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International Conference on Machine Learning for Astrophysics 2nd Ed. - ML4ASTRO2

8–12 Jul 2024
Catania
Europe/Rome timezone

ML4ASTRO SOC

Session

Cosmology & Simulations

10 Jul 2024, 09:00
Aula Magna (Catania)

Aula Magna

Catania

Università degli Studi di Catania - Dipartimento di Fisica e Astronomia Via S. Sofia, 64, 95123 Catania CT

Conveners

Cosmology & Simulations: I

  • Sebastian Trujillo

Presentation materials

There are no materials yet.

  1. 180. [INVITED] Cosmology in the machine learning era
    Francisco Villaescusa
    10/07/2024, 09:00
    Oral Presentation

    Recent advances in deep learning are triggering a revolution across fields. In this talk, I will discuss how we can apply these techniques to tackle complex problems in cosmology and astrophysics. I will first review how we can improve our understanding of fundamental physics by constraining the value of the cosmological parameters with the highest accuracy. After reviewing the standard...

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  2. 184. Inferring Galaxy Baryonic Properties from IllustrisTNG Dark Matter Merger Trees with Graph Neural Networks
    Nick Andreadis (Astronomical Observatory, Ghent University)
    10/07/2024, 09:40
    Oral Presentation

    As more and more data from recent and upcoming large cosmological surveys become available, the need for equally detailed theoretical models of galaxy formation, including large-volume cosmological simulations emerges. The complexity of such simulations, however, implies a great computational cost, which to this day always leads to a compromise in either resolution or size. As a supplement to...

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  3. 186. Recovering the CMB signal with neural networks
    Jose Manuel Casas
    10/07/2024, 10:00
    Oral Presentation

    Artificial neural networks are powerful machine learning models that can be trained to learn non-linear behaviors from data. In this talk, we present a new promising methodology for separating the CMB signal from foregrounds in Planck realistic simulations in temperature and polarization (formed by the CMB, Synchrotron and dust Galactic emissions, PS and thermal SZ extragalactic emissions and...

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  4. 188. EMBER: emulating baryons from dark matter-only simulations over cosmic time
    Mauro Bernardini (University of Zurich)
    10/07/2024, 10:20
    Oral Presentation

    Galaxy formation is fueled by inflowing gas from the cosmic web. While on cosmological scales the gas distribution traces the dark matter, the relation between gas abundances and matter decouples at galactic scales and transitions into a highly non-linear regime due to the complex interplay of various astrophysical processes.

    Hydrodynamical simulations are currently the most accurate tool...

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