Multi-round QAOA and advanced mixers on a trapped-ion quantum computer

TL;DR

This paper demonstrates that multi-round QAOA and advanced mixing Hamiltonians on a trapped-ion quantum computer enhance solution quality and sampling capabilities for combinatorial optimization problems, advancing practical quantum computing applications.

Contribution

The study introduces multi-round QAOA implementation and an advanced mixing Hamiltonian on a trapped-ion quantum computer, improving solution sampling for combinatorial optimization.

Findings

QAOA results improve with more rounds on various graphs.

Advanced mixing Hamiltonian enables sampling of all optimal solutions.

Experimental validation on a trapped-ion quantum computer.

Abstract

Combinatorial optimization problems on graphs have broad applications in science and engineering. The Quantum Approximate Optimization Algorithm (QAOA) is a method to solve these problems on a quantum computer by applying multiple rounds of variational circuits. However, there exist several challenges limiting the real-world applications of QAOA. In this paper, we demonstrate on a trapped-ion quantum computer that QAOA results improve with the number of rounds for multiple problems on several arbitrary graphs. We also demonstrate an advanced mixing Hamiltonian that allows sampling of all optimal solutions with predetermined weights. Our results are a step towards applying quantum algorithms to real-world problems.