It’s a harsh world out there, as the gang learns by trekking out to observe accretion in the wild. Will peers through his simulation binoculars to see whether tidal disruption events can really satisfy a hungry black hole, and Malena grabs her spectroscopic scalpel to pick apart a white dwarf’s last meal. Plus, we learn a few life lessons from planetesimals.
In this episode, we’re blown back and blown away by the solar wind. Will offers a historical overview of how Eugene Parker discovered the solar wind without running a single experiment. Malena covers early results and next steps for the eponymous and incredibly hot Parker Solar Probe, as it ~enters the Sun~. Postdoc Chris Spalding also discusses Mercury’s (literally) impactful and (solar) windy childhood.
We were going to write show notes, but it’s been a little while since we recorded and we forgot what we talked about. I guess you could call our memory…. transient! In this episode we discuss some of the quickest, most high-energy astrophysical phenomena in the Universe. Will describes a possible explanation for some of the speediest and most mysterious flashes of energy ever detected, while Alex describes a bizarre and brilliant stellar explosion.
We’re starting off the new year right by getting ahead of the curve! In this topsy-turvy episode, we tackle the stretching and curving of non-Euclidean geometry -- where it came from, why it teaches us about black holes and the shape of the universe, and how conformal diagrams help us wrap our minds (and our spacetime) around it all. Alex amazes with ascending audio, Will gives the all-clear to keep eating Pringles and Malena explains how theorists can help save trees.
Ever experience the last rays of sunlight sparkling across the ocean? In this episode, PhD student Michael Heslar tells us how we can use this twinkling across the methane seas of Titan to study waves, winds, and much more. Plus, Alex brings us an Astrobite using shimmering starlight to help you find your next exoplanet vacation destination!
Please describe a time in your life when you experienced and overcame hardship. Well, middle school wasn’t great...I stubbed my toe this morning….how much detail are you looking for here?? The decision to apply to grad school can be both thrilling and terrifying. And, just like in research, one question can lead to ten more. Have no fear, the team is here! Will the Worthful helps you find the perfect advisor, Malena the Musicological shares her tips for crafting the perfect personal statement, and Alex the Acaudal weighs the pros and cons of taking a gap year.
Planets and quenching and stars, oh my! In this finale to our four-part series on machine learning in astrophysics, the team hits the (virtual) road to hear from the experts. Our first stop is Irvine, California, where Tae Baxter teaches us that even galaxies struggle to stay active during quarantine. Next, we’re off to Porto, Portugal, where Ana Barboza uses the planetary ends to justify the k-means. We also make a pit stop for some banana-inspired techno.
They say the 20th century explorers were astronauts. The 21st century explorers might be data scientists using unsupervised learning methods to explore big data. In this episode, we learn Alex and computers have a love-hate relationship with authority, Will struggles to introduce his space sound, and Malena tells us she has enough coffee tables.
Today we get to talk about everyone’s favorite problem: too much data and too little time! It’s not yet Halloween, but today’s spooky episode is full of GHOSTs and ASSASNs. Alex shares his recent work applying random forests to create a supernatural catalog and predictor of supernova types, and Will describes a tremendous classification effort to automatically sort variable stars.
This episode takes us into dark notions and oscillating questions! Malena spices rocks that orbit remote places and Will covers his dwarfs with tenderness and instability.
Okay, so none of this is true. But we used machine learning to generate this text! Episode 21 is the first in our three part series covering machine learning methods in astronomy. First up? Neural networks!