Physicists at the Perimeter Institute have developed a novel simulation method to study self-interacting dark matter, a type of dark matter that collides with itself but not with ordinary matter, potentially triggering dramatic collapses within dark matter halos. This research, unveiled on January 19, 2026, offers new insights into how these collisions could heat and densify the cores of dark matter halos, influencing galaxy formation and potentially seeding black holes.

The new simulation code addresses a significant challenge in cosmological modeling: accurately representing the behavior of self-interacting dark matter. Previously, simulating this "crucial middle ground" of behavior was computationally prohibitive. The new code is designed for speed and precision, making it accessible enough to run on a standard laptop, according to researchers.

Dark matter, an invisible substance that makes up a significant portion of the universe's mass, has been a subject of intense scientific inquiry for nearly a century. Its existence is inferred from its gravitational effects on visible matter, shaping galaxies and the large-scale structure of the cosmos. While its presence is well-established, the precise nature of dark matter remains a mystery.

The self-interacting dark matter model proposes that dark matter particles can collide with each other, unlike the more commonly studied "cold dark matter" model, which assumes dark matter particles interact weakly, if at all. These collisions can redistribute energy within dark matter halos, the vast, diffuse structures that surround galaxies.

According to the researchers, the collapse of dark matter halos, driven by self-interactions, could have profound implications for galaxy formation. The heating and densification of halo cores could influence the distribution of stars within galaxies and potentially lead to the formation of supermassive black holes at their centers.

The development of this new simulation tool represents a significant step forward in understanding the complex dynamics of dark matter. By providing a more accurate and efficient way to model self-interacting dark matter, the researchers hope to shed light on the fundamental properties of this elusive substance and its role in shaping the universe. The team plans to use the code to explore a wider range of self-interaction scenarios and compare the simulation results with observational data from telescopes and other astronomical instruments. This comparison will help to refine the model and potentially identify the specific type of self-interacting dark matter that best matches the observed structure of the universe.