IQSOFT 2025 Abstracts

Area 1 - Hybrid Quantum /Classical Software

Full Papers

Paper Nr:	14
Title:	Warm-Starting the VQE with Approximate Complex Amplitude Encoding
Authors:	Felix Truger, Johanna Barzen, Frank Leymann and Julian Obst
Abstract:	The Variational Quantum Eigensolver (VQE) is a Variational Quantum Algorithm (VQA) to determine the ground state of quantum-mechanical systems. As a VQA, it makes use of a classical computer to optimize parameter values for its quantum circuit. However, each iteration of the VQE requires a multitude of measurements, and the optimization is subject to obstructions, such as barren plateaus, local minima, and subsequently slow convergence. We propose a warm-starting technique, that utilizes an approximation to generate beneficial initial parameter values for the VQE aiming to mitigate these effects. The warm-start is based on Approximate Complex Amplitude Encoding, a VQA using fidelity estimations from classical shadows to encode complex amplitude vectors into quantum states. Such warm-starts open the path to fruitful combinations of classical approximation algorithms and quantum algorithms. In particular, the evaluation of our approach shows that the warm-started VQE reaches higher quality solutions earlier than the original VQE.
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Paper Nr:	18
Title:	Parameter Transfers for Warm-Started QAOA
Authors:	Julian Obst, Felix Truger, Johanna Barzen and Frank Leymann
Abstract:	Variational Quantum Algorithms (VQAs) run shallow parameterized quantum circuits on quantum devices and are thus suitable for current limited hardware. However, adverse effects like barren plateaus and local optima may hinder the classical parameter optimization. Warm-starting techniques attempt to alleviate such problems by utilizing pre-computed approximations or known solutions to initialize VQAs. In this work, we analyze a combination of two different kinds of warm-starts, based on biased initial states and parameter transfers, respectively. In particular, we investigate a warm-started variant of the Quantum Approximate Optimization Algorithm (WS-QAOA) applied to the MAXCUT problem and analyze the transferability of optimized parameter values between random graphs. We leverage their decomposition into subgraphs and regularities among these subgraphs to facilitate parameter transfers for WS-QAOA and demonstrate a transfer for a random graph.
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Short Papers

Paper Nr:	33
Title:	Architectural Design and Orchestration of Heterogeneous Quantum-Classical Computing Systems
Authors:	J.A. Bravo-Montes, Miriam Bastante and Cyril Allouche
Abstract:	This study presents a comprehensive multilevel software architecture for integrating quantum and classical computing systems in High-Performance Computing environments. The proposed software architecture implements a hierarchical approach that seamlessly connects quantum circuit development with execution in both emulated and physical quantum processors. The system is structured in distinct layers: a Circuit Generator interface, HPC programming environment with specialized APIs and tools, NISQ calibration layer for managing quantum noise, and an integration layer that orchestrates the hybrid workload distribution. We demonstrate the implementation of this architecture in two leading European supercomputing facilities: the TGCC and the JSC. These implementations showcase the capability of the architecture to manage hybrid quantum-classical work-flows, incorporating both local and remote QPUs while maintaining security and efficiency. The effectiveness of the architecture was validated through implementation of the VQE algorithm, demonstrating its practical application. The results highlight the architecture’s ability to efficiently manage heterogeneous computational resources, provide secure access to quantum hardware, and facilitate the development and execution of hybrid quantum-classical algorithms. This study contributes to the advancement of quantum computing integration in HPC environments, providing a scalable framework for future quantum applications.
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Paper Nr:	30
Title:	Exploring the Challenges of Hybrid Software with Quantum Design Patterns
Authors:	Miriam Fernández-Osuna and Ricardo Pérez-Castillo
Abstract:	Quantum computing has emerged as a new paradigm to solve several complex problems that are intractable for classical computers. This technology is being applied in areas such as optimization and cybersecurity, but its integration with classical software presents several challenges. One approach to overcome these obstacles is the adoption of design patterns, like those used in classical software, which could improve the scalability and maintainability of quantum systems. However, there is still a need to formalize architectural patterns that support this integration. Furthermore, quantum-classical software design can lead to problems that affect its quality, which highlights the importance of detecting and correcting them in time. This study presents an analysis and discussion of the challenges faced by hybrid software architectures such as problem modelling as well as dynamic generation of quantum circuits, execution orchestration, problem partitioning and interpretation of quantum results. The study of these challenges will serve as a starting point for proposing design patterns for hybrid software architectures.
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Area 2 - Quantum Software and AI

Full Papers

Paper Nr:	17
Title:	Periodic Unitary Encoding for Quantum Anomaly Detection of Temporal Series
Authors:	Daniele Lizzio Bosco, Riccardo Romanello and Giuseppe Serra
Abstract:	Anomaly detection in temporal series is a compelling area of research with applications in fields such as finance, healthcare, and predictive maintenance. Recently, Quantum Machine Learning (QML) has emerged as a promising approach to tackle such problems, leveraging the unique properties of quantum systems. Among QML techniques, kernel-based methods have gained significant attention due to their ability to effectively handle both supervised and unsupervised tasks. In the context of anomaly detection, unsupervised approaches are particularly valuable as labeled data is often scarce. Nevertheless, temporal series data frequently exhibit known seasonality, even in unsupervised settings. We propose a novel quantum kernel designed to incorporate seasonality information into anomaly detection tasks. Our approach constructs a Hamiltonian matrix that induces a unitary operator which period corresponds to the seasonality of the task under consideration. This unitary operator is then used to encode the data into the quantum kernel, ensuring that values sampled at instants equivalent under the period are treated consistently by the kernel. We evaluate the proposed method on an anomaly detection task for temporal series, demonstrating that embedding seasonality directly into the quantum kernel generation improves the overall performance of quantum kernel-based support vector machines.
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Short Papers

Paper Nr:	24
Title:	Is Data-Reuploading Really a Cheat Code? An Experimental Analysis
Authors:	Danel Arias Alamo, Sergio Hernández López and Javier Lázaro González
Abstract:	Data Reuploading has been proposed as a generic embedding strategy in Variational Quantum Circuits (VQCs), offering a systematic approach to encoding classical data without the need for problem-specific circuit design. Prior studies have suggested that increasing the number of reuploading layers enhances model performance, particularly in terms of expressibility. In this paper, we present an experimental analysis of Data Reuploading, systematically evaluating its impact on expressibility, trainability, and completeness in classification tasks. Our results indicate that while adding some reuploading layers can improve performance, excessive layering does not lead to expressibility gains and introduces barren plateaus, significantly hindering trainability. Consequently, although Data Reuploading can be beneficial in certain scenarios, it is not a ”cheat code” for optimal quantum embeddings. Instead, the selection of an effective embedding remains an open problem, requiring a careful balance between expressibility and trainability to achieve robust quantum learning models.
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Area 3 - Quantum Software and Engineering

Full Papers

Paper Nr:	22
Title:	AssertsQ: A Quantum Assertion Tool for Quantum Software Debugging
Authors:	Javier Ibarra Veganzones, Danel Arias Alamo, Alfredo Cuzzocrea and Pablo García Bringas
Abstract:	Quantum software debugging faces significant challenges due to measurement-induced state collapse, decoherence, and gate noise. We introduce AssertsQ, a framework that integrates assertion-based debugging into Qiskit, enabling automated verification of quantum circuits. AssertsQ provides three key validation methods: Swap Test-based state fidelity checks, measurement-based Total Variation Distance (TVD) comparisons, and noise-aware assertions adaptable to real hardware constraints. Our evaluation on benchmark circuits, including GHZ, QFT, and Grover’s algorithm, demonstrates the framework’s ability to detect errors and quantify fidelity degradation under noise. By simplifying quantum circuit verification, AssertsQ enhances the reliability of quantum software in the NISQ era.
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Paper Nr:	26
Title:	Fundamental Patterns for Composing Quantum Algorithms
Authors:	Lavinia Stiliadou, Johanna Barzen, Martin Beisel, Frank Leymann and Benjamin Weder
Abstract:	Designing and implementing quantum algorithms is a time-consuming, complex, and error-prone task. As new quantum algorithms are often published as scientific papers without sufficient documentation and no available software implementations, algorithm designers and software developers have to figure out the missing details or redevelop parts of the quantum algorithm. Similar to classical programs, various quantum algorithms share the same subroutines as building blocks to realize the required functionality. Therefore, these building blocks have to be documented in a structured and easily understandable manner to foster their reuse and speed up development. Patterns are a well-established concept for documenting proven solutions to recurring problems and educating new developers. Hence, a pattern language capturing important concepts in the quantum computing domain was established. It already contains an initial set of patterns documenting common building blocks of quantum algorithms. In this paper, we extend the quantum computing pattern language by introducing five novel patterns, documenting fundamental building blocks to realize quantum algorithms.
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Paper Nr:	32
Title:	Exploring Image Search on Quantum Computing Systems
Authors:	Hermann Fürntratt, Werner Bailer, Florian Krebs, Roland Unterberger and Herwig Zeiner
Abstract:	Image search based on descriptor similarities is a fundamental task in computer vision. These descriptors are often highly quantised (e.g. binarised or ternarised). Quantum Computing (QC) has shown to have great potential for a number of tasks including search. Especially Google’s new Quantum Processing Unit called Willow reaches new milestones in error correction and durability and presents a benchmark that runs about five minutes in the quantum domain while it would take more than 1025 years on a state-of-the-art classical supercomputer. The supposed reason that this achievement is not immediately claimed for quantum supremacy is that Google also states that the benchmark — the so called Random Circuit Sampling (RCS) benchmark has ”not yet known real-world applications”. We therefore transform these benchmark results into the real world by exploring the question: what hardware specifications are needed to execute a quantum implementation of an image descriptor search algorithm more quickly than the fastest supercomputer available today? Hence, two distinct implementations of the Compact Descriptor for Video Applications (CDVA) search, which uses 512-bit descriptors are compared to classical code running on a MI300A unit available in El Capitan, the currently fastest supercomputer with AVX512-bit comands. The results indicate that the current key hardware factors, including gate runtime, coherence time, error rate, and the number of qubits, are still considerably (by orders of magnitude) below the performance levels necessary to compete with the El Capitan supercomputer, but with the recent progress in error correction, we can expect the development of larger quantum systems in the near future that reduces the performance gap between classical and quantum computers. Our source code for simulation is available online at GitHub.
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Short Papers

Paper Nr:	19
Title:	Guidelines for the Application of Hybrid Software Design Patterns
Authors:	Michal Baczyk and Ricardo Pérez-Castillo
Abstract:	Quantum Software Engineering is increasingly leveraging design patterns to codify best practices for developing quantum algorithms and applications. In this work, we conduct an extensive review of academic sources and open-source projects focused on quantum software design patterns. We identify dozens of recurring patterns spanning quantum algorithm structure, state preparation, data encoding, hybrid quantum-classical work-flows, variational algorithms, and execution strategies. We organize these patterns into a unified framework, providing a guide detailing each pattern’s qubit and gate requirements, classical processing needs, and categorization relevant from the application perspective. We observe a key trend of the expansion of pattern catalogs to support hybrid variational algorithms and NISQ-era challenges (e.g., warm-starting, circuit cutting), and the emergence of patterns to improve modularity, reusability, and interoperability of quantum software. Our findings aim to guide practitioners in applying proven design solutions in quantum application development.
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Paper Nr:	29
Title:	Mutation-Based Quantum Software Testing
Authors:	Macario Polo-Usaola, Manuel A. Serrano and Ignacio García-Rodríguez de Guzmán
Abstract:	Quantum technology is rapidly improving the capacity of quantum computers, increasing the number of cubits and fostering the development of quantum software capable of solving complex problems that, until now, were beyond the reach of the most powerful classical computers. Unfortunately, quantum computational capacity is growing faster than Quantum Software Engineering, which is necessary to avoid a new (quantum) software crisis. In this article, we focus on quantum software testing, with the specific goal of ensuring the quality of quantum software. For this purpose, we propose to apply the mutation-based software testing technique, applied to the context of quantum computing, since mutation has proven to be one of the most powerful tools to improve the quality of test suites. A set of quantum mutation operators have been developed to improve quantum test suites, and reduce the number of test cases required, which is important due to the cost of using quantum computers (and the need to run each circuit multiple times to obtain reliable results due to their stochastic nature). A tool for automating the generation of quantum mutants from original quantum circuits is also presented.
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Paper Nr:	16
Title:	Towards an Analyzability Model for Hybrid Software
Authors:	Ana Díaz-Muñoz, José A. Cruz-Lemus, Moisés Rodríguez and Teresa Baldasarre
Abstract:	This paper presents an initial validation of a software quality model focused on analyzability, aligned with the ISO/IEC 25010 standard. The model targets hybrid systems that integrate classical and quantum components, combining established classical metrics with quantum-specific measures designed to capture the complexity of quantum circuits. In this first empirical study, we evaluate only the quantum dimension of the model through a quasi-experimental setup involving computer engineering students. The results show that the model’s analyz-ability levels correlate with participants’ comprehension performance, supporting its utility in distinguishing circuit complexity. These findings offer promising evidence for further model refinement and lay the groundwork for future evaluations involving real-world hybrid code bases.
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Area 4 - Quantum Software Technology

Short Papers

Paper Nr:	15
Title:	QCRAFT Quantum Developer Interface: A Tool for Continuous Deployment of Quantum Circuits
Authors:	Javier Romero-Alvarez, Jaime Alvarado-Valiente, Enrique Moguel, Jose Garcia-Alonso and Juan M. Murillo
Abstract:	Quantum computing is evolving quickly, with increasing demand for accessible tools to design, execute, and analyze quantum circuits. However, the lack of standardization and interoperability between different quantum platforms, such as the IBM Quantum Platform and Amazon Braket, presents challenges including a dependence on the platforms. This work introduces the QCRAFT Quantum Developer Interface, a web interface for the Continuous Deployment and execution of quantum circuits in the form of services. By integrating tools like Quirk for circuit design and Docker containers for environment consistency, this tool enables developers to design quantum circuits, store them in databases, and execute them on various quantum platforms with minimal adjustments. This process simplifies and automates quantum deployment workflows, offering an accessible and modular solution for quantum researchers and developers.
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Paper Nr:	21
Title:	Parallel Tensor Network Contraction for Efficient Quantum Circuit Simulation on Multicore CPUs and GPUs
Authors:	Alfred M. Pastor, Maribel Castillo and Jose M. Badia
Abstract:	Quantum computing has the potential to transform fields such as cryptography, optimisation and materials science. However, the limited scalability and high error rates of current and near-term quantum hardware require efficient classical simulation of quantum circuits for validation and benchmarking. One of the most effective approaches to this problem is to represent quantum circuits as tensor networks, where simulation is equivalent to contracting the network. Given the computational cost of tensor network contraction, exploiting parallelism on modern high performance computing architectures is key to accelerating these simulations. In this work, we evaluate the performance of first-level parallelism in contracting individual tensor pairs during tensor network contraction on both multi-core CPUs and many-core GPUs. We compare the efficiency of three Julia packages, two optimised for CPU-based execution and the other for GPU acceleration. Our experiments, conducted with two parallel contraction strategies on highly entangled quantum circuits such as Quantum Fourier Transform (QFT) and Random Quantum Circuits (RQC), demonstrate the benefits of exploiting this level of parallelism on large circuits, in particular the superior performance gains achieved on GPUs.
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Area 5 - Quantum Software Theory

Short Papers

Paper Nr:	12
Title:	Knapsack and Shortest Path Problems Generalizations from a Quantum-Inspired Tensor Network Perspective
Authors:	Sergio Muñiz Subiñas, Jorge Martínez Martín, Alejandro Mata Ali, Javier Sedano and Ángel Miguel García-Vico
Abstract:	In this paper, we present two tensor network quantum-inspired algorithms to solve the knapsack and the shortest path problems, and enables to solve some of its variations. These methods provide an exact equation which returns the optimal solution of the problems. As in other tensor network algorithms for combinatorial optimization problems, the method is based on imaginary time evolution and the implementation of restrictions in the tensor network. In addition, we introduce the use of symmetries and the reutilization of intermediate calculations, reducing the computational complexity for both problems. To show the efficiency of our implementations, we carry out some performance experiments and compare the results with those obtained by other classical algorithms.
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Paper Nr:	20
Title:	Toward Design and Implementation of a Quantum-Classical Hybrid Computing System
Authors:	Shota Arakaki, Masao Hirokawa and Hiroki Watanabe
Abstract:	We propose the paradigm of our quantum-classical hybrid (QCH) computing system. The combination of the quantum and classical parts is realized by a kind of distributed computation with the help of the classical channel such as used in the trusted node of quantum network. In the programming at the front-end of the QCH computing system, the description of quantum circuits is hidden as possible, and then, the intrinsic functions corresponding to the individual quantum circuits is used instead. We show the example of a QCH computation and the results of some of the experiments. We generalize the notion of the QCH computation based on those results, and aim to establish the concept of our paradigm.
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