Monte Carlo-based data analysis
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Updated
Aug 23, 2024 - Jupyter Notebook
Monte Carlo-based data analysis
Python tools for working with the IceCube public data.
Unbinned likelihood analysis code for astroparticle physics datasets
A Supernova TEst Routine for IceCube Analysis
This project aims to incorporate the effects of hole ice into the clsim photon propagation simulation of the icecube neutrino observatory.
Technical specification and documentation for BWS IceCubes, a friendly alternative to AWS Snowballs.
Play and learn with the TinyFPGA development board featuring a Lattice iCE40 LP8K FPGA with a very compact footprint.
Simulation of the Optics of the Imaging Air-Cherenkov Telescopes IceAct with Geant4
Scripts to test dark matter point source candidates using IceCube public PS data.
IceCube - Neutrinos in Deep Ice
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.
Kaggle competition (2023). Predict neutrino particle direction with Deep Graph Neural Networks.
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.
Bayesian constraints on the astrophysical neutrino population from IceCube data
Astrophysical Neutrino Anisotropy
IceCube Astrophysical Flavor analysis using Bayesian inference
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