Quantum technology is rapidly moving beyond controlled laboratory experiments and into practical use. According to a new paper published in Science, the field has reached a critical phase that mirrors the early era of classical computing before the invention of the transistor reshaped modern technology.
The paper was written by researchers from the University of Chicago, Stanford University, the Massachusetts Institute of Technology, the University of Innsbruck in Austria, and the Delft University of Technology in the Netherlands. It examines the current state of quantum information hardware and highlights the key opportunities and obstacles involved in building scalable quantum computers, communication networks, and sensing systems.
“This transformative moment in quantum technology is reminiscent of the transistor’s earliest days,” said lead author David Awschalom, the Liew Family Professor of molecular engineering and physics at the University of Chicago, and director of the Chicago Quantum Exchange and the Chicago Quantum Institute. “The foundational physics concepts are established, functional systems exist, and now we must nurture the partnerships and coordinated efforts necessary to achieve the technology’s full, utility-scale potential. How will we meet the challenges of scaling and modular quantum architectures?”
From Lab Experiments to Early Real-World Uses
Over the last ten years, quantum technologies have progressed from proof-of-concept experiments to systems capable of supporting early applications in communication, sensing, and computing. The authors attribute this rapid progress to close collaboration among universities, government agencies, and industry, the same mix of partnerships that helped microelectronics mature in the twentieth century.
Comparing Today’s Quantum Hardware Platforms
The study reviews six major quantum hardware platforms: superconducting qubits, trapped ions, spin defects, semiconductor quantum dots, neutral atoms, and optical photonic qubits. To compare how far each platform has advanced across computing, simulation, networking, and sensing, the researchers used large language AI models such as ChatGPT and Gemini to estimate technology-readiness levels (TRL).
TRLs measure how mature a technology is, using a scale from 1 (basic principles observed in a lab environment) to 9 (proven in an operational environment). A higher TRL does not necessarily mean a technology is close to widespread use, but rather that it has demonstrated more complete system functionality.
The analysis provides a snapshot of where the field stands today. While some advanced prototypes can already operate as full systems and are accessible through public cloud platforms, their overall performance remains limited. Many high-impact applications, including large-scale quantum chemistry simulations, could require millions of physical qubits with error rates far beyond what current technology can support.
Why Technology Readiness Needs Context
Evaluating readiness without historical perspective can be misleading, explained coauthor William D. Oliver, the Henry Ellis Warren (1894) Professor of electrical engineering and computer science, professor of physics, and director of the Center for Quantum Engineering at MIT.
“While semiconductor chips in the 1970s were TLR-9 for that time, they could do very little compared with today’s advanced integrated circuits,” he said. “Similarly, a high TRL for quantum technologies today does not indicate that the end goal has been achieved, nor does it indicate that the science is done and only engineering remains. Rather, it reflects a significant, yet relatively modest, system-level demonstration has been achieved — one that still must be substantially improved and scaled to realize the full promise.”
Scaling Challenges and Lessons From Computing History
Among the platforms studied, superconducting qubits scored highest for quantum computing, neutral atoms led in quantum simulation, photonic qubits ranked highest for quantum networking, and spin defects performed best for quantum sensing.
The authors identify several major hurdles that must be overcome for quantum systems to scale effectively. Advances in materials science and fabrication are needed to produce consistent, high-quality devices that can be manufactured reliably and at scale. Wiring and signal delivery remain major engineering challenges, since most platforms still rely on individual control lines for each qubit. Simply adding more wiring becomes impractical as systems move toward millions of qubits. (Similar problems were faced in the 1960s by computer engineers, known as the tyranny of numbers.) Power management, temperature control, automated calibration, and system-level coordination present additional challenges that will grow as quantum systems become more complex.
The paper draws parallels to the long development timeline of classical electronics. Many transformative breakthroughs, including lithography techniques and new transistor materials, took years or even decades to move from research labs into industrial production. The authors argue that quantum technology is likely to follow a similar path. They stress the need for top-down system design, open scientific collaboration that avoids early fragmentation, and realistic expectations.
“Patience has been a key element in many landmark developments,” they write, “and points to the importance of tempering timeline expectations in quantum technologies.”