Related papers: Constraining Cosmology with Simulation-based infer…
We present a joint analysis of galaxy clustering and galaxy--galaxy lensing measurements from BOSS galaxies using a simulation-based emulation method combined with a halo occupation distribution model. Our emulators are constructed with the…
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…
We present a study on the inference of cosmological and astrophysical parameters using stacked galaxy cluster profiles. Utilizing the CAMELS-zoomGZ simulations, we explore how various cluster properties--such as X-ray surface brightness,…
Subhalo abundance matching (SHAM) is a popular technique for assigning galaxy mass or luminosity to haloes produced in N-body simulations. The method works by matching the cumulative number functions of the galaxy and halo properties, and…
Context. As recently demonstrated, high-z submillimetre galaxies (SMGs) are the perfect background sample for tracing the mass density profiles of galaxies and clusters (baryonic and dark matter) and their time-evolution through…
Understanding the physical connection between cluster galaxies and massive haloes is key to mitigating systematic uncertainties in next-generation cluster cosmology. We develop a novel method to infer the level of conformity between the…
Computational models are invaluable in capturing the complexities of real-world biological processes. Yet, the selection of appropriate algorithms for inference tasks, especially when dealing with real-world observational data, remains a…
In recent years, the availability of large, complete cluster samples has enabled numerous cosmological parameter inference analyses using cluster number counts. These have provided constraints on the cosmic matter density $\Omega_m$ and the…
Context: Modelling satellite galaxy abundance $N_s$ in Galaxy Clusters (GCs) is a key element in modelling the Halo Occupation Distribution (HOD), which itself is a powerful tool to connect observational studies with numerical simulations.…
The large number of strong lenses discoverable in future astronomical surveys will likely enhance the value of strong gravitational lensing as a cosmic probe of dark energy and dark matter. However, leveraging the increased statistical…
Precise cosmological inference from next-generation weak lensing surveys requires extracting non-Gaussian information beyond standard two-point statistics. We present a hybrid machine-learning (ML) framework that integrates field-level…
Studying the impact of systematic effects, optimizing survey strategies, assessing tensions between different probes and exploring synergies of different data sets require a large number of simulated likelihood analyses, each of which cost…
We constrain the scaling relation between optical richness ($\lambda$) and halo mass ($M$) for a sample of SDSS redMaPPer galaxy clusters within the context of the {\it Planck} cosmological model. We use a forward modeling approach where we…
Model parameter inference is a universal problem across science. This challenge is particularly pronounced in developmental biology, where faithful mechanistic descriptions require spatial-stochastic models with numerous parameters, yet…
The halo assembly bias, a phenomenon referring to dependencies of the large-scale bias of a dark matter halo other than its mass, is a fundamental property of the standard cosmological model. First discovered in 2005 from the Millennium Run…
We present the results of analysis of constraints on cosmological parameters from cosmic microwave background (CMB) alone and in combination with galaxy cluster baryon fraction assuming inflation--generated adiabatic scalar fluctuations.…
Context: We present the first Cosmological Parameter inferences from eROSITA X-ray observations of galaxy clusters using a Machine Learning algorithm. Methods: We train a Random Forest using mock catalogs of clusters from Magneticum…
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…
A promising method for measuring the cosmological parameter combination fsigma_8 is to compare observed peculiar velocities with peculiar velocities predicted from a galaxy density field using perturbation theory. We use N-body simulations…
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…