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Curiouser and curiouser: a riddle at the ALICE detector

12/09/25

Sarah Charley

In 2023, the ALICE experiment was ready for their best year yet, until a mysterious signal threatened everything. As the LHC prepares to start its 2025 lead-ion run, physicists recall how they worked together to solve the puzzle.

06/26/24

John Bahcall: Godfather of solar neutrinos

Bahcall’s scientific legacy is visible across the field of astrophysics

Illustration of billiard balls on a cosmic pool table

06/18/24

Scaling up the dark matter search

Physicists are preparing for the next generation of dark-matter experiments.

Illustration of Raphael Granier De Cassagnac

05/28/24

The physicist gamer

Raphael Granier De Cassagnac recently put his scientific skills to use creating a physics-themed video game.

The shipping crate holding the LSST Camera is transported the final 35 kilometers (21.7 miles) up the winding dirt road to the observatory on the summit of Cerro Pachón.

05/22/24

LSST Camera arrives at Rubin Observatory in Chile

The largest camera ever built for astrophysics has completed the long journey from SLAC National Accelerator Laboratory in California to the summit of Cerro Pachón in Chile.

Illustration: A student scientist embroiders their graduation cap with atom

05/07/24

Tomorrow’s physics test: machine learning

Machine learning is becoming an essential part of a physicist’s toolkit. How should new students learn to use it?

Illustration of a scientist cutting a piece of bias tape with scissors

05/06/24

A physicists’ guide to the ethics of artificial intelligence

Physics may seem like its own world, but different sectors using machine learning are all part of the same universe.

Illustration of a scientist pinpointing part of a galaxy through the lens of a magnifying glass

05/01/24

AI for control rooms

Scientists inside and outside of particle physics and astrophysics are leaning on AI for assistance with complex tasks.

Illustration of someone embroidering a particle collision

04/30/24

Machine learning and theory

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?

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