ZIB | Zuse Institute Berlin (ZIB)

Das Zuse-Institut Berlin (ZIB)

ist ein interdisziplinäres Forschungsinstitut für angewandte Mathematik und datenintensives High-Performance-Computing. Die Forschung konzentriert sich auf die Modellierung, Simulation und Optimierung in Zusammenarbeit mit wissenschaftlichen Kooperationspartnern aus Wissenschaft und Wirtschaft.

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Dynamic Structure of Life

How cells organize patterns in space and time

Researchers at ZIB develop data analysis and mathematical modeling techniques and apply them in cooperation with biologists in order to gain insight into fundamental principles of biological processes, such as cell division, protein regulation, and brain formation and activity.

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Dusting off Cometary Surfaces

Modeling gas and dust around comet Churyumov-Gerasimenko

The European Space Agency Rosetta mission to comet 67P/Churyumov-Gerasimenko (67P/C-G) sent back millions of observations during its journey around the sun. ZIB contributed to the scientific analysis of the space mission by modeling the gas and dust environment around the comet on the HLRN supercomputer. Photo: ESA/Rosetta/NavCam

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Specific fuel consumption for the Lufthansa fleet

New navigation systems for aircraft save fuel and time

Cheap air transport has become a matter of course since the 1980s.

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Mathematics Meets Humanities

Examples from ancient studies and psychology

For many years, the humanities and mathematics were considered as two sciences that have little to do with one another. During the last decade, however, researchers on both sides realized the potential lying in the respective other field. In this article, we present four examples illustrating this potential.

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Software Sustainability in the Age of Open Science

When mathematicians combine mathematical theory and real-world applications, then mathematical research software complements chalk and blackboard, or pencil and paper. Today, mathematical software plays a central role in research and key technologies and has an increasing impact on mathematical education.

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Scalability and Concurrency

Challenges from Two Interdisciplinary Research Projects

How to chop and distribute hundreds of continuous high-bandwidth data streams efficiently in a network so that, for each time frame, the sensor data is collected in a particular analysis node? How to exploit modern network capabilities, like remote direct memory access, to improve the scalability of SAT solving on supercomputers?

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