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Article | High Energy Physics Division

Two HEP Projects Selected for Aurora Early Science Program

Argonne has selected projects from High Energy Physics (HEP) researchers Salman Habib and James Proudfoot for the Aurora Early Science Program at the Argonne Leadership Computing Facility (ALCF).

The ALCF is the U.S. Department of Energy (DOE) Office of Science User Facility slated to become home to Aurora, the nation’s first exascale system, in 2021.

The HEP projects are two of only 10 projects selected from universities and national laboratories across the country. Early Science Program projects will help the ALCF prepare key applications, libraries, and infrastructure for the architecture and scale of the exascale supercomputer.

ALCF staff will help teams port and optimize their applications for the new architecture using systems available today and early Aurora hardware when it is available.

Synthetic galaxy catalog generated from a large-scale cosmological simulation run with the HACC code. The Dark Sky Mining project will use state of the art forward modeling and machine learning techniques to extract cosmological information using joint analysis of simulated sky maps and observations

Dark Sky Mining

Salman Habib, Argonne National Laboratory

This project will connect some of the world’s largest and most detailed extreme-scale cosmological simulations with large-scale data obtained from the Large Synoptic Survey Telescope, the most comprehensive observations of the visible sky. By implementing cutting-edge data-intensive and machine learning techniques, it will usher in a new era of cosmological inference targeted at scientific breakthroughs.

Simulating and Learning in the ATLAS Detector at the Exascale

James Proudfoot, Argonne National Laboratory

The ATLAS experiment at the Large Hadron Collider measures particles produced in proton-proton collision as if it were an extraordinarily rapid camera. These measurements led to the discovery of the Higgs boson, but hundreds of petabytes of data still remain unexamined, and the experiment’s computational needs will grow by an order of magnitude or more over the next decade. This project deploys necessary workflows and updates algorithms for exascale machines, preparing Aurora for effective use in the search for new physics.