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Posted by shashanktomar 10/31/2025

Show HN: Strange Attractors(blog.shashanktomar.com)
I went down the rabbit hole on a side project and ended up building this: Strange Attractors(https://blog.shashanktomar.com/posts/strange-attractors). It’s built with three.js.

Working on it reminded me of the little "maths for fun" exercises I used to do while learning programming in early days. Just trying things out, getting fascinated and geeky, and being surprised by the results. I spent way too much time on this, but it was extreme fun.

My favorite part: someone pointed me to the Simone Attractor on Threads. It is a 2D attractor and I asked GPT to extrapolate it to 3D, not sure if it’s mathematically correct, but it’s the coolest by far. I have left all the params configurable, so give it a try. I called it Simone (Maybe).

If you like math-art experiments, check it out. Would love feedback, especially from folks who know more about the math side.

804 points | 78 comments
cableclasper 11/1/2025|
Visualizations like this truly highlight how much there is to be gained from viewing the 3D phase space, but also how much richness we miss in >3D!

(I wonder if there are slick ways to visualise the >3D case. Like, we can view 3D cross sections surely.

Or maybe could we follow a Lagrangian particle and have it change colour according to the D (or combination of D) it is traversing? And do this for lots of particles? And plot their distributions to get a feeling for how much of phase space is being traversed?)

This visualization also reminds me of the early debates in the history of statistical mechanics: How Boltzmann, Gibbs, Ehrenfest, Loschmidt and that entire conference of Geniuses must have all grappled with phase space and how macroscopic systems reach equilibrium.

Great work Shashank!

flatline 11/1/2025|
The conclusion I’ve come to from works like Flatland, 4D toys, etc., is that we simply don’t have the neural circuitry to grasp anything beyond three dimensions. We can reason about them, we can make inferences about the whole from partial understanding, but we cannot truly grasp more than three, or perhaps only for an instant of forced conceptualization using heuristics like you mentioned. Even three is a stretch, our minds have adapted to build a three dimensional realm from something like a 2.5 dimensional field of combined visual, tactile, and auditory stimuli. I suspect 3D reasoning itself is a huge adaptive trait compared to most other animals.
Laremere 11/1/2025|||
I've managed to visualize a Klein bottle in 4d. I easily visualize 3d objects. However I can't really do color - I startled myself recently when I briefly saw red. On that aphantasia test with an apple, I can hold it's 3d shape, but no surface texture or color.

People seem to have surprisingly different internal experiences. I don't know how common 4d visualization is, and I suspect even those capable require exposure to the concepts and practice. However I do think it possible.

cantor_S_drug 11/1/2025|||
The blind French mathematician Bernard Morin is well-known for creating the first visualization of a sphere eversion, a method for turning a sphere inside out without creasing it. His work was based on Stephen Smale's 1958 proof of sphere eversion's existence and on ideas shared by Arnold Shapiro. Morin's method involved constructing a sequence of models, including his "Morin surface," to demonstrate the process.

https://en.wikipedia.org/wiki/Bernard_Morin

soulofmischief 11/1/2025||||
Your hippocampus has several special clusters of neurons whose members activate and deactivate based on your body's understanding of your position and momentum in a 3D world.

The arrangement of these neurons physically corresponds to reality, and so things are pretty hardwired.

Repurposing these neurons might be possible with advanced training and nootropics, but I'm not sure. You might have better luck engaging other parts of your brain, for example using metaphor or abstraction such as mathematics.

d_tr 11/1/2025|||
For me, being able to visualize 4D would imply that I can picture four mutually perpendicular axes, something which I find completely impossible for me to do. And I thought it is impossible for any human brain. It would be fascinating if I am wrong.
Gooblebrai 11/1/2025||||
I've been waiting for Miegakure for ages
sorokod 11/1/2025||||
At least for 4D, would you not consider 3D-over-time as a four dimensional model? Doesn't watching the evolution as seen here allows for building up an intuition ?
tliltocatl 11/1/2025||
Well, what's interesting about 4D is that's not just an extra dimension slapped on top, it's extra rotational degrees of freedom. You can't really get that with time (at least not until you get relativistic, and it still would be hyperbolic rotation, not euclidean).
lazide 11/1/2025||
Sure you do - waves only exist in 4D as they have a time vector (frequency).
tliltocatl 11/1/2025||
What I'm talking about is something like this: https://en.wikipedia.org/wiki/Rotations_in_4-dimensional_Euc...

You can either sweep a cutting hyperplane through time or rotate a fixed projection or cut through time, but not both simultaneously.

cantor_S_drug 11/1/2025|||
Do you think an AI can learn this intuition by training it in similar environment?
vincnetas 11/1/2025|||
Can we train our neurons? Like the experiment where human vision adapted to upside down image, could our brains somehow adapt to understanding 4D data from VR headset?
gf000 11/1/2025|||
I'm sure some form of training is possible where you get a better understanding of a 4D universe with some limited inference abilities, but with a bad analogy, this would all be "software emulated" with no hardware acceleration - we only have the latter for 3D and we can't update it without a hardware change.
logicchains 11/1/2025||
With future improvements in brain-computer interfaces it might well be possible to send a 4D visual signal into the brain.
lioeters 11/1/2025|||
Yes, I believe it's possible to train our brains and learn to perceive better in higher dimensions. There's a great description in the science-fiction book Neverness, where pilots meld their minds with the spaceship computer to visualize and navigate hyperspace.
apples_oranges 11/1/2025|||
Good point, why not? Communicating it back to us could be a problem. Hmm.. what if future ais hide data from us in dimensions we can’t wrap our heads around?
chuckadams 11/2/2025||
AI already works in an N-dimensional space ... who's to say it's not happening right now?
Xophmeister 11/1/2025||
Neat :) When I was a teenager, some 25+ years ago, I wrote a chaotic attractor visualiser like this — but only in 2D — and it occurred to me, “What if instead of visualising it, I rendered it to audio?” I don’t remember the details: I think frequency was correlated with polar angle and amplitude to magnitude. It forced me to learn how to write WAV format — which was my first introduction to endianness — but the result wasn’t completely inaudible! A bit like the sound effects for computers in old sci-fi movies; random(ish) but not discordant beeps and boops!
gausswho 11/1/2025|
Along these lines there are at least two modules that I know of in Eurorack focused on strange attractors, and they're both a LOT of fun adding this kind of unpredictable-but-cyclical movement to your sounds:

- Hypster by Nonlinear Circuits (https://modulargrid.net/e/nonlinearcircuits-ian-fritz-s-hyps...)

- Orbit 3 by Joranalogue (https://modulargrid.net/e/joranalogue-audio-design-orbit-3)

atombender 11/1/2025||
I bought "Strange Attractors: Creating Patterns in Chaos" (1993) by J. C. Sprott recently, which is a fun book about these kinds of attractors. The whole book can be downloaded online [1] from the author's web site [2].

It's such a typical object of its time. Garishly colored cover, comes with a floppy disk (!) and there are even 3D glasses to view some of the stereoscopic color plates (unfortunately these were missing from the used copy I got). I was surprised to find that most of the programs are in BASIC (maybe easier to do graphics on Windows back then?), though a small number of them are in C.

It's a nice book, and the author seems to have a lot of publications about chaotic systems. Anyone know him? He seems to still be teaching at the University of Wisconsin - Madison.

[1] https://sprott.physics.wisc.edu/fractals/booktext/SABOOK.PDF

[2] https://sprott.physics.wisc.edu/

AlexeyBrin 11/1/2025||
The book software https://sprott.physics.wisc.edu/fractals/bookdisk/
johnwatson11218 11/7/2025||
I have a pdf of this book and was using LLM to translate the old code into modern, idiomatic python and it is very cool. I wonder if somebody will re-release it with modern code and tooling? In fact , google Gemini was able to do it on the fly using the posted links.
Grosvenor 10/31/2025||
This is so cool. Back in highschool during the Jurassic age I used ti play with attractors a lot. Unfortunately on a 486 it took 20-30 minutes to draw one even at low resolution. This renders in realtime and in 3D. Great work!

Still they've had a strong impact in how I see systems - orbits, instability, etc.

anjel 11/1/2025||
Fractint4life https://fractint.org/
mcswell 11/2/2025||
If that was in the Jurassic, I guess I went to high school in the Cambrian. But hey, I like trilobites!
jerf 11/1/2025||
"not sure if it’s mathematically correct,"

There isn't always "a" correct extension into higher dimensions. There may be many, there may be none, and either way something "close enough" may well be interesting in its own right.

If you'd like something concrete to poke at you can try searching around for people's adventures in trying to make a 3D Mandelbrot. I've seen a couple of good write-ups on those adventures. I don't know if anyone has ever landed on a "correct" solution, it's been years since I last looked, but certainly some very interesting possibilities have been found.

evanb 11/1/2025||
> A small change in the parameter a can lead to vastly different particle trajectories and the overall shape of the attractor. Change this value in the control panel and observe the butterfly effect in action.

I think this is slightly inaccurate. The butterfly effect is about the evolution of two nearby states in phase space into well-separated states. But the parameter a is not a state. To see the butterfly effect by changing a we would need to let the system settle down, give the parameter a small change, and then change it back. The evolution during the changed time acts as a perturbation on states.

Instead, showing that the attractor changes qualitatively as a function of the parameter is more akin to a phase transition.

aniijbod 11/1/2025||
I don't care about the math, the computation, the physics. This is just by far the most beautiful thing(s) I have ever seen.
orzig 11/1/2025||
Hobbyists hacking around and sharing their art, best part of the Internet!
srvmshr 11/1/2025||
Coincidentally enough, I dug out my 11th grade CS project on generating fractals from 2002 & modernized it using SFML graphics lib just this week.

https://github.com/gradientwolf/fractals_SFML

Your post gives me so much joy. These tiny little things take me back to teenage years, simpler times & when interests were different. (I put a little note as "why" in my GH repo readme)

shashanktomar 11/1/2025|
Thanks a lot, it was clearly worth the effort.
Libidinalecon 11/1/2025|
Really visually wonderful. I tried to self learn about nonlinear dynamics after reading about Takens's theorem last year but I have to admit, I have no idea what an attractor is actually showing like this.

This might be inspiration to try to grasp these ideas again.

Rotating the Lorenz makes me think otherwise though because given the amount of time I put into this, I should understand that much more than I do.

Chance and Chaos by David Ruelle is a wonderful little book.

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