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Field-Level Inference: Unlocking the Full Potential of Galaxy Maps to Explore New Physics

Galaxies are not islands in the cosmos. While globally the universe expands – driven by the mysterious ‘dark energy’ – locally, galaxies cluster through gravitational interactions, forming the cosmic web held together by dark matter’s gravity. For cosmologists, galaxies are test particles to study gravity, dark matter and dark energy. For the first time, MPA researchers and alumni have now used a novel method that fully exploits all information in galaxy maps and applied it to simulated but realistic datasets. Their study demonstrates that this new method will provide a much more stringent test of the cosmological standard model, and has the potential to shed new light on gravity and the dark universe. more

Explaining the density profiles of dark matter halos with neural networks

Can machine learning make new discoveries in astrophysics? An ‘explainable’ neural network is employed to get insights into the origin of dark matter halo density profiles. The network discovers that the shape of the profile in the halo outskirts is described by a single parameter related to the most recent accretion of mass. This is done without prior knowledge of the halo’s evolution history being provided during training.
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Understanding the cosmic web: Unveiling the evolution of cosmic filaments with the MillenniumTNG simulation

A careful analysis of the filaments in the cosmic large-scale structure has revealed interesting new findings about the evolution and complexities of the cosmic web. While some filaments show a significant evolution – depending on their cosmic environment – global filament properties are preserved, which could be used in future cosmological studies. The MPA team also developed a new method to allow for rigorous calibration of the filament catalogues.
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<span><span><span><span>Unveiling the Universe at the field level</span></span></span></span>

The distribution of galaxies on large, cosmological scales holds important clues on the nature of dark matter, the properties of dark energy and the origin of our Universe. Yet, optimally retrieving this information from observations is challenging. MPA researchers are developing a novel analysis approach, where they follow the evolution of cosmic structures through their entire formation history. Enabling a very detailed comparison between theoretical models and observational data, this approach will allow measuring key parameters of dark matter and dark energy very precisely. more

Maria Werhahn honoured with the Carl Ramsauer Prize

MPA postdoc Maria Werhahn has been awarded the Carl Ramsauer Prize by the Physikalische Gesellschaft zu Berlin for her doctoral thesis “Simulating Galaxy Evolution with Cosmic Rays: The Multi-Frequency View”. The award ceremony took place on 22 November 2023 at the Technical University of Berlin, where she also presented her work in a short lecture. more

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