Intermediate mass black holes as targets for dark matter searches

Dark matter is a hypothetical form of matter that does not seem to interact with light and is only known to exist through its gravitational effects on visible matter. It is estimated that dark matter makes up about 85% of the matter in the Universe. Despite being the most abundant form of matter in the Universe, dark matter has not yet been directly observed. Intermediate mass black holes (IMBHs) are hypothesised to be surrounded by dense regions of dark matter known as dark matter spikes, where the annihilation of dark matter particles could produce detectable gamma rays. Ground-based gamma-ray observatories like H.E.S.S. and the upcoming Cherenkov Telescope Array Observatory (CTAO) are designed to detect such gamma rays. 

In his thesis, Jann Aschersleben investigated the application of pattern spectra, which represent 2D histograms of image features, to train convolutional neural networks (CNNs) for the analysis of CTAO data. While this approach reduced computational costs, it underperformed compared to direct image-based analyses, suggesting that key information is lost in the pattern spectra representation. Furthermore, Aschersleben determined a mock catalogue of IMBHs and their dark matter spikes obtained from the EAGLE cosmological simulations. An analysis shows that we can expect around 15 IMBHs in our galaxy, predominantly in the Galactic Centre and Plane. Aschersleben found that current and future gamma-ray observatories like H.E.S.S. and CTAO are sensitive enough to detect the potential gamma-ray signals from dark matter annihilation around IMBHs.

Read more: Studying the universe to understand the world

Dissertation: https://hdl.handle.net/11370/328836fb-2b3b-40f1-8b5b-30b8e87a4486