Results & publications

Scientific publications

 

References Consortium partner Data Link
Weder, Benjamin; Barzen, Johanna; Leymann, Frank; Salm, Marie: Automated Quantum Hardware Selection for Quantum Workflows. In: Electronics. Vol. 10(8), MDPI, 2021, https://doi.org/10.3390/electronics10080984 USTUTT (IAAS) 04.2021 https://www.mdpi.com/2079-9292/10/8/984
Frank Leymann, Johanna Barzen: Hybrid Quantum Applications Need Two Orchestrations in Superposition: A Software Architecture Perspective USTUTT (IAAS) 03.2021 https://arxiv.org/abs/2103.04320
Johanna Barzen: From Digital Humanities to Quantum Humanities: Potentials and Applications. To appear in the book Quantum Computing in the Arts and Humanities: An Introduction to Core Concepts, Theory and Applications. E. R. Miranda (Ed.). Cham: Springer Nature, (to appear). USTUTT (IAAS) 03.2021 https://arxiv.org/pdf/2103.11825.pdf
Weigold, Manuela; Barzen, Johanna; Leymann, Frank; Salm, Marie: Expanding Data Encoding Patterns For Quantum Algorithms. In: 2021 IEEE 18th International Conference on Software Architecture Companion (ICSA-C), IEEE, 2021(ICSA 2021). IEEE, 2021 USTUTT (IAAS) 03.2021 https://ieeexplore.ieee.org/document/9425837
Paul K. Faehrmann and Mark Steudtner and Richard Kueng and Maria Kieferova and Jens Eisert: Randomizing multi-product formulas for improved Hamiltonian simulation FUB 01.2021 https://arxiv.org/abs/2101.07808
Fisher Information in Noisy Intermediate-Scale Quantum Applications, J. J. Meyer FUB 2021 https://arxiv.org/abs/2103.15191
Roch, Christoph, et al. "Cross Entropy Optimization of Constrained Problem Hamiltonians for Quantum Annealing", Accepted at ICCS 2021

LMU 2021
Weigold, Manuela;  Barzen, Johanna; Leymann, Frank; and Vietz, Daniel: Patterns For Hybrid Quantum Algorithms. In: Proceedings of the 15th Symposium and Summer School on Service-Oriented Computing (SummerSOC 2021), to appear. USTUTT (IAAS) 2021
Salm, Marie; Barzen, Johanna; Leymann, Frank; Weder, Benjamin; Wild, Karoline: Automating the Comparison of Quantum Compilers for Quantum Circuits. In: Proceedings of the 15th Symposium and Summer School on Service-Oriented Computing (SummerSOC 2021), to appear. USTUTT (IAAS) 2021
An Analysis of Ontological Entities to represent Knowledge on Quantum Computing Algorithms and Implementations Fraunhofer FOKUS,

USTUTT (IAAS), StoneOne

2021 http://ceur-ws.org/Vol-2836/qurator2021_paper_15.pdf
Barzen, Johanna; Leymann, Frank; Falkenthal, Michael; Vietz, Daniel; Weder, Benjamin; Wild, Karoline: Relevance of Near-Term Quantum Computing in the Cloud: A Humanities Perspective. In: Ferguson D., Pahl C., Helfert M. (eds) Cloud Computing and Services Science. CLOSER 2020. Communications in Computer and Information Science, vol 1399. Springer 2021. USTUTT (IAAS) 2021 https://doi.org/10.1007/978-3-030-72369-9_2
Schuld, Maria, Ryan Sweke, and Johannes Jakob Meyer. "Effect of data encoding on the expressive power of variational quantum-machine-learning models." Physical Review A 103.3 (2021): 032430. FUB 2021 https://doi.org/10.1103/PhysRevA.103.032430
Weigold, Manuela; Barzen, Johanna; Leymann, Frank; Salm, Marie: Data Encoding Patterns for Quantum Algorithms. In: The Hillside Group (Hrsg): Proceedings of the 27th Conference on Pattern Languages of Programs (PLoP '20), 2021 (to appear). USTUTT (IAAS) 2020/2021
Herr, Daniel; Obert, Benjamin; Rosenkranz, Rosenkranz: Anomaly detection with variational quantum generative adversarial networks d-fine 10.2020 http://arxiv.org/abs/2010.10492
Frank Leymann, Johanna Barzen (2020): The bitter truth about gate-based quantum algorithms in the NISQ era. In: Quantum Sci. Technol. 5 044007 USTUTT (IAAS) 08.2020 https://doi.org/10.1088/2058-9565/abae7d  
Frank Leymann, Johanna Barzen: Pattern Atlas. In: Aiello M., Bouguettaya A., Tamburri D.A., van den Heuvel WJ. (eds) Next-Gen Digital Services. A Retrospective and Roadmap for Service Computing of the Future. Lecture Notes in Computer Science, vol 12521. Springer, Cham. https://doi.org/10.1007/978-3-030-73203-5_5 USTUTT (IAAS) 06.2020 https://doi.org/10.1007/978-3-030-73203-5_5
Leymann, Frank; Barzen, Johanna; Falkenthal, Michael; Vietz, Daniel; Weder, Benjamin; Wild, Karoline: Quantum in the Cloud: Application Potentials and Research Opportunities. In: Proceedings of the 10th International Conference on Cloud Computing and Services Science (CLOSER), 2020 USTUTT (IAAS) 05.2020 https://www.scitepress.org/ProceedingsDetails.aspx?ID=G0NMP0fVQpE=&t=1
T. Gabor, L. Suenkel, F. Ritz, L. Belzner, C. Roch, S. Feld, and C. Linnhoff-Popien, "The Holy Grail of Quantum Artificial Intelligence: Challenges in Accelerating the Machine Learning Pipeline," in Accepted at the 1st International Workshop on Quantum Software Engineering (QSE at ICSE), 2020 LMU 04.2020 https://arxiv.org/abs/2004.14035
Manuela Weigold, Johanna Barzen, Uwe Breitenbücher, Michael Falkenthal, Frank Leymann, and Karoline Wild: Pattern Views: Concept and Tooling for Interconnected Pattern Languages. In: Accepted at Proceedings of the 14th Symposium and Summer School On Service-Oriented Computing (SummerSOC), 2020 USTUTT (IAAS) 03.2020 https://arxiv.org/abs/2003.09127
Marie Salm, Johanna Barzen, Uwe Breitenbücher, Frank Leymann, Benjamin Weder, Karoline Wild: The NISQ Analyzer: Automating the Selection of Quantum Computers for Quantum Algorithms. In: Accepted at Proceedings of the 14th Symposium and Summer School On Service-Oriented Computing (SummerSOC), 2020 USTUTT (IAAS) 03.2020 https://arxiv.org/abs/2003.13409
Roch, C., Impertro, A., Phan, T., Gabor, T., Feld, S., & Linnhoff-Popien, C. (2020). Cross Entropy Hyperparameter Optimization for Constrained Problem Hamiltonians Applied to QAOA. In: Accepted at Proceedings of the IEEE International Conference on Rebooting Computing (ICRC), 2020 LMU 03.2020 https://arxiv.org/abs/2003.05292
Salm, Marie; Barzen, Johanna; Leymann, Frank; Weder, Benjamin: About a criterion of successfully executing a circuit in the NISQ era: What wd << 1/epsilon_eff really means. In: Proceedings of the 1st ACM SIGSOFT International Workshop on Architectures and Paradigms for Engineering Quantum Software (APEQS 2020), ACM, 2020 USTUTT (IAAS) 2020 https://dl.acm.org/doi/10.1145/3412451.3428498
Weder, Benjamin; Breitenbücher, Uwe; Leymann, Frank; Wild, Karoline: Integrating Quantum Computing into Workflow Modeling and Execution. In: Proceedings of the 13th IEEE/ACM International Conference on Utility and Cloud Computing (UCC 2020), 2020 (to appear) USTUTT (IAAS) 2020
Weder, Benjamin; Barzen, Johanna; Leymann, Frank; Salm, Marie; Vietz, Daniel: The Quantum Software Lifecycle. In: Proceedings of the 1st ACM SIGSOFT International Workshop on Architectures and Paradigms for Engineering Quantum Software (APEQS 2020), ACM, 2020 USTUTT (IAAS) 2020 https://dl.acm.org/doi/10.1145/3412451.3428497
Tensor network approaches for learning non-linear dynamical laws,

A. Goeßmann, M. Götte, I. Roth, R. Sweke, G. Kutyniok, J. Eisert,

arXiv:2002.12388

FUB 2020 https://arxiv.org/abs/2002.12388
Quantum certification and benchmarking, J. Eisert, D. Hangleiter, N. Walk, I. Roth, D. Markham, R. Parekh, U. Chabaud, E. Kashefi, Nature Reviews Physics 2, 382-390 (2020), arXiv:1910.06343 FUB 2020 https://arxiv.org/abs/1910.06343
On the quantum versus classical learnability of discrete distributions, R. Sweke, J.-P. Seifert, D. Hangleiter, J. Eisert,

arXiv:2007.14451

FUB 2020 https://arxiv.org/abs/2007.14451
Wild, Karoline; Breitenbücher, Uwe; Leymann, Frank; Vietz, Daniel; Zimmermann, Michael: TOSCA4QC: Two Modeling Styles for TOSCA to Automate the Deployment and Orchestration of Quantum Applications. In: 2020 IEEE 24th International Enterprise Distributed Object Computing Conference (EDOC), 2020. USTUTT (IAAS) 2020
A variational toolbox for quantum multi-parameter estimation, J. J. Meyer, J. Borregaard, J. Eisert,

arXiv:2006.06303

FUB 2020 https://arxiv.org/abs/2006.06303
Sweke, Ryan, et al. "Stochastic gradient descent for hybrid quantum-classical optimization." Quantum 4 (2020): 314. FUB 2020 https://quantum-journal.org/papers/q-2020-08-31-314/
Expressive power of tensor-network factorizations for probabilistic modeling, with applications from hidden Markov models to quantum machine learning, I. Glasser, R. Sweke, N. Pancotti, J. Eisert, J. I. Cirac, Advances in Neural Information Processing Systems 32, Proceedings of the NeurIPS 2019 Conference (2019), arXiv:1907.03741 FUB 2019 https://arxiv.org/abs/1907.03741
Closing gaps of a quantum advantage with short-time Hamiltonian dynamics, J. Haferkamp, D. Hangleiter, A. Bouland, B. Fefferman, J. Eisert, J. Bermejo-Vega, arXiv:1908.08069 FUB 2019 https://arxiv.org/abs/1908.08069

 

 

Talks & Articles

 

Title Author / Speaker Type Event / Location Data Link
Starting the quantum incubation journey with business experiments and partnerships Tim Leonhardt Lecture Politecnico di Milano - Workshops Osservatori Digital Innovation: L’offerta tecnologica di Quantum Computing: player e startup 05.05.2021
PlanQk-Messe 2021: „Quanten-Boost für die Optimierung“ Ulrike Ostler Article Datacenter Insider 30.03.2021 https://www.datacenter-insider.de/planqk-messe-2021-quanten-boost-fuer-die-optimierung-a-1011631/
Randomizing multi-product formulas for improved Hamiltonian simulation Paul Fährmann (FUB) Talk APS March Meeting 18.03.2021
The emerging quantum computing ecosystem Dr. Matthias Ziegler (Accenture) Keynote Quantum Business Europe 16.03.2021 https://www.quantumbusinesseurope.com/conference-program/
An Analysis of Ontological Entities to represent Knowledge on Quantum Computing Algorithms and Implementations Darya Martyniuk Scientific Workshop Conference Qurator 2021 11.02.2021
Randomizing multi-product formulas for improved Hamiltonian simulation Paul Fährmann (FUB) Poster The international Conference on Quantum Information Processing (QIP) 04.02.2021
Quantum Incubation Journey: Theory Founded Use Case and Technology Selection Sebastian Senge
Tim Leonhardt
Kinan Halabi (Accenture)
Article Digitale Welt Feb 2021 https://digitaleweltmagazin.de/magazin/
Quanten Computing für Netzbetreiber - Die Telekom beteiligt sich an PlanQK Ulrike Ostler Article Datacenter Insider 19.1.2021 https://www.datacenter-insider.de/quanten-computing-fuer-netzbetreiber--die-telekom-beteiligt-sich-an-planqk-a-992717/
Telekom setzt auf die Erforschung von Quantentechnologien M. Geitz (DT) website Deutsche Telekom, Medieninfo 18.01.2021 https://www.telekom.com/de/medien/medieninformationen/detail/telekom-setzt-auf-die-erforschung-von-quantentechnologien-616016
Mehr Internet für alle: T‑Labs und Fujitsu optimieren die Nutzung der Netzinfrastruktur Anne-Marie Tumescheit Blog post Fujitsu Blog, online 23.12.2020 https://blog.de.fujitsu.com/allgemeines/mehr-internet-fuer-alle-t-labs-und-fujitsu-optimieren-die-nutzung-der-netzinfrastruktur/
Genetische Algorithmen: Classical and Quantum Christoph Roch (LMU) PlanQK Webinar - 04.12.2020
Quantum Boltzmann Machine mit Anwendungsfall MNIST Datenrekonstruktion und Einblicke zur Behandlung chemischer Probleme Dean Smith Lecture PlanQK Webinar 06.11.2020
Machine Learning: Berlin Science Week Darya Martyniuk & Denny Mattern
(Fraunhofer FOKUS)
Lecture Berlin Science Week 04.11.2020 https://www.fokus.fraunhofer.de/de/fokus/event/science_week2020
Improving Quantum Sensing with Quantum Computers Johannes Jakob Meyer (FUB) Lecture IOP Quantum 2020, Online 21.10.2020 https://screencast-o-matic.com/watch/cY6e2jKolc
What Functions can Quantum Computers Learn? Johannes Jakob Meyer (FUB) Lecture IOP Quantum 2020, Online 19.10.2020 https://screencast-o-matic.com/watch/cY6e68K2SF
Probabilistic Modelling with Tensor Networks - A Bridge from Graphical Models to Quantum Circuits Jens Eisert (FUB) Lecture Quantum and Physics based machine learning 7.7.2020 https://ellisqphml.github.io/qphml2020.html#ellis-qphml-2020
Quantum Computing in der NISQ-Ära Frank Leymann (USTUTT) PlanQK Webinar - 04.06.2020
Einführung in variationelle Quanten-Algorithmen Johannes Meyer (FUB) PlanQK Webinar - 29.05.2020
Quantum in the Cloud: Application Potentials and Research Opportunities Frank Leymann (USTUTT), Keynote 10th International Conference on Cloud Computing and Services Science, CLOSER 2020 08.05.2020 http://closer.scitevents.org/KeynoteSpeakers.aspx#3
Quantum Optimization using Quantum Annealers Christoph Roch (LMU) PlanQK Webinar - 07.05.2020
Towards closing the loopholes of showing a quantum advantage for quantum simulators Jens Eisert (FUB) Lecture Quantum Devices: Simulation, Supremacy, and Optimization 04.05.2020 - 08.05.2020 https://simons.berkeley.edu/workshops/schedule/10560
Supervised Learning Using Quantum Technology Benedikt Sturm (FCE),
Daniel Jaroszewski (FCE)
Paper PHM Europe in Turin, July 27-31, 2020 Submission 30.04.2020 https://github.com/danieljaro/tfq-example-predictivemaintenance/blob/master/Supervised%20Learning%20using%20Quantum%20Technology.pdf
Quanten-Plattformen und Programmiersprachen Frank Leymann (USTUTT) PlanQK Webinar - 16.04.2020
Aufbau und Förderung der Community David Niehaus (SO) PlanQK Webinar - 14.04.2020
Industrial Relevance of Near-Term Quantum Computing Frank Leymann, Johanna Barzen (USTUTT), Industry lecture StoneOne AG, Berlin 06.03.2020
Mit Quantenbits in die Zukunft - Quantencomputer bedeuten eine Revolution in der Künstlichen Intelligenz Dennis Yücel Article - Tagesspiegel of the FU Berlin - 11.02.2020 https://www.fu-berlin.de/presse/publikationen/tsp/2020/tsp-februar-2020/quantenbits/index.html
“Introducing Quantum Computing: Fundamentals and Applications” Frank Leymann, Johanna Barzen (USTUTT), invited colloquium lecture with presentation of PlanQK Universität zu Köln 06.02.2020 https://cceh.uni-koeln.de/2020/01/23/einfuhrung-in-quanten-computing-gastvortrag-prof-dr-frank-leymann-johanna-barzen-6-februar-2020/
PlanQK – Quantum Computing Meets Artificial
Intelligence: how to make an ambitious idea reality
Frank Leymann (USTUTT), Andreas Liebing (SO), Matthias Rosenkranz (d-fine), Wolfgang Mergenthaler (FCE) Industry contribution - Digitale Welt Magazin - 01.02.2020 https://digitaleweltmagazin.de/aktuelle-ausgabe-02-2020/

 

 

Open-Source Code

 

Name Link to repository
Repository mit Begleitcode zum Paper “The effect of data encoding on the expressive power of variational quantum machine learning models”, M. Schuld, R. Sweke, J. J. Meyer, arXiv:2008.08605 https://github.com/XanaduAI/expressive_power_of_quantum_models
Demo: Trainable Quantum-Convolutions https://github.com/PlanQK/TrainableQuantumConvolution