#72 Why the Universe is so Deliciously Crazy, with Daniel Whiteson
Learning Bayesian Statistics
Introduction
Learn Vision Statistics is a fortnightly podcast on Bayesian inference. This week, Alex gets to interview one of his favorites, science authors Daniel Waidson. The episode will be recorded September 6, 2022.
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What happens inside a black hole? Can we travel back in time? Why is the Universe even here? This is the type of chill questions that we’re all asking ourselves from time to time — you know, when we’re sitting on the beach.
This is also the kind of questions Daniel Whiteson loves to talk about in his podcast, “Daniel and Jorge Explain the Universe”, co-hosted with Jorge Cham, the author of PhD comics. Honestly, it’s one of my favorite shows ever, so I warmly recommend it. Actually, if you’ve ever hung out with me in person, there is a high chance I started nerding out about it…
Daniel is, of course, a professor of physics, at the University of California, Irvine, and also a researcher at CERN, using the Large Hadron Collider to search for exotic new particles — yes, these are particles that put little umbrellas in their drinks and taste like coconut.
On his free time, Daniel loves reading, sailing and baking — I can confirm that he makes a killer Nutella roll!
Oh, I almost forgot: Daniel and Jorge wrote two books — We Have No Idea and FAQ about the Universe — which, again, I strongly recommend. They are among my all-time favorites.
Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !
Thank you to my Patrons for making this episode possible!
Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bert≈rand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, George Ho, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Luis Iberico, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, David Haas, Robert Yolken, Or Duek, Pavel Dusek and Paul Cox.
Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)
Links from the show:
- PyMC Labs Meetup, Dec 8th 2022, A Candle in the Dark – How to Use Hierarchical Post-Stratification with Noisy Data: https://www.meetup.com/pymc-labs-online-meetup/events/289949398/
- Daniel’s website: https://sites.uci.edu/daniel/
- Daniel on Twitter: https://twitter.com/DanielWhiteson
- “Daniel and Jorge Explain the Universe”: https://sites.uci.edu/danielandjorge/?pname=danielandjorge.com&sc=dnsredirect
- We Have No Idea – A Guide To The Unknown Universe: https://phdcomics.com/noidea/
- Frequently Asked Questions About The Universe: https://sites.uci.edu/universefaq/
- Learning to Identify Semi-Visible Jets: https://arxiv.org/abs/2208.10062
- Twitter thread about the paper above: https://twitter.com/DanielWhiteson/status/1561929005653057536
Abstract
Big questions are tackled in episode 72 of the Learning Bayesian Statistics Podcast: “What is the nature of the universe?”, “What is the role of science?”, “How are findings in physics created and communicated?”, “What is randomness actually?”. This episode’s guest, Daniel Whitesun, is just the right person to address these questions.
He is well-known for his own podcast “Daniel and Jorge Explain the Universe”, wrote several popular science books on physics and works as a particle physicist with data from the particle physics laboratory CERN.
He manages to make sense of Astrology, although he is not much of a star-gazer himself. Daniel prefers to look for weird stuff in the data of colliding particles and ask unexpected questions.
This comes with great statistical challenges that he tackles with Bayesian statistics and machine learning, while he also subscribes to the frequentist philosophy of statistics.
In the episode, Alex and Daniel touch upon many of the great ideas in quantum physics, the Higgs boson, Schrödinger’s cat, John Bell’s quantum entanglement discoveries, true random processes and much more. Mixed in throughout are pieces of advice for anyone scientifically-minded and curious about the universe.
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