Digitized counterdiabatic quantum optimization

We propose digitized-counterdiabatic quantum optimization (DCQO) to achieve polynomial enhancement over adiabatic for the general Ising spin-glass model, which includes whole class of combinatorial problems. This is accomplished via digitization algorithms that are catalysed by addition non-stoquastic counterdiabatic terms. The latter suitably chosen, not only escaping classical simulability, but also speeding up performance. Finding ground state a Hamiltonian used illustrate inclusion k-local terms can always outperform traditional with stoquastic Hamiltonians. In particular, we show in ground-state success probability be achieved finite-time evolution, even simplest 2-local Furthermore, considered process, within gate-based computing paradigm, provides flexibility introduce arbitrary interactions. Along these lines, using our proposed paradigm on current NISQ computers, speed-up may reached find approximate solutions NP-complete and NP-hard expect DCQO become fast-lane towards advantage era.