Parity Quantum Optimization: Benchmarks

TL;DR

This paper benchmarks the parity transformation for QAOA, showing it requires fewer resources and offers advantages over standard models, potentially accelerating quantum advantage demonstrations.

Contribution

It provides a comprehensive analysis of the resource efficiency of parity transformation in QAOA for complex real-world problems.

Findings

Parity mapping reduces gate resources compared to standard models

Parity transformation enables full parallelization of gates

Potential to accelerate quantum advantage demonstrations

Abstract

We present benchmarks of the parity transformation for the Quantum Approximate Optimization Algorithm (QAOA). We analyse the gate resources required to implement a single QAOA cycle for real-world scenarios. In particular, we consider random spin models with higher order terms, as well as the problems of predicting financial crashes and finding the ground states of electronic structure Hamiltonians. For the spin models studied our findings imply a significant advantage of the parity mapping compared to the standard gate model. In combination with full parallelizability of gates this has the potential to boost the race for demonstrating quantum advantage.