Coqa: Blazing Fast Compiler Optimizations for QAOA

TL;DR

Coqa introduces a specialized compiler optimization technique for QAOA circuits that leverages circuit patterns and hardware topology to significantly reduce gate count and compilation time, enhancing quantum algorithm performance.

Contribution

The paper presents a novel QAOA-specific compilation method that reduces SWAP gates and accelerates compilation by exploiting circuit patterns and hardware connectivity.

Findings

30% average reduction in gate count

39x faster compilation times

Improved fidelity of quantum computations

Abstract

The Quantum Approximate Optimization Algorithm (QAOA) is one of the most promising candidates for achieving quantum advantage over classical computers. However, existing compilers lack specialized methods for optimizing QAOA circuits. There are circuit patterns inside the QAOA circuits, and current quantum hardware has specific qubit connectivity topologies. Therefore, we propose Coqa to optimize QAOA circuit compilation tailored to different types of quantum hardware. Our method integrates a linear nearest-neighbor (LNN) topology and efficiently map the patterns of QAOA circuits to the LNN topology by heuristically checking the interaction based on the weight of problem Hamiltonian. This approach allows us to reduce the number of SWAP gates during compilation, which directly impacts the circuit depth and overall fidelity of the quantum computation. By leveraging the inherent patterns in QAOA circuits, our approach achieves more efficient compilation compared to general-purpose compilers. With our proposed method, we are able to achieve an average of 30% reduction in gate count and a 39x acceleration in compilation time across our benchmarks.