# Machine Learning Meets Quantum State Preparation

These movies accompany the paper Machine Learning Meets Quantum State Preparation: The Phase Diagram of Quantum Control by Bukov et al. For the single qubit, we present three movies showing protocols found by the RL agent (Movie 1-3) and three moves for the one-parameter variational protocols (Movie 4-6) for T=0.5, 1.0, 3.0, respectively. The target state on the Bloch sphere is shown in red, while the instantaneous state - in green (cf. Fig. 2 from main text where the viewpoint is put inside the Bloch sphere). The protocol time step size is $$\delta =0.5$$. The final two movies show the learning dynamics in for a single qubit with T= 2.4 and ten coupled qubit system for T=4.0.

 Single qubit protocols learned by the RL agent. Movies 1-3 show the protocols found by the RL agent for a single qubit for protocol durations of T=0.5, 1.0, 3.0 respectively: Movie 1,Movie 2, Movie 3. Single qubit variational protocols. Movies 4-6 show variational protocols inspired found by the RL agent for a single qubit for protocol durations of T=0.5, 1.0, 3.0 respectively: Movie 4, Movie 5, Movie 6. Learning dynamics. Movies 7-8 shows the learning dynamics of the single qubuit with T=2.4 and ten coupled qubits with T=3.0, respectively. The reward in the manybody Movie 8, $$\tilde F_h(t) = 1 + \log F_h(T)/L$$, can be thought of as the fidelity per site. Movie 7, Movie 8.