Giovanni COSTANTINI

NEURAL NETWORK APPLICATION FOR IMPROVEMENTS OF DATA ANALYSIS WITHIN ANTIMATTER EXPERIMENT ASACUSA

Fundamental Physics group is one of the founders of ASACUSA collaboration. The experiment deals with fine spectroscopic anti- hydrogen measurements to investigate one of the deepest unsolved questions of physics: the CPT violation. Antimatter experiments deal with uncountable technical problems: from the production of the needed antiparticles, to their detection and classification. This last step is of great interest for neural network applications. It involves large data sets that allow strong machine training. Furthermore, the procedure for particle classification relies on data with a high grade of complexity, fact that gives to neural network a great opportunity of improving existing algorithms. My research carries forward the application of this technology in the ASACUSA experiment.

 
Monte Carlo simulations of proton-antiproton annihilations products

Working in a big collaboration means also working on common job for the experiment. I am part of the simulation team of ASACUSA. This means that I am dealing with MC simulation of the current experiment. I am learning and using software as Geant4 and Fluka to simulate annihilation products of proton-antiproton annihilations in order to study the multiplicity of π+ π-.

 

 
Presentation of the first-year research activities (November 25, 2020)


 
 

Curriculum: Physical Sciences for Engineering

Tutor: Luca VENTURELLI

email: g.costantini@unibs.it

 

Link to the research group web page

Link to publication list

 

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