Bereiche | Tage | Auswahl | Suche | Aktualisierungen | Downloads | Hilfe
QI: Fachverband Quanteninformation
QI 14: Quantum Information Poster Session
QI 14.20: Poster
Mittwoch, 11. März 2026, 18:00–21:00, P4
GRAPE with feedback: the method and the Python package — •Pavlo Bilous1 and Florian Marquardt1,2 — 1Max Planck Institute for the Science of Light, Staudtstr. 2, 91058 Erlangen, Germany — 2Department of Physics, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91058 Erlangen, Germany
Quantum control with feedback is an essential component of modern quantum technology applications. While open-loop control tasks are usually solved using gradient methods like GRadient Ascent Pulse Engineering (GRAPE), it was until recently not clear how feedback from measurements in the control process can be integrated in these methods. Here, we discuss the "Feedback GRAPE" method introduced recently in Ref. [1] where feedback is combined with GRAPE using machine learning techniques. Given the potential use of "Feedback GRAPE" for the community, we developed an efficient GPU-accelerated Python package implementing the approach. Here we discuss our codes and showcase them on three main closed-loop tasks: state preparation with feedback, state purification and state stabilization. Using the presented examples as the starting point, the users can conveniently apply our package for their problem at hand.
[1] R. Porotti, V. Peano, and F. Marquardt, PRX Quantum 4, 030305 (2023).
Keywords: quantum control; quantum measurement; quantum feedback; machine learning; GRAPE