Volume 53, Number 2, 2022Machine learning in physics
|Page(s)||22 - 25|
|Published online||27 April 2022|
Machine learning in present day astrophysics
CSFK Konkoly Observatory, H-1121 Budapest, Konkoly Thege Miklo´s u´ t 15-17., Hungary
2 MTA CSFK Lendu¨ let Near-Field Cosmology Research Group
3 ELTE Eo¨ tvo¨ s Lora´nd University, Institute of Physics, Budapest, Hungary
Machine learning is everywhere in our daily life. From the social media and bank sector to transportation and telecommunication, we cannot avoid using it, sometimes even without noticing that we are relying on it. Astronomy and astrophysics are no exception. From telescope time and survey telescope scheduling through object detection and classification, to cleaning images and making large simulations smarter and quicker to it is ubiquitous to use machine learning algorithms. To illustrate this silent revolution, we checked the NASA Astronomical Data System website and searched for the keyword ‘machine learning’ in abstracts of astronomical and astrophysical papers. In 2000 we found 56, in 2010 889, and by 2020 no less than 35,659 abstracts contained the magic two words.
© European Physical Society, EDP Sciences, 2022
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