Antonio Ragagnin ^1,2,3

My track record

• Download my Curriculum Vitae (updated at September 2024)

• Check my SAO/NASA ADS complete list of pubblications

• Check my ORCiD 0000-0002-8106-2742

Meneghetti et al. (2020) highlighted a tension between ΛCDM simulations and GGSL observations. In Ragagnin et al. (2022a), we tested the well-motivated hypothesis that AGN physics could resolve this issue and we concluded that it can not. No current ΛCDM simulation reproduces the observed cores of galaxy clusters. While investigating this problem, I found that this tension is closely linked to the fact that most hydrodynamic simulations tend to overestimate BCG masses.

Resources: youtube presentation recording

It is well known that X-ray observations may be biased toward peaked and centrally concentrated gas distributions, potentially missing a population of X-ray faint objects. In Ragagnin et al. (2022b), I found that clusters that are X-ray faint are gas-poor because they are old and relaxed, thus allowing sufficient time for the gas to be depleted.

I am developing a flexible and modular new implementation of a Gadget-like code (temporary project name: hotwheels), incorporating over a decade of experience working with HPC. It is designed to leverage multicore and GPU architectures, with a strong emphasis on modularity and miniapps, which are essential for collaboration with HPC facilities and GPU vendors.

Follow the progress on Mastodon: astrodon.social/@HotWheelsSims

Check the repository: www.ict.inaf.it/gitlab/hotwheels

I am the lead author of a paper for the Euclid Collaboration: Ragagnin et al. (2025). Within this collaborative effort between observational and simulation teams, I produced mock observations from various multi-wavelength data sources (X-ray, SZ, optical, and inferred weak lensing signals). The paper presents a Euclid-tailored covariance matrix for realistic mock observations across these wavelengths and explores the impact of projection effects, which will assist future cosmology studies based on multi-wavelength observations.

The c2papcosmosim.uc.lrz.de web portal to allows to explore Magneticum simulation results and submit mock-observation jobs through a dedicated computing queue. It features a user-friendly graphical interface to navigate large simulated volumes, perform complex queries on galaxy cluster catalogs, and execute specific post-processing tasks (see Ragagnin et al. 2017).

See c2pap_batch.py for sending batch script.

Press coverage: Science Daily, Gauss Centre.

The github.com/aragagnin/g3read repository contains a collection of Python tools for reading and post-processing Gadget2/3 snapshots, particularly for Magneticum outputs (including the INFO block), and efficiently handling FoF/SubFind catalogs. This repository includes core routines (g3read.py) that combine elements of Pynbody and ported legacy (Klaus') IDL routines. The library utilizes the GadgetFile class from Pynbody. If available, g3read will also leverage Numba for optimized performance.

The package hydro_mc implements the Ragagnin et al. (2021) conversion of mass, concentration, and sparsity parameters between virial and overdensities of Δ = 2500, 500, and 200 (both mean and critical). See the hydro_mc web app or the repo github.com/aragagnin/hydro_mc.

I ported the integration of various Gadget physics integrators (gravity, SPH density, SPH hydrodynamics, and thermal conduction) on GPUs. This was a significant collaborative effort, involving multiple hackathons and long-term partnerships with CSCS, PGI, and NVIDIA (see my CV). For further details, see my paper: Ragagnin et al. (2020).

Resources: youtube presentation recording