The goal of this workshop is to bridge physics and data science, with quantum systems as a specific example. The goal is to explore new methods for managing and learning from large datasets. Topics will include quantum-inspired algorithms for data mining and machine learning techniques for analyzing complex data. While the focus is on the intersection of physics and data science, the data-driven algorithms discussed will be relevant to researchers from various fields who deal with large-scale data analysis. The workshop will provide a platform for Ph.D. students and post-docs to share knowledge, discuss challenges, and foster collaborations at this exciting interface. By encouraging the exchange of ideas between these fields, we hope to spark innovations that could transform both quantum and data analysis methods.

The workshop takes place at the University of Augsburg on Thursday, November 28, and Friday, November 29, 2024.

While application for in-person participation is limited to members of the University of Augsburg and their collaborators, it is planned to video broadcast the talks at the workshop.

Support by the  MNTF Graduate Center is gratefully acknowledged.

• Ulrich Bauer (TU München)
• Annabelle Bohrdt (U Regensburg)

• Paolo Andrea Erdman (FU Berlin)

• Andreas Elben (IQIM & Walter Burke Institute, Caltech)
• Mario Krenn (MPI Science of Light, Erlangen)
• Lode Pollet (LMU München)
• Tiago Mendes-Santos (Pasqal, Paris)
• Roberto Verdel Aranda (ICTP Trieste)