Mock Observations for the CSST Mission: Integral Field Spectrograph--GEHONG: A Package for Generating Ideal Datacubes

TL;DR

GEHONG is a Python package that simulates ideal spectral data cubes for the CSST-IFS, enabling detailed modeling of various astronomical sources with customizable physical parameters.

Contribution

The paper introduces GEHONG, a novel Python package for generating idealized 3D spectral data cubes for the CSST-IFS, accommodating diverse source types and physical models.

Findings

Successfully generates spatially resolved spectral cubes.

Supports multiple spectral types including stellar and gas emission.

Flexible modeling of physical parameters and source types.

Abstract

We developed a Python package GEHONG to mock the three-dimensional spectral data cube under the observation of an ideal telescope for the Integral Field Spectrograph of the Chinese Space Station Telescope (CSST-IFS). This package can generate one-dimensional spectra corresponding to local physical properties at specific positions according to a series of two-dimensional distributions of physical parameters of target sources. In this way, it can produce a spatially resolved spectral cube of the target source. Two-dimensional distributions of physical parameters, including surface brightness, stellar population, and line-of-sight velocity, can be modeled using the parametric model or based on real observational data and numerical simulation data. For the generation of one-dimensional spectra, we have considered four types of spectra, including the stellar continuum spectra, ionized gas emission lines, AGN spectra, and stellar spectra. That makes GEHONG able to mock various types of targets, including galaxies, AGNs, star clusters, and HII regions.