PhD Petru-Mihai POTLOG

Main responsibilities

• project leader, coordinator of all performed activities;
• identify which are the major advantages and drawbacks of the algorithms used in reconstruction of tracks inside neutron detectors;
• asses the performances of algorithms for reconstructing neutrons from NeuLAND - SVA, STA, PNT and R3BRootNT;
• comparatively analyze the SAMURAI19 experimental data and simulations using the most efficient existing algorithm.
• selected the most reliable machine learning algorithm to help fulfill the goals of this project.

The visibility of the scientific contributions

• I was the deputy of the The High Energy Astrophysics and Advanced Technologies Laboratory of the Institute of Space Science from 2012 until 2015 and Secretary of the ISS Scientific Council from 2011 to 2016
• I initiated and developed wide international collaborations
• Currently I am working and leading the romanian team for a cooperation with JINR -Dubna
• I coordinate the Romanian team in the R3B international collaboration.
• In the last couple of years I coordinated the scientific research of the Nuclear Relativistic Physics Group from our institute, mainly trying to form and promote young scientists.
• In the last years, my main scientific work was the investigation of fragmentation in nuclear emulsions irradiated with high energy heavy ion beams.
• I was an expert evaluator of national programs for competition within PN2 Programme.
 

PhD Emil STAN

• 80 % involved in project;
• identified the machine learning algorithms used in high energy physics;
• pointed out the major advantages or disadvantages of most-effective algorithms currently used for particle tracks reconstruction;
• selected the most reliable machine learning algorithm to help fulfill the goals of this project.
• implementation of experimental setups in a Geant4 standalone application and identification of the most common processes which might take place in NeuLAND;
• preliminary analysis of test-experiments results using UCESB software and R3BRoot analysis framework;
• evaluation of SVA and STA reconstruction algorithms;

PhD Alina-Tania NEAGU

• 60 % involved in project;
• evaluation of the reconstruction algorithms for neutrons which can be used for NeuLAND detector;
• establish the parameters for user-interface application to simulations and data analysis macros.
• develop the user-interface application to simulations and data analysis macros;
• develop a conversion macro for the calibration and synchronization part of the analysis chain;
• developer of the user-interface application in Root and of the web-based platform R3Bsuit.

PhD Student Andreea CIRSTIAN

• 60 % involved in project;
• identified the machine learning algorithms used in high energy physics;
• pointed out the major advantages or disadvantages of most-effective algorithms currently used for particle tracks reconstruction;
• evaluation of the local reconstruction algorithms for charged particles and algorithms for neutrons;
• establish the parameters for user-interface application to simulations and data analysis macros;
• testing the unpacking and mapping of raw data using UCESB software and performing time and position calibration using land02;
• evaluation of the probabilistic neutron tracker and reconstruction algorithms currently used in R3BRoot framework;
• developer of the user-interface application in Root.

Economist Liliana Nedelcu

• 10 % involved in project;
• economist
• responsble with the financial situation of the project.