Squeezing and quantum approximate optimization

Understand

Variational quantum algorithms offer fascinating prospects for the solution of combinatorial optimization problems using digital quantum computers.

• However, the achievable performance in such algorithms and the role of quantum correlations therein remain unclear.
• Here, we shed light on this open issue by establishing a tight connection to the seemingly unrelated field of quantum metrology: Metrological applications employ quantum states of spin-ensembles with a reduced variance to achieve an increased sensitivity, and we cast the generation of such squeezed states in the form of finding optimal solutions to a combinatorial MaxCut problem with an increased precision.
• By solving this optimization problem with a quantum approximate optimization algorithm (QAOA), we show numerically as well as on an IBM quantum chip how highly squeezed states are generated in a systematic procedure that can be adapted to a wide variety of quantum machines.