UCL Achieves Breakthrough in Quantum Computing: Atom Placement with Near-Perfect Accuracy

Engineers and physicists at UCL have achieved a significant breakthrough in quantum computer fabrication, demonstrating a new process with an almost zero failure rate and strong scalability potential. The research, published in *Advanced Materials*, details the first reliable method for precisely arranging individual atoms in a grid, a feat realized after 25 years of development. The technique uses arsenic atoms in a silicon crystal, positioning them with near-perfect accuracy using a specialized microscope. This allows for the creation of quantum bits, or qubits, with inherently low error rates. Researchers created a 2x2 array of single arsenic atoms, ready to become qubits. Dr. Taylor Stock, lead author of the study from UCL Electronic & Electrical Engineering, remarked: “The most sophisticated quantum computing systems currently under development are still dealing with the dual challenges of mitigating qubit error rates and scaling up the qubit count. Reliable, atomically precise manufacturing could facilitate the construction of a scalable silicon-based quantum computer. Professor Neil Curson, senior author of the study from UCL Electronic & Electrical Engineering, said: “The ability to place atoms in silicon with near perfect precision and in a way that we can scale up is a huge milestone for the field of quantum computing, the first time that we've demonstrated a way of achieving the accuracy and scale required. While the current method requires manual atom placement, taking several minutes per atom, the authors believe the silicon semiconductor industry can contribute to automating and industrializing the process. This advancement marks a crucial step toward building practical quantum computers capable of solving complex problems beyond the reach of traditional computers, by harnessing quantum mechanics principles like superposition and entanglement. The approach is expected to be highly compatible with current semiconductor processing.