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CAAPS Workshop Recent advancements in electronic structure calculations

Functional materials are widespread, and accurately predicting their properties from quantum mechanics without free parameters is a major goal. The workshop (from October 22nd to 24th, 2025) gathers experts, particularly from the TURBOMOLE community, to share applications, new features, theoretical advances, and future directions. Integrated in this workshop is the CAAPS Symposium.

CAAPS Symposium

CAAPS is celebrating the International Year of Quantum Physics with a symposium at entitled ‘Electron Structure Theory, Quantum Chemistry and Quantum Computing’. It will take place on October 22nd, 2025 in the evening as usual with talks, poster session and reception. Save the Date!

CAAPS Workshop Algebraic Models in Data Science and Quantum Systems

Algebraic methodology has in recent years proven to be a very versatile framework to tackle problems in applied sciences and data. In this workshop (from October 9th to 10th, 2025) we bring together people from the field of applied algebra with scientists working on data science and quantum systems with the goal of fostering fruitful interactions and further expanding the use of algebraic methods in the sciences.

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The analysis and intelligent modelling of data is key to guiding future action. The Centre for Advanced Analytics and Predictive Sciences (CAAPS) unites data collecting and data processing disciplines at the University of Augsburg in a multidisciplinary centre with the goal of enabling progress and innovation in experimental and theoretical methods and their actual application.

Recent developments show how closely data acquisition and data processing interact in current research. This is evident especially in medical computer-aided diagnostics and therapy, in the production of high-tech materials and substances, and the application of Artificial Intelligence.

Such developments require infrastructure consisting of a complex technological process chain and theoretical mathematical and computer science methods for processing extensive sensor information and data sets. This emphasises the need for multidisciplinary cooperation between data collection and processing and offers the potential for innovation in economically and socially relevant fields of research.

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