Friction Problem and Drivetrain Simulation
This rather simple physics problem is at the heart of any simulation involving rubbing parts.
This rather simple physics problem is at the heart of any simulation involving rubbing parts.
Since reading about Lewis Carroll's game of Doublets in Pappas' Joy of Mathematics, I have loved the game and often thought about graphs (networks) in terms of Doublets. Here I present the basics of embeddings, and demonstrate using a genetic algorithm to optimize an embedding of a list of three-letter words from a few games of Doublets.
I've been playing around with the iPhone 4 since I took the plunge about two weeks ago. Amazing device. I really love the iTunes U feature. Access to countless hours of educational material. I've been falling asleep to The Tolkien Professor and the 99% Invisible podcast. The other day I took a long walk while listening to a lecture on the history of probability theory and found myself playing basketball (more vigorously than I'd expect). Why sit in a class, half-asleep, when you can listen to the same lecture while getting some cardio? As Steve Jobs would say, This is HUGE.
I've been reading Dawkins' The Selfish Gene. What I love most about the book is how my mind is just overflowing with genetic systems, simulatable quantitative machines; I'm just dying to code up some simulations of the systems he exposes so eloquently in the book. Every few pages, a new system comes into view. I have to pause, just stare into the void as my mind runs fast, imagining the mathematics needed to construct from the theory a working computer model.
I'm currently taking a course on general relativity, and I have found some course notes by S. Carroll to be rather useful. While reading them I ran across a passage which quite nicely resolves the redshift paradox by pointing out the ultimate falsehood of a common and convenient assumption. It speaks for itself: