Leaders in artificial-intelligence research spoke to the Courier about what's next for the field, and how developments may impact fundamental science.
Jennifer Ngadiuba and Maurizio Pierini describe how ‘unsupervised’ machine learning could keep watch for signs of new physics at the LHC that have not yet been dreamt up by physicists.
The LHC Olympics and Dark Machines data challenges stimulated innovation in the use of machine learning to search for new physics, write Benjamin Nachman and Melissa van Beekveld.
Artificial-intelligence techniques have been used in experimental particle physics for 30 years, and are becoming increasingly widespread in theoretical physics. Anima Anandkumar and John Ellis explor...
The workshop explored new perturbative results and methods in quantum field theory, collider physics and gravity.
The 25th International Conference on Computing in High-Energy and Nuclear Physics gathered more than 1000 participants online across 20 time zones, from Brisbane to Honolulu.
The CMS collaboration, in partnership with the Geneva-based Sharing Knowledge Foundation, has launched a fundraising initiative to support the Lebanese scientific community during an especially diffic...
To confidently discover new physics in the muon g−2 anomaly requires that data-driven and lattice-QCD calculations of the Standard-Model value agree, write Thomas Blum, Luchang Jin and Christoph Leh...
The TOOLS 2020 conference attracted around 200 phenomenologists and experimental physicists to work on numerical tools for dark-matter models, and more.
The new collaboration will work to realise the full potential of the coming generation of high-performance computing technology for data-intensive science.