The Arrow of Time in Causal Networks: a talk I gave yesterday at the Simons Institute at Berkeley. Still a work in progress - a couple of typos on the slides! - but I’m finally happy with how the idea is coming along.
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One manifestation of time’s arrow is that causes precede effects. Modern work on Bayesian networks offers a specific definition of “cause,” so I use that to argue how the entropic arrow of time explains this asymmetry. As it should, but it’s important to get the details right.
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What if the (really really) fundamental laws of physics are not time reversal invariant, but T-invariance simply emerges in effective large scale physical theories, such as Newtonian gravity?
Great video! If entropy is defined by all possible microstates, this implies a) we know all of them, b) these microstates do not change. Right? Otherwise we would mess up the arrow of time, wouldn't we?
Thank God. I've been really hankering for some new you! I love the podcast, but I'm a visual learner.
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It's all about point of view. I see time like the pages (scenes) in a book. When you're inside the book (when you're reading page by page) time "passes". It's a lot like our "view" of the Sun traveling across the sky. When in actuality, we're just spinning in circles.
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What's about the theory by Kip Thorne: Wormholes, Time Machines, and the Weak Energy Condition
