2026-03-13
Recently, research involving core members of Logical Qubit Technology was published in National Science Review under the title Combinatorial optimization enhanced by shallow quantum circuits with 104 superconducting qubits. The study proposed a quantum-classical hybrid algorithm named "Qjump" and experimentally validated it on a 100-qubit-scale superconducting quantum processor. By combining shallow quantum circuit sampling with classical local search, the algorithm demonstrates the potential to outperform general-purpose classical heuristic algorithms that do not rely on problem-specific structures, such as simulated annealing, in solving complex combinatorial optimization problems. The work highlights the potential of large-scale superconducting quantum computing hardware and opens a new path toward practical quantum advantage.
Specifically, the research team experimentally validated the Qjump algorithm on the 104-qubit Tianmu-2 superconducting quantum chip using Logical Qubit Technology's independently developed quantum measurement and control system. The system integrates up to 500 signal channels. Since the experiment required simultaneous execution of single-qubit and two-qubit gate operations across a 100-qubit-scale system, it imposed demanding requirements on parallel control capability, clock synchronization precision, and operational stability.
