SOURCE-LINKED INTELLIGENCE

High energy Intelligence

CORDIS · observation · Publication date unknown

ng of QCD physics, by obtaining the most refined partonic distribution functions of quarks and gluons in nuclear matter. A third objective, timely and novel in the proposed approach, is to combine an Artificial Intelligence and Machine Learning training with cutting-edge research in theoretical physics, having in mind neural networks designs that can be trained on partial data sets, and at the same time, solve the non-perturbative constraint equations coming from theory. The HeI project, for the first time, brings together many scientists working on related aspects of high-energy physics but with different areas of specializations, to make a collaborative scientific breakthrough, through secondments to leading research institutes in Brazil, Canada, Switzerland, and the Jefferson Laboratories. Quantum field theories; Effective Field Theories of QCD; Factorization and RG; Parton Distributions; CFT; S-matrix; Integrable Field Theories; Supersymmetric Theories;

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recordType

award

status

SIGNED

region

EU

value

671600

unit

EUR