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Hong Kong University and Beijing Normal University Study Ultralight Dark Matter

Researchers from the University of Hong Kong and Beijing Normal University have developed a novel approach to simulate ultralight dark matter. Their study predicts, for the first time, how this matter influences gravitational lensing images.

24 September 2026
Hong Kong University and Beijing Normal University Study Ultralight Dark Matter
Image is an AI-generated illustration

Researchers from the University of Hong Kong's physics and astronomy departments, in collaboration with a team from Beijing Normal University, have proposed a more physically realistic method for examining the effects of ultralight dark matter on gravitational lensing images using three-dimensional wave simulations.

This marks the first direct prediction of ultralight dark matter's impact on gravitational lensing imagery based on 3D wave simulations. The research provides a new methodology for studying dark matter properties through high-resolution gravitational lensing observations, with findings published in The Astrophysical Journal Letters.

Dark matter is estimated to constitute about 85% of the universe's matter. It does not emit, absorb, or reflect light and is only detectable through its gravitational effects. Over the past decade, increasing astronomical evidence has suggested that dark matter may be composed of ultralight particles, often referred to as "fuzzy dark matter" due to their extremely low mass and wave-like collective behavior.

The research team compared their simulation results with a widely studied set of quasar gravitational lensing observations. Their models, based on the wave-like interactions of ultralight dark matter, reproduced the positions of lensed images more accurately than the comparative models used in the study. This suggests that gravitational lensing systems could serve as a tool to test ultralight dark matter models. Future work will investigate whether this type of dark matter also causes brightness variations between multiple lensed images.

Original source: ithome.com