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Scripts to test dark matter point source candidates using IceCube public PS data.

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dmpoint

Authors:

  1. Stephan Meighen-Berger

Table of contents

  1. Introduction
  2. Data
  3. Guide
  4. Citation

Introduction

Project to check if we can constrain dm using point source approaches

Data

This code was designed to use data from the public IceCube 10 year point source data release:

IceCube Collaboration (2021): All-sky point-source IceCube data: years 2008-2018. Dataset. DOI: http://doi.org/DOI:10.21234/sxvs-mt83

Guide

The repository includes all scripts required to generate the plots from the publication, except the atmospheric shower one. For that please use MCEq.

The jupyter notebooks should guide through the required steps to analyze the data. (As of yet not designed to be user-friendly. Given interest, this will be changed)

  1. sky_hotspots_density.ipynb: generates the density maps given the IceCube data events
  2. sky_hotspots_density_signal.ipynb: generates the density maps for a given signal
  3. sky_hotspots_kmean.ipynb: performs a kmean test on the data set
  4. cluster_reader.ipynb: Reads cluster generated data from the codes in the cluster folder

The cluster folder contains scripts to run batches on a cluster using slurm.

Citation

Please cite arXiv:2109.07885 when using this code.

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Scripts to test dark matter point source candidates using IceCube public PS data.

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