Python programming code for stellar photometry in astrophysics teaching on a cloud computing service

Nowadays, there is various software used for both education and astronomy research. For photometry, licensed software and high-performance computer operating systems are required, which is a fund limitation for some schools in Thailand. Thus, in this article, we develop and present the Demonstration...

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Main Author: Krittinatham W.
Other Authors: Mahidol University
Format: Conference or Workshop Item
Published: 2023
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Online Access:https://repository.li.mahidol.ac.th/handle/123456789/82247
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spelling th-mahidol.822472023-05-19T14:55:09Z Python programming code for stellar photometry in astrophysics teaching on a cloud computing service Krittinatham W. Mahidol University Physics and Astronomy Nowadays, there is various software used for both education and astronomy research. For photometry, licensed software and high-performance computer operating systems are required, which is a fund limitation for some schools in Thailand. Thus, in this article, we develop and present the Demonstration Photometry Scripts for Astrophysics Teaching (DPSAT version 1.0). The program is designed to work on cloud computing services via internet browsers to avoid hardware and operation requirement pain points. The DPSAT is programming on flexible, low-cost, on-trend language, Python, and Jupyter Notebook online editor. In advance, our new code supports the home-use image or video file format, i.e., jpg, png, or mp4. Thus, it will be more accessible for teachers and students who do not have standard astronomical instruments. The DPSAT measures the stellar light intensity from the time-series still-images or video files from a smartphone or other digital devices. The code can extract video files into sequenced still images, then transform the RGB color space images into greyscale. The light intensity signal of selected pixels is counted with a simple aperture method in time series. It shows the results, for example, the mean signal, standard variation, measured signal as light intensity versus time, and image of light sources. This will be fruitful for low-cost and easily accessible teaching of astrophysics subjects. 2023-05-19T07:55:09Z 2023-05-19T07:55:09Z 2023-01-01 Conference Paper Journal of Physics: Conference Series Vol.2431 No.1 (2023) 10.1088/1742-6596/2431/1/012038 17426596 17426588 2-s2.0-85148043920 https://repository.li.mahidol.ac.th/handle/123456789/82247 SCOPUS
institution Mahidol University
building Mahidol University Library
continent Asia
country Thailand
Thailand
content_provider Mahidol University Library
collection Mahidol University Institutional Repository
topic Physics and Astronomy
spellingShingle Physics and Astronomy
Krittinatham W.
Python programming code for stellar photometry in astrophysics teaching on a cloud computing service
description Nowadays, there is various software used for both education and astronomy research. For photometry, licensed software and high-performance computer operating systems are required, which is a fund limitation for some schools in Thailand. Thus, in this article, we develop and present the Demonstration Photometry Scripts for Astrophysics Teaching (DPSAT version 1.0). The program is designed to work on cloud computing services via internet browsers to avoid hardware and operation requirement pain points. The DPSAT is programming on flexible, low-cost, on-trend language, Python, and Jupyter Notebook online editor. In advance, our new code supports the home-use image or video file format, i.e., jpg, png, or mp4. Thus, it will be more accessible for teachers and students who do not have standard astronomical instruments. The DPSAT measures the stellar light intensity from the time-series still-images or video files from a smartphone or other digital devices. The code can extract video files into sequenced still images, then transform the RGB color space images into greyscale. The light intensity signal of selected pixels is counted with a simple aperture method in time series. It shows the results, for example, the mean signal, standard variation, measured signal as light intensity versus time, and image of light sources. This will be fruitful for low-cost and easily accessible teaching of astrophysics subjects.
author2 Mahidol University
author_facet Mahidol University
Krittinatham W.
format Conference or Workshop Item
author Krittinatham W.
author_sort Krittinatham W.
title Python programming code for stellar photometry in astrophysics teaching on a cloud computing service
title_short Python programming code for stellar photometry in astrophysics teaching on a cloud computing service
title_full Python programming code for stellar photometry in astrophysics teaching on a cloud computing service
title_fullStr Python programming code for stellar photometry in astrophysics teaching on a cloud computing service
title_full_unstemmed Python programming code for stellar photometry in astrophysics teaching on a cloud computing service
title_sort python programming code for stellar photometry in astrophysics teaching on a cloud computing service
publishDate 2023
url https://repository.li.mahidol.ac.th/handle/123456789/82247
_version_ 1781415653904744448