Servizio Comunitario di Informazione in materia di Ricerca e Sviluppo - CORDIS

High energy physics data analysis (application)

The next generation High Energy Physics (HEP) experiments at the Large Hadron Collider (LHC) would produce an unprecedented amount of data. A worldwide spread community of thousands of physicists willing to analyze that data would profit of grid technologies for this work. We have parallelized some algorithms that could be used during this analysis what would save a great amount of time to scientists doing this kind of analysis.

The artificial neural network (ANN) training application is an interactive program that trains a n ANN with simulated HEP events, in order to being able to distinguish the interesting events (signal) from the already known ones (background).

Thanks to the parallelization of the program, and to its good scalability, the wait time for this kind of analysis has been reduced from several hours to a few minutes.

A graphical user interface is provided through the CrossGrid Migrating Desktop (MD). Using it the user can monitor the training process through the training error evolution, and can interrupt it, or reset the weights to be sure of avoiding local minima.

Informazioni correlate

Reported by

Instituto de Fisica de Cantabria, IFCA
Avda de los Castros s/n 39005