Domain, Specialties : Physique nucléaire
Keywords:
Gamma-ray spectroscopy, nuclear fission, beta decay
Research Unit : DPhN / LEARN
Summary
The internship will consist in developing a semi-automatic software tool for the analysis of two-dimensional spectra. It will be applied to data from the FIPPS spectrometer to study the production of delayed gamma rays from the thermal fission of U-235.
Full description
The reactor antineutrino anomaly, namely a significant deficit of 5.5 +/- 1.2 % in the number of antineutrinos detected at short distance from the reactors remains an enigma. The results of several large-scale experiments, including the one carried out by our laboratory with the STEREO detector at the high flux reactor of Grenoble, confirm the anomaly but reject the hypothesis initially proposed, an oscillation of antineutrinos towards a sterile state. The current hypothesis is the existence of biases in the prediction obtained from reference beta spectra, measured in the 1980s with the BILL magnetic spectrometer at the Grenoble reactor. The prediction of antineutrino spectra directly from actual nuclear data, and thus without using the BILL measurements, is also possible but the uncertainties are dominated by errors and/or gaps in the beta decay data (Pandemonium effect).
The aim of the internship is to complete the development of a two-dimensional spectra analysis code based on Machine Learning techniques. This code will be used to extract in data from the FIPPS spectrometer (ILL) the precise production of delayed gamma-rays from various nuclei produced during the thermal fission of U-235, and to compare them with values calculated with current nuclear data (fission yields, decay data). These results will later be used to evaluate a model of the beta force function developed in our laboratory with the aim of correcting for the Pandemonium effect.
A good knowledge of nuclear physics and a strong interest in experimentation and data analysis are essential. This internship requires very good programming skills. Knowledge of the ROOT environment and Maching Learning techniques is an asset, but not a requirement.
Location
Saclay
Internship conditions
- Internship duration: 3 months
- Level of study: Bac+4/5
- Training: Ingenieur/Master
- Continuation in PhD thesis: No
- Application deadline: 1 février 2025
Experimental skills
Language : English
Useful methods and technics:
Gamma-ray spectra analysis
Computer languages and software:
C++, ROOT, python
Links
Supervisor
Materna Thomas
Phone: +33 1 69 08 40 91
Email :
Head of the laboratory DPhN / LEARN
Letourneau Alain
Phone: