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Quantum Machine Learning Applications to Address Climate Change: A Short Review
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Author(s): Sagar Suraj Lachure (Visvesvaraya National Institute of Technology, India), Ashwin Lohidasan (Visvesvaraya National Institute of Technology, India), Ashish Tiwari (Visvesvaraya National Institute of Technology, India), Meera Dhabu (Visvesvaraya National Institute of Technology, India)and Neeraj Dhanraj Bokde (Aarhus University, Denmark)
Copyright: 2023
Pages: 19
Source title:
Handbook of Research on Quantum Computing for Smart Environments
Source Author(s)/Editor(s): Amit Kumar Tyagi (National Institute of Fashion Technology, New Delhi, India)
DOI: 10.4018/978-1-6684-6697-1.ch004
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Abstract
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.
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