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Quantum annealing is a cutting-edge computational approach designed to tackle complex optimization problems by leveraging principles of quantum mechanics, such as superposition and tunnelling.
In the first part of this presentation, I will provide an overview of quantum annealing, focusing on its underlying principles, advantages over classical methods, and ability to explore vast solution spaces efficiently.
In the second part, I will show the practical application of quantum annealing in biomechanics, specifically in estimating muscular activation patterns of the elbow during flexion-extension movements. This problem involves resolving muscle redundancy, where multiple muscle activators can achieve the same motion by minimizing a cost function that reflects metabolic efficiency.
Quantum annealing offers the opportunity to explore efficiently the solution space, potentially uncovering insights into normal and pathological muscle behaviours that are challenging to address with classical methods. This exploratory approach highlights the potential of quantum computing to develop practical solutions in biomechanics.