Hands-on Tutorials on JWST Data Analysis for the International Virtual Course on Astronomy ITB 2022

This repository contains materials for a tutorial on an analysis of the JWST NIRCam imaging data. The tutorial will be given as part of the IVC Astronomy ITB 2022 on August 16, 2022. In this tutorial, we will learn basic anlysis of JWST data, both simulated data and the real one.

What we will learn

In this tutorial, we will learn the following skills

• Point Spread Function (PSF) matching of imaging data across multiple bands
• Creating color RGB images
• Detection and source extraction of astronomical objects in an image
• Aperture photometry and extracting spectral energy distributions (SEDs) of the galaxies in the field
• Photometric redshift measurement
• Performing SED fitting for measuring stellar population properties of galaxies
• Optional: Dissecting spatially resolved properties of galaxies with piXedfit

Data Resources

• Simulated JWST/NIRCam imaging data from the Cosmic Evolution Early Release Science (CEERS) survey. The data that we will analyze, simulated data release v3, are available in the CEERS's webiste here
• First data from the JWST Early Release Observations (ERO) on SMACS 0723 cluster. For this tutorial, we will be using the JWST/NIRCam and HST processed data product on SMACS 0723 cluster that are produced by Gabriel Brammer using grizli and publicly available at https://s3.amazonaws.com/grizli-v2/SMACS0723/Test/image_index.html

You can download the data from the above links or alternatively, you can follow the instructions below and download the required data from the google drive links that are listed there.

Preparations

Software Dependencies and Installation

The codes in this tutorial are all written in Python and can be conveniently run on the jupyter notebook platform. Preferably run on a Linux operating system. Before running the codes, you need to install the following softwares or dependencies

• Python 3.5 or later
• jupyter notebook
• Basic Python packages for astronomy: NumPy, Astropy, matplotlib, SciPy, pysao. These packages are easy to be installed using pip or conda.
• Photometric analysis packages: Photutils and SEP Source Extractor (Bertin & Arnouts 1996). These packages are also easy to be installed. Please follow the installation procedure in their webistes.
• Photometric redshift tool EAZY (Brammer, van Dokkum & Coppi (2008)). Please follow the installation instruction in the EAZY's GitHub page or its older website here. A documentation in PDF file also available here.
• SED fitting tool piXedfit. This is a bit more difficult to install, please follow the installation procedure at https://pixedfit.readthedocs.io/en/latest/install.html.

Download the Required Data

Please follow the instructions below

• Clone this GitHub repository to your local computer

cd <desired_dir>
git clone https://github.com/aabdurrouf/ivcitb2022.git

• Download PSF matching kernels from https://drive.google.com/file/d/1t3aBZ1tj8DOlLbfZMD85Gd1SuW8KE871/view?usp=sharing and put the files into ivcitb2022/kernels/ directory
• Download CEERS simulated NIRCam Images from https://drive.google.com/file/d/1Fc8PRTzhlqIrPac63OeFlUVAoOViyTbk/view?usp=sharing and put the files into ivcitb2022/CEERS/ directory and then decompress it. Alternatively, you can also download the data from CEERS' website https://ceers.github.io/sdr3.html#nircam-imaging-one
• Download JWST and HST images of SMACS 0723. Follow the instruction at https://github.com/aabdurrouf/ivcitb2022/tree/main/ERO_SMACS0723. You can run the download script (download.sh) inside ivcitb2022/ERO_SMACS0723/data directory.

Going Through the Tutorials

The tutorials can be conveniently followed in the following order

cd ivcitb2022

Analysis of simulated NIRCam Images from CEERS survey

cd CEERS

• Step1_checking_cropping_and_color_images.ipynb
• Step2_sources_detection_and_aperture_photometry_crop1.ipynb
• Step2_sources_detection_and_aperture_photometry_crop2.ipynb

cd eazy_photoz

• Step3_measuring_photometric_redshifts_crop1.ipynb
• Step3_measuring_photometric_redshifts_crop2.ipynb

cd ../piXedfit_sedfit

• Step4_SEDfitting_with_piXedfit_derive_global_properties.ipynb

Analysis of JWST ERO data on galaxy cluster SMACS 0723

• Analysis_ERO_SMACS0723.ipynb

Some useful links

• JWST User Documentation
• JWST Science Calibration Pipeline
• General Observer Programs in Cycle 1
• Director’s Discretionary Early Release Science Programs

Contributors

• Abdurro'uf - For any inquiry, please send email to fabdurr1@jhu.edu