Quantum Machine Learning Applications to Address Climate Change
Sagar Lachure, Ashwin Lohidasan, Ashish Tiwari +2 more
In the previous three to four decades, numerical weather and climate modelling have advanced significantly, yet many challenges still exist. Appropriate adaptation techniques to reduce loss of life and property require geographically and temporally targeted predictions. Artificial Intelligence and machine learning (AI and ML) based technologies are improving predictions. However, they are bound by the absence of a hardware's or a software's—or both—capable of handling the enormous data volumes created on a global basis. The burgeoning paradigm of quantum computing (QC) has potential applications across many industries. This review shows that the current progress in quantum ML for quantum computers may lead to technological advancements in climate change research. The subsequent climate forecasting improvements are expected to have several socioeconomic benefits. The authors have also provided three or four examples showing how quantum technology might be used with ML systems to study climate change.
Advances in systems analysis, software engineering, and high performance computing book series•Mar 3, 2023•4 citations