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The competition

Beamline for Schools (BL4S) is an international scientific competition for high school students. For this, teams of students including a supervising teacher submit proposals to experiments that can be performed using a particle beam such as available at the test beam facilities at CERN and DESY. Out of all submitted proposals (2019: 178 proposals from 49 countries) the two best proposals are selected. These two teams get the chance to travel to DESY and perform their experiments with our help.

Beamline for Schools started at CERN, where the SPS T9 Test Beam was used for the winning experiments. In 2019, BL4S comes to DESY and its Test Beam Facility for the first time.


The winning teams 2019

In this edition the two winning teams are ...

The Particle Peers (Groningen, Netherlands)

This team will characterize particle showers regarding their shape, using several layers of silicon detectors with absorbing materials in between, hence a digital calorimeter.
The Particle Peers will perform measurements at different initial beam energies as well as with electrons and positrons and with this look for potential differences in the behaviour of matter and antimatter.

DESY Chain (Salt Lake City, USA)

The team DESY Chain proposed to investigate on the signal of traversing particles in different scintillators - the goal to confirm the correlation between the scintillator signal and the energy that the particles lose while traversing it.
For this experiment the beam particles traverse a scintillator first, of which the signal is recorded, then the deflection of the particle is measured by reconstructing the track angles before and after being deflected by a strong magnetic field. For the latter, three silicon detectors (Mimosa26) are placed before the magnet, and three gaseous detectors (MicroMegas) behind the magnet.
Also here, these measurements will be performed at different beam energies and for different scintillators, as well as for both electrons and positrons.



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Volunteering to support the students with their data analysis

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