CECAM's Machine Learning Workshop: Connecting Theory and Experiment

From July 8th to 16th, the Zuse Institute hosted the CECAM Flagship Workshop titled “Machine Learning of First Principles Observables.” Organized by the Theory Department of the Fritz Haber Institute, the workshop focused on addressing the increasing demand for advanced models, workflows, and databases. The workshop effectively pinpointed key areas for enhancement in predicting observables from first principles and laid the groundwork for a collaborative network to drive future research initiatives.

Overview and Scientific Program

During the CECAM Flagship Workshop: Machine Learning of First Principles Observables, eight subject-specific sessions aimed at bridging these experimental and theory communities, from “Thermodynamic observables” to “Long range interactions” and “Spectroscopy”, where speakers both from theory and experiment were invited. Additionally, a panel discussion after each session of talks addressed how that specific field was advancing with respect to ML for observables.

A poster session allowed many participants to present their work. The Best Poster Awards were awarded to Patricia König (Fritz-Haber-Institut, 1st), Pol Febrer Calabozo (ICN2, 2nd), and Marvin Friede (University of Bonn, 3rd). Non-scientific content in form of coffee breaks, a conference dinner, and an outing with a Berlin city tour enabled the participants to discuss and connect in a less formal setting.

Session and Discussion Topics

The eight sessions of the workshop were focusing on the following topics:

• Thermodynamic Observables
• Electronic Structure and Long Range Interactions (3 sessions)
• Magnetic Observables
• Spectroscopic Observables (2 sessions)
• Databases and Reaction Networks

Overarching all sessions, there were several topics that were identified to be very important in forming this community: Data sharing and management, Bridging Experiment and Simulation, and Metrics for Evaluating Predicted Data.

By addressing these topics, the workshop has not only pushed the boundaries of current methodologies but also fostered a collaborative environment that bridges theoretical and experimental approaches, ultimately contributing to more robust and applicable scientific advancements. Furthermore, there were several tangible outcomes of the workshop, especially with regards to the dissemination of open source codes, new collaboration between experimentalists and theorists, and discussion of new publications combining the research of different participants.

Overall, the workshop successfully identified the critical areas for improvement within the fields of predicting observables from first principles, and established a network for future research efforts.

General Information

Organisers:

• Simone S. Köcher (IET-1, Forschungszentrum Jülich GmbH)
• Angela F. Harper (Fritz-Haber Institut der Max Planck Gesellschaft)
• Hanna Türk (École Polytechnique Fédérale de Lausanne)
• Elena Gelzinyte (Fritz-Haber Institut der Max Planck Gesellschaft)
• Giulia Glorani (Fritz-Haber Institut der Max Planck Gesellschaft)