A small lab for simulation and modeling. The work is written in Rustlab, a fast language in the spirit of MATLAB, and checked by running it.
Rustlab is a matrix algebra and DSP toolkit written in Rust. It is built to be fast and lean: scripts, a REPL, and a library you can embed. The syntax stays close to MATLAB, with ranges, elementwise operators, and plots, so a model reads like the math.
It is meant to be used with AI tools. Ask for an explanation of a hard problem and get a program you can run, plot, and correct, instead of a paragraph you have to trust.
a = 1:5
b = a .* a
print(b)A new worked example, about once a week, written for electrical engineers and scientists. Each page is a Rustlab notebook: the code ran, and the plots and the numbers are the output.
What a two-port measurement says about a low-noise amplifier. Rollett’s K and the µ stability factors, the simultaneous conjugate match, maximum available gain, stability and constant-gain circles on the Smith chart, then a time-domain step response and mixed-mode S-parameters.
Rustlab LLM is a tutorial that builds a language model from the ground up in Rustlab. Each lesson pairs the mathematics with a script and a plot, from tokens and probability through a GPT-style decoder. Nothing is left as a black box.
The rendered lessons, with output and figures, can be read on GitHub without installing anything.
The same approach is being used for quantum computing. States, gates, and small algorithms are written as linear algebra in Rustlab, so the calculation is visible and can be rerun. The point is to see how a quantum step works, not to hide it behind a framework.