Introduction to Bayesian Statistics and Chris Ferrie's Work

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You know I’m a big fan of everything physics. So when I heard that Bayesian stats was especially useful in quantum physics, I had to make an episode about it!

You’ll hear from Chris Ferrie, an Associate Professor at the Centre for Quantum Software and Information of the University of Technology Sydney. Chris also has a foot in industry, as a co-founder of Eigensystems, an Australian start-up with a mission to democratize access to quantum computing. 

Of course, we talked about why Bayesian stats are helpful in quantum physics research, and about the burning challenges in this line of research.

But Chris is also a renowned author — in addition to writing Bayesian Probability for Babies, he is the author of Quantum Physics for Babies and Quantum Bullsh*t: How to Ruin Your Life With Advice from Quantum Physics. So we ended up talking about science communication, science education, and a shocking revelation about Ant Man…

A big thank you to one of my best Patrons, Stefan Lorenz, for recommending me an episode with Chris!

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, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, 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, 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, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady, Kurt TeKolste, Gergely Juhasz, Marcus Nölke, Maggi Mackintosh, Grant Pezzolesi, Avram Aelony, Joshua Meehl, Javier Sabio, Kristian Higgins, Alex Jones, Gregorio Aguilar, Matt Rosinski, Bart Trudeau, Luis Fonseca, Dante Gates, Matt Niccolls, Maksim Kuznecov, Michael Thomas, Luke Gorrie and Cory Kiser.

Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)

Takeaways:

• Quantum computing has the potential to revolutionize various industries, but it requires specialized tools and education to fully harness its power.
• Bayesian inference plays a crucial role in understanding and solving problems in quantum physics, particularly in parameter estimation and model building.
• The field of quantum physics faces challenges in experimental design, data collection, and maintaining the state of isolated quantum systems.
• There is a need for specialized software that can accommodate the unique constraints and models in quantum physics, allowing for more efficient and accurate analysis.
• Common misconceptions in quantum physics include the idea of superposition as being in two places at once and the misinterpretation of quantum experiments. Misconceptions in quantum physics and Bayesian probability are common and can be addressed through clear explanations and analogies.
• Communicating scientific concepts to the general public requires bridging the gap between scientific papers and mainstream media.
• Simplifying complex topics for young minds involves providing relatable examples, analogies, and categories.
• Studying mathematics is essential for a deeper understanding of quantum physics and statistics.
• Taking risks and making mistakes is encouraged in the early stages of a scientific career.

Links from the show:

• Chris’ website: https://www.csferrie.com/
• Chris on Linkedin: https://www.linkedin.com/in/christopher-ferrie-63993190/
• Chris on Twitter: https://twitter.com/csferrie
• Chris on Instagram: https://www.instagram.com/drchrisferrie/
• Chris’ YouTube channel: https://www.youtube.com/csferrie
• Chris’ children’s books: https://www.amazon.com/gp/product/149267043X
• How quantum mechanics turned me into a Bayesian: https://csferrie.medium.com/how-quantum-mechanics-turned-me-into-a-bayesian-655ddf88051f
• Exoplanet, a python package for probabilistic modeling of time series data in astronomy: https://docs.exoplanet.codes/en/latest/
• Quantum Bullsh*t – How to Ruin Your Life with Advice from Quantum Physics : https://www.goodreads.com/en/book/show/61263731
• LBS #93, A CERN Odyssey, with Kevin Greif: https://www.youtube.com/watch?v=rOaqIIEtdpI
• LBS #72, Why the Universe is so Deliciously Crazy, with Daniel Whiteson: https://learnbayesstats.com/episode/72-why-the-universe-is-so-deliciously-crazy-daniel-whiteson/
• LBS #97, Probably Overthinking Statistical Paradoxes, with Allen Downey: https://learnbayesstats.com/episode/97-probably-overthinking-statistical-paradoxes-allen-downey/
• LBS #51, Bernoulli’s Fallacy & the Crisis of Modern Science, with Aubrey Clayton: https://learnbayesstats.com/episode/51-bernoullis-fallacy-crisis-modern-science-aubrey-clayton/
• LBS #50, Ta(l)king Risks & Embracing Uncertainty, with David Spiegelhalter: https://learnbayesstats.com/episode/50-talking-risks-embracing-uncertainty-david-spiegelhalter/

Transcript

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