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·인용수 0
·2026
Harnessing Quantum Computing for Energy Materials: Opportunities and Challenges
Seongmin Kim, In-Saeng Suh, Travis S. Humble, Thomas Beck, eungkyu lee, Tengfei Luo
arXiv (Cornell University)
초록

Developing high-performance materials is critical for diverse energy applications to increase efficiency, improve sustainability and reduce costs. Classical computational methods have enabled important breakthroughs in energy materials development, but they face scaling and time-complexity limitations, particularly for high-dimensional or strongly correlated material systems. Quantum computing (QC) promises to offer a paradigm shift by exploiting quantum bits with their superposition and entanglement to address challenging problems intractable for classical approaches. This perspective discusses the opportunities in leveraging QC to advance energy materials research and the challenges QC faces in solving complex and high-dimensional problems. We present cases on how QC, when combined with classical computing methods, can be used for the design and simulation of practical energy materials. We also outline the outlook for error-corrected, fault-tolerant QC capable of achieving predictive accuracy and quantum advantage for complex material systems.

키워드
Quantum entanglementQuantum computerPerspective (graphical)QuantumEnergy (signal processing)Superposition principleScalingEfficient energy use
타입
preprint
IF / 인용수
- / 0
게재 연도
2026