipes to refuel her body after long training days.  

“I would say, ‘Give me high-protein dinner ideas that are sports dietitian-approved’ for very specific results, so I don’t get a million dinner ideas,” says Delacruz, who lifted a combined 195 kilograms (nearly 430 pounds) and placed fifth at the Paris Games. “It’s fun to explore, because I feel like I get in a rut with dinner.” 

She’s now focusing on the business side of her career and using Copilot to generate ideas for her resume and social media. A registered dietician student, she started the platform Herathlete to support women athletes with evidence-based sports nutrition and performance information. She wants to address issues like menstrual cycles and bone density and says data analytics is important for keeping athletes safe and healthy. 

“Having more women in STEM and sports science means we can study more of these topics,” says Delacruz, who wants to be a role model for all women. 

“I hope I’m inspiring girls and women to try strength-based sports,” she says. “Even if you don’t want to do weightlifting full-time, it’s great when a woman is stronger.” 

Two-time Olympian and 400-meter sprinter Kendall Ellis has talked openly about her anxiety, which emerged in childhood as panic attacks before races and often involved negative self-talk.  

But using data to analyze her mood and time spent sleeping, using social media and being with friends has helped her reinforce good habits for mental health, including connecting with loved ones.  

“As an introvert, I do like spending time alone, and often we’re told as athletes that anything outside of our sport is a distraction,” says Ellis, who competed individually in Paris and won gold and bronze relay medals at the Tokyo Games. “But I also enjoy hanging out with my friends, and it’s nice to have the data to support that. I think the brain loves a logical response to things.” 

She now spends less time on social media and makes a point of seeing friends before a competition, when she often feels anxiety rising despite being ranked among the world’s best athletes. The changes have helped her feel more confident and enjoy her sport more, which includes achieving her personal best of 49.46 seconds this year.  

“The data gives me support to lean into the things I enjoy and that helps me go into competition with a clear head and a happy space,” says Ellis, who is getting ready to train for the 2025 World Athletics Championships in Tokyo.  

The Parity project helped her be more comfortable around AI: One of the first things she did was ask Copilot how to use Copilot. She also asks the AI tool for content ideas for her social media, making the creative part of building her following easier when she feels stuck. 

“As someone who was a little resistant with AI, I’ve found that Copilot has shown me the convenience of having a fast answer to my questions and helpful feedback to my creative blocks,” she says. 

Tandem cyclist Skyler Espinoza was initially skeptical of tracking her well-being data as she trained as a guide for the Paris Paralympics. Her performance was already heavily measured and the idea of tracking more data felt stressful. 

But working with Parity allowed Espinoza to customize the metrics she wanted to analyze, such as resting heart rate, mood and time spent at home or on the road. She also tracked the words she used when journaling notes in Excel about daily things like having a nice dinner or walking in the sun. 

After seeing her trend of lower moods when she traveled, she became more intentional about self-care, like packing a nutritious dinner for a long flight or spending time in nature. The data also gave her a long-term view of her well-being and reaffirmed her decision to take a break from the high-pressure world of elite sports after the Games.  

“I feel so grateful that we went to Paris, and I got to have that experience,” says Espinoza, who competed as an able-bodied guide for tandem partner Hannah Chadwick, who has a visual disability.  

“With the tracking journey and looking back on the highs and lows, I’m feeling really confident in the decision to step away from this level of competition,” she says. “I will forever treasure my Games journey, and I think the data project was very helpful for that self-reflection.”  

Espinoza is building a sports community through her writing and is interested in exploring Copilot for things like drafting content, planning trips and finding recipes. Earlier this year, she asked it for help on a post about supporting teammates after the para-cycling world championship. She and Chadwick had had strong performances but had to compete against their teammates, a difficult part of international events. Copilot helped Espinoza create a compassionate post on a tough topic.  

“I’m still learning about AI, and I’m definitely curious about using it as a tool for creativity,” she says. 

Photo of Delacruz by DV Photo Video; photo of Ellis provided by Ellis; photo of Espinoza by Jim Gensheimer. This story was published on Dec. 17, 2024.