Finding the ground state of a Hamiltonian system is great significance in many-body quantum physics and chemistry. We propose an improved iterative algorithm to prepare Hamiltonian. The crucial point optimize cost function on space via gradient descent (QGD) implemented devices. provide practical guideline selection learning rate QGD by finding fundamental upper bound establishing relationship ...