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Quantum Motion delivers the industry’s first full-stack silicon CMOS quantum computer; using 300 mm wafers and three 19‑inch racks, can scale to millions of qubits

September 17, 2025 //  by Finnovate

Quantum Motion has delivered the industry’s first full-stack quantum computer to be built using a standard silicon CMOS chip fabrication process – the same transistor technology used in conventional computers. Deployed at the UK National Quantum Computing Centre (NQCC), this is the first full-stack quantum computer to use mass manufacturable 300mm silicon CMOS wafer technology and the first silicon spin‑qubit computer installed under the NQCC’s Quantum Computing Testbed Programme. The system integrates the company’s Quantum Processing Unit (QPU) with a user interface and control stack compatible with industry standard software frameworks, such as Qiskit and Cirq, making it a full-stack solution. The system has a data-centre-friendly footprint of just three 19” server racks, housing the dilution refrigerator and integrated control electronics. Auxiliary equipment is designed to sit separately, enabling it to fit in standard data-centre environments and supporting upgrades to much larger QPUs without any change to the system footprint. Unlike other quantum computing approaches, Quantum Motion’s architecture leverages high-volume industrial chipmaking to produce qubits, using industry standard 300 mm processes from commercial chip foundries. Quantum Motion’s architecture, control stack and manufacturing approach is designed to scale to host millions of qubits, enabling fault tolerant, utility-scale and commercially viable quantum computing. Quantum Motion’s QPU is based on a scalable tile architecture which integrates all the needed compute, readout, and control elements into a dense array that can be repeatedly printed onto a chip, enabling future expansion to millions of qubits per QPU. This design enables systems to be easily upgraded by installing future generation QPUs.  The system also represents a breakthrough in AI machine‑learning tuning, enabling more efficient operation and automated algorithms for control and calibration.

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Category: Innovation Topics, Futurism

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