Imroatul Nasiyah
Published on November 5th in the prestigious journal Nature, the Princeton team’s report details their novel qubit’s ability to maintain coherence for over 1 millisecond. This impressive duration is triple the longest coherence times previously documented in laboratory settings and represents a nearly fifteen-fold improvement over the standard coherence times found in industrial quantum processors. To validate their findings and demonstrate practical applicability, the researchers constructed a functional quantum chip utilizing their new qubit design. This chip successfully showcased the architecture’s capacity for error correction and its potential for scalability towards larger, more complex quantum systems.
A crucial aspect of this development is the qubit’s compatibility with existing architectures employed by major quantum computing players like Google and IBM. The Princeton team’s analysis indicates that by integrating their novel qubit components into Google’s Willow processor, a performance enhancement of up to 1,000 times could be achieved. Houck further emphasized that the advantages of this design escalate dramatically as the number of qubits in a system increases, suggesting a synergistic effect that amplifies its impact.
The significance of enhanced qubit durability for quantum computing cannot be overstated. Quantum computers hold immense promise for tackling complex problems that lie beyond the reach of even the most powerful classical supercomputers. However, their current capabilities are severely constrained by the tendency of qubits to lose their delicate quantum states before intricate calculations can be completed. Extending coherence times is therefore a fundamental prerequisite for realizing the full potential of practical quantum hardware. Princeton’s achievement represents the most substantial single gain in qubit coherence time witnessed in over a decade.
While numerous research institutions are exploring diverse qubit technologies, Princeton’s innovation builds upon the widely adopted transmon qubit architecture. Transmons, which operate as superconducting circuits maintained at cryogenic temperatures, are lauded for their inherent resistance to environmental interference and their amenability to contemporary manufacturing processes. Despite these advantages, significantly improving the coherence times of transmon qubits has presented a formidable challenge. Recent findings from Google, for instance, highlighted that material defects have emerged as the principal impediment to advancing their latest processors.
The Princeton researchers ingeniously devised a two-pronged materials strategy to circumvent these persistent material-related obstacles. Their first innovation involved the incorporation of tantalum, a metal renowned for its ability to retain energy within delicate circuitry. Secondly, they replaced the conventional sapphire substrate, a common material in qubit fabrication, with high-purity silicon. Silicon, a cornerstone of the global semiconductor industry, offers inherent advantages in terms of material properties and manufacturing scalability. The process of growing tantalum directly onto a silicon substrate necessitated overcoming several intricate technical hurdles related to material interaction, but the team’s perseverance yielded not only a solution but also uncovered substantial benefits.
Nathalie de Leon, co-director of Princeton’s Quantum Initiative and a co-principal investigator on the project, highlighted the dual advantages of their tantalum-silicon design, stating that it not only delivers superior performance compared to preceding approaches but is also inherently simpler to manufacture at scale. "Our results are really pushing the state of the art," she remarked. Michel Devoret, chief scientist for hardware at Google Quantum AI and a recipient of the 2025 Nobel Prize in Physics, who provided partial funding for the research, underscored the extreme difficulty of extending the operational lifetime of quantum circuits, describing the challenge as a "graveyard" of attempted solutions. He lauded de Leon’s determination, noting, "Nathalie really had the guts to pursue this strategy and make it work."
The project received primary financial backing from the U.S. Department of Energy’s National Quantum Information Science Research Centers and the Co-design Center for Quantum Advantage (C2QA). Houck directed C2QA from 2021 to 2025 and currently serves as its chief scientist. The groundbreaking Nature paper lists postdoctoral researcher Faranak Bahrami and graduate student Matthew P. Bland as co-lead authors, alongside a distinguished group of collaborators.
Andrew Houck, the Anthony H.P. Lee ’79 P11 P14 Professor of Electrical and Computer Engineering, elaborated on the critical factors governing a quantum computer’s efficacy. He explained that a quantum computer’s overall capability is determined by two primary metrics: the total number of qubits that can be interconnected and the number of operations each qubit can perform before accumulating errors. Enhancing the durability of individual qubits directly bolsters both of these crucial aspects. Extended coherence times are fundamental to enabling qubit scaling and facilitating more robust error correction mechanisms.
Energy loss is identified as the most prevalent cause of failure in these sensitive quantum systems. Microscopic surface defects within the metallic components of a qubit can trap stray energy, thereby disrupting calculations and leading to errors. The multiplicative nature of these disruptions becomes increasingly problematic as more qubits are integrated into a system. Tantalum proves exceptionally beneficial in this regard due to its inherent characteristic of possessing significantly fewer such defects compared to commonly used metals like aluminum. The reduction in defects translates directly to a lower error rate, simplifying the complex task of correcting the remaining errors.
Houck and de Leon first introduced tantalum as a promising material for superconducting chips in 2021, with invaluable contributions from Princeton chemist Robert Cava, the Russell Wellman Moore Professor of Chemistry. Cava, a leading expert in superconducting materials, became intrigued by the problem after attending one of de Leon’s presentations. Their subsequent discussions led him to propose tantalum as a potential solution, a suggestion that de Leon enthusiastically pursued. "Then she went and did it," Cava remarked, expressing admiration for her accomplishment. "That’s the amazing part."
Following this insightful suggestion, researchers across the three laboratories collaborated to construct a tantalum-based superconducting circuit fabricated on a sapphire substrate. The initial results demonstrated a marked improvement in coherence time, bringing it close to the previous world record. Bahrami highlighted tantalum’s exceptional durability, noting its resilience to the rigorous cleaning processes essential for removing contaminants during fabrication. "You can put tantalum in acid, and still the properties don’t change," she stated.
Upon meticulous cleaning and contaminant removal, the team meticulously analyzed the remaining sources of energy loss. Their investigation revealed that the sapphire substrate was the primary contributor to these residual losses. The strategic decision to switch to a high-purity silicon substrate effectively eliminated this significant source of energy dissipation. The synergistic combination of tantalum and silicon, coupled with refined fabrication techniques, ultimately resulted in one of the most substantial improvements ever recorded for a transmon qubit. Houck characterized this achievement as "a major breakthrough on the path to enabling useful quantum computing." He further projected that the exponential scaling benefits of this design mean that replacing current industry-leading qubits with the Princeton version could theoretically empower a 1,000-qubit computer to operate approximately 1 billion times more effectively.
The Princeton project’s success is a testament to the synergistic integration of expertise from three distinct areas. Houck’s group specializes in the intricate design and optimization of superconducting circuits. De Leon’s lab focuses on quantum metrology, alongside the critical materials and fabrication methods that dictate qubit performance. Cava’s group brings decades of experience in the development of advanced superconducting materials. By pooling their specialized knowledge, the team achieved results that would have been unattainable by any single group working in isolation. This groundbreaking work has already garnered significant attention from the quantum computing industry.
Devoret emphasized the indispensable role of collaborations between academic institutions and commercial enterprises in propelling advanced technologies forward. He observed a "rather harmonious relationship between industry and academic research," where university researchers explore the fundamental limits of quantum performance, while industry partners leverage these discoveries for the development of large-scale systems. "We’ve shown that it’s possible in silicon," de Leon stated, underscoring the practical implications of their work. "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 research paper, titled "Millisecond lifetimes and coherence times in 2D transmon qubits," was published in Nature on November 5th. The author list includes de Leon, Houck, Cava, Bahrami, and Bland, along with 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 pioneering research was primarily supported by the U.S. Department of Energy, Office of Science, National Quantum Information Science Research Centers, and the Co-design Center for Quantum Advantage (C2QA), with partial support from Google Quantum AI.
