This repository contains open data and methods to supplement the publication Observation of an Ultra-high-energy Cosmic Neutrino with KM3NeT, available at nature.
In this publication, the observation of an exceptionally high-energy neutrino event in the PeV-range by the KM3NeT neutrino telescope is reported. Here, you can find supplementary information to reproduce and reuse selected outcomes reported in the publication.
The repository is mainly based on the use of Jupyter notebooks and provides an interactive event display. You can find the relevant notebooks in the notebooks
folder, which also exemplifies how to read the data provided in data
, and the event display in event-display
. As some analyses require special dependencies, ensure that you set up the environment accordingly as explained below in Getting started.
data/
: Input data for the notebooks, supplementary data and single hit information for the eventevent-display/
: Interactive event display of the event based on Julianotebooks/
: Jupyter notebooks to document the final analysis steps and produce outcomes shown in the publicationsrc/
: Supplementary scripts and functions
The following parts of the publication can be reproduced here:
- Julia-based event display (Figure 1):
/event-display
in a specialized Julia environment - Distribution of number of hits for simulation of neutrinos of 10, 100 and 1000 PeV (Figure 2):
/notebooks/Simulated number of PMTs.ipynb
- Skymap in the direction of KM3-230213A (Figure 4):
/notebooks/Skymap.ipynb
- Comparison of the astrophysical flux with measurements and theoretical predictions, (Figure 5):
/notebooks/Astrophysical flux comparions.ipynb
- Time residual distribution of the event hits (Extended Data, Figure 2):
/notebooks/Hit distributions.ipynb
- Topography in the direction of the event (Extended Data, Figure 4):
/notebooks/Site topography.ipynb
- Emission point of photons along the reconstructed muon trajectory (Supplementary Material, Figure 1):
/notebooks/Hit distributions.ipynb
- Expected number of track events for a variety of diffuse astrophysical fluxes (Supplementary Material, Table 1):
/notebooks/Expected events per flux.ipynb
You can run the repository locally on your machine (recommended in venv or conda environment) or on binder.
For the full use of all notebooks, you have to retrieve the full dataset for /data
from the KM3NeT Open Data Center, as explained in /notebooks/Reading Data.ipynb
. You can use the provided notebook after launching the repository where a download function is provided, or you can directly download larger files from the data set.
Launch the repository on mybinder following this link: https://mybinder.org/v2/gh/https://git.km3net.de/open-data/public-candidates/uhe-event/HEAD?urlpath=%2Fdoc%2Ftree%2Fnotebooks%2FReading+Data.ipyn.
First, download the whole content of the repository using git
or just directly from the download function and change into the directory.
It is recommended to use a virtual environment to install the necessary dependencies, see instructions for either conda or venv below. Alternatively just install the requirements using pip (see last step of venv installation).
In order to use conda to build the environment, conda has to be installed. To see how, use these Installation instructions.
Build environment using conda
from _environment.yml
file:
conda env create -f _environment.yml
conda activate uhe_event
It requires to build a dedicated environment.
Build environment using pip
:
pip install virtualenv
virtualenv venv
acitvate venv
:
# on Windows
.\venv\Scripts\activate.ps1
# on Linux
source venv/bin/activate
Install necessary packages:
pip install -r requirements.txt
In order to run the notebooks, you need to have Jupyter installed. You can install it using pip install jupyter
or following the instructions at the Juypter website.
Jupyter notebook kernel and launch your notebook:
python -m ipykernel install --user --name=uhe_event
jupyter-notebook
And for zsh
shell, you need to execute these lines first before installation of the kernel
conda install -c conda-forge notebook
conda install -c conda-forge nb_conda_kernels
This project is licensed under the terms of the BSD 3-clause license. Be aware that KM3NeT is currently under construction and data taking and processing are still under development. The presented data have been tested to the best current standards. However, the KM3NeT collaboration gives no warranty for the re-use of the data and does not endorse any third-party scientific findings based on the use of the presented data.