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INT Online S@INT Seminar:  "From quarks to nuclei: machine learning the structure of matter"

Phiala Shanahan, MIT
Thursday, July 23, 2020 - 10:30am


With advances in supercomputing, we are beginning to quantitatively understand nuclear structure and interactions directly from the fundamental quark and gluon degrees of freedom of the Standard Model. Recent studies provide insight into the neutrino-nucleus interactions relevant to long-baseline neutrino experiments, double beta decay, and nuclear sigma terms needed for theory predictions of dark matter cross-sections at underground detectors. The rapid progress in this field has been possible because of new algorithms, but challenges still remain to achieve full systematic control. I will describe the physics challenges, and outline how new machine learning tools have the potential to provide a revolutionary way to enable currently-intractable calculations to reveal the physics of nuclei from the Standard Model.

 Zoom link will be available via announcement email, or by contacting: stroberg[at]

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