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

TL;DR

GEHONG addresses the need to generate realistic 3D spectroscopic datacubes for the CSST-IFS by simulating ideal observations with a modular Python framework. It constructs a cube $\mathcal{C}(x,y,\lambda)$ from 2D parameter maps $\mathcal{M}(x,y)$ via the spec1d engine and the map2d maps, then uses the cube3d module to place spectra at each spaxel. The spectral components include a stellar continuum built from SSP templates, ionized gas emission lines with line widths $\sigma_{\text{line},i} = (\sigma_{\text{gas}}/c)\lambda_i$, an AGN consisting of four components, and single-star spectra, enabling both extended and point sources. The outputs are designed for CSST-IFS pipelines and the exposure time calculator (ETC), with planned future PSF convolution to model spatial blurring and instrument effects.

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.

Figures (5)

• Figure 1: Schematic diagram of mocking a galaxy IFS data.
• Figure 2: An example of a synthesized spectrum of a normal galaxy. The green line shows the integrated spectrum of the galaxy, the red line represents the stellar population continuum, and the blue line represents the ionized gas emission lines. The spectrum is generated using the spec1d and map2d modules, with the input parameters summarized in Table \ref{['tab:spec1d']} and Table \ref{['tab:map2d']}. A simple example demonstrating the generation of the galaxy spectrum is provided in Appendix \ref{['app:spec1d']}.
• Figure 3: An example of a generated AGN spectrum (black line), decomposed into its four components: the power-law continuum (yellow line), the iron emission line spectrum (green line), the broad-line region (BLR) emission lines (red line), and the narrow-line region (NLR) emission lines (blue line). The input parameters for each component are summarized in Table \ref{['tab:spec1d']}. A simple example demonstrating the generation of the AGN spectrum is provided in Appendix \ref{['app:spec1d']}.
• Figure 4: An example of a synthesized spectrum of a single star. The spectrum is generated using the spec1d.SingleStar module, with the input parameters summarized in Table \ref{['tab:spec1d']}. A simple example demonstrating the generation of the stellar spectrum is provided in Appendix \ref{['app:spec1d']}.
• Figure 5: An example of two-dimensional maps of physical parameters generated using the map2d module, including surface brightness, line-of-sight velocity, and stellar population age. The input parameters used to create the maps are summarized in Table \ref{['tab:map2d']}, and a simple example demonstrating the generation of the maps is provided in Appendix \ref{['app:map2d']}.