Abstract
The study focuses on exploring the concept of negative entropy flow in cyclones and investigates the potential of applying quantum-inspired approaches to better understand and estimate the negentropy of these complex systems. By incorporating principles from quantum mechanics, such as the second law of thermodynamics and Gibbs energy, we aim to improve the accuracy of entropy predictions for cyclones. Classical methods for estimating entropy flow, such as Shannon entropy and von Neumann entropy, are examined, along with their limitations in capturing the complex dynamics of cyclonic systems. Additionally, the project utilizes the simulated annealing optimization method to explore the quantum aspects of entropy flow in cyclones. The objective is to provide insights into the negentropy of cyclones and its potential applications in weather forecasting. This project analyses data from two recent cyclones "Mocha" and "Biporjoy" and estimates their negentropy using the developed quantum-inspired algorithms. The findings contribute to a deeper understanding of the entropy dynamics in cyclones and showcase the potential of quantum-inspired techniques in weather forecasting and related fields.
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