StarXiv: a podcast discussing the latest astronomy papers
StarXiv: a podcast discussing the latest astronomy papers
Podcast Description
Hello! Welcome to the StarXiv, hosted by Dr Michelle Collins and Dr Payel Das. This is a biweekkly podcast that delves into the latest astronomy papers & results from the arXiv. Michelle and Payel are astronomers at the University of Surrey. They love research, but struggle to find time to read a lot of papers. They’re hoping this podcast fixes that. The beautiful logo is designed by Izzy Gray, a PhD student currently studying at the University of Surrey.
Podcast Insights
Content Themes
The podcast covers a variety of astronomical topics, including dark matter, black hole research, planetary discovery, and machine learning applications in cosmology, with episodes exploring themes such as constraints on mixed dark matter, black hole survival, and the potential detection of Earth-like planets.
Hello! Welcome to the StarXiv, hosted by Dr Michelle Collins and Dr Payel Das. This is a biweekkly podcast that delves into the latest astronomy papers & results from the arXiv. Michelle and Payel are astronomers at the University of Surrey. They love research, but struggle to find time to read a lot of papers. They’re hoping this podcast fixes that. The beautiful logo is designed by Izzy Gray, a PhD student currently studying at the University of Surrey.
This episode, Michelle and Payel delve into the latest constraints on mixed dark matter from the Lyman alpha forest, what happens to stars that get a little too close to a black hole, how machine learning can help identify stars likely to host an Earth-like planet, studying the dark ages from the Moon and witnessing the birth of nuclear star clusters! Check out the episode and papers below!
Constraining Mixed Dark Matter models with high redshift Lyman-alpha forest data – Olga Garcia-Gallego et al.
Black Hole Survival Guide: Searching for Stars in the Galactic Center That Endure Partial Tidal Disruption – Rewa Clark Bush et al.
Earth-like planet predictor: A machine learning approach – Jeanne Davoult et al.
Detecting the 21 cm Signal of the Cosmic Dark Ages – Willow Smith and Jonathan Pober
Evidence of star cluster migration and merger in dwarf galaxies – Mélina Poulain et al.
Disclaimer
This podcast’s information is provided for general reference and was obtained from publicly accessible sources. The Podcast Collaborative neither produces nor verifies the content, accuracy, or suitability of this podcast. Views and opinions belong solely to the podcast creators and guests.
For a complete disclaimer, please see our Full Disclaimer on the archive page. The Podcast Collaborative bears no responsibility for the podcast’s themes, language, or overall content. Listener discretion is advised. Read our Terms of Use and Privacy Policy for more details.