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Deep learning in color: towards automated quark/gluon jet discrimination
Patrick T. Komiske, Eric M. Metodiev, Matthew D. Schwartz
Artificial intelligence offers the potential to automate challenging data-processing tasks in collider physics. To establish its prospects, we explore to what extent deep learning…
Precision direct photon spectra at high energy and comparison to the 8 TeV ATLAS data
Matthew D. Schwartz
The direct photon spectrum is computed to the highest currently available precision and compared to ATLAS data from 8 TeV collisions at the LHC. The prediction includes threshold r…
Precision decay rate calculations in quantum field theory
Anders Andreassen, David Farhi, William Frost +1
Tunneling in quantum field theory is worth understanding properly, not least because it controls the long term fate of our universe. There are however, a number of features of tunn…
Precision physics with pile-up insensitive observables
Christopher Frye, Andrew J. Larkoski, Matthew D. Schwartz +1
To deepen the search for beyond the Standard Model physics, the Large Hadron Collider is pushing to higher and higher luminosity. At high luminosity, precision physics becomes incr…
Factorization for groomed jet substructure beyond the next-to-leading logarithm
Christopher Frye, Andrew J. Larkoski, Matthew D. Schwartz +1
Jet grooming algorithms are widely used in experimental analyses at hadron colliders to remove contaminating radiation from within jets. While the algorithms perform a great servic…
A direct approach to quantum tunneling
Anders Andreassen, David Farhi, William Frost +1
The decay rates of quasistable states in quantum field theories are usually calculated using instanton methods. Standard derivations of these methods rely in a crucial way upon def…