Episode 674: A Massive Star Just Disappeared. No Supernova, Just Straight to Black Hole
When the largest stars die, it’s usually pretty obvious. Supernovae are visible from billions of light-years away. But recently astronomers watched a massive star just disappear. No explosion, nothing, it just… vanished?
Of course, it could have been dust. It’s always dust. But one intriguing possibility is that the star just imploded directly into a black hole, without the supernova detonation. And if that’s the case, is this happening more often, we just didn’t notice it?
Want to see this video early? Join our community at https://www.patreon.com/universetoday
Our Book is out!
https://www.amazon.com/Universe-Today-Ultimate-Viewing-Cosmos/dp/1624145442/
Audio Podcast version:
ITunes: https://itunes.apple.com/us/podcast/universe-today-guide-to-space-audio/id794058155?mt=2
RSS: https://www.universetoday.com/audio
Weekly email newsletter:
https://www.universetoday.com/newsletter
Weekly Space Hangout:
https://www.youtube.com/channel/UC0-KklSGlCiJDwOPdR2EUcg/
Astronomy Cast:
https://www.youtube.com/channel/UCUHI67dh9jEO2rvK--MdCSg
Support us at https://www.patreon.com/universetoday
More stories at https://www.universetoday.com/
Twitch: https://twitch.tv/fcain
Twitter: https://twitter.com/universetoday
Facebook: https://www.facebook.com/universetoday
Instagram - https://instagram.com/universetoday
Team: Fraser Cain - @fcain / frasercain@gmail.com
Karla Thompson - @karlaii / https://www.youtube.com/channel/UCEItkORQYd4Wf0TpgYI_1fw
Chad Weber - weber.chad@gmail.com
References:
https://www.eso.org/public/archives/releases/sciencepapers/eso2010/eso2010a.pdf
https://www.forbes.com/sites/startswithabang/2017/09/05/the-suns-energy-doesnt-come-from-fusing-hydrogen-into-helium-mostly/#456b5d0670f9
https://www.eso.org/public/usa/news/eso2010/
https://www.nasa.gov/feature/goddard/2017/collapsing-star-gives-birth-to-a-black-hole
https://www.forbes.com/sites/startswithabang/2017/12/26/direct-collapse-black-holes-may-explain-our-universes-mysterious-quasars/#1575aa7b71f0
https://www.youtube.com/watch?v=OEZu3pXAFWY
Available Results
Generated results are saved to your library for reuse and search.
Choose Template
Pick the result you want. You can review provider and model before generating.
A concise first-pass summary for understanding the episode quickly.
A comprehensive, source-grounded extraction of the reusable knowledge in an episode.
Scientific findings, mechanisms, studies, hypotheses, and the limits of the evidence discussed.
A dedicated analysis of warnings, limitations, trade-offs, weak evidence, and uncertainty.
Memorable statements and important claims with attribution and source context.
Technologies, AI models, technical methods, capabilities, limitations, and adoption implications.
A concise first-pass summary for understanding the episode quickly.
A detailed readable summary organized by chapter or topic.
A navigable map of subjects, topic flow, and suggested chapters.
A comprehensive, source-grounded extraction of the reusable knowledge in an episode.
Reusable atomic knowledge units extracted from the episode.
A comprehensive extraction focused on health practices, protocols, claims, and safety caveats.
A comprehensive extraction focused on opportunities, strategy, markets, and company building.
Explicit actions, next steps, habits, recommendations, and things to avoid.
A dedicated inventory of concrete resources named in the episode.
A dedicated analysis of warnings, limitations, trade-offs, weak evidence, and uncertainty.
A concise first-pass summary for understanding the episode quickly.
A detailed readable summary organized by chapter or topic.
A navigable map of subjects, topic flow, and suggested chapters.
A comprehensive, source-grounded extraction of the reusable knowledge in an episode.
Reusable atomic knowledge units extracted from the episode.
A comprehensive extraction focused on health practices, protocols, claims, and safety caveats.
A comprehensive extraction focused on opportunities, strategy, markets, and company building.
Scientific findings, mechanisms, studies, hypotheses, and the limits of the evidence discussed.
Technologies, AI models, technical methods, capabilities, limitations, and adoption implications.
Investment theses, assets, catalysts, valuation reasoning, time horizons, and risks.
Chronologies, actors, causes, consequences, turning points, and competing historical interpretations.
Policies, proposals, stakeholders, arguments, implementation constraints, and predicted effects.
Career paths, skills, hiring signals, workplace decisions, transitions, and limitations of the advice.
Behavioral mechanisms, biases, motivation, habits, emotions, interventions, and evidence limitations.
Economic mechanisms, incentives, indicators, market structure, forecasts, and uncertainty.
Leadership principles, team systems, organizational design, culture, feedback, and failure modes.
Audience, positioning, messaging, acquisition, retention, experiments, metrics, and failed approaches.
Teaching methods, learning strategies, practice, feedback, assessment, and effectiveness evidence.
Theses, premises, arguments, objections, values, thought experiments, and unresolved questions.
Communication patterns, conflict, boundaries, expectations, repair methods, and contextual limitations.
Books, papers, authors, courses, and other learning resources mentioned in the episode.
Repeatable methods, frameworks, mental models, processes, and systems.
Explicit actions, next steps, habits, recommendations, and things to avoid.
Memorable statements and important claims with attribution and source context.
A dedicated inventory of concrete resources named in the episode.
A dedicated analysis of warnings, limitations, trade-offs, weak evidence, and uncertainty.