1 code implementation • 2 Mar 2023 • Jiaqi Leng, Ethan Hickman, Joseph Li, Xiaodi Wu
We propose Quantum Hamiltonian Descent (QHD), which is derived from the path integral of dynamical systems referring to the continuous-time limit of classical gradient descent algorithms, as a truly quantum counterpart of classical gradient methods where the contribution from classically-prohibited trajectories can significantly boost QHD's performance for non-convex optimization.
