Publikationen

Wissenschaftliche Publikationen aus SEQUOIA

[1] C. Tutschku, A. Sturm, F. Knäble, B. C. Mummaneni, D. Pranjic, C. Stephan, D. B. Mayer, G. Koßmann, M. Roth, P.-A. Matt, A. Grigorjan, T. Wellens, K. König, M. Beisel, F. Truger, F. Shagieva, O. Denninger and S. Garhofer, »Quantencomputing in der industriellen Applikation. Vom Algorithmen-, Markt- und Hardwareüberblick hin zu anwendungszentriertem Quantensoftware-Engineering«, 2023, 10.24406/publica-805

[2] A. Sturm, B. C. Mummaneni, L. Rullkötter, »Unlocking Quantum Optimization: A Use Case Study on NISQ Systems«, 2024, https://doi.org/10.48550/arXiv.2404.07171

[3] N. Schillo, »Quantum Algorithms and Quantum Machine Learning for Differential Equations«, 2024, https://elib.uni-stuttgart.de/handle/11682/13885

[4] F. Truger, J. Barzen, M. Bechtold, M. Beisel, F. Leymann, A. Mandl, and V. Yussupov »Warm-Starting and Quantum Computing: A Systematic Mapping Study«, 2024, https://doi.org/10.1145/3652510 

[5] P.-A. Matt and Marco Roth, »A heuristic for solving the irregular strip packing problem with quantum optimization«, 2024, https://doi.org/10.48550/arXiv.2402.17542

[6] G. Koßmann, L. Binkowski, C. Tutschku and R. Schwonnek, »Open-Shop Scheduling With Hard Constraints«, 2023, https://doi.org/10.48550/arXiv.2211.05822

[7] A. Sturm, »Theory and Implementation of the Quantum Approximate Optimization Algorithm: A Comprehensible Introduction and Case Study Using Qiskit and IBM Quantum Computers«, 2023, https://doi.org/10.48550/arXiv.2301.09535

[8] S. Garhofer and O. Bringmann »Using an A∗-based framework for decomposing combinatorial optimization problems to employ NISQ computers« in Quantum Information Processing 22:357, 2023, https://doi.org/10.1007/s11128-023-04115-w 

[9] M. Beisel, S. Garhofer, F. Leymann, F. Truger, B. Weder, and V. Yussupov, »Quokka: A Service Ecosystem for Workflow-Based Execution of Variational Quantum Algorithms«, 20th International Conference on Service Oriented Computing, 2022.

[10] M. Beisel, J. Barzen, F. Leymann, F. Truger, B. Weder and V. Yussupov, »Configurable Readout Error Mitigation in Quantum Workflows«, in Electronics, Vol. 11(19), MDPI, 2022.

[11] F. Truger, M. Beisel, J. Barzen, F. Leymann, and V. Yussupov, »Selection and Optimization of Hyperparameters in Warm- Quantum Optimization for the MaxCut Problem« in Electronics, MDPI, 2022.

[12] M. Scheerer, J. Klamroth and O. Denninger, »Fault-tolerant Hybrid Quantum Software Systems«, IEEE International Conference on Quantum Software (QSW), 2022, pp. 52-57, doi: 10.1109/QSW55613.2022.00023

[13] J. Klamroth, M. Scheerer and O. Denninger, »QIn: Enabling Formal Methods to Deal with Quantum Circuits«, Quantum Physics and Logic 2022 (QPL‘22) Poster.

[14] B. Weder, J. Barzen, F. Leymann, and D. Vietz, »Quantum Software Development Lifecycle« in Quantum Software Engineering, Springer International Publishing, 2022 (arXiv).

[15] B. Weder, J. Barzen, M. Beisel, and F. Leymann, »Analysis and Rewrite of Quantum Workflows: Improving the Execution of Hybrid Quantum Algorithms« in Proceedings of the 12th International Conference on Cloud Computing and Services Science (CLOSER 2022), 2022.

[16] M. Beisel, J. Barzen, F. Leymann, F. Truger, B. Weder, and V. Yussupov, »Patterns for Quantum Error Handling« in Proceedings of the Fourteenth International Conference on Pervasive Patterns and Applications (PATTERNS 2022), 2022.

[17] D. Vietz, J. Barzen, F. Leymann, and B. Weder, »Splitting Quantum-Classical Scripts for the Generation of Quantum Workflows«, in Proceedings of the 26th Conference on Enterprise Design, Operations, and Computing (EDOC 2022), Springer International Publishing, 2022.

[18] M. Weigold, J. Barzen, F. Leymann, and D. Vietz, »Patterns for Hybrid Quantum Algorithms«, in Proceedings of the 15th Symposium and Summer School on Service-Oriented Computing (SummerSOC 2021), Sep. 2021, pp. 34–51, doi: 10.1007/978-3-030-87568-8_2

[19] B. Weder, J. Barzen, F. Leymann, and M. Zimmermann, Hybrid Quantum Applications Need Two Orchestrations in Superposition: »A Software Architecture Perspective« in Proceedings of the 18th IEEE International Conference on Web Services (ICWS 2021), 2021, pp. 1–13, doi: 10.1109/ICWS53863.2021.00015

[20] D. Vietz, J. Barzen, F. Leymann, and K. Wild, »On Decision Support for Quantum Application Developers: Categorization, Comparison, and Analysis of Existing Technologies«, in Computational Science — ICCS 2021, 2021, pp. 127–141, doi: 10.1007/978-3-030-77980-1_10

[21] D. Vietz, J. Barzen, F. Leymann, B. Weder, and V. Yussupov, »An Exploratory Study on the Challenges of Engineering Quantum Applications in the Cloud«, in Proceedings of the 2nd Quantum Software Engineering and Technology Workshop (Q-SET 2021) co-located with IEEE International Conference on Quantum Computing and Engineering (QCE21), 2021, pp. 1–12.

[22] M. Scheerer, J. Klamroth, and O. Denninger, »Engineering Reliable Hybrid Quantum Software: An Architectural-driven Approach«, 2nd International Workshop on Quantum Software Engineering & Technology (QSET 2021).

[23] J. Klamroth, M. Scheerer, and O. Denninger, »Holistische Verifikation von Hybriden Quantenprogrammen durch Software Bounded Model Checking« Workshop Herausforderungen beim Testen moderner Softwaresysteme @ GI Jahrestagung 2021.

In Vorbereitung

[24] A. Sturm, F. Knäble, C. Tutschku »Quantum Optimization in Mobility and Logistics«

[25] L. Zhong, Q. Pan, D. Hoppe »Quantum Deep Neural Network for Solving PDEs«

[26] L. Zhong, Q. Pan, D. Hoppe »Is QNN Really Beneficial in Image Processing? A Comparative Study«