High-Level Project Summary
A simple notebook for JWST data analysis and visualization.
Link to Final Project
Link to Project "Demo"
Detailed Project Description
We attempted the CSA Moonwalker Challenge: Exploring the distant universe with James Webb Space Telescope for which we developed a python notebook tutorial that would allow users to learn:
0. How to download JWST data using an API.
1. How to open and view an image from at least one of the sensors.
2. How to create and view a sky map that shows the region that the image covers
3. How to Indicate when the image was acquired.
4. How to apply a custom filter to enhance the image.
5. How to count the number of galaxies visible in the image using computer vision techniques.
Additionally, we created a children's short story about JWST using AI.
Space Agency Data
Our project is a tutorial to show others how to do simple data analysis and visualization with JWST data. We used a combination of NASA and CSA sources to develop our project. The primary image used in the tutorial is jw02736-o001_t001_nircam_clear-f090w/jw02736-o001_t001_nircam_clear-f090w_i2d.fits and was retrieved from MAST using their API.
Hackathon Journey
Thank you to all the space apps organizers, mentors, and judges - we learned so much!
References
This project used the facilities of the Canadian Astronomy Data Centre, operated by the National Research Council of Canada with the support of the Canadian Space Agency, and the facilities of the NASA funded Mikulski Archive for Space Telescopes for obtaining data from the James Webb Space Telescope.
The services of GPT3 and DALLE2 OpenAIs were used in Section 6.
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[Section 0] Adapted code from MAST API Tutorial: https://mast.stsci.edu/api/v0/MastApiTutorial.html
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[Section 2] Star atlas sky map background retrieved from http://www.atlasoftheuniverse.com/galchart.html
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[Section 2] Planck's CMB sky map background retrieved from https://plancksatellite.org.uk/
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[Section 4] The img_scale.py file used for image scaling is written by Min-Su Shin (Astrophysics, Department of Physics, University of Oxford (2012 - )) and has free access. Retrieved from https://www.sciserver.org/wp-content/uploads/2016/04/img_scale.py_.txt
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[Section 5] Adapted galaxy counting code, courtesy of Space Telescope Science Institute: https://github.com/spacetelescope/jdat_notebooks/blob/main/notebooks/NIRCam_photometry/NIRCam_multiband_photometry.ipynb
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ligo.skymap package: https://lscsoft.docs.ligo.org/ligo.skymap/
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photoutils package: https://photutils.readthedocs.io/en/stable/
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pyfits package: https://pyfits.readthedocs.io/en/latest/
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astropy package: https://www.astropy.org/