Scientists from the University of Chicago, Stanford University, the Massachusetts Institute of Technology, the University of Innsbruck in Austria, and Delft University of Technology in the Netherlands have assessed the rapidly advancing field of quantum information hardware in an article published in the December 4, 2025, issue of Science. The authors outline major challenges and opportunities shaping scalable quantum computers, networks, and sensors, noting a turning point similar to the early age of computing. Utilizing large language AI models, they evaluated the technology-readiness level (TRL) of six leading quantum hardware platforms, ranging from a scale of 1 to 9, to compare progress across computing, simulation, networking, and sensing applications. This assessment highlights a maturation driven by collaboration among academia, government, and industry.
Quantum Technology’s Rapid Maturation & Current Status
Quantum technology is rapidly maturing, reaching a turning point comparable to the early days of transistor development. Scientists from multiple US and EU universities assessed the field, noting a transition from laboratory demonstrations to systems enabling early real-world applications in communication, sensing, and computing. This advancement mirrors the tri-sector collaboration—academia, government, and industry—that fueled the rise of microelectronics, suggesting a similar path for quantum technologies.
To compare six leading quantum hardware platforms, researchers utilized large language AI models to assess technology-readiness levels (TRL) on a scale of 1 to 9. Superconducting qubits, neutral atoms, photonic qubits, and spin defects received the highest TRL scores for computing, simulation, networking, and sensing, respectively. However, achieving meaningful applications, like large-scale quantum chemistry simulations, still requires millions of physical qubits with significantly improved error performance beyond current capabilities.
Scaling remains a central challenge for quantum systems. Advancements in materials science, fabrication, wiring, signal delivery, power management, and automated calibration are crucial. The authors draw parallels to 1960s computer engineering—specifically, “the tyranny of numbers”—emphasizing the need for sustained progress and patience, as transformative developments in classical electronics took years to transition from research to industrial deployment.
Comparing Quantum Hardware Platforms & TRLs
Scientists assessed the maturity of six leading quantum hardware platforms – superconducting qubits, trapped ions, spin defects, semiconductor quantum dots, neutral atoms, and optical photonic qubits – using large language AI models like ChatGPT and Gemini. This assessment focused on technology-readiness levels (TRLs), a scale from 1 to 9, evaluating progress across computing, simulation, networking, and sensing. A higher TRL doesn’t necessarily mean a finished product, but reflects a “significant, yet relatively modest, system-level demonstration.”
The assessment revealed superconducting qubits led in TRL for quantum computing, neutral atoms for simulation, photonic qubits for networking, and spin defects for sensing. Despite progress, substantial challenges remain for scaling. The authors emphasize advancements are needed in materials science, fabrication, wiring, signal delivery, power management, calibration, and system control—problems analogous to those faced by computer engineers in the 1960s, referred to as the “tyranny of numbers.”
Context is vital when evaluating TRLs; a quantum technology at TRL-9 today is not comparable to a 1970s semiconductor chip at TRL-9. The authors connect this to historical trends in classical computing, noting transformative developments often take years or decades to move from lab research to industrial deployment. They advocate for system-level design, open scientific knowledge, and, crucially, patience in realizing the full potential of quantum technologies.
“This transformative moment in quantum technology is reminiscent of the transistor’s earliest days.”
David Awschalom
Challenges in Scaling Quantum Systems & Historical Context
The field of quantum technology is at a turning point, mirroring the early days of transistor development and modern computing. Scientists are now focused on scaling these systems, building upon established foundational physics and functional prototypes. Progress is being evaluated by assessing the technology-readiness level (TRL) of six leading hardware platforms—superconducting qubits, trapped ions, and others—on a scale of 1 to 9, though a high TRL doesn’t guarantee a fully realized technology.
A major challenge in scaling quantum systems lies in the sheer complexity of wiring and signal delivery. Current platforms often require individual control channels for each qubit, a system unsustainable as the number of qubits grows into the millions. This echoes the “tyranny of numbers” faced by computer engineers in the 1960s. Advancements in materials science, fabrication, power delivery, and temperature management are also critical for building mass-producible, reliable devices.
Looking to the history of computing, the authors emphasize that transformative developments—like lithography and new transistor materials—took years to move from lab research to industrial deployment. They argue that quantum technologies will likely follow a similar trajectory, requiring patience and a focus on system-level design. A shared, open scientific knowledge base is also crucial to avoid hindering progress.
