A5085624493- Particle Detector Development and Performance
- Radiation Therapy and Dosimetry
- Radiation Detection and Scintillator Technologies
- Parallel Computing and Optimization Techniques
- Nuclear Physics and Applications
- Particle physics theoretical and experimental studies
- Medical Imaging Techniques and Applications
- Electron and X-Ray Spectroscopy Techniques
- Radiation Effects in Electronics
- Numerical Methods and Algorithms
- High-Energy Particle Collisions Research
- Nuclear reactor physics and engineering
- Astrophysics and Cosmic Phenomena
- Computational Physics and Python Applications
- Cellular Automata and Applications
- Advanced Optimization Algorithms Research
- Logic, programming, and type systems
- Quantum Chromodynamics and Particle Interactions
- Distributed and Parallel Computing Systems
- Software Testing and Debugging Techniques
- Computability, Logic, AI Algorithms
- Simulation Techniques and Applications
- PAPR reduction in OFDM
- Advanced Queuing Theory Analysis
- Embedded Systems Design Techniques
University of Kaiserslautern
2021-2025
Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau
2023-2025
Daimler (Germany)
2023-2025
University of Koblenz and Landau
2023-2025
University of Bergen
2023
European Organization for Nuclear Research
2023
European Council
2023
The full optimization of the design and operation instruments whose functioning relies on interaction radiation with matter is a super-human task, due to large dimensionality space possible choices for geometry, detection technology, materials, data-acquisition, information-extraction techniques, interdependence related parameters. On other hand, massive potential gains in performance over standard, "experience-driven" layouts are principle within our reach if an objective function fully...
In this work we consider the problem of determining identity hadrons at high energies based on topology their energy depositions in dense matter, along with time interactions. Using GEANT4 simulations a homogeneous lead tungstate calorimeter transverse and longitudinal segmentation, investigated discrimination protons, positive pions, kaons 100 GeV. The analysis focuses impact granularity by progressively merging detector cells extracting features like deposition patterns andtiming...
The majority of experiments in fundamental science today are designed to be multi-purpose: their aim is not simply measure a single physical quantity or process, but rather enable increased precision the measurement number different observable quantities natural system, extend search for new phenomena, exclude larger phase space candidate theories. Most time, combination above goals pursued; this breadth scope adds layer complexity already demanding task designing apparatus an optimal way,...
Recent advances in machine learning have opened new avenues for optimizing detector designs high-energy physics, where the complex interplay of geometry, materials, and physics processes has traditionally posed a significant challenge. In this work, we introduce $\textit{end-to-end}$ optimization framework AIDO that leverages diffusion model as surrogate full simulation reconstruction chain, enabling gradient-based design exploration both continuous discrete parameter spaces. Although is...
Algorithmic differentiation (AD) is a set of techniques that provide partial derivatives computer-implemented functions. Such functions can be supplied to state-of-the-art AD tools via their source code , or intermediate representations produced while compiling code. We present the novel tool Derivgrind, which augments machine compiled programs with forward-mode logic. Derivgrind leverages Valgrind instrumentation framework for structured access code, and shadow memory store dot values....
We simulate hadrons impinging on a homogeneous lead-tungstate (PbWO4) calorimeter to investigate how the resulting light yield and its temporal structure, as detected by an array of light-sensitive sensors, can be processed neuromorphic computing system. Our model encodes photon distributions spike trains employs fully connected spiking neural network estimate total deposited energy, well position spatial distribution emissions within sensitive material. The extracted primitives offer...
Abstract Objective. Monolithic active pixel sensors are used for charged particle tracking in many applications, from medical physics to astrophysics. The Bergen pCT collaboration designed a sampling calorimeter proton computed tomography, based entirely on the ALICE PIxel DEtector (ALPIDE). same telescope can be in-situ range verification therapy. An accurate charge diffusion model is required convert deposited energy Monte Carlo simulations cluster of pixels, and estimate energy, given an...
Recent advances in machine learning have opened new avenues for optimizing detector designs high-energy physics, where the complex interplay of geometry, materials, and physics processes has traditionally posed a significant challenge. In this work, we introduce end-to-end. AI Detector Optimization framework (AIDO), which leverages diffusion model as surrogate full simulation reconstruction chain, enabling gradient-based design exploration both continuous discrete parameter spaces. Although...
Proton computed tomography (pCT) aims to facilitate precise dose planning for hadron therapy, a promising and effective method cancer treatment. Hadron therapy utilizes protons heavy ions deliver well-focused doses of radiation, leveraging the Bragg peak phenomenon target tumors while sparing healthy tissues. The Bergen pCT Collaboration develop novel scanner, accompanying reconstruction algorithms overcome current limitations. This paper focuses on advancing track image algorithms, thereby...
We simulate hadrons impinging on a homogeneous lead tungstate (PbWO4) calorimeter using GEANT4 software to investigate how the resulting light yield and its temporal structure, as detected by an array of light-sensitive sensors, can be processed neuromorphic computing system. Our model encodes photon distributions spike trains employs fully connected spiking neural network estimate total deposited energy, well position spatial distribution emissions within sensitive material. The extracted...
In this work we consider the problem of determining identity hadrons at high energies based on topology their energy depositions in dense matter, along with time interactions. Using GEANT4 simulations a homogeneous lead tungstate calorimeter transverse and longitudinal segmentation, investigated discrimination protons, positive pions, kaons 100 GeV. The analysis focuses impact granularity by progressively merging detector cells extracting features like deposition patterns timing information....
Abstract We present the performance of a full-length prototype ALICE Forward Calorimeter (FoCal). The detector is composed silicon-tungsten electromagnetic sampling calorimeter with longitudinal and transverse segmentation (FoCal-E) about 20 X 0 hadronic copper-scintillating-fiber (FoCal-H) 5 λ int . data were taken in various test beam campaigns between 2021 2023 at CERN PS SPS lines hadron beams up to energies 350 GeV, electron 300 GeV. Regarding FoCal-E, we report comprehensive analysis...
Abstract The Bergen proton Computed Tomography (pCT) is a prototype detector under construction. It aims to have the capability track and measure ions’ energy deposition minimize uncertainty in treatment planning. high granularity digital tracking calorimeter, where first two layers will act as obtain positional information of incoming particle. remainder calorimeter. Beam tests been performed with multiple beams. These shown that ALPIDE chip sensor can deposited energy, making it possible...
Proton computed tomography (pCT) and radiography (pRad) are proposed modalities for improved treatment plan accuracy in situ validation proton therapy. The pCT system of the Bergen collaboration is able to handle very high particle intensities by means track reconstruction. However, incorrectly reconstructed secondary tracks degrade image quality. We have investigated whether a convolutional neural network (CNN)-based filter improve quality.The CNN was trained simulation reconstruction tens...
The full optimization of the design and operation instruments whose functioning relies on interaction radiation with matter is a super-human task, given large dimensionality space possible choices for geometry, detection technology, materials, data-acquisition, information-extraction techniques, interdependence related parameters. On other hand, massive potential gains in performance over standard, "experience-driven" layouts are principle within our reach if an objective function fully...
Objective.Proton therapy is highly sensitive to range uncertainties due the nature of dose deposition charged particles. To ensure treatment quality, verification methods can be used verify that individual spots in a pencil beam scanning fraction match plan. This study introduces novel metric for proton quality control based on spots.Approach.We employ uncertainty-aware deep neural networks predict Bragg peak depth an anthropomorphic phantom secondary particle detection silicon pixel...
In this article we examine recent developments in the research area concerning creation of end-to-end models for complete optimization measuring instruments. The consider rely on differentiable programming methods and specification a software pipeline including all factors impacting performance -- from data-generating processes to their reconstruction extraction inference parameters interest instrument along with careful utility function well aligned end goals experiment. Building previous...
In this document we describe a model of an array water Cherenkov detectors proposed to study ultra-high-energy gamma rays in the southern hemisphere, and continuous secondary particles produced on ground from proton showers. We use detector parametrization showers for identification most promising configuration elements, using likelihood ratio test statistic classify stochastic gradient descent technique maximize utility function describing measurement precision gamma-ray flux.