Chronological feed of everything captured from Michelle Simmons.
Michelle Simmons, founding director of Australia's ARC Centre of Excellence for Quantum Computation and Communication Technology, built a globally competitive quantum research program around a single contrarian thesis: that atomic-level precision in silicon—not superconducting circuits or trapped ions—offers the most scalable path to practical quantum computing. Her team used scanning tunneling microscopy (STM) to place individual phosphorus atoms within silicon substrates with sub-nanometer accuracy, producing the world's first single-atom transistor and demonstrating stable, readable qubit spin states. This approach treats decoherence as an engineering problem to be eliminated at fabrication rather than corrected at runtime, and leverages silicon's mature semiconductor manufacturing infrastructure for future scalability. Her work repositioned Australia as a serious contender in the global quantum race and established a model for interdisciplinary, talent-pipeline-driven research ecosystems.
Researchers demonstrate a fully controlled 11-qubit quantum processor built from two phosphorus-atom nuclear spin registers in silicon, linked via electron exchange interaction. Nuclear spins in silicon offer coherence times exceeding seconds, and by clustering multiple phosphorus atoms within nanometer-scale proximity, a shared electron mediates multi-qubit control through hyperfine coupling. The system achieves gate fidelities between 99.5% and 99.99%, non-local Bell state fidelities beyond 99%, and GHZ state generation across all data qubits — collectively representing a key hardware milestone toward fault-tolerant quantum computation.
Silicon Quantum Computing (SQC) leverages phosphorus atoms in isotopically pure silicon-28 to create highly stable, low-noise qubits with industry-leading fidelities. Their unique atomic precision manufacturing allows for high-quality, reproducible qubits and proprietary control circuitry. SQC offers three products: quantum machine learning, analog simulation, and aims for a full-scale error-corrected quantum computer by 2033, building on a full-stack in-house development and rapid chip cycle times.