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

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.

Open Research Topics

  • None

Assigned Research Topics

  • Jonathan Wulf, Jonas Stein, Michael Kölle and Claudia Linnhoff-Popien, „Genetic Quantum Architecture Search“, Master’s Thesis
  • Antonia Halbig, Arnold Unterauer, Jonas Stein and Claudia Linnhoff-Popien, „Multimodal Financial Forecasting“, Master’s Thesis
  • Het Dave, Arnold Unterauer, Jonas Stein and Claudia Linnhoff-Popien, „Utilizing GraphCast for Financial Forecasting“, Bachelor’s Thesis
  • David Fischer, Jonas Stein, Philipp Altmann, Dirk André Deckert  and Claudia Linnhoff-Popien, „A Path Towards Quantum Advantage for the Unit Commitment Problem“, Bachelor’s Thesis
  • Jonas Blenninger, Jonas Stein, Maximilian Zorn, Peter Eder and Claudia Linnhoff-Popien, „Benchmarking Decomposition Techniques in Quantum Optimization“, Master’s Thesis
  • Sabrina Egger, Jonas Stein and Claudia Linnhoff-Popien, „Applying parameterized Quantum Walks in Reinforcement Learning“, Master’s Thesis

Supervised Research Topics

  • Jonathan Wulf, Jonas Stein, David Bucher and Claudia Linnhoff-Popien, „Quantum Singular Value Transformation in Practice“, Research Internship
  • Christopher Rieß, Jonas Stein, Michael Kölle and Claudia Linnhoff-Popien, „Benchmarking Quantum Gaussian Processes“, Research Internship
  • Jakob Mayer, Jonas Nüßlein, Jonas Stein and Claudia Linnhoff-Popienm „Towards Efficient Arbitrage Detection: A Study on Quantum Algorithms“, Bachelor’s Thesis
  • Nico Kraus, Jonas Stein, Jonas Nüßlein and Claudia Linnhoff-Popien, „The Influence of Data Characteristics on the Efficacy of Forecasting Models“, Research Internship
  • Constantin Economides, Jonas Stein, Lode Pollet, „A Novel Quantum Circuit for Efficient Computation of Exponentially Large Weighted Sums in Variational Quantum Circuits“, 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
  • Gerhard Stenzel, Michael Kölle, Jonas Stein, Andreas Sedlmeier, Claudia Linnhoff-Popien, „Quantum-Enhanced Denoising Diffusion Model“, Master’s Thesis
  • Vasily Bokov, Jonas Stein, Claudia Linnhoff-Popien, Michael Wolf, „Exploring the suitability of efficient Quantum Kernels for exponential speedups“, Master’s Thesis
  • 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

Projects

Publications

  • P. Altmann, A. Bärligea, J. Stein, M. Kölle, T. Gabor, T. Phan and C. Linnhoff-Popien, “Quantum Circuit Design: A Reinforcement Learning Challenge”. To appear in the Proceedings of the International Conference on Autonomous Agents and Multi-Agent Systems, May 2024.
  • 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”. Agents and Artificial Intelligence (LNCS volume 14546, LNAI), pages 286-309, Mar. 2024. DOI: 10.1007/978-3-031-55326-4_14. arXiv: 2306.05776.
  • J. Stein, T. Rohe, F. Nappi, J. Hager, D. Bucher, M. Zorn, M. Kölle and C. Linnhoff-Popien, “Introducing Reduced-Width QNNs, an AI-inspired Ansatz Design Pattern”. In Proceedings of the International Conference on Agents and Artificial Intelligence – Volume 3, pages 1127-1134, Feb. 2024. DOI: 10.5220/0012449800003636. arXiv: 2306.05047.
  • J. Stein, N. Roshani, M. Zorn, P. Altmann, M. Kölle and C. Linnhoff-Popien, “Improving Parameter Training for VQEs by Sequential Hamiltonian Assembly”. In Proceedings of the International Conference on Agents and Artificial Intelligence – Volume 2, pages 99-109, Feb. 2024. DOI: 10.5220/0012312500003636. arXiv: 2312.05552.
  • 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, “Benchmarking Quantum Surrogate Models on Scarce and Noisy Data”. In Proceedings of the International Conference on Agents and Artificial Intelligence – Volume 3, pages 352-359, Feb. 2024. DOI: 10.5220/0012348900003636. arXiv: 2306.05042.
  • 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”.  In Proceedings of the International Conference on Agents and Artificial Intelligence – Volume 2, pages 177-185, Feb. 2024. DOI: 10.5220/0012326100003636. arXiv: 2306.04998.
  • M. Kölle, T. Schubert, P. Altmann, J. Stein, M. Zorn and C. Linnhoff-Popien, “A Reinforcement Learning Environment for Directed Quantum Circuit Synthesis”. In Proceedings of the International Conference on Agents and Artificial Intelligence – Volume 1, pages 83-94, Feb. 2024. DOI: 10.5220/0012383200003636. arXiv: 2401.07054.
  • M. Kölle, G. Stenzel, J. Stein, S. Zielinski, B. Ommer and C. Linnhoff-Popien, „Quantum Denoising Diffusion Models“. arXiv preprint [cs], Jan. 2024. arXiv: 2401.07049.
  • P. Altmann, A. Bärligea, J. Stein, M. Kölle, T. Gabor, T. Phan and C. Linnhoff-Popien, “Challenges for Reinforcement Learning in Quantum Computing”. arXiv preprint [qp], Dec. 2023. arXiv: 2312.11337.
  • M. Kölle, J. Mauerer, P. Altmann, L. Sünkel, J. Stein and C. Linnhoff-Popien, “Disentangling Quantum and Classical Contributions in Hybrid Quantum Machine Learning Architectures”. In Proceedings of the International Conference on Agents and Artificial Intelligence – Volume 3, pages 649-656, Feb. 2024. DOI: 10.5220/0012381600003636. arXiv: 2311.05559.
  • M. Kölle, M. Hgog, F. Ritz, M. Zorn, J. Stein and C. Linnhoff-Popien, “Quantum Advantage Actor-Critic for Reinforcement Learning”. In Proceedings of the International Conference on Agents and Artificial Intelligence – Volume 1, pages 297-304, Feb. 2024. DOI: 10.5220/0012383900003636. arXiv: 2401.07043.
  • S. Zielinski, J. Nüßlein, J. Stein, T. Gabor, C. Linnhoff-Popien and S. Feld, “Pattern QUBOs: Algorithmic Construction of 3SAT-to-QUBO Transformations”. Electronics – Volume 12, no. 16: 3492. Aug. 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 – Volume 11, no. 15; 3323, Jul. 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”. In Proceedings of the IEEE International Conference on Quantum Computing and Engineering – Volume 2, pages 20-25, Sep. 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”. In Proceedings of the IEEE International Conference on Quantum Computing and Engineering – Volume 2, pages 42-47, Sep. 2023. DOI: 10.1109/QCE57702.2023.10182. arXiv: 2311.15966.
  • 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”. In Proceedings of the IEEE International Conference on Quantum Computing and Engineering – Volume 1, pages 151-160, Sep. 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”. In Proceedings of the IEEE International Conference on Quantum Computing and Engineering – Volume 1, pages 591-600, Sep. 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”. In Proceedings of the Companion Conference on Genetic and Evolutionary Computation, pages 2254–2262, Jul. 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”. In Proceedings of the Companion Conference on Genetic and Evolutionary Computation, pages 2263–2271, Jul. 2023. DOI: 10.1145/3583133.3596330. 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”. In Proceedings of the International Conference on Computational Science – Volume 5, pages 48–55, Jun. 23. DOI: 10.1007/978-3-031-36030-5_4. arXiv: 2206.12510.
  • 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 preprint [qp], Jun. 2023. arXiv: 2305.08482.
  • 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 International Conference on Agents and Artificial Intelligence – Volume 3, pages 744-751, Feb. 2023. 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, pages 251-258, Feb. 2023. 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”. In Proceedings of the Companion Conference on Genetic and Evolutionary Computation, pages 2205–2213, Jul. 2022. DOI: 10.1145/3520304.3534034.
  • 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 preprint [qp], Jun. 2022. arXiv: 2206.14109.

Talks