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The prodigious amount of data produced at the Large Hadron Collider presents a major challenge for data analysis. Coffea, a Python package developed by Fermilab researchers, speeds up computation and helps scientists work more efficiently. Around a dozen international LHC research groups now use Coffea, which draws on big data techniques used outside physics.

Fermilab scientist and University of Chicago professor of astronomy and astrophysics Craig Hogan gives perspective on how the Holometer program aims at a tiny scale — the Planck scale — to help answer one of the universe’s most basic questions: Why does everything appear to happen at definite times and places? He contextualizes the results and offers optimism for future researchers.

NOvA far detector

The NOvA experiment, best known for its measurements of neutrino oscillations using particle beams from Fermilab accelerators, has been turning its attention to measurements of cosmic phenomena. In a series of results, NOvA reports on neutrinos from supernovae, gravitational-wave events from black hole mergers, muons from cosmic rays, and its search for the elusive monopole.

The international Deep Underground Neutrino Experiment collaboration has published a paper about its capability for performing supernova physics. It details the kind of activity DUNE expects in the detector during a supernova burst, how DUNE will know once a supernova occurs and what physics DUNE will extract from the neutrinos. DUNE’s unique strength is its sensitivity to a particular type of neutrino called the electron neutrino, which will provide scientists with supernova data not available from any other experiment.