What's the nicest way to draw a shape with many "holes"?
We can use the principle of repulsion to explore this question: each point of the shape behaves like a charged particle, trying to repel all others. Surface tension prevents everything from shooting off to infinity. 1/n
For millennia people have been drawn to the question: what are the "nicest" possible shapes that exist?
This is really a basic question about nature: these shapes exist outside space and time; the same shapes can be discovered by civilizations anywhere in the universe. 2/n
"Nicest" could mean the most symmetric—for instance, the ancient Greeks discovered there were five so-called Platonic solids where every face and every vertex looks the same: the tetrahedron, cube, octahedron, dodecahedron, and icosahedron. 3/n
Or, "nicest" could mean smoothest.
For instance, according to one criterion (minimum total bending) the smoothest shape with no holes is a round sphere; the smoothest shape with one hole is a perfectly round donut with a certain ratio of inner/outer radii ("Clifford torus"). 4/n
In fact, this principle of least bending even shows up inside the human body. For instance, the shape of red blood cells is extremely well-predicted by minimizing bending among all shapes with a given volume (due to fluid pressure) and surface area (due to surface tension). 5/n
However, shapes that minimize total bending—formally known as "Willmore energy"—don't look as nice if you start adding more holes.
The conjectured minimizers, called "Lawson surfaces," feel pretty asymmetrical compared to how one might imagine an "ideal" shape with holes. 6/n
The reason is that Willmore energy doesn't look for shapes that are nice & symmetrical in the ordinary 3-dimensional space where we live (Euclidean space).
Instead, it considers symmetry relative to the "3-sphere": the set of all points unit distance from the origin in 4D. 7/n
So to get nicer shapes with holes, we can take a different approach.
We look for shapes that minimize the so-called "tangent-point energy," which tries to keep all pairs of points far away from each other—much like the repulsive Coulomb forces exerted by electrons. 8/n
Of course, in the absence of any other forces, two electrons will just shoot off to infinity.
Likewise, to keep our shape from exploding, we need additional forces to hold it together—like the force of surface tension which gives water droplets their nice round shapes. 9/n
Starting with several donuts glued together along a straight line, we then make small changes that gradually reduce tangent-point energy. The final shapes tend to look a lot more "natural" than the Lawson surfaces—often exhibiting the same symmetries as the Platonic solids! 10/n
These shapes were found using the algorithm described in
Entropy is one of those formulas that many of us learn, swallow whole, and even use regularly without really understanding.
(E.g., where does that “log” come from? Are there other possible formulas?)
Yet there's an intuitive & almost inevitable way to arrive at this expression.
When I first heard about entropy, there was a lot of stuff about "free states" and "disorder." Or about the number of bits needed to communicate a message.
These are ultimately important connections—but it's not clear it's the best starting point for the formula itself.
A better starting point is the idea of "surprise."
In particular, suppose an event occurs with probability p. E.g., if the bus shows up on time about 15% of the time, p = 0.15.
How *surprising*, then, is an event with probability p? Let's call this quantity S(p).
We often think of an "equilibrium" as something standing still, like a scale in perfect balance.
But many equilibria are dynamic, like a flowing river which is never changing—yet never standing still.
These dynamic equilibria are nicely described by so-called "detailed balance"
In simple terms, detailed balance says that if you have less "stuff" at point x, and more "stuff" at point y, then to maintain a dynamic equilibrium, the fraction of stuff that moves from x to y needs to be bigger than the fraction that moves from y to x.
Detailed balance is also the starting point for algorithms that efficiently generate samples of a given distribution, called "Markov chain Monte Carlo" algorithms.
The idea is to "design" a random procedure that has the target distribution as the equilibrium distribution.
Even though Newton's laws are deterministic, the behavior of many interacting bodies is so chaotic that it looks essentially "random."
Statistical mechanics effectively says: why bother with all those complex trajectories? Just go ahead and replace them with truly random motion.
A good way to think about the difference is to imagine actually simulating the particles.
With Newtonian simulation, you track both positions & velocities. Velocities increase or decrease according to forces (like attraction/repulsion); positions are then updated by velocities.
With (overdamped) Langevin simulation, you track just the positions. Positions follow the same forces (i.e., the potential gradient), plus some random "noise" that models all that chaotic motion.
Near equilibrium, these two simulators yield motions with very similar statistics.
I work on fundamental algorithms for geometric and visual computing. Here's a taste of our group's work, as a list of "explainer" threads posted on Twitter/X over the years. (🧵)
Signed distance functions (SDFs) are an important surface representation, which can be directly visualized via the “sphere tracing” algorithm.
At #SIGGRAPH2024 we showed how to sphere trace a whole new class of surfaces, based on *harmonic functions* rather than SDFs. [1/n]
Harmonic functions are everywhere in geometric & visual computing, as well as in math, engineering, and physics. So, it's pretty powerful to be able to visualize them directly.
We show how they open up a variety of applications beyond what people currently do with SDFs. [2/n]
For instance, want to visualize a point cloud as a smooth surface?
Don't need to run a reconstruction algorithm (or fit a neural net): just trace some rays, and voila! [3/n]