alt Hacker NewsI’m building a quantum photonics experiment that is a variation of the quantum eraser.
One aspect that HN may find interesting is my use of Bayesian optimization to control and perfect key experimental settings. About a dozen of the wave plates and other optical components are motorized and under computer control.
Given a goal metric like "maximally entangle the photon pairs" the optimizer will run the experiment 50-100 times, tweaking the angles of various optics and collecting data. Ultimately it will learn to maximize the given cost function.
This sort of thing is commonly done with tools like Optuna during NN/LLM training to optimize hyper-parameters, but seems less common in physics especially quantum photonics. I'm using a great tool called M-loop to drive the optimization, which was originally developed for creating Bose-Einstein condensates.