More from Bartosz Ciechanowski
In the vastness of empty space surrounding Earth, the Moon is our closest celestial neighbor. Its face, periodically filled with light and devoured by darkness, has an ever-changing, but dependable presence in our skies. In this article, we’ll learn about the Moon and its path around our planet, but to experience that journey first-hand, we have to enter the cosmos itself. This article has many interactive demonstrations which are best seen on the website.
The dream of soaring in the sky like a bird has captivated the human mind for ages. Although many failed, some eventually succeeded in achieving that goal. These days we take air transportation for granted, but the physics of flight can still be puzzling. In this article we’ll investigate what makes airplanes fly by looking at the forces generated by the flow of air around the aircraft’s wings. More specifically, we’ll focus on the cross section of those wings to reveal the shape of an airfoil – you can see it presented in yellow below: This article has many interactive demonstrations which are best seen on the website.
Invisible and relentless, sound is seemingly just there, traveling through our surroundings to carry beautiful music or annoying noises. In this article I’ll explain what sound is, how it’s created and propagated. Throughout this presentation you will be hearing different sounds, which you will often play yourself on little keyboards like the one below. You can either click its keys with your mouse or use WER keys on your computer keyboard, but before you do so make sure your system volume is at a reasonable level:You can press its keys with your fingers, but before you do so make sure your system volume is at a reasonable level. This article has many interactive demonstrations which are best seen on the website.
In the world of modern portable devices, it may be hard to believe that merely a few decades ago the most convenient way to keep track of time was a mechanical watch. Unlike their quartz and smart siblings, mechanical watches can run without using any batteries or other electronic components. Over the course of this article I’ll explain the workings of the mechanism seen in the demonstration below. You can drag the device around to change your viewing angle, and you can use the slider to peek at what’s going on inside: This article has many interactive demonstrations which are best seen on the website.
More in science
The physicist Sidney Nagel delights in solving mysteries of the universe that are hiding in plain sight. The post Finding Beauty and Truth in Mundane Occurrences first appeared on Quanta Magazine
Federal enforcement of environmental laws has slowed significantly under President Trump. Read more on E360 →
Earlier today I gave a talk in the graduate student seminar titled “Counting is Hard. Complex Analysis is Easy.” based in part on my recent blog post about analytic combinatorics and based in part on Varilly’s notes on Dirichlet’s Theorem, showing how to count the number of trees of a certain shape and the number of “primes of a certain shape” by doing complex analysis. While prepping for this talk, I realized there’s a very pretty geometric way to see what’s going on when counting rooted ordered ternary trees! I don’t usually write blog posts about my local seminar talks anymore, but I think this is more than worthy of an exception! For instance, I think this could serve as a great visiual example of branches and mild singularities in complex analysis. So, let’s remember the problem! We want to count the number of rooted ordered ternary trees with $n$ nodes. Call this number $t_n$. We note that every such tree is either a root node a root with one child a root with two children a root with three children where each child is recursively a rooted ordered ternary tree. If we define $T(z) = \sum_n t_n z^n$ to be the (ordinary) generating function for the $t_n$ we see from this recurrence relation that it must satisfy the functional equation That is, if $P(z,w) = -w + z + zw + zw^2 + zw^3$ then $P(z,T(z)) = 0$. If we draw (the real locus of) $P$ it looks like and the implicit function theorem says that we can find functions $f(z)$ so that $P(z,f(z)) = 0$ through any starting point $P(z_0,f_0)$ on the curve for as long as $\frac{\partial P}{\partial w} \neq 0$. In particular, we know that our $T(0) = t_0 = 0$ since there are no trees with zero vertices, so that our $T(z)$ takes $z$ to the unique part of this curve passing through the origin, for as long as this is defined. Here we’ll plot our curve $P$ in blue, and the implicit function $T(z)$ in orange. Note we have to stop at $z \approx 0.27695$ since here $\frac{\partial P}{\partial w} = 0$ so that the slope is infinite and we can’t continue. Said another way, we bend backwards and if we tried to continue we would fail the vertical line test. But since we have to stop here, we see that $0.27695$ is the radius of convergence for $T$, and is the dominant singularity! Next, can we find a good approximation for $T$ near this singularity? In the main post we used puiseux series for this, but it’s instructive to do it by hand! Note that $\frac{\partial P}{\partial z} \neq 0$ at $(0.27695, 0.65730)$ so there’s nothing stopping us from approximating $z$ as a function of $w$ at this point (then inverting it). Indeed, we can solve for $z = \frac{w}{1+w+w^2+w^3}$ and then just taylor expand this at our point of interest: Of course, we chose this point because $\frac{\mathrm{d}z}{\mathrm{d}w} = \frac{- \frac{\partial P}{\partial w}}{\frac{\partial P}{\partial z}}$ is $0$ here. So we know this $2.97 \times 10^{-8}$ is a rounding error and our leading order expansion is Here’s a graph zoomed into near the singularity. The actual graph of $P$ is shown in blue, and our approximating parabola is shown in orange: But of course if $z - 0.27695 \approx -.34680 (w - 0.6573)^2$ then we can solve for and if we want this to agree with our $w = T(z)$ branch through the origin we obviously have to choose the negative square root (since we want the lower half of this sideways parabola1). Here we draw our $T(z)$ in blue, and we draw the approximation $0.6573 - 0.8936 \sqrt{1 - \frac{z}{0.27695}}$ in orange so you can see how well they line up! But now from here we can run exactly the same argument as in the previous post! We compute $t_n = \frac{1}{2\pi i} \oint \frac{T}{z^{n+1}} \ \mathrm{d}z$, along a keyhole contour around the singular point $z=0.27695$ with a branch cut along the real axis. The brunt of this integral comes from the cutout near the singular point, where $T$ is well approximated by $0.6573 - 0.8936 \sqrt{1 - \frac{z}{0.27695}}$ so that Again, for more details about exactly what this keyhole contour is and how you estimate this integral along it, see the main post. Let’s go ahead and call it here! My actual talk was slightly longer than this, since I also sketched a proof of Dirichlet’s Theorem following Varilly’s notes on the subject, but there’s no sense in me writing that up since those notes are already so good! Plus it’s getting late and I want to go to bed, haha. As always, here’s a copy of my title and abstract. Unfortunately I don’t have any slides or recordings today, but I’m giving another talk at WiSCons in Madison next week and I should have slides for that. I’m also hoping to finish a sister blog post for that talk where I do more example computations in more detail than I could possibly do in a 20 minute talk. Lots of writing to do this week! Take care all, stay safe, and I can’t wait to talk soon ^_^ Counting is Hard. Complex Analysis is Easy. Don’t you miss being a kid, when your mom would ask you to count how many of your alphabet fridge magnets were both red and vowels? When you saw the answer was “2”, you felt such accomplishment…. But counting has only gotten harder since then, and now if you want to count how many objects satisfy some properties (say, being both red and vowels) it can be borderline impossible! In this talk we’ll show how you can solve counting problems by doing complex analysis instead. First we’ll count the number of trees of a certain shape, then (given time) we’ll count how many prime numbers are of a (different) certain shape. In the main post we used puiseux series for this, and we had to essentially guess which branch was correct. Now we see how the geometry of the situation tells us that we have to choose the negative branch of the square root! After all, this is the one that locally agrees with the rest of the graph of $T$! ↩
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