SPOT
SPOT is an interactive visualization tool for multi-dimensional data. It allows quick analysis of complex datasets and easy identification of correlations between variables.
The intelligent Dark Matter survey
Astronomical observations have established that more than 80% of all matter in the Universe is made up of Dark Matter (DM). The determination of the nature of Dark Matter is one of the most important questions in Physics and Astronomy; it will most likely be the result of a combination of all worldwide available experimental data. Combining the worldwide data within the most general models of Dark Matter was the objective of this project. This will test the models, determine the allowed parameter space for Dark Matter and help focus the effort for experimental searches. Finding viable solutions and exploring in a statistically convergent manner huge DM-model parameter spaces is the challenge which we like to attack with advanced eScience methods. Technical solutions to these questions have also multiple applications in society.
We developed new algorithms to find DM solutions in large multidimensional parameter spaces. Furthermore we developed SUSY-AI to accelerate the computing machinery for DM searches. Finally we could develop a prototype for the first web-accessible) “DM model” database.
With the help of such eScience machinery we will establish one the most promising ways to pinpoint DM in the upcoming years.
Self-learning machines hunt for explosions in the universe and speed up innovations in industry and...
Interpretable large scale deep generative models for Dark Matter searches
New tools for researchers in plasma, combustion and chemical reactor science
Transferring code to the larger community
Large scale statistical data analysis in particle physics
Observing processes that are inaccessible to optical telescopes
Modern big data front and backends in the hunt for Dark Matter
SPOT is an interactive visualization tool for multi-dimensional data. It allows quick analysis of complex datasets and easy identification of correlations between variables.