The purpose of this Masters thesis is split into two sections. Firstly and largely, explore the viability, usability, and scalability of Artificial Intelligence (AI) for particle identification with silicon detectors. Secondly, determine the efficiency of a multichannel plate detector (MCP) with and without the application of a Caesium Iodine (CsI) doped layer.

The purpose of this Masters thesis is split into two sections. Firstly and largely, explore the viability, usability, and scalability of Artificial Intelligence (AI) for particle identification with silicon detectors. Secondly, determine the efficiency of a multichannel plate detector (MCP) with and without the application of a Caesium Iodine (CsI) doped layer.

Exploitation of Artificial Intelligence for Particle Identification with Silicon Detectors

MICHIE, CRAIG THOMAS
2024/2025

Abstract

The purpose of this Masters thesis is split into two sections. Firstly and largely, explore the viability, usability, and scalability of Artificial Intelligence (AI) for particle identification with silicon detectors. Secondly, determine the efficiency of a multichannel plate detector (MCP) with and without the application of a Caesium Iodine (CsI) doped layer.
2024
Exploitation of Artificial Intelligence for Particle Identification with Silicon Detectors
The purpose of this Masters thesis is split into two sections. Firstly and largely, explore the viability, usability, and scalability of Artificial Intelligence (AI) for particle identification with silicon detectors. Secondly, determine the efficiency of a multichannel plate detector (MCP) with and without the application of a Caesium Iodine (CsI) doped layer.
A.I
Particle ID
Machine Learning
Silicon Detectors
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12608/91195