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Simulation-based Bayesian inference (SBI) methods are widely used for parameter estimation in complex models where evaluating the likelihood is challenging but generating simulations is relatively straightforward. However, these methods…
Understanding the source of the universe's asymmetry between matter and antimatter is one of the major open questions in particle physics. In this work, the sensitivity of novel machine-learning-based inference techniques to CP-odd and…
We trace the formation and advection of several elements within a cosmological adaptive mesh refinement simulation of an L* galaxy. We use nine realisations of the same initial conditions with different stellar Initial Mass Functions…
Chemical abundances and abundance ratios measured in galaxies provide precious information about the mechanisms, modes and time scales of the assembly of cosmic structures. Yet, the nucleogenesis and chemical evolution of elements heavier…
We studied the chemical enrichment of the interstellar medium and stellar population of the building blocks of current typical galaxies in the field, in cosmological hydrodynamics simulations. The simulations include detail modeling of…
Recent results form the James Webb Space Telescope (JWST) report space densities for bright and massive galaxies at z>7 that far exceed expectations of theoretical models of galaxy formation, prompting a revision of our understanding of the…
How much cosmological information can we reliably extract from existing and upcoming large-scale structure observations? Many summary statistics fall short in describing the non-Gaussian nature of the late-time Universe in comparison to…
In Bayesian inference prior hyperparameters are chosen subjectively or estimated using empirical Bayes methods. Generalised Bayesian Inference (GBI) also has a learning rate hyperparameter. This is compounded in Semi-Modular Inference…
We develop a new method to account for the finite lifetimes of stars and trace individual abundances within a semi-analytic model of galaxy formation. At variance with previous methods, based on the storage of the (binned) past star…
Cosmological probes pose an inverse problem where the measurement result is obtained through observations, and the objective is to infer values of model parameters which characterize the underlying physical system -- our Universe. Modern…
Single-molecule force spectroscopy (smFS) is a powerful approach to studying molecular self-organization. However, the coupling of the molecule with the ever-present experimental device introduces artifacts, that complicates the…
Single-molecule experiments are a unique tool to characterize the structural dynamics of biomolecules. However, reconstructing molecular details from noisy single-molecule data is challenging. Simulation-based inference (SBI) integrates…
I will present predictions from chemical evolution model aimed at a self-consistent study of both optical (i.e. stellar) and X-ray (i.e.gas) properties of present-day elliptical galaxies. Detailed cooling and heating processes in the…
Some of the issues that make sampling parameter spaces of various beyond the Standard Model (BSM) scenarios computationally expensive are the high dimensionality of the input parameter space, complex likelihoods, and stringent experimental…
We analyze the stellar abundances of massive galaxies ($\log M_\ast/M_\odot>10.5$) at $z=2$ in the IllustrisTNG simulation with the goal of guiding the interpretation of current and future observations, particularly from the James Webb…
Simulation-based inference (SBI) methods typically require fully observed data to infer parameters of models with intractable likelihood functions. However, datasets often contain missing values due to incomplete observations, data…
Direct comparisons between galaxy simulations and observations that both reach scales < 100 pc are strong tools to investigate the cloud-scale physics of star formation and feedback in nearby galaxies. Here we carry out such a comparison…
Making inferences about physical properties of the Universe requires knowledge of the data likelihood. A Gaussian distribution is commonly assumed for the uncertainties with a covariance matrix estimated from a set of simulations. The noise…
We discuss a model for treating chemical enrichment by SNII and SNIa explosions in simulations of cosmological structure formation. Our model includes metal-dependent radiative cooling and star formation in dense collapsed gas clumps.…
Field-level inference has emerged as a promising framework to fully harness the cosmological information encoded in next-generation galaxy surveys. It involves performing Bayesian inference to jointly estimate the cosmological parameters…