The Cones Package was born from my need to illustrate the position reconstruction algorithm that we use for the novel HPGe Detector Compton Scanner at MPI. However, due to its parametric form and multiple degrees of freedom, I soon realized that it could be used as an educational tool for linear algebra – or simply to create visually aesthetic gifs.

Code – in Julia – is publicly available at https://github.com/hervasa2/cones.

 
 
 

A genetic algorithm evolves random pixels to match a predetermined image. Each frame corresponds to the most competitive individual (image) in a generation. Competitive individuals are able to mix their genetic (pixel) code to create the next generation of candidates. In addition to genetic mixing, random mutations are introduced in each individual. Implementation in MATLAB. As an undergraduate exchange student at the University of Illinois at Urbana-Champaign I participated in a research team which used a genetic algorithm to control a deformable mirror. In a publication from 2017, we demonstrated that the system can be used successfully to optimize light collection from point-like sources.