Argonne Physics Seminar: Daniel Hackett, Fermi National Accelerator Laboratory
- When:
- Monday, March 25, 2024 3:30 pm - 4:30 pm
- Where:
- Argonne National Laboratory, Building 203, Room R-150, 9700 S. Cass Ave., Lemont, IL 60439 and Virtual
- Speaker:
- Daniel Hackett, Fermi National Accelerator Laboratory
- Title:
- Applications of machine-learned flows to lattice QCD events section menu
- Description:
-
Numerical lattice quantum field theory is one of our important tools for investigating quantum chromodynamics (QCD), but what physics may be treated is limited by presently available computing resources. Recent work suggests that machine learning techniques may provide algorithmic advances that could open access to calculations which are presently intractable. In particular, normalizing flows are machine-learned maps between different lattice theories which can be used as components in exact sampling and inference schemes. Ongoing work yields increasingly expressive flows on gauge fields, but it remains an open question how flows can best be used to improve lattice QCD at state-of-the-art scales. This talk will review this effort and discuss recent progress, in particular several applications which are viable with presently available flows.