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Machine Learning Solutions to the Yang Baxter Equation

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  • UserShailesh Lal (Beijing Institute of Mathematical Sciences and Applications)
  • ClockMonday 06 November 2023, 11:30-12:30
  • HouseExternal.

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BLHW02 - Machine learning toolkits and integrability techniques in gravity

We develop a novel neural network architecture, inspired in part by Siamese Networks, that learns solutions to the Yang Baxter equation for R matrices of difference form. This method already enables us to learn all solution classes of the 2d Yang Baxter equation. We propose and test paradigms for exploring the landscape of Yang Baxter equation solution space aided by these methods. Further, we shall also comment on the application of these methods to generating new solutions of the Yang Baxter equation. The talk is based on joint work with Suvajit Majumder and Evgeny Sobko available in part in arXiv:2304.07247.

This talk is part of the Isaac Newton Institute Seminar Series series.

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