SNU_AOclass

TA seminar notes for the AO classes from 2016-present at SNU, Korea. All the lecture notes were primarily made by Yoonsoo P. Bach. I tried not to make typos, logically wrong statements, etc. If any problem is found in the note, that's solely my fault, so please be kind and let me know so that the notes can be updated.

1. Short History

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Semester	Instructor	TA
- 2023 spr	professor Masateru Ishiguro	*, Yoonsoo P. Bach (unofficial)
2020 Spring	professor Masateru Ishiguro	Jooyeon Geem, Yoonsoo P. Bach (unofficial)
2019 Fall	professor Masateru Ishiguro	Hangbin Jo, Yoonsoo P. Bach (unofficial)
2019 Spring	professor Masateru Ishiguro	Sunho Jin, Yoonsoo P. Bach (unofficial)
2018 Fall	professor Masateru Ishiguro	Sunho Jin, Yoonsoo P. Bach (unofficial)
2018 Spring	professor Masateru Ishiguro	Sunho Jin, Yoonsoo P. Bach (unofficial)
2017 Fall	professor Masateru Ishiguro	Yoonsoo P. Bach (& Da-Eun Kang)
2017 Spring	professor Masateru Ishiguro	Yoonsoo P. Bach (& Na-Eun Shin)
2016 Fall	professor Masateru Ishiguro	Yoonsoo P. Bach

• In 2023: The repo is splitted into SNU_AOclass (this repo) and SNU_AOpython (see Python Practice in contents below).
• In 2020: The name of the repo changed (Jan). All previous repos (2017, 2018) are archived (Jan).
• In 2019: Made this repo.
• In 2018: Made GitHub repo link. Many documents changed from ipynb to md.
• In 2017: Made GitHub repo AO_2017 and website.
• In 2016: No GitHub, but just MS Word-based lecture notes of PyRAF.

2. To Use This Repo

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You may have preferences for using this repo. One of the possible suggestions is to clone/fork this repo and pull regularly to keep updated:

$ cd <Where you want to download this lecture note>

For the first time only:

$ git clone https://github.com/ysBach/SNU_AOclass.git

From the second time:

$ git pull

3. Seminar Contents

The following lecture notes only give you an idea of how to use tools for data reduction. You must be aware of what you are doing! An identical procedure to the lecture note may give different results, depending on what you've done other than what I did when I made the notes.

• This repo contains this README, theoretical part (book), presentations, and reference materials.
• The lecture is mainly composed of
  1. Theory: Book material (theoretical parts and codes)
  2. Python Practice: Jupyter-book in separate repo (practical parts including codes & HW assignments)
  3. Tutorial data:

(Plus. Presentation files, which are just auxiliary seminar notes)

Outstanding Student's Outputs

• Jiyong Youn (@hletrd)
  • spectools: long-slit spectral analysis (class of 2017)
  • PyPreprocessor: preprocessor in CLI (class of 2017)