Dynamiqs: Experimental data fitting

This challenge is an introductory tutorial to the dynamiqs library. It’s intended for you to discover the main functionalities of dynamiqs with fun yet challenging examples. The physics we do at Alice&Bob is close to the hardware but we built the examples so you don’t have to worry too much about the details.

We split the challenge in two tasks:

We provide you with real experimental data and the model we used to fit it. However the parameters are not fully known yet. It’s up to you to exploit gradient descent to fit them the best you can. Keep in mind that it’s a model, so it cannot fully fit the data.

For this example your goal is to find  control sequence that will lead you to prepare highly quantum states in your system. Once again, gradient descent will be your ally in finding the optimal control sequence, but maybe you can think of other ways to meet your objectives?

For any competition-related questions, please open a topic in the discussions section.

Welcome to the wonderful world of quantum systems simulations, have fun!