Jonas Stein, M.Sc.

Jonas Stein, M.Sc. Lehrstuhl für Mobile und Verteilte Systeme Ludwig-Maximilians-Universität München, Institut für Informatik Oettingenstraße 67 80538 München Raum G 008 Telefon: +49 89 / 2180-9163 Fax: +49 89 / 2180-9148 Mail: jonas.stein@ifi.lmu.de

Research Interests

• Quantum Applications and Research Lab (QAR-Lab)
• Quantum Computing
• Quantum Optimization
• Quantum Machine Learning
• Quantum Simulation
• Quantum Reinforcement Learning
• Quantum Walks

Remarks concerning Bachelor’s / Master’s Theses

If you are interested in writing a thesis (BA/MA) on a topic within a subset of my research interests, feel free to contact me. While a list of currently announced theses can be found below, any further ideas are welcome as well. When contacting me, please use your @campus.lmu.de e-mail address and enclose a current transcript of records.

Currently Announced Bachelor’s Theses

• None

Currently Announced Master’s Theses

• None

Assigned Theses

• Gerhard Stenzel, Michael Kölle, Jonas Stein, Andreas Sedlmeier, Claudia Linnhoff-Popien, „Quantum-Enhanced Denoising Diffusion Model“, Master’s Thesis
• Max Adler, Jonas Stein, Jonas Nüßlein, Nico Kraus, Claudia Linnhoff-Popien, „Using Quantum Machine Learning to predict asset prices in financial markets“, Master’s Thesis
• Vasily Bokov, Jonas Stein, Michael Wolf, „Exploring the suitability of efficient Quantum Kernels for exponential speedups“, Master’s Thesis
• Constantin Economides, Jonas Stein, Lode Pollet, „Quantum Average Gradient Descent“, Master’s Thesis

Supervised Theses

• Navid Roshani, Jonas Stein, Lode Pollet, „Introducing sequential Hamiltonian assembly for training VQEs and its application in graph coloring“, Masters’s Thesis
• Dominik Ott, Jonas Stein, Jonas Nüßlein, Claudia Linnhoff-Popien, „NISQ-ready community detection on weighted graphs using separation-node identification“, Bachelor’s Thesis
• Lorena Wemmer, Jonas Stein, Michael Kölle, Elena Van der Vorst, Claudia Linnhoff-Popien, „Analyzing Reinforcement Learning strategies from a prameterized quantum walker“, Bachelor’s Thesis
• Anant Agnihotri, Jonas Stein, Jeanette Lorenz, „Introducing Linear Entropy Based Community Detection“, Master’s Thesis
• Viktoryia Patapovich, Jonas Stein, Michael Kölle, Maximilian Balthasar Mansky, Claudia Linnhoff-Popien, „Efficient quantum circuit architecture for coined quantum walks on many bipartite graphs“, Bachelor’s Thesis
• Ahmad Issa, Jonas Stein, Daniëlle Schuman, Claudia Linnhoff-Popien, „Anomaly Detection using Quantum Circuit Born Machines“, Bachelor’s Thesis
• Ivo Christ, Jonas Stein, Robert Müller, Claudia Linnhoff-Popien, „Investor sentiment analysis using classical and quantum algorithms“, Master’s Thesis
• Soren Little, Christoph Roch, Jonas Stein, Claudia Linnhoff-Popien, „Structural Analysis of Graph Based Optimization Problems and their QUBO Formulations“, Bachelor’s Thesis
• David Münzer, Michael Kölle, Jonas Stein, Claudia Linnhoff-Popien, „Data Embedding for efficient Quantum Machine Learning“, Bachelor’s Thesis
• Petros Stougiannidis, Jonas Stein, Sebastian Feld, Claudia Linnhoff-Popien, „Introducing a space-efficient polynomial rotation circuit for bypassing traditional Quantum Arithmetic in NISQ-applications of HHL and beyond“, Bachelor’s Thesis
• Leopold Bodendörfer, Jonas Stein, Michael Kölle, Claudia Linnhoff-Popien, „Efficient Data Embedding for offline Handwriting Recognition using Quantum Support Vector Machines“, Bachelor’s Thesis
• Johannes Kolb, Jonas Stein, Christoph Roch, Claudia Linnhoff-Popien, „Comparing the performance of PUBO and QUBO based QAOA for continuous optimization problems“, Bachelor’s Thesis
• Tobias Rohe, Jonas Stein, Julian Hager, Claudia Linnhoff-Popien, „Introducing a Hardware-efficient Layer-VQE based Ansatz“, Bachelor’s Thesis
• Franziska Wörle, Jonas Stein, Maximilian Mansky, Robert Müller, Claudia Linnhoff-Popien, „Possibilities and limitations of Quantum Machine Translation: Adaption of the DisCoCat-Model for Question Answering in the Chinese Language“, Bachelor’s Thesis
• Jonathan Wulf, Jonas Stein, Michael Kölle, Claudia Linnhoff-Popien, „Efficient embedding in Quantum Support Vector Machines using a specialized NISQ approach“, Bachelor’s Thesis
• Philip Hierhager, Sebastian Zielinski, Jonas Stein, Claudia Linnhoff-Popien, „Evaluation of quantum-classical hybrid algorithms for solving 3-SAT problems“, Bachelor’s Thesis
• Ivelina Bozhinova, Jonas Stein, Sebastian Feld, Claudia Linnhoff-Popien, „Pruning the search space in QUBO-based Community Detection“, Master’s Thesis
• Kai-Chun Lin, Jonas Stein, Christoph Roch, Claudia Linnhoff-Popien, „Community Detection in Multilayer Networks via Quantum Annealing“, Master’s Thesis
• Maximilian Beer, Jonas Stein, Sebastian Feld, Claudia Linnhoff-Popien, „Local Community Detection via Quantum Walks in the Quantum Gate Model“, Bachelor’s Thesis
• Moritz Finsterwalder, Christoph Roch, Jonas Stein, Claudia Linnhoff-Popien, „Optimizing Shift Plans Using Classical Methods“, Bachelor’s Thesis
• Peter Lang, Jonas Stein, Sebastian Feld, Claudia Linnhoff-Popien, „Optimized Community Detection through edge deletion on quantum annealers“, Bachelor’s Thesis
• Bob Godar, Christoph Roch, Jonas Stein, Claudia Linnhoff-Popien, „Optimizing a Quantum Key Distribution Network using Quantum Annealing“, Masters’s Thesis

Teaching

• Quantum Computing Programming (Practical Course): S21, W21/22, S22, W22/23, S23, W23/24
• Trends in Mobile and Distributed Systems (Seminar): S21
• Seminar on advanced topics in Mobile and Distributed Systems (Seminar): W21/22, S22, W22/23, W22/23, S23

Projects

• PlanQK, QAR-Lab Bayern, CAQAO, QCHALLenge, MQV

Publications

• S. Zielinski, J. Nüßlein, J. Stein, T. Gabor, C. Linnhoff-Popien and S. Feld, “Pattern QUBOs: Algorithmic Construction of 3SAT-to-QUBO Transformations”. Electronics 2023, 12, 3492. August 2023. DOI: 10.3390/electronics12163492. arXiv: 2305.02659.
• J. Stein, D. Ott, J. Nüßlein, D. Bucher, M. Schönfeld and S. Feld, „NISQ-ready community detection based on separation-node identification“. Mathematics 2023, 11, 3323. July 2023. DOI: 10.3390/math11153323. arXiv: 2212.14717.
• J. Stein, I. Christ, N. Kraus, M. B. Mansky, R. Müller and C. Linnhof-Popien, „Applying QNLP to sentiment analysis in finance“. QCE23: IEEE International Conference on Quantum Computing and Engineering Companion. Bellevue (Washington), September 17-22, 2023. DOI:10.1109/QCE57702.2023.10178. arXiv:2307.11788
• D. J. Schuman, L. Sünkel, P. Altmann, J. Stein, C. Roch, T. Gabor and C. Linnhof-Popien, „Towards Transfer Learning for Large-Scale Image Classification Using Annealing-based Quantum Boltzmann Machines“. QCE23: IEEE International Conference on Quantum Computing and Engineering Companion. Bellevue (Washington), September 17-22, 2023. DOI: 10.1109/QCE57702.2023.10182.
• P. Stougiannidis, J. Stein, D. Bucher, S. Zielinski, C. Linnhoff-Popien and S. Feld, “Approximative lookup-tables and arbitrary function rotations for facilitating NISQ-implementations of the HHL and beyond”. QCE23: IEEE International Conference on Quantum Computing and Engineering. Bellevue (Washington), September 17-22, 2023. DOI: 10.1109/QCE57702.2023.00025. arXiv: 2306.05024.
• M. B. Mansky, F. Wörle, J. Stein, R. Müller and C. Linnhoff-Popien, “Adapting the DisCoCat framework for Question Answering to the Chinese Language”. QCE23: IEEE International Conference on Quantum Computing and Engineering. Bellevue (Washington), September 17-22, 2023. DOI: 10.1109/QCE57702.2023.00073.
• J. Stein, F. Chamanian, M. Zorn, J. Nüßlein, S. Zielinski, M. Kölle and C. Linnhoff-Popien, “Evidence that PUBO outperforms QUBO when solving continuous optimization problems with the QAOA”. GECCO 2023: The 2023 Genetic and Evolutionary Computation Conference Companion. Lisbon, July 15-19, 2023. DOI: 10.1145/3583133.3596358. arXiv: 2305.03390.
• S. Zielinski, J. Nüßlein, J. Stein, T. Gabor, C. Linnhoff-Popien and S. Feld, “Influence of Different 3SAT-to-QUBO Transformations on the Solution Quality of Quantum Annealing: A Benchmark Study”. To appear in GECCO 2023: The 2023 Genetic and Evolutionary Computation Conference. Lisbon, July 15-19, 2023. DOI: 10.48550/arXiv.2305.00720. arXiv: 2305.00720.
• J. Nuesslein, C. Roch, T. Gabor, J. Stein, C. Linnhoff-Popien and S. Feld, “Black Box Optimization Using QUBO and the Cross Entropy Method”. Computational Science – ICCS 2023. ICCS 2023. Lecture Notes in Computer Science, vol 10477. Springer, Cham. DOI: 10.1007/978-3-031-36030-5_4. arXiv: 2206.12510.
• P. Altmann, L. Sünkel, J. Stein, T. Müller, C. Roch and C. Linnhoff-Popien, “SEQUENT: Towards Traceable Quantum Machine Learning using Sequential Quantum Enhanced Training“. In Proceedings of the 15th International Conference on Agents and Artificial Intelligence – Volume 3: ICAART, ISBN 978-989-758-623-1; ISSN 2184-433X, SciTePress, pages 744-751. DOI: 10.5220/0011772400003393. arXiv: 2301.02601.
• M. Kölle, A. Giovagnoli, J. Stein, M. B. Mansky, J. Hager and C. Linnhoff-Popien, “Improving Convergence for Quantum Variational Classifiers using Weight Re-Mapping“. In Proceedings of the 15th International Conference on Agents and Artificial Intelligence – Volume 2: ICAART, ISBN 978-989-758-623-1; ISSN 2184-433X, SciTePress, pages 251-258. DOI: 10.5220/0011696300003393. arXiv: 2212.14807.
• T. Gabor, M. Lachner, N. Kraus, J. Stein, C. Roch, D. Ratke and C. Linnhoff-Popien, “Modifying the Quantum-Assisted Genetic Algorithm”. Proceedings of the Genetic and Evolutionary Computation Conference Companion. July, 2022. DOI: 10.1145/3520304.3534034.
• J. Stein, „Quantencomputing-Der neueste Stand der Super-Technologie“, Digitale Welt 6, 3 (2022). DOI: 10.1007/s42354-022-0464-7
• J. Stein, L. Borrmann, S. Feld, T. Gabor, C. Roch, L. Sünkel, S. Zielinski and C. Linnhoff-Popien, „Wie gelingt meinem Unternehmen der Einstieg ins Quantencomputing? Über das Ökosystem für die Quantencomputing-Anwenderkompetenz des QAR-Lab“, Digitale Welt 5, 18–23 (2021). DOI: 10.1007/s42354-021-0331-y

Preprints

• J. Stein, J. Jojo, A. Farea, D. Bucher, P. Altmann, M. S. Çelebi and C. Linnhoff-Popien, „Combining the QAOA and HHL Algorithm to achieve a Substantial Quantum Speedup for the Unit Commitment Problem“, arXiv:2305.08482 [qp], Jun. 2023. DOI: 10.48550/arXiv.2305.08482. arXiv: 2305.08482.
• J. Stein,T. Rohe, F. Nappi, J. Hager, D. Bucher, M. Zorn, M. Kölle, C. Linnhoff-Popien, „Introducing Reducing-Width-QNNs, an AI-inspired Ansatz design pattern“, arXiv:2306.05047 [qp], Jun. 2023. DOI: 10.48550/arXiv.2306.05047. arXiv: 2306.05047.
• J. Stein, D. Schuman, M. Benkard, T. Holger, W. Sajko, M. Kölle, J. Nüßlein, L. Sünkel, O. Salomon and C. Linnhoff-Popien, „Exploring Unsupervised Anomaly Detection with Quantum Boltzmann Machines in Fraud Detection“, arXiv:2306.04998 [qp], Jun. 2023. DOI: 10.48550/arXiv.2306.04998. arXiv: 2306.04998.
• J. Stein, M. Poppel, P. Adamczyk, R. Fabry, Z. Wu, M. Kölle, J. Nüßlein, D. Schuman, P. Altmann, T. Ehmer, V. Narasimhan and C. Linnhoff-Popien, „Quantum Surrogate Modeling for Chemical and Pharmaceutical Development“, arXiv:2306.05042 [qp], Jun. 2023. DOI: 10.48550/arXiv.2306.05042. arXiv: 2306.05042.
• M. Kölle, A. Giovagnoli, J. Stein, M. B. Mansky, J. Hager, T. Rohe, R. Müller and C. Linnhoff-Popien, „Weight Re-Mapping for Variational Quantum Algorithms“, arXiv:2306.05776 [qp], Jun. 2023. DOI: arXiv.2306.05776. arXiv: 2306.05776.
• J. Stein, J. Nüßlein, M. Kölle, C. Linnhoff-Popien, „Practical course: Quantum Computing Programming“, 4th Edition, LMU Munich, October 2022. pdf
• B. Godar, C. Roch, J. Stein, M. Geitz, B. Lehmann, M. Gunkel, V. Fürst and F. Hofmann, “Optimization of QKD Networks with Classical and Quantum Annealing”, arXiv.2206.14109 [qp], Jun. 2022, DOI: 10.48550/ARXIV.2206.14109. arXiv: 2206.14109.

Talks

• „Exploring Quantum Advantage for the German industry“, 20.09.2023, Bitkom Quantum Summit, Berlin