Quantum Computing Faces Thermal Scale Challenges - Design News

Former IBM quantum expert discusses cooling systems, environmental stability hurdles, and workforce needs for practical quantum deployment. Over a month ago, the NSF Engineering Research Visioning Alliance (ERVA) released a report on the state of quantum computing. Design News posted a slideshow on some of the report’s key findings. But we also followed up with ERVA to get a little more insight into quantum computing challenges. Brian Gaucher of the ERVA Thematic Task Force and former Principal Research Scientist, Systems Design Manager, Quantum Computing for IBM, generously took the time to respond to several follow-up questions. His responses are below, and he references several points in the report for each response. You can view ERVA’s report on quantum computing here. Related:4 Ways the US Can Win the Competitive Global Quantum Sector BG: Substantial progress in cryogenic cooling has been made—today’s systems can support thousands of qubits—but thermal management and inter-system interconnect are now system-level challenges. The limits are no longer just temperature; they include wiring density, heat leakage, vibration, reliability, and how these systems are operated and serviced at scale. Future progress will come as much from architectural and layout innovations as from cryogenic improvements and system/fridge level interconnects. Current cryostats can support thousands of qubits, but require top-to-bottom refrigerator wiring with low loss, high-speed electrical properties, and high thermal resistance to limit heat transfer between cooling stages. Existing commercial cryogenic systems are suitable for experiments, but high-thermal-capacity, interconnectable, vibration-isolated, low-cost, low-power systems do not yet exist for large-scale deployment. Thermal capacity and volumetric limits constrain a single dilution refrigerator to thousands of qubits, while meaningful applications are expected to require tens to hundreds of thousands of qubits. Scaling will require new approaches to reliability, availability, inter-connectability, and serviceability, including the ability to monitor and diagnose failures within refrigerators or networks of refrigerators. Related:Quantum Tech Ready to Emerge From the Lab, Expert Says BG: Quantum systems are extremely sensitive by design, which makes them powerful but also vulnerable to vibration, electromagnetic interference, and thermal fluctuations. The challenge is not eliminating all noise, but engineering systems that can operate predictably and reliably in noisy, real-world environments. Quantum systems are inherently sensitive to environmental disturbances, including vibration, electromagnetic interference, and temperature fluctuations, which can couple into quantum states and degrade coherence and signal fidelity. Mechanical and vibrational stability require multi-level design, including vibration-isolated mounting, cryostat- and facility-level damping, and careful routing of mechanical supports and services. Electromagnetic compatibility is a system-level concern, addressed through shielding, grounding strategies, filtering, and careful co-design of control electronics, interconnects, and quantum hardware. Integration and layout choices matter, including physical separation of noise sources, modular architectures, and standardized interfaces that reduce unintended coupling. BG: Quantum technologies will not replace existing electronic infrastructure wholesale. The near-term path is hybrid systems—quantum components integrated with classical electronics, software, and networks. Over time, standards will emerge where they add value, while much of today’s infrastructure remains in place. Quantum technologies are at an early, pre-standardization stage, similar to classical computing and semiconductors in their early decades, where architectures and interfaces are still evolving. Interfacing quantum and classical systems is a primary engineering challenge, involving signal conversion, timing synchronization, control electronics, and software stacks that can manage both quantum and classical resources. Standards will emerge incrementally, driven by practical integration needs, interoperability requirements, and shared engineering experience, rather than being imposed upfront. BG: ERVA does not fund research and does not track individual budget impacts but serves as a neutral convener to identify engineering research directions that organizations across sectors may choose to pursue. Speaking more broadly, quantum R&D—like many advanced technologies—is sensitive to funding stability. While there have been budget pressures in some areas, overall investment in quantum technologies remains strong in the U.S. and globally. The high cost of development makes sustained, coordinated investment—including public–private partnerships—especially important. Overall investment in quantum technologies remains strong, with continued federal, international, and private-sector commitments reflecting sustained strategic interest. The high cost of developing quantum technologies does shape startup activity, favoring longer timelines, deeper technical risk, and closer ties to government programs, national laboratories, and industrial partners. Many quantum startups rely on hybrid funding models, combining venture capital with public funding, partnerships, and early application-focused deployments. BG: Quantum technology development will not rely only on a small group of specialists. It will be built by engineers, technicians, software developers, and manufacturers who already have strong skills and are gaining quantum literacy. Workforce efforts are focused on helping people transition into these roles, not on creating an entirely new profession. Training across disciplines and sectors is essential, bringing together expertise from universities, community colleges, trade schools, national laboratories, and industry to support everything from research and prototyping to manufacturing and deployment. Through public–private partnerships, hands-on training and workforce pipelines can connect education directly to practical applications. A mature quantum technology ecosystem requires two complementary groups: deep quantum specialists and a much larger quantum-literate workforce capable of engineering, operating, and integrating quantum systems. Most future quantum roles will build on existing skill sets, including electrical and mechanical engineering, physics, software development, materials science, manufacturing, and systems integration, rather than requiring entirely new career paths. Workforce development efforts are already underway, focusing on understanding near- and long-term workforce needs, expanding educational pathways, and aligning training with real-world engineering and industrial requirements. BG: Today, AI is most useful in quantum computing as an engineering partner—helping manage complexity, optimize control, and learn from large volumes of experimental data. It does not replace physical understanding, but it can accelerate learning and help guide decisions when systems become too complex to manage by hand. Cross-domain applications are also emerging, such as AI-assisted materials discovery and data analysis for biological and chemical systems, where quantum and AI tools can reinforce one another. There is growing interest in using AI to accelerate scientific discovery and improve research workflows. For example, the White House recently launched the Genesis Mission, a coordinated federal effort to integrate AI into scientific workflows. AI can serve as an effective engineering partner for quantum computing, particularly in managing complexity, optimizing control, and accelerating learning from experimental data. In the longer term, AI may assist in system design, including architecture exploration, code optimization, and component co-design, but these applications remain an active area of research rather than established practice. Cross-domain applications are emerging, such as AI-assisted materials discovery and data analysis for biological and chemical systems, where quantum and AI tools can reinforce one another. Spencer Chin is a Senior Editor for Design News, covering the electronics beat, which includes semiconductors, components, power, embedded systems, artificial intelligence, augmented and virtual reality, and other related subjects. When Spencer began covering electronics years ago, there was no internet, no cell phones, let alone smartphones, and PCs were emerging but not widespread. Robots and artificial intelligence? Only in a science fiction film. Modems were a curiosity requiring patience fumbling with connection scripts, and Bluetooth and wireless communications did not exist. Spencer has witnessed and covered, first-hand, many developments in the underpinnings of these modern technologies that we take for granted. Now, we're in the age of artificial intelligence, autonomous vehicles, high-speed signaling hardware, FPGAs, microcontrollers, and advanced design tools. Spencer is again in the trenches covering these developments, and looking forward to the technologies of the future. At the same time, Spencer has adapted his reporting and editing style to the digital age. It's not just news stories and features but also social media posts, and videos, as seen below. Adapting to 21st-century media consumption habits has kept Spencer on his toes learning new tools and skills, though he admits it is sometimes hard to teach an old dog new tricks. Spencer's long list of editorial stops reads like a Who's Who in technical content brands, including Electronic Products, Electronic Buyers News, EE Times, Power Electronics, and NASA Tech Briefs. He is proud to be the go-to electronics editor at Design News. Got an idea for a story or subject you would like covered. You can reach Spencer through his e-mail Spencer.Chin@informa.com, follow him at @spencerchin, or contact him on Linkedin at https://www.linkedin.com/in/spencerchin/. He looks forward to hearing from and engaging with you!

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