相关论文: Generating synthetic star catalogs from simulated …
The increasing availability of high-quality optical and near-infrared spectroscopic data, as well as advances in modelling techniques, have greatly expanded the scientific potential of spectroscopic studies. However, the software tools…
Hydrodynamic simulations are powerful tools for studying galaxy formation. However, it is crucial to test and improve the sub-grid physics underlying these simulations by comparing their predictions with observations. To this aim,…
We present and analyze a series of synthetic galaxy survey fields based on the IllustrisTNG Simulation suite. With the Illustris public data release and JupyterLab service, we generated a set of twelve lightcone catalogs covering areas from…
The spatial and temporal relationships between stellar age, kinematics, and chemistry are a fundamental tool for uncovering the physics driving galaxy formation and evolution. Observationally, these trends are derived using carefully…
Fully automated astronomical data calibration and imaging pipelines are difficult to develop without a good prototyping method which permits to bridge the time between observatory commissioning and the moment when the special features and…
We present a visual analytics tool, based on the VisIVO suite, to exploit a combination of all new-generation surveys of the Galactic Plane to study the star formation process of the Milky Way. The tool has been developed within the…
The Space Telescope Imaging Product Simulator (STIPS) is a Python-based package that can be used to simulate scenes from the upcoming \textit{Nancy Grace Roman Space Telescope} (\nancy). STIPS is able to generate post-pipeline astronomical…
We present FORECAST, a new flexible and adaptable software package that performs forward modeling of the output of any cosmological hydrodynamical simulations to create a wide range of realistic synthetic astronomical images. With…
The next generation of wide-area sky surveys offer the power to place extremely precise constraints on cosmological parameters and to test the source of cosmic acceleration. These observational programs will employ multiple techniques based…
The future astronomical imaging surveys are set to provide precise constraints on cosmological parameters, such as dark energy. However, production of synthetic data for these surveys, to test and validate analysis methods, suffers from a…
Stellar streams are sensitive probes of the Galactic potential. The likelihood of a stream model given stream data is often assessed using simulations. However, comparing to simulations is challenging when even the stream paths can be hard…
This manual accompanies the release of the particle data for 24 simulations of the EAGLE suite of cosmological hydrodynamical simulations of galaxy formation by the virgo consortium. It describes how to download these snapshots and how to…
PHOTOMETRYPIPELINE (PP) is an automated pipeline that produces calibrated photometry from imaging data through image registration, aperture photometry, photometric calibration, and target identification with only minimal human interaction.…
Biosciences have been revolutionized by next generation sequencing (NGS) technologies in last years, leading to new perspectives in medical, industrial and environmental applications. And although our motivation comes from biosciences, the…
Cloud computing offers an opportunity to run compute-resource intensive climate models at scale by parallelising model runs such that datasets useful to the exoplanet community can be produced efficiently. To better understand the…
This paper introduces foundations for a new kind of cosmology. We advocate that computer simulations are needed to address two key cosmological issues. First, the robustness of the emergence of complexity, which boils down to ask: "what…
We introduce our new code MYOSOTIS (Make Your Own Synthetic ObservaTIonS) which is designed to produce synthetic observations from simulated clusters. The code can synthesise observations from both ground- and spaced-based observatories,…
We present cosmo_learn, an open-source python-based software package designed to simulate cosmological data and perform data-driven inference using a range of modern statistical and machine learning techniques. Motivated by the growing…
During the last couple of years, observers have started to make plans for a Virtual Observatory, as a federation of existing data bases, connected through levels of software that enable rapid searches, correlations, and various forms of…
Observations of protostars are often compared with synthetic observations of models in order to infer the underlying physical properties of the protostars. The majority of these models have a single protostar, attended by a disc and an…