Eungkyu Lee

1 month ago | nature.com | SeongMin Kim |In-Saeng Suh |Alexander W. Dowling |Eungkyu Lee |Sang-Woo Ahn

AbstractQuantum annealing (QA) has the potential to significantly improve solution quality and reduce time complexity in solving combinatorial optimization problems compared to classical optimization methods. However, due to the limited number of qubits and their connectivity, the QA hardware did not show such an advantage over classical methods in past benchmarking studies.

Jan 6, 2025 | nature.com | Zhihao Xu |SeongMin Kim |Eungkyu Lee

AbstractHigh Entropy Alloys (HEAs) have drawn great interest due to their exceptional properties compared to conventional materials. The configuration of HEA system is considered a key to their superior properties, but exhausting all possible configurations of atom coordinates and species to find the ground energy state is extremely challenging.

Nov 12, 2024 | nature.com | Zhihao Xu |SeongMin Kim |Eungkyu Lee

AbstractQuantum algorithms are emerging tools in the design of functional materials due to their powerful solution space search capability. How to balance the high price of quantum computing resources and the growing computing needs has become an urgent problem to be solved. We propose a novel optimization strategy based on an active learning scheme that combines the Quantum-inspired Genetic Algorithm (QGA) with machine learning surrogate model regression.