D-Wave Quantum Inc. has announced a non-binding memorandum of understanding (MOU) with LG CNS Co., Ltd. to advance quantum computing adoption for enterprise optimization in South Korea and international markets. The collaboration, signed on October 28, 2026, focuses on applying D-Wave’s annealing quantum computing technology to complex optimization challenges. The goal is to move applications from proof of concept into production.
The partnership aims to combine D-Wave’s commercial quantum computing technology with LG CNS’s industry expertise, mathematical optimization capabilities, and systems integration experience. The companies intend to develop applications for customers in the manufacturing, telecommunications, finance, and retail sectors. Additionally, the parties plan to pursue joint go-to-market opportunities.
The MOU was announced by D-Wave CEO Dr. Alan Baratz and LG CNS President and CEO Hyun Shin-Gyoon at D-Wave’s Qubits Asia conference in Seoul. LG CNS brings extensive mathematical optimization expertise across industries, including manufacturing and the public sector, with end-to-end capabilities spanning problem definition, mathematical modeling, algorithm validation, and real-world implementation. The company has also been conducting research on applying mathematical optimization and quantum computing to real-world industrial challenges, including image reconstruction and inspection and the detection of underground anomalies.
In related news, D-Wave reported that its customer Shionogi & Co., Ltd. won first place in the Quality of Life (QOL) category of the NEDO Challenge for research exploring the application of quantum computing to drug discovery. The award-winning research, conducted in collaboration with D-Wave, includes a peer-reviewed study published in Scientific Reports in July 2026. The study integrated D-Wave annealing quantum computing technology into a generative AI model for molecular design. The research found that 97% of molecular representations generated by the quantum-assisted model were chemically valid, compared with 73% using an equivalent classical model. The quantum-assisted model also generated a higher proportion of molecules with strong drug-likeness scores, exceeding both the classical model and the training dataset. Shionogi will receive a prize of 40 million yen to support continued research into applying quantum computing to drug discovery.
