Investigation of Poly-QAOA (multi-QAOA, multi-Δt) Trotter “Steps”

Advances in quantum information processing for noisy intermediate scale quantum devices have improved quantum chemistry applications, but limitations in Suzuki-Trotter (ST) methods are still difficult to find some functional Δt. One method to select an optimal set of Trotter steps is to generalize QAOA with continuous-time quantum walks like the Quantum Walk-based Optimization Algorithm (QWOA). However, implementing a full QWOA may be too intensive, and a multi-QAOA, multi-Δt (“poly-QAOA”) may be more appropriate for some devices and quantum chemistry modeling, such as a molecular complex. Several recent Trotterization automation of target Hamiltonians for benchmarking QPUs, such as HamLib integration tool suites, make poly-QAOA experiments easier. Our experimental modifications of QAOA MaxCut Hamiltonians in our poly-QAOA investigate the realism of Hamiltonian simulation on classical and quantum hardware, may reveal persistent error types, and also could demonstrate the utility of progressively iterating through practical Trotter step count numbers (as a hyperparameterized Δt) for various quantum chemistry and proteomics problems efficiently. This approach may ultimately pave a roadmap for further R&D towards a totally quantum function for multi-core/multi-modal QPUs.