Data for the KM3-230213A high energy event observation

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.

Overview

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.

Project Structure

• data/: Input data for the notebooks, supplementary data and single hit information for the event
• event-display/: Interactive event display of the event based on Julia
• notebooks/: Jupyter notebooks to document the final analysis steps and produce outcomes shown in the publication
• src/: Supplementary scripts and functions

Contents

The following parts of the publication can be reproduced here:

Figures

• 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

Tables

• Expected number of track events for a variety of diffuse astrophysical fluxes (Supplementary Material, Table 1): /notebooks/Expected events per flux.ipynb

Getting started

You can run the repository locally on your machine (recommended in venv or conda environment) or on binder.

Adding full data

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.

Using mybinder

Launch the repository on mybinder following this link: https://mybinder.org/v2/git/https%3A%2F%2Fgit.km3net.de%2Fopen-data%2Fpublic-candidates%2Fvhe-event/HEAD?urlpath=%2Fdoc%2Ftree%2Fnotebooks%2FReading+Data.ipynb.

Alternative: Run the repository locally

First, download the whole content of the repository using git or just directly from the download function and change into the directory.

Creating the environment

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).

Using conda

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: sh conda env create -f _environment.yml conda activate uhe_event

Using venv

It requires to build a dedicated environment. Build environment using pip: ```sh pip install virtualenv

virtualenv venv

acitvate `venv`: sh

on Windows

.\venv\Scripts\activate.ps1

on Linux

source venv/bin/activate Install necessary packages: sh pip install -r requirements.txt ```

Using Jupyter

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.

Running the Jupyter kernel

Jupyter notebook kernel and launch your notebook: sh 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 zsh conda install -c conda-forge notebook conda install -c conda-forge nb_conda_kernels

License and Disclaimer

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.