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arXiv:2608.04081

Guiding Compiler Optimizations for Neutral Atom Quantum Computers Through Visualizations

Yannick Stade, Robert Wille

quant-phcs.ETSubmitted Aug 4, 2026• Announced Aug 6, 2026• 0 citations
arXivHTMLPDF

Abstract

The scale of Neutral Atom (NA) quantum computers requires automated compilation tools. Designing the required heuristic methods demands a deep understanding of complex hardware trade-offs, for which visualizations can provide crucial insights. This work introduces NAViz, the first publicly available app to visualize quantum computations on NA devices in real-time. A case study demonstrates how NAViz was instrumental in identifying and resolving inefficiencies in an existing compilation strategy, leading to a new, more performant one. The tool is available as part of the Munich Quantum Toolkit (MQT) at https://github.com/munich-quantum-toolkit/naviz.

Comments
2 pages, 2 figures

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The scale of Neutral Atom (NA) quantum computers requires automated compilation tools. Designing the required heuristic methods demands a deep understanding of complex hardware trade-offs, for which visualizations can provide crucial insights. This work introduces NAViz, the first publicly available app to visualize quantum computations on NA devices in real-time. A case study demonstrates how NAViz was instrumental in identifying and resolving inefficiencies in an existing compilation strategy, leading to a new, more performant one. The tool is available as part of the Munich Quantum Toolkit (MQT) at https://github.com/munich-quantum-toolkit/naviz.
Zoned neutral atom architectures are emerging as a promising platform for large-scale quantum computing. Their growing scale, however, creates a critical need for efficient and automated compilation solutions. Yet, existing methods fail to scale to the thousands of qubits these devices promise. State-of-the-art compilers, in particular, suffer from immense memory requirements that limit them to small-scale problems. This work proposes a scalable compilation strategy that "searches smarter, not harder". We introduce Iterative Diving Search (IDS), a goal-directed search algorithm that avoids the memory issues of previous methods, and relaxed routing, an optimization to mitigate atom rearrangement overhead. Our evaluation confirms that this approach compiles circuits with thousands of qubits and, in addition, even reduces rearrangement overhead by 28.1% on average. The complete code is publicly available in open-source as part of the Munich Quantum Toolkit (MQT) at https://github.com/munich-quantum-toolkit/qmap.
Quantum computing promises to solve previously intractable problems, with neutral atoms emerging as a promising technology. Zoned neutral atom architectures allow for immense parallelism and higher coherence times by shielding idling atoms from interference with laser beams. However, in addition to hardware, successful quantum computation requires sophisticated software support, particularly compilers that optimize quantum algorithms for hardware execution. In the compilation flow for zoned neutral atom architectures, the effective interplay of the placement and routing stages decides the overhead caused by rearranging the atoms during the quantum computation. Suboptimal placements can lead to unnecessary serialization of the rearrangements in the subsequent routing stage. Despite this, all existing compilers treat placement and routing independently thus far—focusing solely on minimizing travel distances. This work introduces the first routing-aware placement method to address this shortcoming. It groups compatible movements into parallel rearrangement steps to minimize both rearrangement steps and travel distances. The implementation utilizing the A* algorithm reduces the rearrangement time by 17% on average and by 49% in the best case compared to the state-of-the-art. The complete code is publicly available in open-source as part of the Munich Quantum Toolkit (MQT) at https://github.com/cda-tum/mqt-qmap.
Quantum computing promises to solve problems previously deemed infeasible. However, high error rates necessitate quantum error correction for practical applications. Seminal experiments with zoned neutral atom architectures have shown remarkable potential for fault-tolerant quantum computing. To fully harness their potential, efficient software solutions are vital. A key aspect of quantum error correction is the initialization of physical qubits representing a logical qubit in a highly entangled state. This process, known as state preparation, is the foundation of most quantum error correction codes and, hence, a crucial step towards fault-tolerant quantum computing. Generating a schedule of target-specific instructions to perform the state preparation is highly complex. First software tools exist but are not suitable for the zoned neutral atom architectures. This work addresses this gap by leveraging the computational power of SMT solvers and generating minimal schedules for the state preparation of logical arrays. Experimental evaluations demonstrate that actively utilizing zones to shield idling qubits consistently results in higher fidelities than solutions disregarding these zones. The complete code is publicly available in open-source as part of the Munich Quantum Toolkit (MQT) at https://github.com/cdatum/mqt-qmap.
Recent experimental achievements have demonstrated the potential of neutral atom architectures for fault-tolerant quantum computing. These architectures feature the dynamic rearrangement of atoms during computation-enabling nearly arbitrary two-dimensional rearrangements. Additionally, they employ a zoned layout with dedicated regions for entangling, storage, and readout. This architecture requires design automation software that efficiently compiles quantum circuits to this hardware and takes care that atoms are in the right place at the right time. In this paper, we initiate this line of work by providing, (1) an abstract model of the novel architecture and, (2) an efficient solution to the routing problem of entangling gates. By this, we aim to maximize the parallelism of entangling gates and minimize the overhead caused by the routing of atoms between zones. In addition to that, we keep the realm of fault-tolerant quantum computing in mind and consider logical qubit arrays, each of which encodes one logical qubit. We implemented the proposed idea as a tool called NALAC and demonstrated its effectiveness and efficiency by showing that it can significantly reduce the routing overhead of logical entangling gates compared to the naive approach. As part of the Munich Quantum Toolkit (MQT), NALAC is publicly available as open-source at https://github.com/cda-tum/mqt-qmap.
With quantum computers promising advantages even in the near-term NISQ era, there is a lively community that develops software and toolkits for the design of corresponding quantum circuits. Although the underlying problems are different, expertise from the design automation community, which developed sophisticated design solutions for the conventional realm in the past decades, can help here. In this respect, decision diagrams provide a promising foundation for tackling many design tasks such as simulation, synthesis, and verification of quantum circuits. However, users of the corresponding tools often do not have a proper background or an intuition about how these methods based on decision diagrams work and what their strengths and limits are. In this work, we first review the concepts of how decision diagrams can be employed, e.g., for the simulation and verification of quantum circuits. Afterwards, in an effort to make decision diagrams for quantum computing more accessible, we then present a visualization tool for quantum decision diagrams, which allows users to explore the behavior of decision diagrams in the design tasks mentioned above. Finally, we present decision diagram-based tools for simulation and verification of quantum circuits using the methods discussed above as part of the open-source Munich Quantum Toolkit (MQT)—a set of tools for quantum computing developed at the Technical University of Munich and the Johannes Kepler University Linz and released under the MIT license. More information about the corresponding tools is available at https://github.com/cda-tum/ddsim . By this, we provide an introduction of the concepts and tools for potential users who would like to work with them as well as potential developers aiming to extend them.
Quantum computers are becoming a reality and numerous quantum computing applications with a near-term perspective (e.g., for finance, chemistry, machine learning, and optimization) and with a long-term perspective (e.g., for cryptography or unstructured search) are currently being investigated. However, designing and realizing potential applications for these devices in a scalable fashion requires automated, efficient, and user-friendly software tools that cater to the needs of end users, engineers, and physicists at every level of the entire quantum software stack. Many of the problems to be tackled in that regard are similar to design problems from the classical realm for which sophisticated design automation tools have been developed in the previous decades.The Munich Quantum Toolkit (MQT) is a collection of software tools for quantum computing developed by the Chair for Design Automation at the Technical University of Munich which explicitly utilizes this design automation expertise. Our overarching objective is to provide solutions for design tasks across the entire quantum software stack. This entails high-level support for end users in realizing their applications, efficient methods for the classical simulation, compilation, and verification of quantum circuits, tools for quantum error correction, support for physical design, and more. These methods are supported by corresponding data structures (such as decision diagrams or the ZX-calculus) and core methods (such as SAT encodings/solvers). All of the developed tools are available as open-source implementations and are hosted on github.com/cda-tum.Note: A live version of this document is available at mqt.readthedocs.io.