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Titre : Tensor networks for physics from counting: Ising models, ice, and dominoes
Résumé :
For more than a century, the Ising model’s universality has led to important insights in magnetism and even beyond physics. Its deceptively simple formulation hides a wealth of complex problems and rich physics, notably in frustrated magnetism.
In this talk, I will trace connections between Ising models, counting problems, and key historical ideas that inspired the development of tensor networks, a powerful family of numerical methods for classical and quantum many-body problems. I aim to provide a pedagogical introduction to tensor networks for statistical mechanics. I will conclude with some applications of these methods to questions from frustrated magnetism.
