Proton structure

Unravelling Proton Structure with Hyperoptimised Machine Learning

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At energy-frontier facilities such as the Large Hadron Collider, scientists study the laws of Nature in their quest for novel phenomena both within and beyond the Standard Model of particle physics. An in-depth understanding of the quark and gluon substructure of protons and heavy nuclei is crucial to address pressing questions from the nature of the Higgs boson to the origin of cosmic neutrinos. In this project we will tackle long-standing puzzles in our understanding of the strong interactions, from the origin of the proton spin to the strange content of nucleons. The key to achieve this will be the first-ever universal analysis of nucleon structure from the simultaneous determination of the momentum and spin distributions of quarks and gluons and their fragmentation into hadrons. We will combine an extensive experimental dataset and cutting-edge theory calculations within a machine learning framework where neural networks parametrise the underlying physical laws while minimizing ad-hoc model assumptions. Given that computing resources represent the major bottleneck in this ambitious research program, it will be crucial to optimize the model training by exploiting GPUs. Further, the exploration of the resulting complex parameter space demands an algorithmic strategy to determine the model hyperparameters such as network architectures.

Participating organisations

Netherlands eScience Center
Vrije Universiteit Amsterdam
Natural Sciences & Engineering
Natural Sciences & Engineering

Team

JR
Juan Rojo
Principal investigator
Vrije Universiteit Amsterdam
TR
Tanjona Radonirina Rabemananjara
Postdoctoral researcher
Vrije Universiteit Amsterdam
Alessio Sclocco
eScience Research Engineer
Netherlands eScience Center
Aron Jansen
Aron Jansen
eScience Research Engineer
Netherlands eScience Center
Gijs van den Oord
Gijs van den Oord
Senior RSE
Netherlands eScience Center
Merijn Verstraaten
Merijn Verstraaten
Rena Bakhshi
Rena Bakhshi
Programme Manager
Netherlands eScience Center
Elena Ranguelova
Elena Ranguelova
Tech Lead
Netherlands eScience Center
Carlos M. R. Rocha
Carlos M. R. Rocha
Lead RSE
Netherlands eScience Center

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Updated 19 months ago
In progress