Speaker
Annarita Scocco
(Scuola Superiore Meridionale)
Description
Adiabatic quantum computation and quantum annealing exploit
slow quantum evolutions to solve hard problems in different areas. Long-time dynamics are often infeasible and leave the system more prone to noise. Therefore we present a numerical approach based on genetic algorithms to speed up quantum annealing, optimizing the annealing schedules starting from the polynomial ansatz and exploiting shortcuts to adiabaticity. With this genetically optimized annealing schedules and/or optimal driving operators, we are able to perform quantum annealing in relatively short timescales and with higher fidelity compared to traditional approaches.
