TY - INPR A1 - Periyasamy, Maniraman A1 - Plinge, Axel A1 - Mutschler, Christopher A1 - Scherer, Daniel D. A1 - Mauerer, Wolfgang T1 - Guided-SPSA: Simultaneous Perturbation Stochastic Approximation assisted by the Parameter Shift Rule N2 - The study of variational quantum algorithms (VQCs) has received significant attention from the quantum computing community in recent years. These hybrid algorithms, utilizing both classical and quantum components, are well-suited for noisy intermediate-scale quantum devices. Though estimating exact gradients using the parameter-shift rule to optimize the VQCs is realizable in NISQ devices, they do not scale well for larger problem sizes. The computational complexity, in terms of the number of circuit evaluations required for gradient estimation by the parameter-shift rule, scales linearly with the number of parameters in VQCs. On the other hand, techniques that approximate the gradients of the VQCs, such as the simultaneous perturbation stochastic approximation (SPSA), do not scale with the number of parameters but struggle with instability and often attain suboptimal solutions. In this work, we introduce a novel gradient estimation approach called Guided-SPSA, which meaningfully combines the parameter-shift rule and SPSA-based gradient approximation. The Guided-SPSA results in a 15% to 25% reduction in the number of circuit evaluations required during training for a similar or better optimality of the solution found compared to the parameter-shift rule. The Guided-SPSA outperforms standard SPSA in all scenarios and outperforms the parameter-shift rule in scenarios such as suboptimal initialization of the parameters. We demonstrate numerically the performance of Guided-SPSA on different paradigms of quantum machine learning, such as regression, classification, and reinforcement learning. Y1 - 2024 ER - TY - CHAP A1 - Zwingel, Maximilian A1 - Kedilioglu, Oguz A1 - Reitelshöfer, Sebastian A1 - Mauerer, Wolfgang T1 - Optimization Problems in Production and Planning: Approaches and Limitations in View of Possible Quantum Superiority T2 - Annals of Scientific Society for Assembly, Handling and Industrial Robotics 2023 Y1 - 2023 SN - 9783031740091 PB - Springer Nature ER - TY - CHAP A1 - Tresp, Volker A1 - Udluft, Steffen A1 - Hein, Daniel A1 - Hauptmann, Werner A1 - Leib, Martin A1 - Mutschler, Christopher A1 - Scherer, Daniel D. A1 - Mauerer, Wolfgang T1 - Workshop Summary: Quantum Machine Learning T2 - 2023 IEEE International Conference on Quantum Computing and Engineering, Bellevue, WA, United States, September 17-22, 2023 Y1 - 2023 U6 - https://doi.org/10.1109/QCE57702.2023.10174 PB - IEEE ER - TY - CHAP A1 - Gogeißl, Martin A1 - Safi, Hila A1 - Mauerer, Wolfgang T1 - Quantum Data Encoding Patterns and their Consequences T2 - Q-Data '24: Proceedings of the 1st Workshop on Quantum Computing and Quantum-Inspired Technology for Data-Intensive Systems and Applications, June 9 - 15, 2024, Santiago AA Chile N2 - The use of quantum processing units (QPUs) promises speed-ups for solving computational problems, in particular for discrete optimisation. While a few groundbreaking algorithmic approaches are known that can provably outperform classical computers, we observe a scarcity of programming abstractions for constructing efficient quantum algorithms. A good fraction of the literature that addresses solving concrete problems related to database management concentrates on casting them as quadratic unconstrained binary optimisation problems (QUBOs), which can then, among others, be processed on gate-based machines (using the quantum approximate optimisation algorithm), or quantum annealers. A critical aspect that affects efficiency and scalability of either of these approaches is how classical data are loaded into qubits, respectively how problems are encoded into QUBO representation. The effectiveness of encodings is known to be of crucial importance for quantum computers, especially since the amount of available qubits is strongly limited in the era of noisy, intermediate-size quantum computers. In this paper, we present three encoding patterns, discuss their impact on scalability, and their ease of use. We consider the recreational (yet computationally challenging) Sudoku problem and its reduction to graph colouring as an illustrative example to discuss their individual benefits and disadvantages. Our aim is enable database researchers to choose an appropriate encoding scheme for their purpose without having to acquire in-depth knowledge on quantum peculiarities, thus easing the path towards applying quantum acceleration on data management systems. Y1 - 2024 SN - 979-8-4007-0553-3 U6 - https://doi.org/10.1145/3665225.3665446 SP - 27 EP - 37 PB - ACM ER - TY - INPR A1 - Jung, Matthias A1 - Krumke, Sven O. A1 - Schroth, Christof A1 - Lobe, Elisabeth A1 - Mauerer, Wolfgang T1 - QCEDA: Using Quantum Computers for EDA N2 - The field of Electronic Design Automation (EDA) is crucial for microelectronics, but the increasing complexity of Integrated Circuits (ICs) poses challenges for conventional EDA: Corresponding problems are often NP-hard and are therefore in general solved by heuristics, not guaranteeing optimal solutions. Quantum computers may offer better solutions due to their potential for optimization through entanglement, superposition, and interference. Most of the works in the area of EDA and quantum computers focus on how to use EDA for building quantum circuits. However, almost no research focuses on exploiting quantum computers for solving EDA problems. Therefore, this paper investigates the feasibility and potential of quantum computing for a typical EDA optimization problem broken down to the Min-k-Union problem. The problem is mathematically transformed into a Quadratic Unconstrained Binary Optimization (QUBO) problem, which was successfully solved on an IBM quantum computer and a D-Wave quantum annealer. Y1 - 2024 ER - TY - CHAP A1 - Mauerer, Wolfgang ED - Exman, Iaakov ED - Perez-Castillo, Ricardo ED - Piattini, Mario ED - Felderer, Michael T1 - Superoperators for Quantum Software Engineering T2 - Quantum Software: Aspects of Theory and System Design N2 - As implementations of quantum computers grow in size and maturity, the question of how to program this new class of machines is attracting increasing attention in the software engineering domain. Yet, many questions from how to design expressible quantum languages augmented with formal semantics via implementing appropriate optimizing compilers to abstracting details of machine properties in software systems remain challenging. Performing research at this intersection of quantum computing and software engineering requires sufficient knowledge of the physical processes underlying quantum computations, and how to model these. In this chapter, we review a superoperator-based approach to quantum dynamics, as it can provide means that are sufficiently abstract, yet concrete enough to be useful in quantum software and systems engineering, and outline how it is used in several important applications in the field. KW - quantum computing KW - quantum software engineering KW - software development KW - software engineering Y1 - 2024 U6 - https://doi.org/10.1007/978-3-031-64136-7_3 SN - 978-3-031-64136-7 PB - Springer Nature ER - TY - CHAP A1 - Safi, Hila A1 - Wintersperger, Karen A1 - Mauerer, Wolfgang T1 - Influence of HW-SW-Co-Design on Quantum Computing Scalability T2 - 2023 IEEE International Conference on Quantum Software (QSW), Chicago, IL, USA, 02-08 July 2023 N2 - The use of quantum processing units (QPUs) promises speed-ups for solving computational problems. Yet, current devices are limited by the number of qubits and suffer from significant imperfections, which prevents achieving quantum advantage. To step towards practical utility, one approach is to apply hardware-software co-design methods. This can involve tailoring problem formulations and algorithms to the quantum execution environment, but also entails the possibility of adapting physical properties of the QPU to specific applications. In this work, we follow the latter path, and investigate how key figures— circuit depth and gate count—required to solve four cornerstone NP-complete problems vary with tailored hardware properties. Our results reveal that achieving near-optimal performance and properties does not necessarily require optimal quantum hardware, but can be satisfied with much simpler structures that can potentially be realised for many hardware approaches.m Using statistical analysis techniques, we additionally identify an underlying general model that applies to all subject problems. This suggests that our results may be universally applicable to other algorithms and problem domains, and tailored QPUs can find utility outside their initially envisaged problem domains. The substantial possible improvements nonetheless highlight the importance of QPU tailoring to progress towards practical deployment and scalability of quantum software. KW - quantum computing KW - software engineering KW - hardware-software co-design KW - quantum algorithm performance analysis KW - scalability of quantum applications Y1 - 2023 SN - 979-8-3503-0479-4 U6 - https://doi.org/10.1109/QSW59989.2023.00022 SP - 104 EP - 115 PB - IEEE ER - TY - JOUR A1 - Wintersperger, Karen A1 - Dommert, Florian A1 - Ehmer, Thomas A1 - Hoursanov, Andrey A1 - Klepsch, Johannes A1 - Mauerer, Wolfgang A1 - Reuber, Georg A1 - Strohm, Thomas A1 - Yin, Ming A1 - Luber, Sebastian T1 - Neutral Atom Quantum Computing Hardware: Performance and End-User Perspective JF - EPJ Quantum Technology N2 - We present an industrial end-user perspective on the current state of quantum computing hardware for one specific technological approach, the neutral atom platform. Our aim is to assist developers in understanding the impact of the specific properties of these devices on the effectiveness of algorithm execution. Based on discussions with different vendors and recent literature, we discuss the performance data of the neutral atom platform. Specifically, we focus on the physical qubit architecture, which affects state preparation, qubit-to-qubit connectivity, gate fidelities, native gate instruction set, and individual qubit stability. These factors determine both the quantum-part execution time and the end-to-end wall clock time relevant for end-users, but also the ability to perform fault-tolerant quantum computation in the future. We end with an overview of which applications have been shown to be well suited for the peculiar properties of neutral atom-based quantum computers. KW - Neutral atom quantum computers KW - Review KW - Quantum computing platforms KW - Performance metrics KW - Benchmarks Y1 - 2023 U6 - https://doi.org/10.1140/epjqt/s40507-023-00190-1 VL - 10 PB - Springer Nature ER - TY - CHAP A1 - Greiwe, Felix A1 - Krüger, Tom A1 - Mauerer, Wolfgang T1 - Effects of Imperfections on Quantum Algorithms BT - A Software Engineering Perspective T2 - 2023 IEEE International Conference on Quantum Software (QSW), Chicago, IL, USA, 02-08 July 2023 N2 - Quantum computers promise considerable speedups over classical approaches, which has raised interest from many disciplines. Since any currently available implementations suffer from noise and imperfections, achieving concrete speedups for meaningful problem sizes remains a major challenge. Yet, imperfections and noise may remain present in quantum computing for a long while. Such limitations play no role in classical software computing, and software engineers are typically not well accustomed to considering such imperfections, albeit they substantially influence core properties of software and systems. In this paper, we show how to model imperfections with an approach tailored to (quantum) software engineers. We intuitively illustrate, using numerical simulations, how imperfections influence core properties of quantum algorithms on NISQ systems, and show possible options for tailoring future NISQ machines to improve system performance in a co-design approach. Our results are obtained from a software framework that we provide in form of an easy-to-use reproduction package. It does not require computer scientists to acquire deep physical knowledge on noise, yet provide tangible and intuitively accessible means of interpreting the influence of noise on common software quality and performance indicators. KW - noisy quantum computing KW - NISQ systems KW - quantum software engineering KW - HW-SW co-design Y1 - 2023 U6 - https://doi.org/10.1109/QSW59989.2023.00014 SP - 31 EP - 42 PB - IEEE ER - TY - CHAP A1 - Yue, Tao A1 - Mauerer, Wolfgang A1 - Ali, Shaukat A1 - Taibi, Davide T1 - Challenges and Opportunities in Quantum Software Architecture T2 - Software Architecture: Research Roadmaps from the Community N2 - Quantum computing is a relatively new paradigm that has raised considerable interest in physics and computer science in general but has so far received little attention in software engineering and architecture. Hybrid applications that consist of both quantum and classical components require the development of appropriate quantum software architectures. However, given that quantum software engineering (QSE) in general is a new research area, quantum software architecture–a subresearch area in QSE is also understudied. The goal of this chapter is to provide a list of research challenges and opportunities for such architectures. In addition, to make the content understandable to a broader computer science audience, we provide a brief overview of quantum computing and explain the essential technical foundations. KW - Quantum Computing KW - Software Architecture KW - Quantum Applications KW - Quantum Software Engineering Y1 - 2023 SN - 978-3-031-36847-9 U6 - https://doi.org/10.1007/978-3-031-36847-9_1 SP - 1 EP - 23 ER - TY - CHAP A1 - Schönberger, Manuel A1 - Trummer, Immanuel A1 - Mauerer, Wolfgang T1 - Quantum Optimisation of General Join Trees T2 - Joint Workshops at 49th International Conference on Very Large Data Bases (VLDBW’23) — International Workshop on Quantum Data Science and Management (QDSM’23), August 28 - September 1, 2023, Vancouver, Canada (CEUR Workshop Proceedings) N2 - Recent advances in the manufacture of quantum computers attract much attention over a wide range of fields, as early-stage quantum processing units (QPU) have become accessible. While contemporary quantum machines are very limited in size and capabilities, mature QPUs are speculated to eventually excel at optimisation problems. This makes them an attractive technology for database problems, many of which are based on complex optimisation problems with large solution spaces. Yet, the use of quantum approaches on database problems remains largely unexplored. In this paper, we address the long-standing join ordering problem, one of the most extensively researched database problems. Rather than running arbitrary code, QPUs require specific mathematical problem encodings. An encoding for the join ordering problem was recently proposed, allowing first small-scale queries to be optimised on quantum hardware. However, it is based on a faithful transformation of a mixed integer linear programming (MILP) formulation for JO, and inherits all limitations of the MILP method. Most strikingly, the existing encoding only considers a solution space with left-deep join trees, which tend to yield larger costs than general, bushy join trees. We propose a novel QUBO encoding for the join ordering problem. Rather than transforming existing formulations, we construct a native encoding tailored to quantum systems, which allows us to process general bushy join trees. This makes the full potential of QPUs available for solving join order optimisation problems. Y1 - 2023 UR - https://ceur-ws.org/Vol-3462/QDSM2.pdf SP - 1 EP - 12 PB - RWTH Aachen, Sun SITE Central Europe CY - Aachen ER -