Progress towards analytically optimal angles in quantum approximate optimisation

Understand

The Quantum Approximate Optimisation Algorithm is a $p$ layer, time-variable split operator method executed on a quantum processor and driven to convergence by classical outer loop optimisation.

• The classical co-processor varies individual application times of a problem/driver propagator sequence to prepare a state which approximately minimizes the problem's generator.
• Analytical solutions to choose optimal application times (called angles) have proven difficult to find, whereas outer loop optimisation is resource intensive.
• Here we prove that optimal Quantum Approximate Optimisation Algorithm parameters for $p=1$ layer reduce to one free variable and in the thermodynamic limit, we recover optimal angles.