Détail du document
Identifiant
oai:arXiv.org:2406.05574
Sujet
Astrophysics - Astrophysics of Gal...Auteur
Oman, Kyle A.Catégorie
sciences : astrophysique
Année
2024
Date de référencement
12/06/2024
Mots clés
class martiniRésumé
MARTINI is a modular Python package that takes smoothed-particle hydrodynamics (SPH) simulations of galaxies as input and creates synthetic spatially- and/or spectrally-resolved observations of the 21-cm radio emission line of atomic hydrogen (data cubes).
The various aspects of the mock-observing process are divided logically into sub-modules handling the data cube, source galaxy, telescope beam pattern, noise, spectral model and SPH kernel.
MARTINI is object-oriented: each sub-module provides a class (or classes) which can be configured as desired.
For most sub-modules, base classes are provided to allow for straightforward customization.
Instances of each sub-module class are given as parameters to an instance of a main "Martini" class; a mock observation is then constructed by calling a handful of functions to execute the desired steps in the mock-observing process.
;Comment: Peer-reviewed software published in the Journal of Open Source Software (JOSS)
Oman, Kyle A., 2024, MARTINI: Mock Array Radio Telescope Interferometry of the Neutral ISM
Configurable Safety Tuning of Language Models with Synthetic Preference Data
data preference cst dpo configurable language safety
Affective flexibility as a developmental building block of cognitive reappraisal: An fMRI study
cognitive success affective flexibility
