PADQOC, high-performance solver for Quantum Optimal Control
Michael Chen
Designing control pulses to generate desired unitary evolution subjugated to experimental constraints (e.g., decoherence time, bandwidth) is a common task for quantum platforms, these type of problems are often addressed in the context of quantum optimal control. Parallel Automatic Differentiation Quantum Optimal Control (PADQOC) is an open-source, Python based general quantum optimal control solver built on top of Tensorflow 2. It is designed to be fast, extensible and useful for controlling general quantum systems.