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We propose an original approach to describe the scientific progress in aquantitative way. Using innovative Machine Learning techniques we create avector representation for the PACS codes and we use them to represent therelative movements of the various domains of Physics in a multi-dimensionalspace. This methodology unveils about 25 years of scientific trends, enables usto predict innovative couplings of fields, and illustrates how Nobel Prizepapers and APS milestones drive the future convergence of previously unrelatedfields.

Where is your field going? A Machine Learning approach to study the relative motion of the domains of Physics