In this talk, I will give an overview of how to do field-level likelihood-free inference with galaxies catalogs. More specifically, only using galaxy phase-space information, not imposing a scale cutoff, I will show how to convert these into graphs. Also, I will briefly explain how to use graph neural networks to infer the Omega matter of these simulations. I will show that the model is robust across 5 different hydrodynamic simulations (Astrid, IllustrisTNG, SIMBA, Magneticum, and SWIFT-EAGLE), i.e., 5 different sub-grid physics models, being one of the first able to do this task.

Extracting information from stochastic fields is a ubiquitous task in science. However, from cosmology to biology, it tends to be done either through a power spectrum analysis, which is often too limited, or recently the use of convolutional neural networks, which require large training sets and lack interpretability. I will present a new powerful tool called the “scattering transform”, which borrows ideas from both sides and stands nicely between the two extremes.

Strong gravitational lensing by galaxies provides us with a powerful laboratory for testing dark matter models. Various particle models for dark matter give rise to different small-scale distributions of mass in the lens galaxy, which can be differentiated if the observation is sensitive enough.  The sensitivity of a gravitational lens observation to the presence (or absence) of low-mass dark structures in the lens galaxy is determined mainly by the angular resolution of the instrument and the spatial structure of the source.

Intergalactic Medium (IGM)-based cosmology established itself as a powerful cosmological probe at high redshift (z >2) with the wide success of the SDSS-III Baryon Oscillation Spectroscopic Survey (BOSS), followed by the extended BOSS (eBOSS). The ongoing Dark Energy Spectroscopic Instrument (DESI) survey, now in its second year of operation, offers an opportunity to review the achievements of SDSS-III and put in context the progress that is underway with DESI. I will give an overview of Lyman-alpha forest early results from DESI and discuss what comes next.

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I will discuss recent and ongoing work focused on attempts to restore concordance amongst cosmological data sets, motivated by discrepancies between some measurements of the cosmic expansion rate (H_0) and the matter clustering amplitude (S_8). Particular attention will be paid to models invoking new physics in the high-redshift universe, including quasi-accelerating early dark energy models (and extensions thereof, featuring EDE-dark matter interactions) and generalized decaying particle scenarios.

Lokken:

The ongoing merger of the Milky Way and the Large Magellanic Cloud (LMC) is deforming the dark matter haloes of both galaxies, effectively making these galaxies a local dark matter collider. With stellar streams being sensitive to the gravitational potential, the Orphan-Chenab (OC) stream is particularly insightful as it spans the inner and outer Milky Way, and it passes close to the LMC. I will present the first models of the OC stream in time-dependent halos of the Milky Way and the LMC that are described by basis function expansions of N-body simulations of the Milky Way-LMC passage.