I’m thrilled about this preprint w Martin Kassabov and Alex Townsend. We prove that a network of identical Kuramoto oscillators synchronizes —regardless of the details of its wiring diagram — if every oscillator is connected to at least 75% of the others. arxiv.org/abs/2105.11406
This puzzle has fascinated a lot of us in my little corner of nonlinear dynamics since 2012. What’s the smallest level of connectivity that guarantees that a homogeneous Kuramoto model (the simplest kind of oscillator system) will always fall into sync?
We still don’t know the answer. The magic level of connectivity was previously proven to lie between 68.38 and 78.89%, and conjectured to be exactly 75%. In this preprint we’ve now reduced the upper bound to 75%. But that’s still far away from the best known lower bound.
The gap between the upper and lower bound is tantalizing. We argue in the paper that the gap may be unbridgeable by linear stability analysis; there may be a minefield of states in the gap whose linear stability is marginal. If so, they’ll require a delicate nonlinear analysis.
In any case, we know for certain that the upper bound of 0.75 is the best one can achieve by linear arguments. If the actual value of the critical connectivity turns out to be < 0.75, that will require a nonlinear argument for its proof. (We explain why in the paper.)
Caveat: our results are only for identical Kuramoto oscillators. If the oscillators are not identical, or if they are other types of dynamical systems, our analysis does not apply. Almost nothing is known about networks of generic dynamical systems. Beware of generalizing here!
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Regarding the natural place to introduce e, my preference is to wait until calculus. Once you learn that the antiderivative of x^n is x^[n+1]/(n+1), it becomes fascinating to ask: what happens when n = -1? So define L(x) as the indefinite integral of 1/x and explore it.
Doing it this way, you discover something truly amazing and beautiful: L(x) behaves like a logarithm! For instance, it obeys L(ax)=L(a)+L(x), as you can show by taking d/dx of L(ax). Once you know L is a log function, the natural question is: what is its base? Answer: call it e
Then, once e is in hand, define e^x as the inverse function to L(x). After that, you discover further wonders: e^x is its own derivative! Or as my old HS calc book (by Lynch and Ostberg) put it, e^x is "indestructible" under differentiation.
I’ve spent the morning reading this preprint: arxiv.org/abs/1805.11556. It has a story behind it. A finance person named @MarcosCarreira does math for pleasure, inspired by @CutTheKnotMath. While playing with a classic problem, he finds something weird in a famous paper about it.
It seems that Marcos discovered an error in that famous paper (by Gilbert and Mosteller) which nobody noticed until now. But I’m not an expert in probability, and it would be great if those of you who are would take a look at Marcos’s paper. It strikes as a neat piece of work.
Marcos uncovered the error by running numerical simulations and finding that his results didn’t quite match the predictions of the classic analysis. Puzzled, he redid the analysis very carefully himself, helped by Mathematica, and found a subtle mistake in the earlier work.
I just received this new book, and at a glance, it looks terrific. Very creatively conceived, written, and illustrated. I came to that conclusion after reading two pages at random. Take a look at them below and see what you think:
The teacher in me likes the question in the cloudy enclosure, and the gentle way it’s approached after that. The playful drawings help too. The question itself is really deep, and you can see the author appreciates that.
And now that the right question has been asked, we can learn what geometry and topology are really about, and the key distinction between them. Again, all this is helped by precise yet lighthearted drawings and layout.
For those pointing out that the Fibonacci sequence originated in India, yes, I agree! I learned this from Manjul Bhargava, and discussed the matter in some tweets a few years ago:
I'm teaching a course on asymptotics and perturbation methods, and thought it might be fun to share the lectures on @YouTube. Here's lecture 1, which introduces the idea of asymptotic expansions. (For more about the course, see the rest of this thread.)
Asymptotic methods and perturbation theory are clever techniques for finding approximate analytical solutions to complicated problems by exploiting the presence of a large or small parameter. This course is an introduction to such methods.
The prerequisites are a knowledge of calculus and differential equations at an undergraduate level. The course emphasizes concrete examples, intuition, and applications to science and engineering, rather than theorems, proofs, and rigor. The treatment is friendly yet careful.
In an hour, I'll meet my students in Math Explorations, a course we teach in an inquiry-based format. I LOVE this class! But like all teachers, I'm feeling the usual first-day jitters. To calm myself, I'm re-reading "The art of asking good questions": artofmathematics.org/blogs/vecke/th…
The course materials are available at the website for the wonderful "Discovering the Art of Mathematics" project artofmathematics.org. They offer 11 free books on fascinating topics like math and music, patterns, dance, games and puzzles, knots, infinity, etc. A real feast!