Optimizing Quantum Circuits, Fast and Slow

TL;DR

This paper introduces GUOQ, a unified framework combining fast rewriting and slow unitary synthesis techniques to optimize quantum circuits more effectively, demonstrated by superior performance on various benchmarks.

Contribution

The paper presents GUOQ, a simple algorithm that unifies rewriting and resynthesis for quantum circuit optimization, outperforming existing methods.

Findings

GUOQ outperforms existing optimizers on multiple benchmarks.

Unified framework effectively combines fast and slow optimization techniques.

Extensive evaluation confirms the efficiency of the proposed approach.

Abstract

Optimizing quantum circuits is critical: the number of quantum operations needs to be minimized for a successful evaluation of a circuit on a quantum processor. In this paper we unify two disparate ideas for optimizing quantum circuits, rewrite rules, which are fast standard optimizer passes, and unitary synthesis, which is slow, requiring a search through the space of circuits. We present a clean, unifying framework for thinking of rewriting and resynthesis as abstract circuit transformations. We then present a radically simple algorithm, GUOQ, for optimizing quantum circuits that exploits the synergies of rewriting and resynthesis. Our extensive evaluation demonstrates the ability of GUOQ to strongly outperform existing optimizers on a wide range of benchmarks.