In factories handling fissile materials, criticality accidents can occur. The CAAS-3S system produced by Mirion Technologies includes a range of equipment to detect these accidents and alert employees to evacuate the facility and protect their health. The system consists of four types of plastic scintillation detectors. To determine the potential locations of the detectors and to ensure that the system detects all criticality accidents, Mirion Technologies is conducting positioning studies. These studies simulate criticality accidents using the Monte Carlo based code MCNP. Mirion Technologies would like to develop an MCNP model of these probes to build a response function to predict the experimental stress of the probes. Furthermore, during a criticality accident, the ambient temperature may increase significantly and the system must be able to detect an accident during a temperature rise without generating a false alarm. The CAAS-3S system includes a temperature correction. This master thesis has demonstrated that the temperature correction was able to trigger the alarm without generating false alarms for temperatures up to 70°C. MCNP models of the four probes of the system have been designed. It appeared that the energy rate deposited in the gamma scintillator calculated numerically by MCNP allowed to predict the experimental voltage during irradiation under photon radiation. In the case of neutron irradiation it has been proven that the reaction rate (n,alpha) on lithium contained in the scintillation matrix allows to predict the experimental voltage without having to simulate the alpha particles, thus reducing the calculation time. Correlation coefficients based on experimental results and numerical simulations have been determined for several incident particle energies in order to create a probe response function. / I fabriker som hanterar klyvbart material kan kriticitetsolyckor inträffa. CAAS-3S-systemet som tillverkas av Mirion Technologies innehåller en rad olika utrustningar för att upptäcka dessa olyckor och varna de anställda så att de kan evakuera anläggningen och skydda sin hälsa. Systemet består av fyra typer av plastsintillationsdetektorer. För att fastställa de potentiella platserna för detektorerna och för att se till att systemet upptäcker alla kriticitetsolyckor genomför Mirion Technologies positioneringsstudier. I dessa studier simuleras kritiska olyckor med hjälp av den Monte Carlo-baserade koden MCNP. Mirion Technologies skulle vilja utveckla en MCNP-modell av dessa sonder för att bygga upp en responsfunktion för att förutsäga den experimentella belastningen på sonderna. Under en kritisk olycka kan dessutom omgivningstemperaturen öka avsevärt och systemet måste kunna upptäcka en olycka under en temperaturökning utan att generera ett falsklarm. CAAS-3S-systemet innehåller en temperaturkorrigering. I detta examensarbete har det visats att temperaturkorrigeringen kunde utlösa larmet utan att generera falska larm för temperaturer upp till 70 °C. MCNP-modeller av systemets fyra prober har utformats. Det visade sig att den energihastighet som deponeras i gammascintillatorn, som beräknats numeriskt med MCNP, gjorde det möjligt att förutsäga den experimentella spänningen under bestrålning med fotonstrålning. Vid neutronbestrålning gör reaktionshastigheten (n,alfa) på litium i scintillationsmatrisen det möjligt att förutsäga den experimentella spänningen utan att simulera alfapartiklarna, vilket minskar beräkningstiden. Korrelationskoefficienter baserade på experimentella resultat och numeriska simuleringar har bestämts för flera energier av infallande partiklar för att skapa en sonderesponsfunktion.

The γ-ray characterizing possibility of the neutron collimated flux monitor (in short, Neutron Camera) at the Mega Ampere Spherical Tokamak (MAST) is explored. Typically used to monitor neutron emission, the Neutron Camera has excellent neutron/γ-ray discrimination properties and thus presents the opportunity to measure spatially and temporally resolved γ-ray emission - a possibility of an additional fusion diagnostics method with already existing equipment. An Online Data Analysis (ODA) code was used to analyze the data on γ-rays from several plasma discharges with similar plasma parameters. A high statistics temporal distribution of the γ-ray emission and a lower statistics spatial distribution were analyzed. However, the low energy resolution and range for the Neutron Camera γ-ray measurements revealed few conclusive results on the origin of the higher energy γ-rays. Detection systems with higher energy resolution and range are suggested for an extensive analysis of γ-ray emission at MAST Upgrade.

After nearly 100 years of particle acceleration, particle accelerator experiments continue providing results within the field of high energy physics. Particle acceleration is used worldwide in practical applications such as radiation therapy and materials science research. Unfortunately, these accelerators are large and expensive. Dielectric Laser Acceleration (DLA) is a promising technique for accelerating particles with high acceleration gradients, without requiring large-scale accelerators. DLA utilizes the electric field of a high energy laser to accelerate electrons in the proximity of a nanostructured dielectric surface.The aim of this project was limited to laser beam routing and imaging techniques for a DLA experiment. The goal was to design the laser beam pathway between the laser and the dielectric sample, and testing a proposed imaging system for aiming the laser. This goal was achieved in a test setup using a low-energy laser. In the main setup including a femtosecond laser, the result indicated lack of focus. For a full experimental setup, a correction of this focus is essential and the beam path would need to be combined with a Scanning Electron Microscope (SEM) as an electron source.

The new millennium has seen revolutionary advances in photonsource technology. As the newly constructed synchrotron facilityMAX IV in Lund, Sweden, pushes brilliance toward what isphysically possible, low-yield spectroscopic techniques, such asresonant inelastic X-ray scattering (RIXS), open new doors inmolecular and condensed matter research. The VERITAS beamline atMAX IV is designed for high-resolution vibrational RIXS on gases.X-rays interact with flowing molecules inside a window-cappedcell, but the radiation intensity is expected to be large enoughto damage the windows, and cause build-up of photochemicalproducts, which lowers transmission. To address these issues, anovel gas cell design is presented, wherein the distance betweensample gas and window is increased by using a flowing heliumbuffer. The main challenge is maintaining a steep sample gasconcentration gradient within the cell, and to that end, gas flowswere simulated on various geometries by using the finite elementmethod to solve the Navier-Stokes equations. Results were used toconstruct a prototype, and confocal Raman microscopy was used forconcentration characterization. Preliminary measurements revealeda uniform sample gas distribution, and the technique proved to beinefficient for wide scanning of parameter values. This suggeststhat a supplementary experiment is required to find roughestimates of good parameter values, which can then be followed upwith new Raman measurements for fine-tuning of the properparameter space. Real-time visualization of the sample gas flow,using a visible gas under an optical microscope, is one candidatefor this supplementary experiment.

To study electron emissions and dark currents in the accelerating structures in particle colliders, a test facility with a spectrometer has been constructed at CERN. This spectrometer has been simulated in the C++ toolkit GEANT4 and in this project the simulation has been improved to handle new realistic input data of the emitted electrons. The goal was to find relations between where the electrons are emitted inside the accelerating structure and the energy or position of the particles measured by the spectrometer. The result was that there is a linear relation between the initial position of the electrons and the width in the positions of the particles measured by the spectrometer. It also appears to be a relations between energy the emitted electrons get in the accelerating structure, which is related to the position, and the energy they deposit in the spectrometer. Further studies where the simulations are compared with real measurement data are required to determine whether these relations are true or not, find better reliability in the relations and get a better understanding of the phenomena.

In the planned linear accelerator called Compact Linear Collider, CLIC, electrons and positrons will be accelerated to velocities near the speed of light. A limiting factor in accelerating structures are vacuum breakdowns, which are electrical discharges from a surface as a result of a large electric field being applied. In the preparatory studies for the CLIC, Uppsala University in collaboration with The European Organization for Nuclear Research, CERN, is building a DC Spark system to analyze vacuum breakdowns. This system containing large planar electrodes will be cooled down all the way down to around 4 K in order to limit the rate of wich vacuum breakdowns happen. When cooling a system like this, which consists of different components made of different materials there is the question of how the system will be affected. The objective of this project is to investigate how the cooling will affect the stability in terms of stresses and to analyze the cool down time of the system. Another goal is to make a material recommendation for a few parts based on the results. This will be done by simulating the cooling in COMSOL Multiphysics, which is a program that uses finite element analysis to solve complex problems where different branches of physics interact. The conclusion is that the system will most likely be stable as it is and there is no need to redesign it. The choice of recommended material is alumina with the reason being it should cause the least stress and the smallest gap between the electrodes when the cooling is done. There was no big difference in the cool down time between the materials. Further studies and simulations on the system is also recommended since there are many factors not taken into consideration in this study.

While holding a firm position in popular culture and science fiction, Dark Matter (DM) is nonetheless a highly relevant topic at the forefront of modern particle physics. We study the applicability of characterizing DM particle candidates SUSY neutralino and sneutrino using Deep Learning (DL) methods. We focus on the monojet and mono-Z signatures and the emergence of missing transverse energy as the result of the undetectable DM candidates. Based on kinematic distributions of outgoing particles as input, a DM candidate classifier is built for each signature, along with a DM mass regressor. The DM candidate classifier obtained near perfect accuracy of 0.995 for the monojet, and 0.978 for mono-Z signature. The monojet and mono-Z mass regressors achieved a Mean Absolute Percentage Error (MAPE) of 17.9 % and 8.5 % respectively. Furthermore, we discuss both the shortcomings and simplification that our choice of model implied, as well as an interpretation of the results. Finally, we debate the prospects of DL in the discovery of new physics and it's use in experiments.

Artificial intelligence (AI) and deep learning have made a full impact on society the last decades, including the realm of particle physics. This thesis explores whether a neural network, a deep learning program mimicking the biological brain, can be used to reject noise in real time at the Radio Neutrino Observatory in Greenland (RNO-G). RNO-G aims to detect radio waves in the ice cape of Greenland, induced by ultra high energy neutrinos ($>10^{18}$ eV). Due to the low flux of neutrinos at these energies, it is desired to increase the sensititivty of RNO-G by lowering the trigger threshold as much as possible. However, lowering the threshold is currently limited by unavoidable thermal noise fluctuations that would otherwise saturate the detector. Previous research has shown that a neural network could be used on a similar neutrino detector, ARIANNA, to reject thermal noise in real time, thus making it possible to lower the trigger threshold below the noise floor. This thesis aims to do the same for RNO-G.

The Large Hadron Collider at CERN is scheduled to undergo upgrades in 2026-2028 to significantly increase its luminosity. These upgrades, while providing the experiments with a higher collision rate, pose a number of challenges to the design of the hardware and software in the detectors. The Tile Calorimeter (a scintillating sampling calorimeter read out by photomultiplier tubes) at the ATLAS experiment will have its read-out electronics completely replaced to enable performance and reliability improvements.  Advances in electronics, new requirements due to the luminosity upgrade as well as lessons learned from the current readout scheme drove development with the goals to partition the readout into small independent units with full granularity readout and a robust mitigation strategy for radiation induced errors. To verify the functionality of the new system while retaining backward compatibility a "Demonstrator'' has been developed to emulate the current functionality while using new and improved hardware. The board responsible for managing digitized calorimeter data and communicating with the off-detector electronics, called the DaughterBoard, is the main focus of this thesis. It has two electrically isolated sides for redundancy where each side consists of voltage regulators, two optical transceivers, a GigaBit transceiver chip (for clocking and configuration) and a Kintex FPGA for data processing. In addition to data management and transmission, the FPGA (and every other component) needs to be able to withstand the effects of radiation both in terms of total dose (ionization and displacement damage) and due to single event effects. The DaughterBoard was developed with this in mind and has undergone several radiation tests during its development to verify reliability and fault tolerance. / CERN

Memory corruption attacks pose a significant threat to the security of embedded devices with limited resources that lack basic protection mechanisms. Control Flow Integrity (CFI) is a promising technique to mitigate these attacks by ensuring that the program’s control flow adheres to a predetermined set of rules. In this project, we propose a CFI solution tailored for embedded devices based on combining a type-based approach for indirect branches with a shadow stack approach to protect return addresses. Our solution targets the ARM Cortex-M33 architecture and is evaluated on various applications that are adequate for low-end devices, including embedded cryptographic primitives and a real-time operating system. Our solution provides a high level of security, allowing for a 99.99% reduction in attacks using the average reduction metric (AIR). However, we acknowledge that the performance overhead may be a concern for some use cases. The evaluation of our Control Flow Integrity (CFI) implementation shows that it incurs a performance overhead ranging between 7% and 81%, with a relatively small size overhead of around 3%. Therefore, we propose that the use of adequate architectural models could help reduce the performance overhead while still maintaining good security guarantees. Our study highlights the trade-off between security and performance in CFI implementations and provides insights into potential areas for improvement. / Minneskorruptionsattacker utgör ett betydande hot mot säkerheten för inbyggda enheter med begränsade resurser som saknar grundläggande skyddsmekanismer. Kontrollflödesintegritet (CFI) är en lovande teknik för att mildra dessa attacker genom att säkerställa att programkontrollen följer en förutbestämd uppsättning regler. I detta projekt föreslår vi en CFI-lösning anpassad för inbyggda enheter som bygger på en kombination av en typbaserad metod för indirekta grenar med en skuggstackmetod för att skydda returadresser. Vår lösning riktar sig mot ARM Cortex-M33-arkitekturen och utvärderas på olika applikationer som är lämpliga för lågpresterande enheter, inklusive inbyggda kryptografiska grundläggande funktioner och ett realtidsoperativsystem. Vår lösning erbjuder en hög säkerhetsnivå och möjliggör en minskning av attacker med 99,99% enligt genomsnittsmätningsmetoden (AIR). Vi erkänner dock att prestandaöverhuvud kan vara en oro i vissa användningsfall. Utvärderingen av vår CFI-implementering visar att den medför en prestandaöverhuvud som varierar mellan 7% och 81%, med en relativt liten storleksöverhuvud på cirka 3%. Därför föreslår vi att användningen av lämpliga arkitekturmodeller kan bidra till att minska prestandaöverhuvudet samtidigt som goda säkerhetsgarantier bibehålls. Vår studie belyser avvägningen mellan säkerhet och prestanda i CFI-implementeringar och ger insikter om potentiella områden för förbättring.