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arXiv:2605.22980 · IEEE International Conference on Quantum Software (QSW)

Automatic De-Quantization of Quantum Programs Using Constant Propagation

Lian Remme, Alexander Weinert, Andre Waschk, Lukas Burgholzer, Robert Wille

quant-phcs.ETSubmitted May 21, 2026• Announced May 25, 2026• 0 citations
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Abstract

Quantum computing promises to solve problems beyond the reach of classical computers, but today's quantum hardware is error-prone and much slower than classical hardware. Every quantum operation is costly, making it crucial to minimize quantum resource usage in near-term algorithms. Quantum resources should only be used when they are truly essential for quantum advantage, and not wasted on operations that can be efficiently handled by classical computation. In this work, we focus on de-quantizing quantum operations to classical computation whenever possible. The approach we propose for this is hybrid quantum-classical constant propagation, an optimization which reduces quantum operations by trading them for fast, reliable classical instructions. This is done by tracking between quantum and classical states to identify and eliminate unnecessary quantum gates and controls. We formalize a hybrid state model for quantum-classical constant propagation, implement our optimizations in the open-source MQT Core tool, and evaluate them on benchmark circuits. The obtained results show that quantum-classical constant propagation can reduce costly multi-qubit operations, making quantum programs more practical and robust for near-term devices. This opens the door to new hybrid compiler strategies that leverage the best of both quantum and classical worlds.

Comments
12 pages, 10 figures, published in IEEE International Conference on Quantum Software QSW 2026

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Quantum computing promises to solve problems beyond the reach of classical computers, but today's quantum hardware is error-prone and much slower than classical hardware. Every quantum operation is costly, making it crucial to minimize quantum resource usage in near-term algorithms. Quantum resources should only be used when they are truly essential for quantum advantage, and not wasted on operations that can be efficiently handled by classical computation.
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We formalize a hybrid state model for quantum-classical constant propagation, implement our optimizations in the open-source MQT Core tool, and evaluate them on benchmark circuits.
The obtained results show that quantum-classical constant propagation can reduce costly multi-qubit operations, making quantum programs more practical and robust for near-term devices. This opens the door to new hybrid compiler strategies that leverage the best of both quantum and classical worlds.
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Quantum computing has become an increasingly relevant topic in computer science due to the development of functional quantum computers in recent years. Quantum processing units (QPUs) use quantum particles in the form of qubits as information carriers. By using properties of quantum particles, quantum algorithms have been developed that can solve problems in polynomial time, for which only exponentially scaling classical algorithms are known. QPUs will not run on their own in the foreseeable future, due to high error rates and low stability of qubits. Instead, quantum devices will be one component in a quantum-classical (hybrid) computing system (distributed system). Quantum computers embedded in distributed hybrid quantum-classical systems get instructions from a main CPU, execute them and report their results. To fully utilize quantum calculations, a QPU should be able to communicate with a CPU in real-time. This means the qubits information content should stay stable during communication time. In this thesis, we will look at quantum computing systems with real-time feedback between a QPU and a CPU. As quantum computers are going to be used in real-time hybrid systems, we need optimization routines for code running on these systems. Existing works on the optimization of quantum code focus on the optimization of quantum circuits only, and neglect potential classical calculations that are necessary on a hybrid distributed system. We want to examine which kind of optimization routines are possible and sensible for hybrid quantum-classical computations. We will evaluate some of todays quantum programming languages (QPLs), especially with respect to their ability to support and optimize real-time hybrid calculations. We will find that most languages support real-time calculations to some extent, but are more adapted to the programming approach of static circuit creation. Additionally, none of the QPLs offer optimization routines targeted at quantum-classical calculations. Therefore, we will examine options for real-time quantum-classical optimization. For this, we use the low-level QPL Quil. We will introduce optimization operations and apply them to real-time quantum-classical algorithms. We will present metrics to evaluate the performance of hybrid calculations. The results of applying our optimization operations to Quil code will be evaluated against our performance metrics. We will find that we are in principle able to optimize hybrid quantum-classical programs. We encourage more research in this field. QPLs will become more abstract in the future and need more compilation steps until they can be executed on hardware. This will make the optimization of quantum-classical hybrid code more relevant.
As the capabilities of quantum computing hardware continue to rise, algorithms that exploit them are becoming increasingly complex. These developments increase the need for sophisticated compilation frameworks that translate high-level algorithms into executable code. In the past, most solutions were built with a quantum-first approach and handled mostly pure quantum programs without classical elements such as structured control flow. However, developments in quantum algorithms, error correction, and optimization, as well as the integration into high-performance computing (HPC) environments, depend on such classical elements. As quantum-first approaches increasingly struggle to handle these concepts, classical-first approaches are becoming a promising alternative. In this work, we present the MQT Compiler Collection, a blueprint for a future-proof quantum-classical compilation framework built on the Multi-Level Intermediate Representation (MLIR). After years of experience with the quantum-first approach and its shortcomings, we propose a framework that embraces core MLIR concepts to support the full compilation pipeline from high-level algorithms to hardware-specific instructions. The proposed architecture is designed from the ground up to support complex optimizations beyond, e.g., simple gate cancellation. It is publicly available at https://github.com/munich-quantum-toolkit/core.