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Towards Quantum Software for Quantum Simulation
arXiv
Authors: Maja Franz, Lukas Schmidbauer, Joshua Ammermann, Ina Schaefer, Wolfgang Mauerer
Year
2025
Paper ID
17031
Status
Preprint
Abstract Read
~2 min
Abstract Words
190
Citations
N/A
Abstract
Quantum simulation is a leading candidate for demonstrating practical quantum advantage over classical computation, as it is believed to provide exponentially more compute power than any classical system. It offers new means of studying the behaviour of complex physical systems, for which conventionally software-intensive simulation codes based on numerical high-performance computing are used. Instead, quantum simulations map properties and characteristics of subject systems, for instance chemical molecules, onto quantum devices that then mimic the system under study. Currently, the use of these techniques is largely limited to fundamental science, as the overall approach remains tailored for specific problems: We lack infrastructure and modelling abstractions that are provided by the software engineering community for other computational domains. In this paper, we identify critical gaps in the quantum simulation software stack-particularly the absence of general-purpose frameworks for model specification, Hamiltonian construction, and hardware-aware mappings. We advocate for a modular model-driven engineering (MDE) approach that supports different types of quantum simulation (digital and analogue), and facilitates automation, performance evaluation, and reusability. Through an example from high-energy physics, we outline a vision for a quantum simulation framework capable of supporting scalable, cross-platform simulation workflows.
Why This Paper Matters
- This paper contributes to the Quantum Simulation research area in the Quantum Articles archive.
- It adds a 2025 reference point for readers tracking recent quantum research.
- Quantum simulation is a leading candidate for demonstrating practical quantum advantage over classical computation, as it is believed to provide exponentially more compute...
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