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Scott Aaronson on Complexity, Computation, and Quantum Gravity

Scott Aaronson on Complexity, Computation, and Quantum Gravity

Released Monday, 1st June 2020
 1 person rated this episode
Scott Aaronson on Complexity, Computation, and Quantum Gravity

Scott Aaronson on Complexity, Computation, and Quantum Gravity

Scott Aaronson on Complexity, Computation, and Quantum Gravity

Scott Aaronson on Complexity, Computation, and Quantum Gravity

Monday, 1st June 2020
 1 person rated this episode
Rate Episode

There are some problems for which it’s very hard to find the answer, but very easy to check the answer if someone gives it to you. At least, we think there are such problems; whether or not they really exist is the famous P vs NP problem, and actually proving it will win you a million dollars. This kind of question falls under the rubric of “computational complexity theory,” which formalizes how hard it is to computationally attack a well-posed problem. Scott Aaronson is one of the world’s leading thinkers in computational complexity, especially the wrinkles that enter once we consider quantum computers as well as classical ones. We talk about how we quantify complexity, and how that relates to ideas as disparate as creativity, knowledge vs. proof, and what all this has to do with black holes and quantum gravity.

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Scott Aaronson received his Ph.D. in computer science from the University of California, Berkeley. He is currently the David J. Bruton Jr. Centennial Professor of Computer Science at the University of Texas at Austin, and director of the Quantum Information Center there. He specializes in quantum computing and computational complexity theory, but has written on topics from free will to the nature of consciousness. Among his awards are the Tomassoni-Chisesi Prize in Physics (Italy) and the Alan T. Waterman Award from the National Science Foundation. His blog Shtetl-Optimized is known both for its humor and as the most reliable source of information on news in quantum computing. He is the author of Quantum Computing Since Democritus.


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