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We present a toolkit, CosmoDS, designed to study cosmological models at the background level using dynamical system analysis within the Cobaya framework. Dynamical system analysis is a powerful mathematical approach for studying nonlinear…
We present $N$-body simulations in which either all, or a fraction of, the cold dark matter decays non-relativistically to a relativistic, non-interacting dark radiation component. All effects from radiation and general relativity are…
Spectral line profiles are powerful diagnostic tools for both laboratory and astrophysical plasmas, as their shape is sensitive to the plasma environment. The low-frequency component of the electric microfield is an important input for…
We study the semi-holographic idea in context of decaying dark components. The energy flow between dark energy and the compensating dark matter is thermodynamically generalized to involve a particle number variable dark component with…
We present the online MultiDark Database -- a Virtual Observatory-oriented, relational database for hosting various cosmological simulations. The data is accessible via an SQL (Structured Query Language) query interface, which also allows…
TorchOptics is an open-source Python library for differentiable Fourier optics simulations, developed using PyTorch to enable GPU-accelerated tensor computations and automatic differentiation. It provides a comprehensive framework for…
The (py)LIon package is a set of tools to simulate the classical trajectories of ensembles of ions in electrodynamic traps. Molecular dynamics simulations are performed using LAMMPS, an efficient and feature-rich program. (py)LIon has been…
In this manuscript we present a theoretical framework and its numerical implementation to simulate the out-of-equilibrium electron dynamics induced by the interaction of ultrashort laser pulses in condensed-matter systems. Our approach is…
An important step of many image editing tasks is to extract specific objects from an image in order to place them in a scene of a movie or compose them onto another background. Alpha matting describes the problem of separating the objects…
With recent advancements in machine learning for interatomic potentials, Python has become the go-to programming language for exploring new ideas. While machine-learning potentials are often developed in Python-based frameworks, existing…
High-resolution cosmological N-body simulations were performed in order to study the substructure of Milky Way-like galactic halos and the density profiles of halos in a warm dark matter scenario. The results favor this scenario with…
In this work, we carry out a suite of specially-designed numerical simulations to shed further light on dark matter (DM) subhalo survival at mass scales relevant for gamma-ray DM searches, a topic subject to intense debate nowadays.…
Self-interacting dark matter (SIDM) models feature short-range interactions between dark matter (DM) particles that lead to larger diversity in the inner parts of galactic rotation curves and potentially unique gravitational lensing…
Collaborations in astronomy and astrophysics are faced with numerous cyber infrastructure challenges, such as large data sets, the need to combine heterogeneous data sets, and the challenge to effectively collaborate on those large,…
This paper introduces a hybrid numerical scheme for the fuzzy dark matter model: It combines a wave-based approach to solve the Schr\"odinger equation using Fourier continuations with Gram polynomials and a fluid-based approach to solve the…
Dynamical simulations are a fundamental tool for studying the secular evolution of disc galaxies. Even at their maximum resolution, they still follow a limited number of particles and typically resolve scales of the order of a few tens of…
The question of the nature of the dark matter in the Universe remains one of the most outstanding unsolved problems in basic science. One of the best motivated particle physics candidates is the lightest supersymmetric particle, assumed to…
Generative deep learning methods built upon Convolutional Neural Networks (CNNs) provide a great tool for predicting non-linear structure in cosmology. In this work we predict high resolution dark matter halos from large scale, low…
We investigate the dynamics of eccentric binary pulsars embedded in dark matter environments. While previous studies have primarily focused on circular orbits in collisionless dark matter halos, we extend this framework to eccentric systems…
Simulated dark matter profiles are often modelled as a `NFW' density profile rather than a single power law. Recently, attention has turned to the rather rigorous power-law behaviour exhibited by the `pseudo phase-space density' of the dark…