Quantum adiabatic optimization for nuclear ground state

A class of processes known as quantum adiabatic optimization is used to solve optimization problems on a quantum computer. The foundation of this adiabatic quantum computing is the adiabatic theorem of quantum mechanics. The system can modify its configuration in accordance with gradually changing circumstances. If the system starts in a close approximation of the Hamiltonians ground state, it will eventually reach to its appropriate eigenstate. The quantum many-body states and operators must be converted into qubit basis states and operations using a variety of encodings and transformations to simulate the Hamiltonian H. To illustrate our approach, we have used the deuteron Hamiltonian using Jordan-Wigner transformation (JW) and then used the modified Quantum Phase Estimation (QPE) algorithm to obtain its ground state energy for various basis sizes. We have successfully used a modified Quantum Phase Estimation Algorithm to find out the convergence of a non-parameterized ansatz to an eigenstate and then obtained binding energy values for deuteron in EFT truncated at different basis sizes, using QPE. Although the method is applied to a specific problem, it can be used in general to any many-body problem