How an astrophysicist uses Codex to help simulate black holes
Astrophysicist Chi-kwan Chan is using OpenAI's Codex to develop and test algorithms that simulate the extreme physics surrounding black holes. By helping derive mathematical approaches to model plasma behavior, Codex allows researchers to bypass decades-old computing bottlenecks. The work aims to support ongoing studies by the Event Horizon Telescope collaboration.
The Core Development
The gravity around a black hole is so extreme that nothing, not even light, can escape once it gets close enough. Astrophysicists like Chi-kwan Chan study black holes with computer simulations and observations. But current algorithms and computing power limit how realistic those simulations can be.
With Codex, Chan—a researcher at the University of Arizona and Steward Observatory—is tackling this problem.
Black holes are among the best places to test Einstein’s general theory of relativity, he said. The theory is currently our best explanation of gravity: instead of a force pulling objects together, gravity is the result of mass and energy bending the fabric of space and time.
Strategic Perspective & Ecosystem Impact
Chan is part of the international Event Horizon Telescope (EHT) collaboration, which published the first image of a black hole in 2019. The team is currently gathering observations to produce the first video of a supermassive black hole, focusing on the one at the center of the M87 galaxy.
But turning observations into scientific understanding requires enormous amounts of data processing, large-scale computing workflows, and simulations capable of modeling some of the most extreme physics in the universe.
Since light can’t escape a black hole, scientists instead study the region around it called the event horizon, a boundary beyond which matter can’t escape. “It’s a surface of no return,” said Chan. Matter swirling just outside this boundary emits light that astrophysicists can see, measure, and simulate.
Why it matters
The application highlights how large language models can assist in specialized scientific research by accelerating algorithm development and hypothesis generation while relying on rigorous human verification.