Astrophysicist Chi-kwan Chan is using artificial intelligence to tackle one of physics' most stubborn puzzles: what really happens at the edge of a black hole. His tool of choice is Codex, an AI system that helps him write and refine the complex code needed to simulate the warping of space and time around these cosmic monsters.
Chan's simulations let researchers test whether Einstein's theory of general relativity holds up under the most extreme conditions the universe can produce. Black holes compress matter so densely that normal physics breaks down, making them perfect laboratories for pushing Einstein's century-old framework to its limits.
The traditional way to build these simulations is punishing: scientists spend weeks writing thousands of lines of code to describe gravitational forces, spacetime curvature, and radiation emissions near the event horizon. Codex accelerates the process by understanding what Chan is trying to compute and suggesting optimized code, catching bugs, and helping him work through the mathematical logic faster.
This hybrid approach, where a physicist partners with an AI assistant, reveals something important about how science evolves. Rather than replacing human insight, Codex handles the grinding mechanical work of translation, letting Chan focus on the physics itself. His simulations feed into efforts to understand how black holes actually behave in nature, complementing observational data from telescopes and gravitational wave detectors.
The payoff extends beyond pure research. Better models of black hole physics could eventually improve our understanding of gravity itself and how it connects to quantum mechanics, one of the deepest unsolved problems in science.
Author Emily Chen: "Using AI to speed up physics code is smart pragmatism, but it only works because Chan knows exactly what he's asking for."
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