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Simons Foundation

In this artist’s concept, a magnetar—a type of neutron star—is shown ejecting material into space, an event that would slow its rotation. The magnetar’s strong, twisted magnetic field lines (illustrated in green) shape the flow of electrically charged particles.

A Planet’s Worth of Gold: Magnetar Flares Forge Universe’s Heaviest Elements

Categories Physics & Mathematics, Space

A mosaic of simulations included in the Well collection of datasets.

AI Takes Scientific Cross-Training to New Heights with Massive Open Dataset

Categories Technology

An illustration of a quantum system that was simulated by both classical and quantum computers. The highlighted sections show how the influence of the system’s components is confined to nearby neighbors.

The surprising reason a classical computer beat a quantum computer at its own game

Categories Physics & Mathematics, Technology

Infographic describing how the Betelbuddy affects Betelgeuse's apparent brightness.

Betelgeuse, Betelgeuse: Mysterious Companion Key to Its Pulsing Brightness

Categories Physics & Mathematics, Space

An infographic showcasing the methodology behind the Simulation-Based Inference of Galaxies (SimBIG) project.

AI Unlocks Hidden Data to Refine Universe’s ‘Settings’

Categories Physics & Mathematics, Space

An illustration showing how electrons, which can have either an up or a down spin, can form a striped pattern in the Hubbard model. Recent breakthrough computations with this model are helping scientists better understand a class of high-temperature superconductors called cuprates.

Researchers Unveil Breakthrough in Understanding High-Temperature Superconductivity in Cuprates

Categories Physics & Mathematics

An infographic explaining the creation of a new map of around 1.3 million quasars from across the visible universe.

Astronomers Create Largest 3D Map of the Universe Using Bright Black Holes

Categories Physics & Mathematics, Space

A visualization of a mathematical apparatus used to capture the physics and behavior of electrons moving on a lattice. Each pixel represents a single interaction between two electrons. Until now, accurately capturing the system required around 100,000 equations — one for each pixel. Using machine learning, scientists reduced the problem to just four equations. That means a similar visualization for the compressed version would need just four pixels.

Artificial intelligence reduces a 100,000-equation quantum physics problem to just four equations

Categories Physics & Mathematics, Technology

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