SQC’s quantum machine learning cuts chip design time from hours to minutes

Photo: Noah Bethke · sqc.com SQC has reduced the time needed to pattern its Watermelon quantum-enhanced AI chips from hours to minutes through the deployment of custom machine learning scripts, the company says. The company’s Precision Atom Qubit Manufacturing process, PAQMan, achieves 0.13 nanometer accuracy when placing phosphorous atoms in silicon, a scale 100 times smaller than the best classical processes. This automation, built around specially adapted Scanning Tunneling Microscopes, has already delivered success in patterning and enables SQC’s one-week chip iteration cycle. “Atomic precision becoming a routine, automated manufacturing step is what moves quantum computing from exotic to industrial,” says SQC, demonstrating a practical step toward scalable quantum computing.

Machine Learning Scripts Automate Watermelon Chip Patterning These scripts operate within Quokka, SQC’s proprietary atomic fabrication control software, generating precise command sequences for the company’s Scanning Tunneling Microscopes (STMs). This automation significantly accelerates a process previously reliant on manual intervention by skilled atomic fabrication scientists. The advance builds upon SQC’s 25 years of experience refining its Precision Atom Qubit Manufacturing process, PAQMan, which achieves 0.13 nanometer accuracy when positioning phosphorous atoms within silicon, according to the company. This level of precision, a hundredfold improvement over the best classical semiconductor manufacturing techniques, is now further enhanced by machine learning’s ability to rapidly translate design changes into physical chip layouts. The company’s one-week chip iteration cycle, already a competitive advantage, is now even more responsive, allowing for faster optimisation of the Watermelon processor for its target markets. The deployment of these scripts is not simply about speed; it’s about unlocking design possibilities. According to SQC, “When device patterning is fast, repeatable and automated, changes to a device design are no longer limited by time, or what can be achieved by hand.” This capability has already been demonstrated through the successful patterning of hundreds of thousands of quantum dots, freeing the team to explore more complex and ambitious device architectures. SQC is currently extending this machine learning-enabled patterning to its gate-based quantum processing units, the firm reports. The company envisions a future where atomic precision is not an exceptional achievement, but a routine step in manufacturing, and the success with Watermelon demonstrates this vision in practice, establishing a pathway toward scalable and efficient quantum computer production. Source: https://sqc.com/news/automating-atomic-precision-semiconductor-manufacturing More like thisQuantum Research NewsIonQ and partners show practical applications and future roadmap at IEEE 2026Artificial IntelligenceQuandela and NVIDIA link quantum processors to AI with NVQLinkQuantum HardwareLogical advantage of Pinnacle confirmed on spin-qubit hardwareQuantum HardwareInfleqtion and Cisco link quantum computers into early networksStay currentSee today’s quantum computing news on Quantum Zeitgeist for the latest breakthroughs in qubits, hardware, algorithms, and industry deals. Tags: The Neuron With a keen intuition for emerging technologies, The Neuron brings over 5 years of deep expertise to the AI conversation. Coming from roots in software engineering, they've witnessed firsthand the transformation from traditional computing paradigms to today's ML-powered landscape. Their hands-on experience implementing neural networks and deep learning systems for Fortune 500 companies has provided unique insights that few tech writers possess. From developing recommendation engines that drive billions in revenue to optimizing computer vision systems for manufacturing giants, The Neuron doesn't just write about machine learning—they've shaped its real-world applications across industries. Having built real systems that are used across the globe by millions of users, that deep technological bases helps me write about the technologies of the future and current. Whether that is AI or Quantum Computing. Latest Posts by The Neuron: Photonic Inc. pursues quantum gains to keep Canadian tech manufacturing at home September 14, 2026 Photonic Inc. proposes $500M Canada chip facility for quantum and AI September 14, 2026 IonQ and partners show practical applications and future roadmap at IEEE 2026 September 14, 2026