RESUMEN
We present a scalable architecture for solving higher-order constrained binary optimization (HCBO) problems on current neutral-atom hardware operating in the Rydberg blockade regime. In particular, we formulate the recently developed parity encoding of arbitrary connected HCBO problems as a maximum-weight independent set (MWIS) problem on disk graphs, that are directly encodable on such devices. Our architecture builds from small MWIS modules in a problem-independent way, crucial for practical scalability.
RESUMEN
We propose a universal gate set for quantum computing with all-to-all connectivity and intrinsic robustness to bit-flip errors based on parity encoding. We show that logical controlled phase gate and R_{z} rotations can be implemented in parity encoding with single-qubit operations. Together with logical R_{x} rotations, implemented via nearest-neighbor controlled-NOT gates and an R_{x} rotation, these form a universal gate set. As the controlled phase gate requires only single-qubit rotations, the proposed scheme has advantages for several cornerstone quantum algorithms, e.g., the quantum Fourier transform. We present a method to switch between different encoding variants via partial on-the-fly encoding and decoding.
RESUMEN
A large ongoing research effort focuses on obtaining a quantum advantage in the solution of combinatorial optimization problems on near-term quantum devices. A particularly promising platform implementing quantum optimization algorithms are arrays of trapped neutral atoms, laser coupled to highly excited Rydberg states. However, encoding combinatorial optimization problems in atomic arrays is challenging due to limited interqubit connectivity of the native finite-range interactions. Here, we present a four-body Rydberg parity gate, enabling a direct and straightforward implementation of the parity architecture, a scalable architecture for encoding arbitrarily connected interaction graphs. Our gate relies on adiabatic laser pulses and is fully programmable by adjusting two hold times during operation. We numerically demonstrate implementations of the quantum approximate optimization algorithm (QAOA) for small-scale test problems. Variational optimization steps can be implemented with a constant number of system manipulations, paving the way for experimental investigations of QAOA beyond the reach of numerical simulations.
