Nouvelles Approches de Machine Learning pour la Caractérisation des Détecteurs AGATA et Étude de la Structure Nucléaire des Isotopes de Niobium Riches en Neutrons

In-beam gamma-ray spectroscopy, particularly with high-velocity recoil nuclei, requires precise Doppler correction. The Advanced GAmma Tracking Array (AGATA) represents a groundbreaking development in gamma-ray spectrometers, boosting the ability to track gamma-rays within the detector. This capability leads to exceptional position resolution which ensures optimal Doppler corrections. The high-purity germanium crystals used in AGATA are divided into 36 segments. The determination of interaction point positions is achieved by analyzing the shape of the measured electrical pulses. The algorithm used, PSA (Pulse Shape Analysis), compares the measured signals with simulated reference simulated databases, which presents accuracy limitations. On the other hand, experimental databases can be obtained by scanning crystals with collimated gamma-ray sources using a computationally expensive method called Pulse Shape Coincidence Scan (PSCS). This work proposes, a novel machine learning algorithm based on Long Short-Term Memory (LSTM) networks that replaces the PSCS method, reducing processing time and achieving higher consistency and accuracy. This thesis also explores the nuclear structure of neutron-rich Niobium isotopes. These nuclei, with Z and N around 40 and 60, respectively, exhibit one of the most remarkable examples of a sudden shape transition between spherical and highly deformed nuclei. These isotopes were produced at GANIL during two experiments involving transfer-induced fission and fusion. The combination of the VAMOS++ spectrometer, AGATA, and the EXOGAM gamma spectrometer offers a unique opportunity to obtain precise isotopic identification (A, Z) on an event-by-event basis for one of the fission fragments, with the prompt and delayed gamma-rays emitted in coincidence with unprecedented resolution. The research presents updated level schemes for the Nb isotopes and introduces new band structures for the Nb nuclei, pushing the boundaries of what is possible in fission experiments. It highlights spherical/deformed shape coexistence in theNb isotope, reassesses the level scheme of Nb and the placement of its rotational band, and tracks the evolution of nuclear deformation with increasing neutron number, providing valuable experimental data to refine nuclear models. The results are compared with the most recent theoretical calculations of each isotope.

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theses.fr (ABES)
Published
2024-12-12
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Nuclear physics research studies
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article

Nouvelles Approches de Machine Learning pour la Caractérisation des Détecteurs AGATA et Étude de la Structure Nucléaire des Isotopes de Niobium Riches en Neutrons

theses.fr (ABES)
Nuclear physics research studies
article

Nouvelles Approches de Machine Learning pour la Caractérisation des Détecteurs AGATA et Étude de la Structure Nucléaire des Isotopes de Niobium Riches en Neutrons

article en

Abstract

In-beam gamma-ray spectroscopy, particularly with high-velocity recoil nuclei, requires precise Doppler correction. The Advanced GAmma Tracking Array (AGATA) represents a groundbreaking development in gamma-ray spectrometers, boosting the ability to track gamma-rays within the detector. This capability leads to exceptional position resolution which ensures optimal Doppler corrections. The high-purity germanium crystals used in AGATA are divided into 36 segments. The determination of interaction point positions is achieved by analyzing the shape of the measured electrical pulses. The algorithm used, PSA (Pulse Shape Analysis), compares the measured signals with simulated reference simulated databases, which presents accuracy limitations. On the other hand, experimental databases can be obtained by scanning crystals with collimated gamma-ray sources using a computationally expensive method called Pulse Shape Coincidence Scan (PSCS). This work proposes, a novel machine learning algorithm based on Long Short-Term Memory (LSTM) networks that replaces the PSCS method, reducing processing time and achieving higher consistency and accuracy. This thesis also explores the nuclear structure of neutron-rich Niobium isotopes. These nuclei, with Z and N around 40 and 60, respectively, exhibit one of the most remarkable examples of a sudden shape transition between spherical and highly deformed nuclei. These isotopes were produced at GANIL during two experiments involving transfer-induced fission and fusion. The combination of the VAMOS++ spectrometer, AGATA, and the EXOGAM gamma spectrometer offers a unique opportunity to obtain precise isotopic identification (A, Z) on an event-by-event basis for one of the fission fragments, with the prompt and delayed gamma-rays emitted in coincidence with unprecedented resolution. The research presents updated level schemes for the Nb isotopes and introduces new band structures for the Nb nuclei, pushing the boundaries of what is possible in fission experiments. It highlights spherical/deformed shape coexistence in theNb isotope, reassesses the level scheme of Nb and the placement of its rotational band, and tracks the evolution of nuclear deformation with increasing neutron number, providing valuable experimental data to refine nuclear models. The results are compared with the most recent theoretical calculations of each isotope.

theses.fr (ABES)
Institute of Nuclear Physics of Lyon (FR), Institut de Physique des 2 Infinis de Lyon (FR)
Openalex Percentile: Top 87%
Nuclear physics research studies
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