Exploring massive star formation physics: from simulations to observations

  • Alina, Dana (PI)
  • Abdikamalov, Ernazar (Other Faculty/Researcher)
  • Makarova, Dana (Other participant)
  • Matzhan, Aruzhan (Undergraduate student)
  • Mukash, Alua (Undergraduate student)
  • Yergaliyev, Argyn (Other participant)
  • Telmen, Yerassyl (Undergraduate student)

Project: FDCRGP

Project Details

Grant Program

Faculty Development Competitive Research Grant Program (General) 2024-2026

Project Description

This project aims at studying the dynamics of the interstellar medium by using numerical simulations, radiative transfer, synthetic observations, and data analysis. We will develop a method for the detection of hub-filament systems in numerical simulations and synthetic observations to elucidate the physics of massive star formation. Possibilities of observations of star-forming regions will also be explored.
The proposed project will actively involve undergraduate and graduate students. This allows them to gain valuable educational and research experience. In-demand skills such as programming, data analysis, teamwork, scientific writing and communication will be cultivated.
Within the framework of this project, we aim to contribute to building a sustainable system for astronomy research in Kazakhstan. Sustainable astronomical research is based on a balanced approach that relies not only on traditional observational facilities but also on cutting-edge tools: computational methods, numerical simulations, open access data usage and analysis. Our work will advance knowledge in this area, attract talented researchers, nurture local expertise in numerical simulations, algorithm development, and astronomy, in particular in the infrared band, where star formation processes can be traced. This expertise will establish Kazakhstan as a qualified actor in the ISM dynamics studies and propel the growth of astronomy research in the country.
StatusActive
Effective start/end date1/1/2412/31/26

Keywords

  • Astrophysics
  • star formation
  • data analysis
  • numerical simulations
  • Computational methods

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