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Tau Neutrino Appearance with ANTARES

📖 Overview

An open-source repository containing the SWIM-based analysis for a feasibility study of tau-neutrino appearance measurements with the ANTARES neutrino telescope. This repository accompanies the Master's thesis from FAU Erlangen-Nuremberg, supervised by PD Dr. Thomas Eberl.


📂 Repository Structure

The repository is organized into modules, each addressing a different step of the analysis:

├── README.md <- Overview of the project, setup instructions, and usage.
│
├── LICENSE <- Open-source license for this repository.
|
├── external_library <- Collection of custom functions and classes for data handling and analysis.
│
├── ReconstructionPerformance <- Scripts to evaluate reconstruction performance,
│                              comparing AntDSTs and NNFit outputs.
│
├── CanDimension <- Scripts to add required 3D coordinate vectors to data
│                samples for constructing the detector response matrix.
│
├── Chi2Profile <- Scripts to compute χ² profiles with smeared and
│               unsmeared datasets using the SWIM framework.
│
├── Smearing <- Contains smearing strategies (flat-based, performance-based)
│             and NNFit parameterizations for reconstruction.
│
└── Plotter <- Contains plotter.py for visualizing χ² profiles 
              and significance results.

⚙️ Requirements

  • SWIM – C++ framework for neutrino oscillation analyses and sensitivity studies.
  • Python 3.8+ with standard scientific libraries:
    • numpy
    • matplotlib
    • scipy
    • pandas
    • h5py
    • pyyaml
    • tabulate
    • tqdm
    • json

🚀 Quick Start

Clone the repository:

git clone https://github.com/mchadolias/tau-appearance-antares.git
cd tau-appearance-antares

Install SWIM:

git clone https://git.km3net.de/oscillation/Swim.git
cd Swim
mkdir build
cd build
cmake ..
make

Run the analysis based on the submission bash script:

./Chi2Profile/submit_full_no_systematics.sh

The results will be stored in the output directory.


📝 License

This repository is distributed under the MIT License.


🙏 Acknowledgments

Special thanks to the ANTARES Collaboration for providing the data used in this study and the KM3NeT Collaboration for the SWIM framework. Further acknowledgments are in the section of the masters thesis.


📖 References