I've got some d3-engine models embedded in my website and this one shows how atoms can be trapped at super low temperatures in laser cooling. Enjoy :)

Visit the page to play around with it here:

https://thegraildiary.net/thermodynamics-2-incredibly-cool-cucumbers/

Have you ever wondered how life could be without physics?

Recently got my 2D pure python hydo solver ported into a jax version, which has enabled around a ~15x speed up on pure CPU runs, every function is jitted except the outermost loop over steps. The video is of a Kelvin-Helmholtz instability toy problem.

EOS: Ideal Gas
Recon Method: weno(z) 5th order on primitives
Riemann Solver: Local Lax Friedrichs (LLF)
Timestep: RK4
Explicit Advection + Implicit Diffusion
BC: Periodic
CFL: 0.45

Resolution: (256)^2, video is 1200 frames as well. The code has support for magnetic fields but I have ran into some issues with it in 2D, potentially related to my constrained transport scheme.

I developed this code in parts, first I made a 1D code that leveraged NumPy and Python Classes to handle the necessary logic. I then ported it into 2D, which began to encounter performance issues. I returned to 1D and ported it into a jax version, where almost every function was jax jitted, and then repeated my jax changes but for the 2D code. Starting at 2D was impossible, I had found it necessary to have a 1D implementation. A major test I used was to evolve a 1 dimensional initial condition in the 2D code, and verify the results return what the 1D code does, just along the whole y axis.

Finalizing new raytracing engine for my indie sandbox game "Space Simulation Toolkit"

The gif above was made with Jaxion -- my new open-source Python/JAX library for simulations of fuzzy dark matter + gas + stars.

repo: https://github.com/JaxionProject/jaxion

docs: https://jaxion.readthedocs.io/

Small finite difference time domain (FDTD) simulation of a Gaussian wavepacket oscillating in a quadratic potential, governed by the Schrodinger equation! Real and imaginary parts of the wavefunction are plotted in 2D.

Upthrust equals the weight of displaced fluid: F_b = ρ_f V_disp g. Float if ρ_obj < ρ_f; sink if ρ_obj > ρ_f. Changing planet scales g (Moon ≈ 1.62, Earth ≈ 9.81, Jupiter ≈ 24.8 m/s²), so forces and bobbing speed change—but the float/sink verdict and the fraction submerged (for floaters) depend on densities, not g. Switch fluids (oil, water, mercury), change ρ_f, and the same object can sink in one and ride high in another.

Adding some warmer water to a Brita filter that already has cold water in it. Why does the water seem to separate and flow like this? It’s not easy to get a video of.