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University of Cambridge > Talks.cam > Isaac Newton Institute Seminar Series > Machine Learning Integrability in 1D and 2D Models of Gravity
Machine Learning Integrability in 1D and 2D Models of GravityAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact nobody. BLHW02 - Machine learning toolkits and integrability techniques in gravity We construct deformed Breitenlohner-Maison linear systems to demonstrate the integrability of a class of 4D solutions of gravity coupled to U(1) gauge fields and neutral scalars subject to a scalar potential. These solutions also admit a 1D description. We cast the problem of writing a Lax pair for the 1D system in an ML amenable form. Consquently, we have generated numerical Lax pairs, which hint at the existence of a Lax pair rewriting, complementary to the deformed BM system. Joint work with G. Lopes Cardoso and S. Nampuri. This talk is part of the Isaac Newton Institute Seminar Series series. This talk is included in these lists:
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