Edgar Marrufo Villalpando went from Mexico to the United States and from computational physics to astronomical instrumentation to pursue his childhood dream of becoming a physicist.
Theoretical physicists use machine-learning algorithms to speed up difficult calculations and eliminate untenable theories—but could they transform what it means to make discoveries?
The Particle Physics Project Prioritization Panel recently recommended, among their top priorities for the next decade, moving forward with two experiments based at the South Pole.
The United Kingdom will eventually contribute three assembled cryomodules—known as HB650 for the radio frequency they use to operate—to Fermilab’s new particle accelerator.
In the culmination of a decade’s worth of effort, the DES collaboration of scientists analyzed an unprecedented sample of more than 1,500 supernovae classified using machine learning.
In Her Space, Her Time, physicist Shohini Ghose elucidates the stories of women scientists who contributed to and led some of the biggest breakthroughs in astronomy and physics.
Indirectly testing this theory, motivated by the mysterious mass of the Higgs boson, could be within reach for experiments at the Large Hadron Collider.
To build the DUNE neutrino experiment and its associated accelerator upgrade, experts invent customized ways to transport fragile, expensive and highly specialized components.
