T2K (Tokai to Kamioka) is a long-baseline neutrino experiment based in Japan, designed to measure neutrino oscillation parameters through electron neutrino appearance and muon neutrino survival probabilities. In recent years, T2K has undergone significant upgrades to its beam-line and the magnetized Near Detector (ND280) to increase the neutrino flux and reduce systematic uncertainties. These upgrades are critical for both T2K and the upcoming long-baseline program of Hyper-Kamiokande experiment, expected to be completed in 2027. A central component of the ND280 upgrade is the installation of two High-Angle Time Projection Chambers (HA-TPCs), capable of detecting charged particles at large angles relative to the beam direction. Both HA-TPCs were successfully installed at J-PARC by May 2024. This thesis focuses on three core aspects: (i) the design, production, and validation of field cages, (ii) electric field studies, and (iii) the development of a machine learning-based track reconstruction algorithm. Each HA-TPC consists of a gaseous active volume enclosed in a field cage made of lightweight composite materials, optimized for both mechanical strength and minimal material interference. Readout is performed using Resistive Micromegas sensors, which include a resistive layer to enhance spatial resolution and protect electronics from sparks. These detectors were validated through test beams and cosmic ray campaigns at CERN and J-PARC. After installation in late 2023 and early 2024, they were commissioned using cosmic rays and subsequently a neutrino beam. Field cages serve several purposes: they provide mechanical support, maintain a uniform electric field, and contain the gas mixture while preventing contamination. Constructed from low-Z composite materials, the cages are designed to reduce scattering and particle interactions. Achieving precise geometries and robust electrical insulation required careful design, prototyping, and testing. This thesis presents my contributions to the development and implementation of the HA-TPCs, focusing on electric field behavior and novel track reconstruction techniques. My work is divided into three main parts: 1.Field Cage Production and Validation: I investigated the electrical and mechanical properties of the field cages, addressing a key issue during the production of the first full-scale prototype (FC0). Non-linear current-voltage behavior suggested parasitic resistive paths. Through testing, modeling, and design refinements, I identified and resolved this issue. I also supervised the production process, established quality assessment protocols, and contributed to the assembly and commissioning of the HA-TPCs at CERN and J-PARC. Electric Field Characterization: I evaluated the uniformity of the electric drift field, which is essential for accurate track reconstruction. Using finite element method (FEM) simulations and cosmic ray data, I identified distortions near the cathode. A 3D field map from FEM simulations was used to correct these distortions, significantly improving reconstruction accuracy. Novel Track Reconstruction Algorithm: I developed a machine learning-based algorithm that uses the amplitude and full width at half maximum (FWHM) of pad signals to model the local trajectory of particle tracks. While traditional methods perform well for momentum reconstruction, the new approach shows promising improvements in spatial resolution, especially for diagonal tracks. Further optimizations include refining input features and enhancing the model architecture. In conclusion, this thesis presents the successful development, testing, and commissioning of the HA-TPCs, which play a vital role in the ND280 upgrade and the broader T2K and Hyper-Kamiokande programs. The work presented here advances the understanding of electric field effects in TPCs and introduces innovative reconstruction techniques, paving the way for future improvements in neutrino detection and measurement.
The Field Cages of the new Time Projection Chambers (TPCs) for the T2K Upgraded Near Detector: production, characterization, electric field performance and advanced track reconstruction
FELTRE, MATTEO
2025
Abstract
T2K (Tokai to Kamioka) is a long-baseline neutrino experiment based in Japan, designed to measure neutrino oscillation parameters through electron neutrino appearance and muon neutrino survival probabilities. In recent years, T2K has undergone significant upgrades to its beam-line and the magnetized Near Detector (ND280) to increase the neutrino flux and reduce systematic uncertainties. These upgrades are critical for both T2K and the upcoming long-baseline program of Hyper-Kamiokande experiment, expected to be completed in 2027. A central component of the ND280 upgrade is the installation of two High-Angle Time Projection Chambers (HA-TPCs), capable of detecting charged particles at large angles relative to the beam direction. Both HA-TPCs were successfully installed at J-PARC by May 2024. This thesis focuses on three core aspects: (i) the design, production, and validation of field cages, (ii) electric field studies, and (iii) the development of a machine learning-based track reconstruction algorithm. Each HA-TPC consists of a gaseous active volume enclosed in a field cage made of lightweight composite materials, optimized for both mechanical strength and minimal material interference. Readout is performed using Resistive Micromegas sensors, which include a resistive layer to enhance spatial resolution and protect electronics from sparks. These detectors were validated through test beams and cosmic ray campaigns at CERN and J-PARC. After installation in late 2023 and early 2024, they were commissioned using cosmic rays and subsequently a neutrino beam. Field cages serve several purposes: they provide mechanical support, maintain a uniform electric field, and contain the gas mixture while preventing contamination. Constructed from low-Z composite materials, the cages are designed to reduce scattering and particle interactions. Achieving precise geometries and robust electrical insulation required careful design, prototyping, and testing. This thesis presents my contributions to the development and implementation of the HA-TPCs, focusing on electric field behavior and novel track reconstruction techniques. My work is divided into three main parts: 1.Field Cage Production and Validation: I investigated the electrical and mechanical properties of the field cages, addressing a key issue during the production of the first full-scale prototype (FC0). Non-linear current-voltage behavior suggested parasitic resistive paths. Through testing, modeling, and design refinements, I identified and resolved this issue. I also supervised the production process, established quality assessment protocols, and contributed to the assembly and commissioning of the HA-TPCs at CERN and J-PARC. Electric Field Characterization: I evaluated the uniformity of the electric drift field, which is essential for accurate track reconstruction. Using finite element method (FEM) simulations and cosmic ray data, I identified distortions near the cathode. A 3D field map from FEM simulations was used to correct these distortions, significantly improving reconstruction accuracy. Novel Track Reconstruction Algorithm: I developed a machine learning-based algorithm that uses the amplitude and full width at half maximum (FWHM) of pad signals to model the local trajectory of particle tracks. While traditional methods perform well for momentum reconstruction, the new approach shows promising improvements in spatial resolution, especially for diagonal tracks. Further optimizations include refining input features and enhancing the model architecture. In conclusion, this thesis presents the successful development, testing, and commissioning of the HA-TPCs, which play a vital role in the ND280 upgrade and the broader T2K and Hyper-Kamiokande programs. The work presented here advances the understanding of electric field effects in TPCs and introduces innovative reconstruction techniques, paving the way for future improvements in neutrino detection and measurement.File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.14242/210577
URN:NBN:IT:UNISI-210577