Hunting anomalies with an AI trigger
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.
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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.
The workshop attracted more than 300 participants from 45 countries to discuss how the lessons learned in the past two years might help HEP transition to a more sustainable future.
Launched in February 2019, the European Union project ESCAPE is making strides towards an open scientific analysis infrastructure for particle physics and astronomy.
Accelerator physicist and science communicator Suzie Sheehy discusses her work, her new book, and how to increase the appeal of a research career.
The question of making research data findable, accessible, interoperable and reusable is a burning one throughout modern science.
The TOOLS 2020 conference attracted around 200 phenomenologists and experimental physicists to work on numerical tools for dark-matter models, and more.
CERN technologies and expertise are helping in the collective global fight against COVID-19.
Barry Barish speaks to the Courier about his role in turning LIGO into a Nobel Prize-winning machine.
John Ellis reflects on 50 years at the forefront of theoretical high-energy physics - and whether the field is ripe for a paradigm shift.