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Recently, the option to use large language models as a middleware connecting various AI tools and other large language models led to the development of so-called large multimodal foundation models, which have the power to process spoken text, music, images and videos. In this overview, we explain a new set of opportunities and challenges that arise from the integration of large multimodal foundation models in education.

In this paper we investigate the potential of current and upcoming cosmological surveys to constrain the mass and abundance of ultra-light axion (ULA) cosmologies with galaxy cluster number counts. ULAs, sometimes also referred to as Fuzzy Dark Matter, are well-motivated in many theories beyond the Standard Model and could potentially solve the \\(\\Lambda\\)CDM small-scale crisis. Galaxy cluster counts provide a robust probe of the formation of structures in the Universe. Their distribution in mass and redshift is strongly sensitive to the underlying linear matter perturbations. In this forecast paper we explore two scenarios, firstly an exclusion limit on axion mass given a no-axion model and secondly constraints on an axion model. With this we obtain lower limits on the ULA mass on the order of \\(m_a \\gtrsim 10^{-24}\\) eV. However, this result depends heavily on the mass of the smallest reliably observable clusters for a given survey. Cluster counts, like many other cosmological probes, display an approximate degeneracy in the ULA mass vs. abundance parameter space, which is dependent on the characteristics of the probe. These degeneracies are different for other cosmological probes. Hence galaxy cluster counts might provide a complementary window on the properties of ultra-light axions.

With several examples and in an analysis of the Pantheon+ supernova sample we discuss the properties of the marginal posterior distribution versus the profiled posterior distribution -- the profile likelihood in a Bayesian disguise. We investigate whether maximisation, as used for the profiling, or integration, as used for the marginalisation, is more appropriate. To report results we recommend the marginal posterior distribution.

We review some of the common methods for model selection: the goodness of fit, the likelihood ratio test, Bayesian model selection using Bayes factors, and the classical as well as the Bayesian information theoretic approaches. We illustrate these different approaches by comparing models for the expansion history of the Universe. In the discussion we highlight the premises and objectives entering these different approaches to model selection and finally recommend the information theoretic approach.

We present the first nonlinear lattice simulation of an axion field coupled to a U(1) gauge field during inflation. We use it to fully characterize the statistics of the primordial curvature perturbation {\\zeta}. We find high-order statistics to be essential in describing non-Gaussianity of {\\zeta} in the linear regime of the theory. On the contrary, non-Gaussianity is suppressed when the dynamics becomes nonlinear. This relaxes bounds from overproduction of primordial black holes, allowing for an observable gravitational waves signal at pulsar timing array and interferometers scales. Our work establishes lattice simulations as a crucial tool to study the inflationary epoch and its predictions.

We use the Magneticum suite of state-of-the-art hydrodynamical simulations to identify cosmic voids based on the watershed technique and investigate their most fundamental properties across different resolutions in mass and scale. This encompasses the distributions of void sizes, shapes, and content, as well as their radial density and velocity profiles traced by the distribution of cold dark matter particles and halos. We also study the impact of various tracer properties, such as their sparsity and mass, and the influence of void merging on these summary statistics. Our results reveal that all of the analyzed void properties are physically related to each other and describe universal characteristics that are largely independent of tracer type and resolution. Most notably, we find that the motion of tracers around void centers is perfectly consistent with linear dynamics, both for individual, as well as stacked voids. Despite the large range of scales accessible in our simulations, we are unable to identify the occurrence of nonlinear dynamics even inside voids of only a few Mpc in size. This suggests voids to be among the most pristine probes of cosmology down to scales that are commonly referred to as highly nonlinear in the field of large-scale structure.

Ghost-free bimetric theory describes two nonlinearly interacting spin-2 fields, one massive and one massless, thus extending general relativity. We confront bimetric theory with observations of Supernovae type 1a, Baryon Acoustic Oscillations and the Cosmic Microwave Background in a statistical analysis, utilising the recently proposed physical parametrisation. This directly constrains the physical parameters of the theory, such as the mass of the spin-2 field and its coupling to matter. We find that all models under consideration are in agreement with the data. Next, we compare these results to bounds from local tests of gravity. Our analysis reveals that all two- and three-parameter models are observationally consistent with both cosmological and local tests of gravity. The minimal bimetric model (only \\(\\beta_1\\)) is ruled out by our combined analysis.

We use a lattice simulation to study a model of axion inflation where the inflaton is coupled to a U(1) gauge field through Chern-Simons interaction. These kinds of models have already been studied with a lattice simulation in the context of reheating. In this work, we focus on the deep inflationary phase and discuss the new aspects that need to be considered in order to simulate gauge fields in this regime. Our main result is reproducing with precision the growth of the gauge field on the lattice induced by the rolling of the axion on its potential, thus recovering the results of linear perturbation theory for this model. In order to do so, we study in detail how the spatial discretization, through the choice of the spatial derivatives on the lattice, influences the dynamics of the gauge field. We find that the evolution of the gauge field is highly sensitive to the choice of the spatial discretization scheme. Nevertheless, we are able to identify a discretization scheme for which the growth of the gauge field on the lattice reproduces the one of continuous space with good precision.

Bimetric theory describes a massless and a massive spin-2 field with fully non-linear (self-)interactions. It has a rich phenomenology and has been successfully tested with several data sets. However, the observational constraints have not been combined in a consistent framework, yet. We propose a parametrization of bimetric solutions in terms of the effective cosmological constant \\(\\Lambda\\) and the mass \\(m_\\mathrm{FP}\\) of the spin-2 field as well as its coupling strength to ordinary matter \\(\\bar\\alpha\\). This simplifies choosing priors in statistical analysis and allows to directly constrain these parameters with observational data not only from local systems but also from cosmology. By identifying the physical vacuum of bimetric theory these parameters are uniquely determined. We work out the dictionary for the new parametrization for various submodels and present the implied consistency constraints on the physical parameter space. We then apply the dictionary to derive observational constraints from SN1a on the physical parameters. As a result we find that even self-accelerating models with a heavy spin-2 field are in perfect agreement with current supernova data.

In this work we revisit five different point sources within or behind galaxy clusters in order to constrain the coupling constant between axion-like particles (ALPs) and photons. We use three distinct machine learning (ML) techniques and compare our results with a standard \\(\\chi^2\\) analysis. For the first time we apply approximate Bayesian computation to searches for ALPs and find consistently good performance across ML classifiers. Further, we apply more realistic 3D magnetic field simulations of galaxy clusters and compare our results with previously used 1D simulations. We find constraints on the ALP-photon coupling at the level of state-of-the-art bounds with \\(g_{a\\gamma\\gamma} \\lesssim 0.6 \\times 10^{-12}\\) GeV\\({}^{-1}\\), hence improving on previous constraints obtained from the same observations.