GSI/FAIR AI Workshop

Using the recent advances in machine learning (ML) algorithms, especially in the area of image recognition, we plan to develop new ML particle identification algorithms for the PANDA Barrel DIRC and compare the results to conventional reconstruction methods.
First network implementations show a performance comparable to conventional methods on a limited phase space. As a next step, we are...

The calibration of detectors in heavy-ion experiments is key to the measurement of several physics observables. Corrections must be applied to the expected detector signal in order to account for changes in environmental or hardware conditions over time and in different spatial regions. The use of neural network-based corrections trained on clean input signals allows this to be performed with...

LISA project aims to develop an array of five 5 × 5 grids of thin single-crystal diamond detectors, to measure otherwise inaccessible lifetimes in exotic nuclei. Determining reaction positions in the target is a pivotal component of the project and we are developing ML algorithms for characterization.We used ANN and Random Forest Algorithm on the simulated data. RF algorithm has shown the most...

Non-destructive Schottky detectors can be used to accurately determine the masses and lifetimes of exotic nuclear species and/or their isomeric states in storage rings. The analysis requires time-resolved spectra to undergo particle identification and determination of frequency spread ∆f and decay time. Often times corrections for rigidity, drift, etc. need to be applied, or spectra need to be...