Monte Carlo-based data analysis
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Updated
Jan 27, 2025 - Jupyter Notebook
Monte Carlo-based data analysis
Python tools for working with the IceCube public data.
Unbinned likelihood analysis code for astroparticle physics datasets
Bayesian constraints on the astrophysical neutrino population from IceCube data
This repository contains the code used to perform the analysis described in the paper "A stacked search for spatial coincidences between IceCube neutrinos and radio pulsars" (https://arxiv.org/abs/2306.03427). The code is written in Python 3.10 and uses the following packages: numpy, scipy, matplotlib, pandas, numba, multiprocessing.
This project aims to incorporate the effects of hole ice into the clsim photon propagation simulation of the icecube neutrino observatory.
A Supernova TEst Routine for IceCube Analysis
Technical specification and documentation for BWS IceCubes, a friendly alternative to AWS Snowballs.
IceCube Astrophysical Flavor analysis using Bayesian inference
Simulation of the Optics of the Imaging Air-Cherenkov Telescopes IceAct with Geant4
Play and learn with the TinyFPGA development board featuring a Lattice iCE40 LP8K FPGA with a very compact footprint.
Astrophysical Neutrino Anisotropy
Scripts to test dark matter point source candidates using IceCube public PS data.
An OpenCL-based photon-tracking simulation using a (source-based) ray tracing algorithm modeling scattering and absorption of light in the deep glacial ice at the South Pole or Mediterranean sea water.
IceCube - Neutrinos in Deep Ice
Kaggle competition (2023). Predict neutrino particle direction with Deep Graph Neural Networks.
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