"The real challenge, the thing that stops us from having useful quantum computers today, is that you build a qubit and the information just doesn't last very long," said Andrew Houck, leader of a federally funded national quantum research center, Princeton's dean of engineering and co-principal investigator on the paper. "This is the next big jump forward."
In a Nov. 5 article in the journal Nature, the Princeton team reported their new qubit lasts for over 1 millisecond. This is three times longer than the best ever reported in a lab setting, and nearly 15 times longer than the industry standard for large-scale processors. The researchers built a fully functioning quantum chip based on this qubit to validate its performance, clearing one of the key obstacles to efficient error correction and scalability for industrial systems.
The new qubit design is similar to those already used by leading companies like Google and IBM, and could easily be slotted into existing processors, according to the researchers. Swapping Princeton's components into Google's best quantum processor, called Willow, would enable it to work 1,000 times better, Houck said. The benefits of the Princeton qubit grow exponentially as system size grows, so adding more qubits would bring even greater benefit.
While engineers are pursuing a range of technologies to develop qubits, the Princeton version relies on a type of circuit called a transmon qubit. Transmon qubits, used in efforts by companies including Google and IBM, are superconducting circuits that run at extremely low temperatures. Their advantages include a relatively high tolerance for outside interference and compatibility with current electronics manufacturing.
But the coherence time of transmon qubits has proven extremely hard to extend. Recent work from Google showed that the major limitation faced in improving their latest processor comes down to the material quality of the qubits.
The Princeton team took a two-pronged approach to redesigning the qubit. First, they used a metal called tantalum to help the fragile circuits preserve energy. Second, they replaced the traditional sapphire substrate with high-quality silicon, the standard material of the computing industry. To grow tantalum directly on silicon, the team had to overcome a number of technical challenges related to the materials' intrinsic properties. But ultimately they prevailed, unlocking the deep potential of this combination.
Nathalie de Leon, the co-director of Princeton's Quantum Initiative and co-principal investigator of the new qubit, said that not only does their tantalum-silicon chip outperform existing designs, but it's also easier to mass-produce. "Our results are really pushing the state of the art," she said.
Michel Devoret, chief scientist for hardware at Google Quantum AI, which partially funded the research, said that the challenge of extending the lifetimes of quantum computing circuits had become a "graveyard" of ideas for many physicists. "Nathalie really had the guts to pursue this strategy and make it work," said Devoret, a recipient of the 2025 Nobel Prize in physics.
The research was primarily funded by the U.S. Department of Energy National Quantum Information Science Research Centers and the Co-design Center for Quantum Advantage (C2QA) - a center that Houck directed from 2021 to 2025, and where he is now chief scientist. The paper's co-lead authors are postdoctoral researcher Faranak Bahrami and graduate student Matthew P. Bland.
The most common source of error in these qubits is energy loss. Tiny, hidden surface defects in the metal can trap and absorb energy as it moves through the circuit. This causes the qubit to rapidly lose energy during a calculation, introducing errors that multiply as more qubits are added to a chip. Tantalum typically has fewer of these defects than more commonly used metals like aluminum. Fewer errors also make it easier for engineers to correct those that do occur.
Houck and de Leon, who is an associate professor of electrical and computer engineering, first introduced the use of tantalum for superconducting chips in 2021 in collaboration with Princeton chemist Robert Cava, the Russell Wellman Moore Professor of Chemistry. Despite having no background in quantum computing, Cava, an expert on superconducting materials, had been inspired by a talk de Leon had delivered a few years earlier, and the two struck up an ongoing conversation about qubit materials. Eventually, Cava pointed out that tantalum could provide more benefits and fewer downsides. "Then she went and did it," Cava said, referring to de Leon and the broader team. "That's the amazing part."
Researchers from all three labs followed Cava's intuition and built a superconducting tantalum circuit on a sapphire substrate. The design demonstrated a significant boost in coherence time, in line with the world record.
Tantalum's main advantage is that it's exceptionally robust and can survive the harsh cleaning needed for removing contamination from the fabrication process. "You can put tantalum in acid, and still the properties don't change," said Bahrami, co-lead author on the new paper.
Once the contaminants were removed, the team then came up with a way to measure the next sources of energy loss. Most of the remaining loss came from the sapphire substrate. They replaced the sapphire with silicon, a material that is widely available with extremely high purity.
Combining these two materials while refining manufacturing and measurement techniques has led to one of the largest single improvements in the transmon's history. Houck called the work "a major breakthrough on the path to enabling useful quantum computing."
Because the improvements scale exponentially with system size, Houck said that swapping the current industry best for Princeton's design would enable a hypothetical 1,000-qubit computer to work roughly 1 billion times better.
Devoret, the Google scientist, who is also a professor of physics at the University of California-Santa Barbara, said that partnerships between universities and industry are important for advancing the frontiers of technology. "There is a rather harmonious relationship between industry and academic research," he said. University labs are well positioned to focus on the fundamental aspects that limit the performance of a quantum computer, while industry scales up those advances into large-scale systems.
"We've shown that it's possible in silicon," said de Leon. "The fact that we've shown what the critical steps are, and the important underlying characteristics that will enable these kinds of coherence times, now makes it pretty easy for anyone who's working on scaled processors to adopt."
The paper "Millisecond lifetimes and coherence times in 2D transmon qubits" was published in Nature on Nov. 5. Besides de Leon, Houck, Cava, Bahrami, and Bland, authors include Jeronimo G.C. Martinez, Paal H. Prestegaard, Basil M. Smitham, Atharv Joshi, Elizabeth Hedrick, Alex Pakpour-Tabrizi, Shashwat Kumar, Apoorv Jindal, Ray D. Chang, Ambrose Yang, Guangming Cheng and Nan Yao. This work was primarily supported by the U.S. Department of Energy, Office of Science, National Quantum Information Science Research Centers, Co-design Center for Quantum Advantage (C2QA), and was partially supported by Google Quantum AI.
Research Report:Millisecond lifetimes and coherence times in 2D transmon qubits
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