# Optimizing Quantum Circuits, Fast and Slow

arXiv: https://arxiv.org/abs/2411.04104 · HTML: https://mlsanity.com/paper/2411.04104/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Nov 2024.

## Built on by (most cited first, 2 of 2)

- [OrQstrator: An AI-Powered Framework for Advanced Quantum Circuit Optimization](https://mlsanity.com/paper/2507.09682/) (2025)
- [AutoQuREO: A Framework for Automated Quantum Resource Estimation and Optimization](https://mlsanity.com/paper/2608.12936/) (2026)

## Abstract (arXiv)

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.