Argonne National Laboratory and Intel Deploy 12-Qubit Silicon Quantum Dot Processor
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Argonne National Laboratory and Intel Deploy 12-Qubit Silicon Quantum Dot Processor Argonne National Laboratory and Intel have successfully deployed and operated a 12-qubit quantum dot processor as part of a strategic industry-government partnership. The results of this collaboration, led by the Q-NEXT National Quantum Information Science Research Center, were recently published in Nature Communications. This milestone validates the use of existing high-volume semiconductor manufacturing techniques to produce scalable, high-yield quantum hardware. The processor, code-named Tunnel Falls, leverages Intel’s 300-millimeter silicon manufacturing line and extreme ultraviolet (EUV) lithography. Unlike superconducting or ion-trap systems, which require vastly different architectures than classical electronics, silicon spin qubits are essentially modified single-electron transistors. This compatibility allows Intel to fabricate tens of thousands of quantum dot devices across a single wafer with over 95% yield. By confining single electrons within these dots, researchers can manipulate their quantum spin to store and process information, benefiting from the long coherence times and small physical footprint inherent to silicon-based systems. Strategically, the deployment at Argonne provides an open-science testbed to study the physics of multi-qubit interactions and characterize device variability. Argonne researchers are investigating the optimal methods for qubit “tune-up” and control, providing critical feedback to Intel to inform the development of larger, hundreds-of-qubit processors. This partnership is a cornerstone of the recently renewed Q-NEXT mission, which focuses on integrating quantum materials into practical devices and establishing a robust domestic supply chain for quantum technologies. Read the official announcement from Argonne National Laboratory here and the technical study in Nature Communications here. January 8, 2026 Mohamed Abdel-Kareem2026-01-08T04:56:24-08:00 Leave A Comment Cancel replyComment Type in the text displayed above Δ This site uses Akismet to reduce spam. Learn how your comment data is processed.