Large-scale quantum annealing simulation with tensor networks and belief propagation

Understand

Quantum annealing and quantum approximate optimization algorithms hold a great potential to speed-up optimization problems.

• This could be game-changing for a plethora of applications.
• Yet, in order to hope to beat classical solvers, quantum circuits must scale up to sizes and performances much beyond current hardware.
• In that quest, intense experimental effort has been recently devoted to optimizations on 3-regular graphs, which are computationally hard but experimentally relatively amenable.